From acb5935b327fb2678bf5bfa5cc1eab31f251dccd Mon Sep 17 00:00:00 2001
From: zm711 <92116279+zm711@users.noreply.github.com>
Date: Sun, 9 Mar 2025 16:29:09 -0400
Subject: [PATCH 01/30] test a ruff action

---
 .github/workflows/ruff.yml | 19 +++++++++++++++++++
 pyproject.toml             |  5 +++++
 2 files changed, 24 insertions(+)
 create mode 100644 .github/workflows/ruff.yml

diff --git a/.github/workflows/ruff.yml b/.github/workflows/ruff.yml
new file mode 100644
index 0000000000..23e3567fed
--- /dev/null
+++ b/.github/workflows/ruff.yml
@@ -0,0 +1,19 @@
+name: Ruff Linting
+
+on:
+  pull_request:
+    types: [synchronize, opened, reopened]
+    branches:
+      - main
+
+concurrency:  # Cancel previous workflows on the same pull request
+    group: ${{ github.workflow }}-${{ github.ref }}
+    cancel-in-progress: true
+
+jobs:
+  ruff-linting:
+    name: Ruff Linting
+    strategy:
+      fail-fast: false
+    steps:
+      - uses: astral-sh/ruff-action@v3
diff --git a/pyproject.toml b/pyproject.toml
index 97ba77299e..808403b113 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -50,6 +50,11 @@ exclude = ["spikeinterface.*.tests"]
 [tool.black]
 line-length = 120
 
+[tool.ruff]
+line-length = 120
+[tool.ruff.lint]
+select = ['F401']
+
 [project.urls]
 homepage = "https://github.com/SpikeInterface/spikeinterface"
 repository = "https://github.com/SpikeInterface/spikeinterface"

From f5154cb91390552c026f5a9f6bffed7297ca4e7c Mon Sep 17 00:00:00 2001
From: zm711 <92116279+zm711@users.noreply.github.com>
Date: Sun, 9 Mar 2025 16:33:18 -0400
Subject: [PATCH 02/30] oops

---
 .github/workflows/ruff.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/ruff.yml b/.github/workflows/ruff.yml
index 23e3567fed..d02e24ef29 100644
--- a/.github/workflows/ruff.yml
+++ b/.github/workflows/ruff.yml
@@ -11,7 +11,7 @@ concurrency:  # Cancel previous workflows on the same pull request
     cancel-in-progress: true
 
 jobs:
-  ruff-linting:
+  run:
     name: Ruff Linting
     strategy:
       fail-fast: false

From 5ed3ddc17ddb6163621270d0391031b627216014 Mon Sep 17 00:00:00 2001
From: zm711 <92116279+zm711@users.noreply.github.com>
Date: Sun, 9 Mar 2025 16:37:24 -0400
Subject: [PATCH 03/30] add ruff check

---
 .github/workflows/ruff.yml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/.github/workflows/ruff.yml b/.github/workflows/ruff.yml
index d02e24ef29..2dad88e493 100644
--- a/.github/workflows/ruff.yml
+++ b/.github/workflows/ruff.yml
@@ -17,3 +17,4 @@ jobs:
       fail-fast: false
     steps:
       - uses: astral-sh/ruff-action@v3
+      - run: ruff check

From 0e61521779f10871fbf66f2fe31bb8eae8fcadc9 Mon Sep 17 00:00:00 2001
From: zm711 <92116279+zm711@users.noreply.github.com>
Date: Sun, 9 Mar 2025 16:43:19 -0400
Subject: [PATCH 04/30] another try

---
 .github/workflows/ruff.yml | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/ruff.yml b/.github/workflows/ruff.yml
index 2dad88e493..0860cd8fc9 100644
--- a/.github/workflows/ruff.yml
+++ b/.github/workflows/ruff.yml
@@ -13,8 +13,11 @@ concurrency:  # Cancel previous workflows on the same pull request
 jobs:
   run:
     name: Ruff Linting
+    runs-on: ubuntu-latest
     strategy:
       fail-fast: false
     steps:
+      - uses: actions/checkout@v4
       - uses: astral-sh/ruff-action@v3
-      - run: ruff check
+        with:
+          args: check

From b8dde0550a382c4995a43e6099e9a672cd46afa8 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Fri, 5 Sep 2025 14:11:16 +0000
Subject: [PATCH 05/30] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 src/spikeinterface/extractors/phykilosortextractors.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/spikeinterface/extractors/phykilosortextractors.py b/src/spikeinterface/extractors/phykilosortextractors.py
index 8209d93543..46a8e4cecb 100644
--- a/src/spikeinterface/extractors/phykilosortextractors.py
+++ b/src/spikeinterface/extractors/phykilosortextractors.py
@@ -40,7 +40,7 @@ class BasePhyKilosortSortingExtractor(BaseSorting):
     The cluster_id column is used as the merge key to combine properties from multiple files.
     All loaded properties are added to the sorting extractor as unit properties, with some
     renamed for SpikeInterface conventions: 'group' becomes 'quality', 'cluster_id'
-    becomes 'original_cluster_id'. These properties can be accessed via ``sorting.get_property()`` 
+    becomes 'original_cluster_id'. These properties can be accessed via ``sorting.get_property()``
     function.
     """
 

From e8e9b0c6e617de07664a96be4cf20efeb5f3ba88 Mon Sep 17 00:00:00 2001
From: Alessio Buccino <alejoe9187@gmail.com>
Date: Mon, 9 Nov 2026 14:50:41 +0100
Subject: [PATCH 06/30] fix: core ruff checks

---
 .github/scripts/serialization/objects.py      |   1 -
 .pre-commit-config.yaml                       |   9 +-
 conftest.py                                   |   2 +-
 doc/images/make_comparison_figures.py         |   1 -
 examples/forhowto/plot_extract_lfps.py        |   2 -
 examples/get_started/quickstart.py            |   3 -
 examples/how_to/auto_label_units.py           |   1 -
 .../benchmark_with_hybrid_recordings.py       |   1 -
 examples/how_to/customize_a_plot.py           |   1 -
 .../plot_5_comparison_sorter_weaknesses.py    |   2 -
 .../core/plot_1_recording_extractor.py        |   1 -
 .../plot_5_append_concatenate_segments.py     |   3 +-
 .../curation/plot_1_automated_curation.py     |   2 +-
 .../widgets/plot_3_waveforms_gallery.py       |   1 -
 installation_tips/check_your_install.py       |   4 +-
 pyproject.toml                                |  14 ++-
 .../benchmark/benchmark_base.py               |  11 +-
 .../benchmark/benchmark_clustering.py         |  10 +-
 .../benchmark/benchmark_matching.py           |   2 -
 .../benchmark/benchmark_merging.py            |   3 -
 .../benchmark/benchmark_motion_estimation.py  |   6 -
 .../benchmark/benchmark_peak_localization.py  |   5 -
 .../benchmark/benchmark_peak_selection.py     |  10 --
 .../benchmark/benchmark_plot_tools.py         |  25 ++--
 .../benchmark/benchmark_sorter.py             |   1 -
 .../benchmark/benchmark_sorter_without_gt.py  |   3 +-
 .../tests/common_benchmark_testing.py         |   3 -
 .../benchmark/tests/test_benchmark_merging.py |   1 -
 .../tests/test_benchmark_sorter_without_gt.py |   1 -
 .../benchmark/tests/test_residual_analysis.py |   2 -
 .../comparison/basecomparison.py              |   1 -
 src/spikeinterface/comparison/collision.py    |   3 -
 .../comparison/comparisontools.py             |  20 ++--
 .../comparison/multicomparisons.py            |   7 +-
 .../comparison/paircomparisons.py             |   4 +-
 .../tests/test_groundtruthcomparison.py       |   1 -
 .../tests/test_multisortingcomparison.py      |   2 +-
 .../tests/test_templatecomparison.py          |   2 -
 .../core/analyzer_extension_core.py           |  21 +---
 src/spikeinterface/core/base.py               |  33 ++----
 src/spikeinterface/core/baserecording.py      |  17 ++-
 src/spikeinterface/core/basesorting.py        |  26 ++---
 src/spikeinterface/core/binaryfolder.py       |   3 +-
 .../core/binaryrecordingextractor.py          |   2 +-
 .../core/channelsaggregationrecording.py      |  13 +--
 src/spikeinterface/core/core_tools.py         |   8 +-
 src/spikeinterface/core/generate.py           |  41 +++----
 src/spikeinterface/core/loading.py            |  12 +-
 src/spikeinterface/core/motion.py             |   4 +-
 src/spikeinterface/core/node_pipeline.py      |  10 +-
 src/spikeinterface/core/npzfolder.py          |   2 -
 src/spikeinterface/core/old_api_utils.py      |   2 +-
 src/spikeinterface/core/sorting_tools.py      |  30 +++--
 src/spikeinterface/core/sortinganalyzer.py    | 110 ++++++++----------
 src/spikeinterface/core/sortingfolder.py      |   4 +-
 src/spikeinterface/core/sparsity.py           |  56 +++++----
 src/spikeinterface/core/testing.py            |   2 -
 .../tests/test_analyzer_extension_core.py     |   2 +-
 src/spikeinterface/core/tests/test_base.py    |   2 +-
 .../core/tests/test_baserecording.py          |   3 +-
 .../core/tests/test_basesorting.py            |   2 -
 .../core/tests/test_binaryfolder.py           |   4 -
 .../tests/test_binaryrecordingextractor.py    |   1 -
 .../core/tests/test_core_tools.py             |   1 -
 .../core/tests/test_frameslicerecording.py    |   3 +-
 .../core/tests/test_jsonification.py          |   2 -
 src/spikeinterface/core/tests/test_loading.py |   7 +-
 .../core/tests/test_motion_core.py            |   1 -
 .../core/tests/test_node_pipeline.py          |   1 -
 .../tests/test_noise_levels_propagation.py    |   8 +-
 .../core/tests/test_npzsortingextractor.py    |   3 -
 .../core/tests/test_read_python_safe.py       |   5 +-
 .../core/tests/test_recording_tools.py        |   2 -
 .../core/tests/test_segmentutils.py           |   3 -
 .../core/tests/test_sorting_folder.py         |   3 +-
 .../core/tests/test_sorting_tools.py          |   1 -
 .../core/tests/test_sortinganalyzer.py        |   4 +-
 .../core/tests/test_waveform_tools.py         |   2 +-
 src/spikeinterface/core/time_series_tools.py  |   7 +-
 .../core/unitsaggregationsorting.py           |   6 +-
 src/spikeinterface/core/waveform_tools.py     |   8 +-
 ...forms_extractor_backwards_compatibility.py |  25 ++--
 src/spikeinterface/core/zarrextractors.py     |   9 +-
 src/spikeinterface/curation/auto_merge.py     |   6 +-
 src/spikeinterface/curation/curation_model.py |   6 +-
 .../curation/curationsorting.py               |   2 +-
 .../curation/model_based_curation.py          |   6 +-
 .../curation/sortingview_curation.py          |   2 +-
 .../curation/tests/test_auto_merge.py         |   3 -
 .../curation/tests/test_bombcell_curation.py  |   3 -
 .../curation/tests/test_curation_model.py     |   1 -
 .../tests/test_model_based_curation.py        |   1 -
 .../curation/tests/test_remove_redundant.py   |   2 +-
 .../tests/test_sortingview_curation.py        |   8 --
 .../tests/test_train_manual_curation.py       |   3 +-
 .../tests/test_unitrefine_curation.py         |   1 -
 .../curation/threshold_metrics_curation.py    |   1 -
 .../curation/train_manual_curation.py         |  16 +--
 src/spikeinterface/exporters/tests/common.py  |   2 -
 .../exporters/tests/test_export_to_ibl.py     |   1 -
 .../exporters/tests/test_export_to_phy.py     |   3 -
 .../exporters/tests/test_report.py            |   3 -
 src/spikeinterface/exporters/to_phy.py        |  10 +-
 src/spikeinterface/extractors/cbin_ibl.py     |   9 +-
 .../extractors/extractor_classes.py           |   6 -
 .../extractors/klustaextractors.py            |   8 +-
 .../extractors/mdaextractors.py               |   9 +-
 .../extractors/neoextractors/neo_utils.py     |   5 +-
 .../extractors/neoextractors/spike2.py        |   2 +-
 .../extractors/nwbextractors.py               |   8 +-
 .../extractors/phykilosortextractors.py       |   4 +-
 .../extractors/sinapsrecordingextractors.py   |   8 +-
 .../tests/test_cbin_ibl_extractors.py         |   4 +-
 .../extractors/tests/test_iblextractors.py    |   7 +-
 .../extractors/tests/test_neoextractors.py    |   2 -
 .../extractors/tests/test_nwbextractors.py    |   4 +-
 .../tests/test_nwbextractors_streaming.py     |   2 +-
 .../extractors/yassextractors.py              |   2 +-
 .../generation/drifting_generator.py          |  11 +-
 .../metrics/quality/pca_metrics.py            |  14 +--
 .../quality/tests/test_metrics_functions.py   |   3 +-
 .../template/tests/test_template_metrics.py   |   3 +-
 .../postprocessing/amplitude_scalings.py      |  27 +++--
 .../postprocessing/localization_tools.py      |   2 -
 .../postprocessing/noise_level.py             |   1 -
 .../postprocessing/principal_component.py     |   8 +-
 .../postprocessing/template_similarity.py     |  15 +--
 .../tests/test_multi_extensions.py            |   1 -
 .../postprocessing/unit_locations.py          |   2 +-
 .../postprocessing/valid_unit_periods.py      |  12 +-
 src/spikeinterface/preprocessing/decimate.py  |  10 +-
 .../tests/test_deepinterpolation.py           |   1 -
 .../preprocessing/interpolate_bad_channels.py |   1 -
 src/spikeinterface/preprocessing/motion.py    |   6 +-
 src/spikeinterface/preprocessing/pipeline.py  |  12 +-
 src/spikeinterface/preprocessing/resample.py  |   1 -
 .../preprocessing/tests/test_astype.py        |   7 +-
 .../tests/test_common_reference.py            |   2 -
 .../tests/test_detect_artifacts.py            |  16 ++-
 .../preprocessing/tests/test_filter.py        |   1 -
 .../preprocessing/tests/test_pipeline.py      |   3 -
 .../tests/test_preprocessing_tools.py         |   3 -
 .../tests/test_remove_artifacts.py            |   2 -
 .../preprocessing/tests/test_resample.py      |   2 +-
 .../tests/test_silence_periods.py             |   2 -
 .../preprocessing/tests/testing_tools.py      |   6 -
 src/spikeinterface/sorters/basesorter.py      |   4 +-
 .../sorters/external/dartsort.py              |  10 +-
 src/spikeinterface/sorters/external/hdsort.py |   4 +-
 .../sorters/external/rt_sort.py               |   3 +-
 .../sorters/external/tests/test_combinato.py  |   2 +-
 .../sorters/external/tests/test_hdsort.py     |   2 +-
 .../sorters/external/tests/test_ironclust.py  |   3 +-
 .../external/tests/test_kilosort2_5.py        |   2 +-
 .../tests/test_singularity_containers_gpu.py  |   1 -
 .../external/tests/test_tridesclous.py        |   1 -
 .../sorters/external/tests/test_waveclus.py   |   3 +-
 .../sorters/external/waveclus.py              |   2 +-
 src/spikeinterface/sorters/internal/lupin.py  |   3 +-
 .../sorters/internal/si_based.py              |   2 +-
 .../sorters/internal/simplesorter.py          |   5 +-
 .../sorters/internal/spyking_circus2.py       |  11 +-
 .../sorters/internal/tests/test_lupin.py      |   3 +-
 .../internal/tests/test_tridesclous2.py       |   1 -
 .../sorters/internal/tridesclous2.py          |   7 +-
 src/spikeinterface/sorters/runsorter.py       |  14 +--
 src/spikeinterface/sorters/sorterlist.py      |   2 +-
 .../tests/test_runsorter_dependency_checks.py |  20 ++--
 src/spikeinterface/sorters/utils/misc.py      |   2 +-
 .../sorters/utils/shellscript.py              |  10 +-
 .../clustering/cleaning_tools.py              |   8 --
 .../clustering/graph_clustering.py            |   2 -
 .../clustering/itersplit_tools.py             |   4 +-
 .../sortingcomponents/clustering/main.py      |   8 +-
 .../sortingcomponents/clustering/positions.py |   1 -
 .../clustering/tests/test_itersplit_tool.py   |   5 -
 .../clustering/tests/test_merging_tools.py    |   8 --
 .../sortingcomponents/clustering/tools.py     |   1 -
 .../sortingcomponents/matching/circus.py      |  10 +-
 .../sortingcomponents/matching/main.py        |   1 -
 .../sortingcomponents/matching/nearest.py     |  11 +-
 .../matching/tests/test_template_matching.py  |   4 -
 .../matching/tests/test_wobble.py             |   2 -
 .../sortingcomponents/motion/decentralized.py |   5 +-
 .../sortingcomponents/motion/medicine.py      |   4 -
 .../motion/motion_estimation.py               |   1 -
 .../sortingcomponents/motion/motion_utils.py  |   3 -
 .../motion/tests/test_drege.py                |   3 -
 .../motion/tests/test_motion_estimation.py    |   2 +-
 .../sortingcomponents/peak_detection/main.py  |   2 +-
 .../tests/test_peak_detection.py              |   2 +-
 .../peak_localization/grid.py                 |   1 -
 .../peak_localization/main.py                 |  14 +--
 .../tests/test_peak_localization.py           |   3 -
 .../tests/test_peak_selection.py              |  43 ++++---
 .../waveforms/features_from_peaks.py          |   7 +-
 .../waveforms/neural_network_denoiser.py      |  18 +--
 .../tests/test_features_from_peaks.py         |   2 -
 .../waveforms/tests/test_hanning_filter.py    |   3 -
 .../tests/test_neural_network_denoiser.py     |   4 +-
 .../waveforms/tests/test_savgol_denoiser.py   |   3 -
 .../waveforms/tests/test_temporal_pca.py      |   3 -
 .../widgets/all_amplitudes_distributions.py   |   1 -
 src/spikeinterface/widgets/amplitudes.py      |   1 -
 .../widgets/autocorrelograms.py               |   2 -
 .../widgets/bombcell_curation.py              |   4 +-
 src/spikeinterface/widgets/collision.py       |   5 -
 src/spikeinterface/widgets/comparison.py      |   2 -
 .../widgets/crosscorrelograms.py              |   2 -
 src/spikeinterface/widgets/drift_templates.py |   2 +-
 .../widgets/isi_distribution.py               |   2 -
 src/spikeinterface/widgets/metrics.py         |   7 +-
 src/spikeinterface/widgets/multicomparison.py |   3 -
 src/spikeinterface/widgets/peak_activity.py   |   2 +-
 src/spikeinterface/widgets/peaks_on_probe.py  |   7 +-
 .../widgets/potential_merges.py               |   1 -
 src/spikeinterface/widgets/probe_map.py       |   1 -
 src/spikeinterface/widgets/rasters.py         |   9 +-
 src/spikeinterface/widgets/spike_locations.py |   1 -
 .../widgets/spike_locations_by_time.py        |   3 +-
 .../widgets/spikes_on_traces.py               |   7 --
 .../widgets/template_similarity.py            |   1 -
 .../widgets/tests/test_widgets.py             |   2 -
 .../widgets/tests/test_widgets_utils.py       |  13 +--
 src/spikeinterface/widgets/traces.py          |  25 ++--
 src/spikeinterface/widgets/unit_depths.py     |   1 -
 src/spikeinterface/widgets/unit_labels.py     |   7 +-
 src/spikeinterface/widgets/unit_locations.py  |   1 -
 src/spikeinterface/widgets/unit_presence.py   |   2 -
 src/spikeinterface/widgets/unit_probe_map.py  |   1 -
 src/spikeinterface/widgets/unit_summary.py    |   1 -
 .../widgets/unit_valid_periods.py             |   1 -
 src/spikeinterface/widgets/unit_waveforms.py  |  14 +--
 src/spikeinterface/widgets/utils.py           |   4 +-
 .../widgets/utils_ipywidgets.py               |  10 +-
 src/spikeinterface/widgets/widget_list.py     |   2 +-
 236 files changed, 517 insertions(+), 951 deletions(-)

diff --git a/.github/scripts/serialization/objects.py b/.github/scripts/serialization/objects.py
index f2f3469076..9544e4a8d9 100644
--- a/.github/scripts/serialization/objects.py
+++ b/.github/scripts/serialization/objects.py
@@ -140,7 +140,6 @@ def _check_recording_with_probe(rec, check_extra_data=None):
 
 
 def _build_recording_with_interleaved_probes():
-    import numpy as np
     from probeinterface import ProbeGroup, generate_linear_probe
     from spikeinterface.core import generate_recording
 
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 6d35bc8cd3..315c4cff72 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -5,8 +5,11 @@ repos:
     -   id: check-yaml
     -   id: end-of-file-fixer
     -   id: trailing-whitespace
--   repo: https://github.com/psf/black-pre-commit-mirror
-    rev: 26.10.1
+-   repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: v0.15.0
     hooks:
-    -   id: black
+    -   id: ruff-check
+        args: [--fix]
+        files: ^src/
+    -   id: ruff-format
         files: ^src/
diff --git a/conftest.py b/conftest.py
index 6c4bfbef3a..24a74fe1ec 100644
--- a/conftest.py
+++ b/conftest.py
@@ -56,7 +56,7 @@ def pytest_collection_modifyitems(config, items):
 
         try:
             rel_path = Path(item.fspath).relative_to(modules_location)
-        except:
+        except Exception:
             continue
 
         module = rel_path.parts[0]
diff --git a/doc/images/make_comparison_figures.py b/doc/images/make_comparison_figures.py
index cdf0c03f9f..be88e474b4 100644
--- a/doc/images/make_comparison_figures.py
+++ b/doc/images/make_comparison_figures.py
@@ -11,7 +11,6 @@
 sys.path.append('../../examples/modules/comparison/')
 from generate_erroneous_sorting import generate_erroneous_sorting
 
-import spikeinterface.extractors as se
 import spikeinterface.comparison as sc
 import spikeinterface.widgets as sw
 
diff --git a/examples/forhowto/plot_extract_lfps.py b/examples/forhowto/plot_extract_lfps.py
index 53c4c256c2..404af6edb6 100644
--- a/examples/forhowto/plot_extract_lfps.py
+++ b/examples/forhowto/plot_extract_lfps.py
@@ -44,12 +44,10 @@
 import time
 import numpy as np
 import matplotlib.pyplot as plt
-from pathlib import Path
 import pandas as pd
 import seaborn as sns
 
 import spikeinterface as si
-import spikeinterface.extractors as se
 import spikeinterface.preprocessing as spre
 import spikeinterface.widgets as sw
 from spikeinterface.core import generate_ground_truth_recording
diff --git a/examples/get_started/quickstart.py b/examples/get_started/quickstart.py
index 75d5c8d63a..d53bb1d9ea 100644
--- a/examples/get_started/quickstart.py
+++ b/examples/get_started/quickstart.py
@@ -34,7 +34,6 @@
 # The spikeinterface module by itself imports only the spikeinterface.core submodule
 # which is not useful for the end user
 
-import spikeinterface
 
 # We need to import one by one different submodules separately (preferred).
 # There are several modules:
@@ -50,9 +49,7 @@
 
 import spikeinterface as si  # import core only
 import spikeinterface.extractors as se
-import spikeinterface.preprocessing as spre
 import spikeinterface.sorters as ss
-import spikeinterface.postprocessing as spost
 import spikeinterface.metrics as sm
 import spikeinterface.comparison as sc
 import spikeinterface.exporters as sexp
diff --git a/examples/how_to/auto_label_units.py b/examples/how_to/auto_label_units.py
index b70d5e66b2..ac4fbf13dc 100644
--- a/examples/how_to/auto_label_units.py
+++ b/examples/how_to/auto_label_units.py
@@ -24,7 +24,6 @@
 # 3. UnitRefine: pre-trained classifiers to label units as noise or SUA/MUA [Jain]_
 
 # %%
-import numpy as np
 
 import spikeinterface as si
 import spikeinterface.curation as sc
diff --git a/examples/how_to/benchmark_with_hybrid_recordings.py b/examples/how_to/benchmark_with_hybrid_recordings.py
index d983578797..ebac618421 100644
--- a/examples/how_to/benchmark_with_hybrid_recordings.py
+++ b/examples/how_to/benchmark_with_hybrid_recordings.py
@@ -32,7 +32,6 @@
 import spikeinterface.generation as sgen
 import spikeinterface.widgets as sw
 
-from spikeinterface.sortingcomponents.motion import estimate_motion
 
 import numpy as np
 import matplotlib.pyplot as plt
diff --git a/examples/how_to/customize_a_plot.py b/examples/how_to/customize_a_plot.py
index 5568534b52..23bff39d72 100644
--- a/examples/how_to/customize_a_plot.py
+++ b/examples/how_to/customize_a_plot.py
@@ -81,7 +81,6 @@
 # Here's an example of making a unit summary plot.
 
 # +
-import matplotlib.pyplot as plt
 fig, axs = plt.subplots(ncols=2, nrows=1)
 
 unit_id=8
diff --git a/examples/tutorials/comparison/plot_5_comparison_sorter_weaknesses.py b/examples/tutorials/comparison/plot_5_comparison_sorter_weaknesses.py
index c588ee82cb..68480c6dc7 100644
--- a/examples/tutorials/comparison/plot_5_comparison_sorter_weaknesses.py
+++ b/examples/tutorials/comparison/plot_5_comparison_sorter_weaknesses.py
@@ -34,8 +34,6 @@
 ##############################################################################
 # Import
 
-import numpy as np
-import pandas as pd
 import matplotlib.pyplot as plt
 
 from spikeinterface.comparison import compare_sorter_to_ground_truth
diff --git a/examples/tutorials/core/plot_1_recording_extractor.py b/examples/tutorials/core/plot_1_recording_extractor.py
index a3143161b2..a73ffa2716 100644
--- a/examples/tutorials/core/plot_1_recording_extractor.py
+++ b/examples/tutorials/core/plot_1_recording_extractor.py
@@ -14,7 +14,6 @@
 
 """
 
-import matplotlib.pyplot as plt
 
 import numpy as np
 import spikeinterface.extractors as se
diff --git a/examples/tutorials/core/plot_5_append_concatenate_segments.py b/examples/tutorials/core/plot_5_append_concatenate_segments.py
index 5cb1cccb6f..29fb9147ca 100644
--- a/examples/tutorials/core/plot_5_append_concatenate_segments.py
+++ b/examples/tutorials/core/plot_5_append_concatenate_segments.py
@@ -22,11 +22,10 @@
 Here is a short example.
 """
 
-import matplotlib.pyplot as plt
 import numpy as np
 
 
-from spikeinterface import NumpyRecording, NumpySorting
+from spikeinterface import NumpyRecording
 from spikeinterface import append_recordings, concatenate_recordings
 
 ##############################################################################
diff --git a/examples/tutorials/curation/plot_1_automated_curation.py b/examples/tutorials/curation/plot_1_automated_curation.py
index 97fc05bc6e..8826852cdc 100644
--- a/examples/tutorials/curation/plot_1_automated_curation.py
+++ b/examples/tutorials/curation/plot_1_automated_curation.py
@@ -193,7 +193,7 @@ def calculate_moving_avg(label_df, confidence_label, window_size):
 plt.figure(figsize=(6, 6))
 plt.plot(p_agreement_sorted, p_agreement_moving_avg, label = 'Moving Average')
 plt.axhline(y=1/len(np.unique(predictions)), color='black', linestyle='--', label='Chance')
-plt.xlabel('Confidence'); #plt.xlim(0.5, 1)
+plt.xlabel('Confidence') #plt.xlim(0.5, 1)
 plt.ylabel('Proportion Agreement with Human Label'); plt.ylim(0, 1)
 plt.title('Agreement vs Confidence (Moving Average)')
 plt.legend(); plt.grid(True); plt.show()
diff --git a/examples/tutorials/widgets/plot_3_waveforms_gallery.py b/examples/tutorials/widgets/plot_3_waveforms_gallery.py
index 76041aab1a..94276a72e0 100644
--- a/examples/tutorials/widgets/plot_3_waveforms_gallery.py
+++ b/examples/tutorials/widgets/plot_3_waveforms_gallery.py
@@ -8,7 +8,6 @@
 import matplotlib.pyplot as plt
 
 import spikeinterface as si
-import spikeinterface.extractors as se
 import spikeinterface.widgets as sw
 
 ##############################################################################
diff --git a/installation_tips/check_your_install.py b/installation_tips/check_your_install.py
index caafe09e24..cdaa702e8d 100644
--- a/installation_tips/check_your_install.py
+++ b/installation_tips/check_your_install.py
@@ -11,11 +11,11 @@
 
 
 def check_import_si():
-    import spikeinterface as si
+    pass
 
 
 def check_import_si_full():
-    import spikeinterface.full as si
+    pass
 
 
 def _create_recording(short=False):
diff --git a/pyproject.toml b/pyproject.toml
index 4990bfba0d..aa741e9373 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -51,13 +51,15 @@ include = ["spikeinterface*"]
 namespaces = false
 exclude = ["spikeinterface.*.tests"]
 
-[tool.black]
-line-length = 120
-
 [tool.ruff]
 line-length = 120
 [tool.ruff.lint]
-select = ['F401']
+select = ['E4', 'E7', 'E9', 'F']
+exclude = ["**/tests/**", "**/test_*.py", "**/conftest.py"]
+ignore = ['E741', 'E731', 'F821']
+[tool.ruff.lint.per-file-ignores]
+"**/__init__.py" = ["F401"]
+"src/spikeinterface/core/testing_tools.py" = ["E402","F403"]
 
 [project.urls]
 homepage = "https://github.com/SpikeInterface/spikeinterface"
@@ -237,7 +239,7 @@ docs = [
 
 dev = [
     "spikeinterface[docs]",
-    "black",
+    "ruff",
     "pre-commit",
 ]
 
@@ -347,7 +349,7 @@ test-all = [
 
 # Tools for the pre-commit hooks. uv installs this group by default.
 dev = [
-    "black",
+    "ruff",
     "pre-commit",
 ]
 
diff --git a/src/spikeinterface/benchmark/benchmark_base.py b/src/spikeinterface/benchmark/benchmark_base.py
index 47ec6a70cd..ebf4b0dde5 100644
--- a/src/spikeinterface/benchmark/benchmark_base.py
+++ b/src/spikeinterface/benchmark/benchmark_base.py
@@ -8,8 +8,6 @@
 
 
 from spikeinterface.core import SortingAnalyzer, ChannelSparsity, NumpySorting
-from spikeinterface.core import SortingAnalyzer, NumpySorting
-from spikeinterface.core.job_tools import fix_job_kwargs, split_job_kwargs
 from spikeinterface import load, create_sorting_analyzer, load_sorting_analyzer
 from spikeinterface.widgets import get_some_colors
 
@@ -332,7 +330,6 @@ def run(self, case_keys=None, keep=True, verbose=False, **job_kwargs):
 
         job_keys = []
         for key in case_keys:
-
             result_folder = self.folder / "results" / self.key_to_str(key)
             sorter_folder = self.folder / "sorters" / self.key_to_str(key)
 
@@ -443,9 +440,9 @@ def get_grouped_keys_mapping(self, levels_to_group_by=None, case_keys=None):
             keys_mapping = {key: [key] for key in case_keys}
         else:
             study_levels = self.levels
-            assert np.all(
-                [l in study_levels for l in levels_to_group_by]
-            ), f"levels_to_group_by must be in {study_levels}, got {levels_to_group_by}"
+            assert np.all([l in study_levels for l in levels_to_group_by]), (
+                f"levels_to_group_by must be in {study_levels}, got {levels_to_group_by}"
+            )
             keys_mapping = {}
             for key in case_keys:
                 new_key = tuple(key[list(study_levels).index(level)] for level in levels_to_group_by)
@@ -609,7 +606,6 @@ def get_pairs_by_level(self, level):
 
         pairs = []
         for key in self.cases.keys():
-
             case0 = list(key)
             case1 = list(key)
             case0[level_index] = possible_values[0]
@@ -702,7 +698,6 @@ def load_folder(cls, folder):
 
                 zarr_folder = folder / k
                 if zarr_folder.exists():
-
                     result[k] = Templates.from_zarr(zarr_folder)
             elif format == "sorting_analyzer":
                 analyzer_folder = folder / k
diff --git a/src/spikeinterface/benchmark/benchmark_clustering.py b/src/spikeinterface/benchmark/benchmark_clustering.py
index 8b5b6de3b8..0af908ff20 100644
--- a/src/spikeinterface/benchmark/benchmark_clustering.py
+++ b/src/spikeinterface/benchmark/benchmark_clustering.py
@@ -1,20 +1,15 @@
 from spikeinterface.sortingcomponents.clustering import find_clusters_from_peaks
 from spikeinterface.core import NumpySorting
 from spikeinterface.comparison import GroundTruthComparison
-from spikeinterface.widgets import (
-    plot_probe_map,
-    plot_agreement_matrix,
-)
 
 
 import numpy as np
-from spikeinterface.core.job_tools import fix_job_kwargs, split_job_kwargs
+from spikeinterface.core.job_tools import fix_job_kwargs
 from .benchmark_base import Benchmark, BenchmarkStudy, MixinStudyUnitCount
 from spikeinterface.core.sortinganalyzer import create_sorting_analyzer
 
 
 class ClusteringBenchmark(Benchmark):
-
     def __init__(self, recording, gt_sorting, params, indices, peaks, exhaustive_gt=True):
         self.recording = recording
         self.gt_sorting = gt_sorting
@@ -238,7 +233,6 @@ def plot_error_metrics(self, metric="cosine", case_keys=None, figsize=(15, 5)):
         fig, axes = plt.subplots(ncols=len(case_keys), nrows=1, figsize=figsize, squeeze=False)
 
         for count, key in enumerate(case_keys):
-
             result = self.get_result(key)
             scores = result["gt_comparison"].get_ordered_agreement_scores()
 
@@ -279,7 +273,6 @@ def plot_metrics_vs_snr(self, metric="agreement", case_keys=None, figsize=(15, 5
             fig = None
 
         for count, key in enumerate(case_keys):
-
             result = self.get_result(key)
             scores = result["gt_comparison"].agreement_scores
 
@@ -334,7 +327,6 @@ def plot_metrics_vs_depth_and_snr(self, metric="agreement", case_keys=None, figs
         fig, axes = plt.subplots(ncols=len(case_keys), nrows=1, figsize=figsize, squeeze=False)
 
         for count, key in enumerate(case_keys):
-
             result = self.get_result(key)
             scores = result["gt_comparison"].agreement_scores
 
diff --git a/src/spikeinterface/benchmark/benchmark_matching.py b/src/spikeinterface/benchmark/benchmark_matching.py
index 8f28f18a73..c6d4ec4fa5 100644
--- a/src/spikeinterface/benchmark/benchmark_matching.py
+++ b/src/spikeinterface/benchmark/benchmark_matching.py
@@ -4,7 +4,6 @@
 from spikeinterface.core import NumpySorting
 from spikeinterface.comparison import CollisionGTComparison, compare_sorter_to_ground_truth
 from spikeinterface.widgets import (
-    plot_agreement_matrix,
     plot_comparison_collision_by_similarity,
 )
 
@@ -14,7 +13,6 @@
 
 
 class MatchingBenchmark(Benchmark):
-
     def __init__(self, recording, gt_sorting, params):
         self.recording = recording
         self.gt_sorting = gt_sorting
diff --git a/src/spikeinterface/benchmark/benchmark_merging.py b/src/spikeinterface/benchmark/benchmark_merging.py
index 5f16ce3cab..0b25d851fa 100644
--- a/src/spikeinterface/benchmark/benchmark_merging.py
+++ b/src/spikeinterface/benchmark/benchmark_merging.py
@@ -7,12 +7,10 @@
     plot_crosscorrelograms,
 )
 
-import numpy as np
 from .benchmark_base import Benchmark, BenchmarkStudy
 
 
 class MergingBenchmark(Benchmark):
-
     def __init__(self, recording, splitted_sorting, params, gt_sorting, splitted_cells=None):
         self.recording = recording
         self.splitted_sorting = splitted_sorting
@@ -45,7 +43,6 @@ def compute_result(self, match_score=0.5, exhaustive_gt=True):
 
 
 class MergingStudy(BenchmarkStudy):
-
     benchmark_class = MergingBenchmark
 
     def create_benchmark(self, key):
diff --git a/src/spikeinterface/benchmark/benchmark_motion_estimation.py b/src/spikeinterface/benchmark/benchmark_motion_estimation.py
index fabca60b2d..b864b34bba 100644
--- a/src/spikeinterface/benchmark/benchmark_motion_estimation.py
+++ b/src/spikeinterface/benchmark/benchmark_motion_estimation.py
@@ -1,6 +1,3 @@
-import json
-from pathlib import Path
-import pickle
 import time
 
 import numpy as np
@@ -183,7 +180,6 @@ def plot_drift(
             case_keys = list(self.cases.keys())
 
         for key in case_keys:
-
             bench = self.benchmarks[key]
 
             fig = plt.figure(figsize=figsize)
@@ -258,7 +254,6 @@ def plot_errors(self, case_keys=None, figsize=None, lim=None):
             case_keys = list(self.cases.keys())
 
         for key in case_keys:
-
             bench = self.benchmarks[key]
             label = self.cases[key]["label"]
 
@@ -329,7 +324,6 @@ def plot_summary_errors(self, case_keys=None, show_legend=True, figsize=(15, 5))
         colors = self.get_colors()
 
         for count, key in enumerate(case_keys):
-
             bench = self.benchmarks[key]
             label = self.cases[key]["label"]
 
diff --git a/src/spikeinterface/benchmark/benchmark_peak_localization.py b/src/spikeinterface/benchmark/benchmark_peak_localization.py
index f38e1de916..054ef3f38d 100644
--- a/src/spikeinterface/benchmark/benchmark_peak_localization.py
+++ b/src/spikeinterface/benchmark/benchmark_peak_localization.py
@@ -9,7 +9,6 @@
 
 
 class PeakLocalizationBenchmark(Benchmark):
-
     def __init__(self, recording, gt_sorting, params, gt_positions, channel_from_template=False):
         self.recording = recording
         self.gt_sorting = gt_sorting
@@ -69,7 +68,6 @@ def compute_result(self, **result_params):
 
 
 class PeakLocalizationStudy(BenchmarkStudy):
-
     benchmark_class = PeakLocalizationBenchmark
 
     def create_benchmark(self, key):
@@ -152,7 +150,6 @@ def plot_comparison_positions(self, case_keys=None):
 
 
 class UnitLocalizationBenchmark(Benchmark):
-
     def __init__(self, recording, gt_sorting, params, gt_positions):
         self.recording = recording
         self.gt_sorting = gt_sorting
@@ -264,8 +261,6 @@ def plot_comparison_positions(self, case_keys=None):
             zdx = np.argsort(distances_to_center)
             idx = np.argsort(norms)
 
-            from scipy.signal import savgol_filter
-
             wdx = np.argsort(snrs)
 
             data = result["errors"]
diff --git a/src/spikeinterface/benchmark/benchmark_peak_selection.py b/src/spikeinterface/benchmark/benchmark_peak_selection.py
index a18743f81b..a0b0c72c3d 100644
--- a/src/spikeinterface/benchmark/benchmark_peak_selection.py
+++ b/src/spikeinterface/benchmark/benchmark_peak_selection.py
@@ -1,16 +1,7 @@
-from spikeinterface.sortingcomponents.clustering import find_clusters_from_peaks
-from spikeinterface.core import NumpySorting
-from spikeinterface.comparison import GroundTruthComparison
-from spikeinterface.comparison.comparisontools import make_matching_events
-from spikeinterface.core import get_noise_levels
-
-import numpy as np
-
 from .benchmark_base import Benchmark, BenchmarkStudy
 
 
 class PeakSelectionBenchmark(Benchmark):
-
     def __init__(self, recording, gt_sorting, params, indices, exhaustive_gt=True):
         pass
 
@@ -34,7 +25,6 @@ def compute_result(self, **result_params):
 
 
 class PeakSelectionStudy(BenchmarkStudy):
-
     benchmark_class = PeakSelectionBenchmark
 
     def create_benchmark(self, key):
diff --git a/src/spikeinterface/benchmark/benchmark_plot_tools.py b/src/spikeinterface/benchmark/benchmark_plot_tools.py
index 7f0fc64cb4..530678da5b 100644
--- a/src/spikeinterface/benchmark/benchmark_plot_tools.py
+++ b/src/spikeinterface/benchmark/benchmark_plot_tools.py
@@ -1,7 +1,4 @@
-import warnings
-
 import numpy as np
-from spikeinterface.widgets import get_some_colors
 from .benchmark_tools import sigmoid, fit_sigmoid
 
 
@@ -308,7 +305,7 @@ def plot_unit_counts(
                 else:
                     yerr = None
 
-            if not "well_detected" in col and revert_bad:
+            if "well_detected" not in col and revert_bad:
                 y = -y
 
             if i == 0:
@@ -455,7 +452,6 @@ def _plot_performances_vs_metric(
         fig = axs[0].get_figure()
 
     for count, performance_name in enumerate(performance_names):
-
         ax = axs[count]
         if levels_to_group_by is not None:
             case_group_keys, labels = study.get_grouped_keys_mapping(
@@ -467,9 +463,9 @@ def _plot_performances_vs_metric(
 
         colors = study.get_colors(levels_to_group_by=levels_to_group_by)
 
-        assert all(
-            [key in colors for key in case_group_keys]
-        ), f"colors must have a color for each case key: {case_group_keys}"
+        assert all([key in colors for key in case_group_keys]), (
+            f"colors must have a color for each case key: {case_group_keys}"
+        )
 
         for key, key_list in case_group_keys.items():
             color = colors[key]
@@ -827,9 +823,9 @@ def plot_performances_swarm(
     perfs = study.get_performance_by_unit(case_keys=case_keys)
     perfs, case_keys, _, _ = aggregate_dataframe_by_levels(perfs, study, case_keys, levels_to_group_by)
 
-    assert all(
-        [key in performance_colors for key in performance_names]
-    ), f"performance_colors must have a color for each performance name: {performance_names}"
+    assert all([key in performance_colors for key in performance_names]), (
+        f"performance_colors must have a color for each performance name: {performance_names}"
+    )
 
     if ax is None:
         fig, ax = plt.subplots(figsize=figsize)
@@ -897,9 +893,9 @@ def plot_performances_comparison(
     num_methods = len(case_keys)
     assert num_methods >= 2, "plot_performances_comparison need at least 2 cases!"
 
-    assert all(
-        [key in performance_colors for key in performance_names]
-    ), f"performance_colors must have a color for each performance name: {performance_names}"
+    assert all([key in performance_colors for key in performance_names]), (
+        f"performance_colors must have a color for each performance name: {performance_names}"
+    )
 
     if axs is None:
         fig, axs = plt.subplots(ncols=num_methods - 1, nrows=num_methods - 1, figsize=figsize, squeeze=False)
@@ -1081,7 +1077,6 @@ def plot_performance_losses(
         fig = axs[0].get_figure()
 
     for count, perf_name in enumerate(performance_names):
-
         ax = axs[count]
 
         positions = study.get_gt_unit_locations(case0)
diff --git a/src/spikeinterface/benchmark/benchmark_sorter.py b/src/spikeinterface/benchmark/benchmark_sorter.py
index 932334f209..e22aafae28 100644
--- a/src/spikeinterface/benchmark/benchmark_sorter.py
+++ b/src/spikeinterface/benchmark/benchmark_sorter.py
@@ -2,7 +2,6 @@
 This replace the previous `GroundTruthStudy`
 """
 
-import numpy as np
 from spikeinterface.core import NumpySorting, create_sorting_analyzer
 from .benchmark_base import Benchmark, BenchmarkStudy, MixinStudyUnitCount
 from spikeinterface.sorters import run_sorter
diff --git a/src/spikeinterface/benchmark/benchmark_sorter_without_gt.py b/src/spikeinterface/benchmark/benchmark_sorter_without_gt.py
index 818ed3f009..c9c26b0d29 100644
--- a/src/spikeinterface/benchmark/benchmark_sorter_without_gt.py
+++ b/src/spikeinterface/benchmark/benchmark_sorter_without_gt.py
@@ -4,7 +4,7 @@
 
 import numpy as np
 from spikeinterface.core import NumpySorting, create_sorting_analyzer
-from .benchmark_base import Benchmark, BenchmarkStudy, MixinStudyUnitCount
+from .benchmark_base import Benchmark, BenchmarkStudy
 from spikeinterface.sorters import run_sorter
 from spikeinterface.comparison import compare_multiple_sorters
 
@@ -107,7 +107,6 @@ def compute_results(
         groups = self._get_comparison_groups()
 
         for data_key, group in groups.items():
-
             sorting_list = [self.get_result(key)["sorting"] for key in group]
             name_list = [key for key in group]
             multi_comp = compare_multiple_sorters(
diff --git a/src/spikeinterface/benchmark/tests/common_benchmark_testing.py b/src/spikeinterface/benchmark/tests/common_benchmark_testing.py
index 49f9e9350a..7a77b40342 100644
--- a/src/spikeinterface/benchmark/tests/common_benchmark_testing.py
+++ b/src/spikeinterface/benchmark/tests/common_benchmark_testing.py
@@ -4,12 +4,9 @@
 This only a local testing.
 """
 
-import pytest
-from pathlib import Path
 import os
 from spikeinterface.core.job_tools import fix_job_kwargs
 
-import numpy as np
 
 from spikeinterface.core import (
     generate_ground_truth_recording,
diff --git a/src/spikeinterface/benchmark/tests/test_benchmark_merging.py b/src/spikeinterface/benchmark/tests/test_benchmark_merging.py
index 022ba18ebd..e09faa10af 100644
--- a/src/spikeinterface/benchmark/tests/test_benchmark_merging.py
+++ b/src/spikeinterface/benchmark/tests/test_benchmark_merging.py
@@ -1,6 +1,5 @@
 import pytest
 from pathlib import Path
-import numpy as np
 
 import shutil
 
diff --git a/src/spikeinterface/benchmark/tests/test_benchmark_sorter_without_gt.py b/src/spikeinterface/benchmark/tests/test_benchmark_sorter_without_gt.py
index 62492cbdbe..15131e0f28 100644
--- a/src/spikeinterface/benchmark/tests/test_benchmark_sorter_without_gt.py
+++ b/src/spikeinterface/benchmark/tests/test_benchmark_sorter_without_gt.py
@@ -3,7 +3,6 @@
 from pathlib import Path
 
 from spikeinterface import generate_ground_truth_recording
-from spikeinterface.preprocessing import bandpass_filter
 from spikeinterface.benchmark import SorterStudyWithoutGroundTruth
 
 
diff --git a/src/spikeinterface/benchmark/tests/test_residual_analysis.py b/src/spikeinterface/benchmark/tests/test_residual_analysis.py
index 738e4ac3fe..4d01590681 100644
--- a/src/spikeinterface/benchmark/tests/test_residual_analysis.py
+++ b/src/spikeinterface/benchmark/tests/test_residual_analysis.py
@@ -1,6 +1,4 @@
-import shutil
 import pytest
-from pathlib import Path
 
 
 from spikeinterface.benchmark.tests.common_benchmark_testing import make_dataset
diff --git a/src/spikeinterface/comparison/basecomparison.py b/src/spikeinterface/comparison/basecomparison.py
index 3b6dd47c5a..d532f59a2d 100644
--- a/src/spikeinterface/comparison/basecomparison.py
+++ b/src/spikeinterface/comparison/basecomparison.py
@@ -28,7 +28,6 @@ class BaseMultiComparison(BaseComparison):
     """
 
     def __init__(self, object_list, name_list, match_score=0.5, chance_score=0.1, verbose=False, n_jobs=1):
-        import networkx as nx
 
         BaseComparison.__init__(
             self,
diff --git a/src/spikeinterface/comparison/collision.py b/src/spikeinterface/comparison/collision.py
index f6dfcc2e95..ce803b988e 100644
--- a/src/spikeinterface/comparison/collision.py
+++ b/src/spikeinterface/comparison/collision.py
@@ -1,5 +1,3 @@
-import importlib
-
 from .paircomparisons import GroundTruthComparison
 
 from .comparisontools import make_collision_events
@@ -161,7 +159,6 @@ def compute_all_pair_collision_bins(self):
             loop = tqdm(loop, desc="collision by bin")
 
         for c in loop:
-
             score1 = labels_st1[unit_ids1[c]][seg_index][spike_indices1[c]]
             score2 = labels_st1[unit_ids2[c]][seg_index][spike_indices2[c]]
 
diff --git a/src/spikeinterface/comparison/comparisontools.py b/src/spikeinterface/comparison/comparisontools.py
index 4892014575..90e807f45d 100644
--- a/src/spikeinterface/comparison/comparisontools.py
+++ b/src/spikeinterface/comparison/comparisontools.py
@@ -275,9 +275,9 @@ def make_match_count_matrix(
 
     num_segments_sorting1 = sorting1.get_num_segments()
     num_segments_sorting2 = sorting2.get_num_segments()
-    assert (
-        num_segments_sorting1 == num_segments_sorting2
-    ), "make_match_count_matrix : sorting1 and sorting2 must have the same segment number"
+    assert num_segments_sorting1 == num_segments_sorting2, (
+        "make_match_count_matrix : sorting1 and sorting2 must have the same segment number"
+    )
 
     # Segments should be matched one by one
     for segment_index in range(num_segments_sorting1):
@@ -495,7 +495,6 @@ def make_best_match(agreement_scores, min_score) -> "tuple[pd.Series, pd.Series]
     best_match_21 : pd.Series
 
     """
-    import pandas as pd
 
     unit1_ids = np.array(agreement_scores.index)
     unit2_ids = np.array(agreement_scores.columns)
@@ -539,7 +538,6 @@ def make_hungarian_match(agreement_scores, min_score):
     hungarian_match_21 : pd.Series
 
     """
-    import pandas as pd
 
     unit1_ids = np.array(agreement_scores.index)
     unit2_ids = np.array(agreement_scores.columns)
@@ -1328,9 +1326,9 @@ def compute_distance_matrix(
 
     num_segments_sorting1 = sorting1.get_num_segments()
     num_segments_sorting2 = sorting2.get_num_segments()
-    assert (
-        num_segments_sorting1 == num_segments_sorting2
-    ), "make_match_count_matrix : sorting1 and sorting2 must have the same number of segments"
+    assert num_segments_sorting1 == num_segments_sorting2, (
+        "make_match_count_matrix : sorting1 and sorting2 must have the same number of segments"
+    )
 
     squared_norm_1_vector = _compute_spike_vector_squared_norm(spike_vector_per_segment1, num_units1, delta_frames)
     squared_norm_2_vector = _compute_spike_vector_squared_norm(spike_vector_per_segment2, num_units2, delta_frames)
@@ -1401,9 +1399,9 @@ def calculate_generalized_comparison_metrics(
 
     num_segments_sorting1 = sorting1.get_num_segments()
     num_segments_sorting2 = sorting2.get_num_segments()
-    assert (
-        num_segments_sorting1 == num_segments_sorting2
-    ), "make_match_count_matrix : sorting1 and sorting2 must have the same number of segments"
+    assert num_segments_sorting1 == num_segments_sorting2, (
+        "make_match_count_matrix : sorting1 and sorting2 must have the same number of segments"
+    )
 
     squared_norm1 = _compute_spike_vector_squared_norm(spike_vector1_segments, num_units2, delta_frames)
     squared_norm2 = _compute_spike_vector_squared_norm(spike_vector2_segments, num_units2, delta_frames)
diff --git a/src/spikeinterface/comparison/multicomparisons.py b/src/spikeinterface/comparison/multicomparisons.py
index a0feda4a52..e3740c7e36 100644
--- a/src/spikeinterface/comparison/multicomparisons.py
+++ b/src/spikeinterface/comparison/multicomparisons.py
@@ -1,11 +1,6 @@
-from pathlib import Path
-import json
-import pickle
-import warnings
-
 import numpy as np
 
-from spikeinterface.core import load, BaseSorting, BaseSortingSegment
+from spikeinterface.core import BaseSorting, BaseSortingSegment
 from spikeinterface.core.core_tools import define_function_from_class
 from .basecomparison import BaseMultiComparison, MixinSpikeTrainComparison, MixinTemplateComparison
 from .paircomparisons import SymmetricSortingComparison, TemplateComparison
diff --git a/src/spikeinterface/comparison/paircomparisons.py b/src/spikeinterface/comparison/paircomparisons.py
index 47e85a03de..be05ca5d8a 100644
--- a/src/spikeinterface/comparison/paircomparisons.py
+++ b/src/spikeinterface/comparison/paircomparisons.py
@@ -39,7 +39,7 @@ def __init__(
         if sorting2_name is None:
             sorting2_name = "sorting2"
         assert sorting1.get_num_segments() == sorting2.get_num_segments(), (
-            "The two sortings must have the same " "number of segments! "
+            "The two sortings must have the same number of segments! "
         )
 
         BasePairComparison.__init__(
@@ -100,7 +100,6 @@ def _do_agreement(self):
                 self.match_event_count, self.event_counts1, self.event_counts2
             )
         elif self.agreement_method == "distance":
-
             self.agreement_scores = calculate_agreement_scores_with_distance(
                 self.sorting1,
                 self.sorting2,
@@ -294,7 +293,6 @@ def __init__(
         compute_misclassifications: bool = False,
         verbose: bool = False,
     ):
-        import pandas as pd
 
         if gt_name is None:
             gt_name = "ground truth"
diff --git a/src/spikeinterface/comparison/tests/test_groundtruthcomparison.py b/src/spikeinterface/comparison/tests/test_groundtruthcomparison.py
index 27b8f73077..48b91c6877 100644
--- a/src/spikeinterface/comparison/tests/test_groundtruthcomparison.py
+++ b/src/spikeinterface/comparison/tests/test_groundtruthcomparison.py
@@ -1,4 +1,3 @@
-import numpy as np
 from numpy.testing import assert_array_equal
 
 
diff --git a/src/spikeinterface/comparison/tests/test_multisortingcomparison.py b/src/spikeinterface/comparison/tests/test_multisortingcomparison.py
index 72f39f74ea..64f4efdc1d 100644
--- a/src/spikeinterface/comparison/tests/test_multisortingcomparison.py
+++ b/src/spikeinterface/comparison/tests/test_multisortingcomparison.py
@@ -8,7 +8,7 @@
 from spikeinterface.core import generate_sorting
 from spikeinterface.core.job_tools import get_usable_cpu_count
 from spikeinterface.extractors import NumpySorting
-from spikeinterface.comparison import compare_multiple_sorters, MultiSortingComparison
+from spikeinterface.comparison import compare_multiple_sorters
 
 ON_GITHUB = bool(os.getenv("GITHUB_ACTIONS"))
 
diff --git a/src/spikeinterface/comparison/tests/test_templatecomparison.py b/src/spikeinterface/comparison/tests/test_templatecomparison.py
index 001f80f4f6..6879629e6d 100644
--- a/src/spikeinterface/comparison/tests/test_templatecomparison.py
+++ b/src/spikeinterface/comparison/tests/test_templatecomparison.py
@@ -1,5 +1,3 @@
-import shutil
-import pytest
 import numpy as np
 
 from spikeinterface.core import create_sorting_analyzer, generate_ground_truth_recording
diff --git a/src/spikeinterface/core/analyzer_extension_core.py b/src/spikeinterface/core/analyzer_extension_core.py
index 070176244f..8159c18160 100644
--- a/src/spikeinterface/core/analyzer_extension_core.py
+++ b/src/spikeinterface/core/analyzer_extension_core.py
@@ -181,7 +181,6 @@ def _run(self, verbose=False, **job_kwargs):
         self.data.clear()
 
         recording = self.sorting_analyzer.recording
-        sorting = self.sorting_analyzer.sorting
 
         # retrieve spike vector and the sampling
         some_spikes = self.sorting_analyzer.get_extension("random_spikes").get_random_spikes()
@@ -252,8 +251,6 @@ def _select_units_extension_data(self, unit_ids):
         some_spikes = self.sorting_analyzer.get_extension("random_spikes").get_random_spikes()
 
         keep_unit_indices = self.sorting_analyzer.sorting.ids_to_indices(unit_ids)
-        spikes = self.sorting_analyzer.sorting.to_spike_vector()
-        # some_spikes = spikes[random_spikes_indices]
         keep_spike_mask = np.isin(some_spikes["unit_index"], keep_unit_indices)
 
         new_data = dict()
@@ -529,9 +526,9 @@ def _compute_and_append_from_waveforms(self, operators):
         # spikes = self.sorting_analyzer.sorting.to_spike_vector()
         # some_spikes = spikes[self.sorting_analyzer.random_spikes_indices]
 
-        assert self.sorting_analyzer.has_extension(
-            "random_spikes"
-        ), "compute 'templates' requires the random_spikes extension. You can run sorting_analyzer.compute('random_spikes')"
+        assert self.sorting_analyzer.has_extension("random_spikes"), (
+            "compute 'templates' requires the random_spikes extension. You can run sorting_analyzer.compute('random_spikes')"
+        )
         some_spikes = self.sorting_analyzer.get_extension("random_spikes").get_random_spikes()
         for unit_index, unit_id in enumerate(unit_ids):
             spike_mask = some_spikes["unit_index"] == unit_index
@@ -1359,7 +1356,6 @@ def _run(self, **job_kwargs):
         # Check if we need to propagate any old metrics. If so, we'll do that.
         # Otherwise, we'll avoid attempting to load an empty metrics.
         if set(self.params["metrics_to_compute"]) != set(self.params["metric_names"]):
-
             extension = self.sorting_analyzer.get_extension(self.extension_name)
             if delete_existing_metrics is False and extension is not None and extension.data.get("metrics") is not None:
                 existing_metrics = extension.params["metric_names"]
@@ -1451,7 +1447,6 @@ def _merge_extension_data(
         dict
             Dictionary containing the merged metrics DataFrame.
         """
-        import pandas as pd
 
         available_metric_names = self.get_available_metric_names()
         metric_names = [m for m in self.params["metric_names"] if m in available_metric_names]
@@ -1497,7 +1492,6 @@ def _split_extension_data(
         verbose : bool, default: False
             Whether to print verbose output.
         """
-        import pandas as pd
         from itertools import chain
 
         available_metric_names = [m.metric_name for m in self.metric_list]
@@ -1524,7 +1518,6 @@ def _split_extension_data(
         return new_data
 
     def set_data(self, ext_data_name, data):
-        import pandas as pd
 
         if ext_data_name == "metrics":
             metrics = self._cast_metrics(data)
@@ -1629,9 +1622,9 @@ def _get_data(self, outputs="numpy", concatenated=False, return_data_name=None,
             if return_data_name is None:
                 return_data_name = self.nodepipeline_variables[0]
             else:
-                assert (
-                    return_data_name in self.nodepipeline_variables
-                ), f"return_data_name {return_data_name} not in nodepipeline_variables {self.nodepipeline_variables}"
+                assert return_data_name in self.nodepipeline_variables, (
+                    f"return_data_name {return_data_name} not in nodepipeline_variables {self.nodepipeline_variables}"
+                )
 
         all_data = self.data[return_data_name]
         # data gathered directly into a zarr store (e.g. by the node pipeline) is kept as a
@@ -1799,12 +1792,10 @@ def _select_channels_sparse_data(old_sorting_analyzer, old_data, new_channel_ids
     new_data = np.zeros_like(old_data)
     max_num_active_channels = 0
     for data_index, (one_old_data, unit_index) in enumerate(zip(old_data, random_spikes["unit_index"])):
-
         unit_id = unit_ids[unit_index]
         channel_slice = unit_sparsity_slices[unit_id]
 
         if len(channel_slice) > 0:
-
             size_of_new_mask = len(channel_slice)
             new_data[data_index, :, :size_of_new_mask] = one_old_data[:, channel_slice]
 
diff --git a/src/spikeinterface/core/base.py b/src/spikeinterface/core/base.py
index dbecd82bbe..eae31791a3 100644
--- a/src/spikeinterface/core/base.py
+++ b/src/spikeinterface/core/base.py
@@ -1,5 +1,4 @@
 from pathlib import Path
-import shutil
 from typing import Any
 from collections.abc import Iterable, Sequence
 import importlib
@@ -7,26 +6,19 @@
 import weakref
 import json
 import pickle
-import random
-import string
 from packaging.version import parse
 from copy import deepcopy
 
 import numpy as np
 
-from .globals import get_global_tmp_folder, is_set_global_tmp_folder
 from .core_tools import (
-    clean_zarr_folder_name,
     is_dict_extractor,
     SIJsonEncoder,
-    is_path_remote,
     make_paths_relative,
     make_paths_absolute,
     check_paths_relative,
     retrieve_importing_provenance,
-    load_properties_from_folder,
 )
-from .job_tools import _shared_job_kwargs_doc
 
 # base dtypes used throughout spikeinterface
 base_peak_dtype = [
@@ -87,9 +79,9 @@ def __init__(self, main_ids: Sequence) -> None:
             # string column. Store it as fixed-width unicode like every other source.
             self._main_ids = np.array(self._main_ids.tolist())
         if len(self._main_ids) > 0:
-            assert (
-                self._main_ids.dtype.kind in "uiSU"
-            ), f"Main IDs can only be integers (signed/unsigned) or strings, not {self._main_ids.dtype}"
+            assert self._main_ids.dtype.kind in "uiSU", (
+                f"Main IDs can only be integers (signed/unsigned) or strings, not {self._main_ids.dtype}"
+            )
 
         self._segments: "list[BaseSegment]" = []
 
@@ -117,7 +109,7 @@ def _get_common_repr_html(self, common_style):
         html_annotations = f"<details style='{common_style}'>  <summary><strong>Annotations</strong></summary><ul>"
         for key, value in self._annotations.items():
             html_annotations += f"<li> <strong> {key} </strong>: {value}</li>"
-        html_annotations += f"</details>"
+        html_annotations += "</details>"
 
         html_properties = f"<details style='{common_style}'><summary><strong>Properties</strong></summary><ul>"
         for key, value in self._properties.items():
@@ -337,9 +329,9 @@ def set_property(
         dtype_kind = dtype.kind
 
         if ids is None:
-            assert (
-                values.shape[0] == size
-            ), f"Values must have the same size as the main ids: {size} but got array of size {values.shape[0]}"
+            assert values.shape[0] == size, (
+                f"Values must have the same size as the main ids: {size} but got array of size {values.shape[0]}"
+            )
             self._properties[key] = values
         else:
             ids = np.array(ids)
@@ -351,7 +343,6 @@ def set_property(
             # Sam: this is used because you could set all ids (like the None) but with the vector.
             if ids.size < size:
                 if key not in self._properties:
-
                     if missing_value is None:
                         if dtype_kind not in self.default_missing_property_values.keys():
                             raise ValueError(
@@ -386,9 +377,9 @@ def set_property(
                         return
                 else:
                     existing_property = self._properties[key].dtype
-                    assert (
-                        dtype_kind == existing_property.kind
-                    ), f"Mismatch between existing property dtype {existing_property.kind} and provided values dtype {dtype_kind}."
+                    assert dtype_kind == existing_property.kind, (
+                        f"Mismatch between existing property dtype {existing_property.kind} and provided values dtype {dtype_kind}."
+                    )
 
                 indices = self.ids_to_indices(ids)
                 if dtype_kind == "U":
@@ -690,7 +681,7 @@ def _get_file_path(file_path: str | Path, extensions: Sequence) -> Path:
         folder_path = file_path.parent
         if Path(file_path).suffix == "":
             file_path = folder_path / (str(file_path) + ext)
-        assert file_path.suffix in extensions, "'file_path' should have one of the following extensions:" " %s" % (
+        assert file_path.suffix in extensions, "'file_path' should have one of the following extensions: %s" % (
             ", ".join(extensions)
         )
         return file_path
@@ -964,7 +955,7 @@ def _get_class_from_string(class_string):
 
     try:
         imported_class = getattr(imported_module, class_name)
-    except:
+    except Exception:
         imported_class = None
 
     return imported_class
diff --git a/src/spikeinterface/core/baserecording.py b/src/spikeinterface/core/baserecording.py
index d4bb36f2ab..4228b3d825 100644
--- a/src/spikeinterface/core/baserecording.py
+++ b/src/spikeinterface/core/baserecording.py
@@ -7,7 +7,6 @@
 
 from .base import BaseExtractor
 from .time_series import TimeSeriesSegment, TimeSeries
-from .base import BaseExtractor
 from .core_tools import convert_bytes_to_str, convert_seconds_to_str
 from .job_tools import split_job_kwargs
 from .recording_tools import _set_group_property_based_on_probegroup, check_probe_do_not_overlap
@@ -111,7 +110,7 @@ def _repr_header(self, display_name=True):
             sampling_frequency_repr = f"{sf_hz:f} Hz"
         else:
             # Khz for high sampling rate and Hz for LFP
-            sampling_frequency_repr = f"{(sf_hz/1000.0):0.1f}kHz" if sf_hz > 10_000.0 else f"{sf_hz:0.1f}Hz"
+            sampling_frequency_repr = f"{(sf_hz / 1000.0):0.1f}kHz" if sf_hz > 10_000.0 else f"{sf_hz:0.1f}Hz"
 
         if display_name and self.name != self.__class__.__name__:
             name = f"{self.name} ({self.__class__.__name__})"
@@ -591,9 +590,9 @@ def _get_probegroup_based_on_device_channel_indices(self, probegroup: ProbeGroup
         if not isinstance(probegroup, ProbeGroup):
             raise ValueError("The input must be a ProbeGroup or dict")
 
-        assert all(
-            probe.device_channel_indices is not None for probe in probegroup.probes
-        ), "Probe must have device_channel_indices"
+        assert all(probe.device_channel_indices is not None for probe in probegroup.probes), (
+            "Probe must have device_channel_indices"
+        )
 
         # Remove unconnected contacts and slice the probe group accordingly
         device_channel_indices = probegroup.get_global_device_channel_indices()["device_channel_indices"]
@@ -1098,7 +1097,7 @@ def rename_channels(self, new_channel_ids: list | np.ndarray | tuple) -> "BaseRe
         from .channelslice import ChannelSliceRecording
 
         assert len(new_channel_ids) == self.get_num_channels(), (
-            "new_channel_ids must have the same length as the " "number of channels in the recording"
+            "new_channel_ids must have the same length as the number of channels in the recording"
         )
 
         return ChannelSliceRecording(self, renamed_channel_ids=new_channel_ids)
@@ -1142,9 +1141,9 @@ def time_slice(self, start_time: float | None, end_time: float | None) -> "BaseR
             A new recording object with only samples between start_time and end_time
         """
         num_segments = self.get_num_segments()
-        assert (
-            num_segments == 1
-        ), f"Time slicing is only supported for single segment recordings. Found {num_segments} segments."
+        assert num_segments == 1, (
+            f"Time slicing is only supported for single segment recordings. Found {num_segments} segments."
+        )
 
         t_start = self.get_start_time()
         t_end = self.get_end_time()
diff --git a/src/spikeinterface/core/basesorting.py b/src/spikeinterface/core/basesorting.py
index 84257592ef..4272d623cf 100644
--- a/src/spikeinterface/core/basesorting.py
+++ b/src/spikeinterface/core/basesorting.py
@@ -4,7 +4,6 @@
 
 import numpy as np
 
-from pathlib import Path
 
 from .base import BaseExtractor, BaseSegment, minimum_spike_dtype
 from .waveform_tools import has_exceeding_spikes
@@ -118,9 +117,9 @@ def get_num_samples(self, segment_index=None) -> int:
         int
             The number of samples
         """
-        assert (
-            self.has_recording()
-        ), "This methods requires an associated recording. Call self.register_recording() first."
+        assert self.has_recording(), (
+            "This methods requires an associated recording. Call self.register_recording() first."
+        )
         return self._recording.get_num_samples(segment_index=segment_index)
 
     def get_total_samples(self) -> int:
@@ -144,9 +143,9 @@ def get_total_duration(self) -> float:
         float
             The duration in seconds
         """
-        assert (
-            self.has_recording()
-        ), "This methods requires an associated recording. Call self.register_recording() first."
+        assert self.has_recording(), (
+            "This methods requires an associated recording. Call self.register_recording() first."
+        )
         return self._recording.get_total_duration()
 
     def search_cached_spikes_sorted(
@@ -316,7 +315,6 @@ def get_unit_spike_train_in_seconds(
         # If sorting has a registered recording, get the frames and get the times from the recording
         # Note that this take into account the segment start time of the recording
         if self.has_recording():
-
             # Get all the spike times and then slice them
             start_frame = None
             end_frame = None
@@ -385,12 +383,12 @@ def register_recording(self, recording, check_spike_frames: bool = True):
         check_spike_frames : bool, default: True
             If True, assert for each segment that all spikes are within the recording's range.
         """
-        assert np.isclose(
-            self.get_sampling_frequency(), recording.get_sampling_frequency(), atol=0.1
-        ), "The recording has a different sampling frequency than the sorting!"
-        assert (
-            self.get_num_segments() == recording.get_num_segments()
-        ), "The recording has a different number of segments than the sorting!"
+        assert np.isclose(self.get_sampling_frequency(), recording.get_sampling_frequency(), atol=0.1), (
+            "The recording has a different sampling frequency than the sorting!"
+        )
+        assert self.get_num_segments() == recording.get_num_segments(), (
+            "The recording has a different number of segments than the sorting!"
+        )
         if check_spike_frames:
             if has_exceeding_spikes(self, recording):
                 warnings.warn(
diff --git a/src/spikeinterface/core/binaryfolder.py b/src/spikeinterface/core/binaryfolder.py
index c3c4e07cb8..4f21dc7edb 100644
--- a/src/spikeinterface/core/binaryfolder.py
+++ b/src/spikeinterface/core/binaryfolder.py
@@ -1,7 +1,6 @@
 from pathlib import Path
 import json
 
-from copy import deepcopy
 import shutil
 
 import numpy as np
@@ -190,7 +189,7 @@ def write_recording(
         # All properties, annotations, and probe information are already saved in the folder,
         # so we don't need to include them in the si_folder.json
         cached = BinaryFolderRecording(folder_path=folder_path)
-        si_folder_path = folder_path / f"si_folder.json"
+        si_folder_path = folder_path / "si_folder.json"
         cached.dump_to_json(
             file_path=si_folder_path,
             relative_to=folder_path,
diff --git a/src/spikeinterface/core/binaryrecordingextractor.py b/src/spikeinterface/core/binaryrecordingextractor.py
index 37f4ba3467..4ac3fb72ba 100644
--- a/src/spikeinterface/core/binaryrecordingextractor.py
+++ b/src/spikeinterface/core/binaryrecordingextractor.py
@@ -281,7 +281,7 @@ def __del__(self):
             try:
                 self._time_vector._mmap.close()  # Close the underlying mmap object
                 del self._time_vector
-            except Exception as e:
+            except Exception:
                 pass
 
 
diff --git a/src/spikeinterface/core/channelsaggregationrecording.py b/src/spikeinterface/core/channelsaggregationrecording.py
index ae7309d1ab..6af28adeed 100644
--- a/src/spikeinterface/core/channelsaggregationrecording.py
+++ b/src/spikeinterface/core/channelsaggregationrecording.py
@@ -1,5 +1,3 @@
-import warnings
-
 import numpy as np
 
 from probeinterface import ProbeGroup
@@ -52,12 +50,11 @@ def __init__(self, recording_list_or_dict=None, renamed_channel_ids=None):
         # Generate a default list of channel ids that are unique and consecutive numbers as strings.
         num_all_channels = sum(rec.get_num_channels() for rec in recording_list)
         if renamed_channel_ids is not None:
-            assert (
-                len(np.unique(renamed_channel_ids)) == num_all_channels
-            ), "'renamed_channel_ids' doesn't have the right size or has duplicates!"
+            assert len(np.unique(renamed_channel_ids)) == num_all_channels, (
+                "'renamed_channel_ids' doesn't have the right size or has duplicates!"
+            )
             channel_ids = list(renamed_channel_ids)
         else:
-
             # Explicitly check if all channel_ids arrays are either all integers or all strings.
             all_ids_are_int_dtype = all(np.issubdtype(rec.channel_ids.dtype, np.integer) for rec in recording_list)
             all_ids_are_str_dtype = all(np.issubdtype(rec.channel_ids.dtype, np.str_) for rec in recording_list)
@@ -89,7 +86,7 @@ def __init__(self, recording_list_or_dict=None, renamed_channel_ids=None):
                             property_dict[prop_name] = np.concatenate(
                                 (property_dict[prop_name], rec.get_property(prop_name))
                             )
-                        except Exception as e:
+                        except Exception:
                             print(f"Skipping property '{prop_name}' for shape inconsistency")
                             del property_dict[prop_name]
                             break
@@ -214,7 +211,7 @@ def __init__(self, channel_map, parent_segments):
         else:
             for ps in parent_segments:
                 assert ps.get_times_kwargs()["t_start"] == times_kargs0["t_start"], (
-                    "All segments should have the same " "t_start"
+                    "All segments should have the same t_start"
                 )
 
         BaseRecordingSegment.__init__(self, **times_kargs0)
diff --git a/src/spikeinterface/core/core_tools.py b/src/spikeinterface/core/core_tools.py
index 75cf2ad64a..6404cabe4a 100644
--- a/src/spikeinterface/core/core_tools.py
+++ b/src/spikeinterface/core/core_tools.py
@@ -502,7 +502,7 @@ def check_paths_relative(input_dict, relative_folder) -> bool:
 
         # check relative is possible
         try:
-            p2 = _relative_to(p, relative_folder)
+            _ = _relative_to(p, relative_folder)
         except ValueError:
             not_possible.append(p)
             continue
@@ -562,8 +562,6 @@ def make_paths_absolute(input_dict, base_folder) -> dict:
         A copy of the input dict with modified paths.
     """
     base_folder = Path(base_folder)
-    # use as_posix instead of str to make the path unix like even on window
-    func = lambda p: (base_folder / p).resolve().absolute().as_posix()
 
     path_elements_in_dict = [e for e in extractor_dict_iterator(input_dict) if element_is_path(e)]
     output_dict = deepcopy(input_dict)
@@ -981,10 +979,10 @@ def load_annotations_from_folder(folder: str | Path, extractor: "BaseExtractor")
 def save_provenance_to_folder(folder: str | Path, extractor: "BaseExtractor", relative_to: str | Path | None = None):
     folder = Path(folder)
     if extractor.check_serializability("json"):
-        provenance_file_path = folder / f"provenance.json"
+        provenance_file_path = folder / "provenance.json"
         extractor.dump_to_json(file_path=provenance_file_path, relative_to=relative_to)
     elif extractor.check_serializability("pickle"):
-        provenance_file = folder / f"provenance.pkl"
+        provenance_file = folder / "provenance.pkl"
         extractor.dump_to_pickle(provenance_file, relative_to=folder)
     else:
         warnings.warn("The extractor is not serializable to file. The provenance will not be saved.")
diff --git a/src/spikeinterface/core/generate.py b/src/spikeinterface/core/generate.py
index 5e8c352e44..798b961935 100644
--- a/src/spikeinterface/core/generate.py
+++ b/src/spikeinterface/core/generate.py
@@ -8,9 +8,9 @@
 from .basesorting import SpikeVectorSortingSegment
 from .numpyextractors import NumpySorting
 
-from probeinterface import Probe, generate_linear_probe, generate_multi_columns_probe
+from probeinterface import generate_linear_probe, generate_multi_columns_probe
 
-from spikeinterface.core import BaseRecording, BaseRecordingSegment, BaseSorting
+from spikeinterface.core import BaseRecording, BaseRecordingSegment, BaseSorting, BaseSortingSegment
 from .core_tools import define_function_from_class, ms_to_samples, _ensure_seed
 
 
@@ -355,11 +355,11 @@ def __init__(
 
         if new_unit_ids is not None:
             new_unit_ids = list(new_unit_ids)
-            assert ~np.any(
-                np.isin(new_unit_ids, sorting.unit_ids)
-            ), "some units ids are already present. Consider using added_spikes_existing_units"
+            assert ~np.any(np.isin(new_unit_ids, sorting.unit_ids)), (
+                "some units ids are already present. Consider using added_spikes_existing_units"
+            )
             if len(new_unit_ids) > 0:
-                assert type(unit_ids[0]) == type(new_unit_ids[0]), "unit_ids should have the same type"
+                assert type(unit_ids[0]) is type(new_unit_ids[0]), "unit_ids should have the same type"
                 unit_ids = unit_ids + list(new_unit_ids)
 
         BaseSorting.__init__(self, sampling_frequency, unit_ids)
@@ -372,10 +372,9 @@ def __init__(
         self.added_spikes_from_new_mask = np.zeros(len(self._cached_spike_vector), dtype=bool)
 
         if added_spikes_existing_units is not None and len(added_spikes_existing_units) > 0:
-            assert (
-                added_spikes_existing_units.dtype == minimum_spike_dtype
-            ), "added_spikes_existing_units should be a spike vector"
-            added_unit_indices = np.arange(len(self.parent_unit_ids))
+            assert added_spikes_existing_units.dtype == minimum_spike_dtype, (
+                "added_spikes_existing_units should be a spike vector"
+            )
             self._cached_spike_vector = np.concatenate((self._cached_spike_vector, added_spikes_existing_units))
             self.added_spikes_from_existing_mask = np.concatenate(
                 (self.added_spikes_from_existing_mask, np.ones(len(added_spikes_existing_units), dtype=bool))
@@ -385,9 +384,9 @@ def __init__(
             )
 
         if added_spikes_new_units is not None and len(added_spikes_new_units) > 0:
-            assert (
-                added_spikes_new_units.dtype == minimum_spike_dtype
-            ), "added_spikes_new_units should be a spike vector"
+            assert added_spikes_new_units.dtype == minimum_spike_dtype, (
+                "added_spikes_new_units should be a spike vector"
+            )
             self._cached_spike_vector = np.concatenate((self._cached_spike_vector, added_spikes_new_units))
             self.added_spikes_from_existing_mask = np.concatenate(
                 (self.added_spikes_from_existing_mask, np.zeros(len(added_spikes_new_units), dtype=bool))
@@ -449,10 +448,10 @@ def add_from_sorting(sorting1: BaseSorting, sorting2: BaseSorting, refractory_pe
             of spikes. Any spike times in added_spikes violating the refractory period will be
             discarded.
         """
-        assert (
-            sorting1.get_sampling_frequency() == sorting2.get_sampling_frequency()
-        ), "sampling_frequency should be the same"
-        assert type(sorting1.unit_ids[0]) == type(sorting2.unit_ids[0]), "unit_ids should have the same type"
+        assert sorting1.get_sampling_frequency() == sorting2.get_sampling_frequency(), (
+            "sampling_frequency should be the same"
+        )
+        assert type(sorting1.unit_ids[0]) is type(sorting2.unit_ids[0]), "unit_ids should have the same type"
         # We detect the indices that are shared by the two sortings
         mask1 = np.isin(sorting2.unit_ids, sorting1.unit_ids)
         common_ids = sorting2.unit_ids[mask1]
@@ -1019,9 +1018,6 @@ def synthesize_amplitude_factor(
         return None
 
 
-from spikeinterface.core.basesorting import BaseSortingSegment, BaseSorting
-
-
 class SortingGenerator(BaseSorting):
     def __init__(
         self,
@@ -1686,7 +1682,6 @@ def generate_templates(
 
     """
     unit_params = unit_params or dict()
-    rng = np.random.default_rng(seed=seed)
 
     # neuron location must be 3D
     assert units_locations.shape[1] == 3
@@ -2331,9 +2326,7 @@ def generate_ground_truth_recording(
 
         prb_kwargs = generate_probe_kwargs.copy()
         if "num_contact_per_column" in prb_kwargs:
-            assert (
-                prb_kwargs["num_contact_per_column"] * prb_kwargs["num_columns"]
-            ) == num_channels, (
+            assert (prb_kwargs["num_contact_per_column"] * prb_kwargs["num_columns"]) == num_channels, (
                 "generate_multi_columns_probe : num_channels do not match num_contact_per_column x num_columns"
             )
         elif "num_contact_per_column" not in prb_kwargs and "num_columns" in prb_kwargs:
diff --git a/src/spikeinterface/core/loading.py b/src/spikeinterface/core/loading.py
index 8cc679d95e..24d0588723 100644
--- a/src/spikeinterface/core/loading.py
+++ b/src/spikeinterface/core/loading.py
@@ -1,4 +1,3 @@
-import warnings
 from pathlib import Path
 
 import json
@@ -99,7 +98,6 @@ def load(
         return _load_object_from_dict(d, object_type, base_folder=base_folder)
 
     elif is_local and file_path.is_dir():
-
         folder = file_path
         if folder.suffix == ".zarr":
             # Local zarr can be
@@ -195,7 +193,7 @@ def _guess_object_from_local_folder(folder):
     elif (folder / "waveforms").is_dir():
         # before the SortingAnlazer, it was WaveformExtractor (v<0.101)
         return "WaveformExtractor"
-    elif (folder / f"si_folder.json").is_file():
+    elif (folder / "si_folder.json").is_file():
         # In later versions (0.94<v<=0.105) we use the si_folder.json file
         # This should be Recording | Sorting
         return "Recording|Sorting"
@@ -204,8 +202,7 @@ def _guess_object_from_local_folder(folder):
         for dump_ext in ("json", "pkl", "pickle"):
             f = folder / f"cached.{dump_ext}"
             if f.is_file():
-                file = f
-        return "Recording|Sorting"
+                return "Recording|Sorting"
 
 
 def _load_object_from_folder(folder, object_type: str, **kwargs):
@@ -235,10 +232,10 @@ def _load_object_from_folder(folder, object_type: str, **kwargs):
         return analyzer
 
     elif object_type in ("Recording", "Sorting", "Recording|Sorting"):
-        if (folder / f"si_folder.json").is_file():
+        if (folder / "si_folder.json").is_file():
             # In later versions (0.94<v<0.102) we use the si_folder.json file
             # This should be Recording | Sorting
-            si_file = folder / f"si_folder.json"
+            si_file = folder / "si_folder.json"
         else:
             # For backward compatibility (v<=0.94) we check for the cached.json/pkl/pickle files
             for dump_ext in ("json", "pkl", "pickle"):
@@ -248,7 +245,6 @@ def _load_object_from_folder(folder, object_type: str, **kwargs):
         return load(si_file, base_folder=folder)
 
     elif object_type.startswith("Group"):
-
         sub_object_type = object_type.split("[")[1].split("]")[0]
         with open(folder / "spikeinterface_info.json", "r") as f:
             spikeinterface_info = json.load(f)
diff --git a/src/spikeinterface/core/motion.py b/src/spikeinterface/core/motion.py
index 50622b2e7d..668108701b 100644
--- a/src/spikeinterface/core/motion.py
+++ b/src/spikeinterface/core/motion.py
@@ -184,7 +184,7 @@ def save(self, folder, overwrite=False):
                 raise FileExistsError(f"Folder {folder} already exists. Use `overwrite=True` to overwrite.")
         folder.mkdir(exist_ok=True, parents=True)
 
-        info_file = folder / f"spikeinterface_info.json"
+        info_file = folder / "spikeinterface_info.json"
         info = dict(
             version=spikeinterface.__version__,
             dev_mode=spikeinterface.DEV_MODE,
@@ -206,7 +206,7 @@ def save(self, folder, overwrite=False):
     def load(cls, folder):
         folder = Path(folder)
 
-        info_file = folder / f"spikeinterface_info.json"
+        info_file = folder / "spikeinterface_info.json"
         err_msg = f"Motion.load(folder): the folder {folder} does not contain a Motion object."
         if not info_file.exists():
             raise IOError(err_msg)
diff --git a/src/spikeinterface/core/node_pipeline.py b/src/spikeinterface/core/node_pipeline.py
index 56f43cf3bf..0e3a209ba5 100644
--- a/src/spikeinterface/core/node_pipeline.py
+++ b/src/spikeinterface/core/node_pipeline.py
@@ -10,7 +10,7 @@
 from spikeinterface.core.base import base_peak_dtype, spike_peak_dtype
 from spikeinterface.core.time_series import TimeSeries
 from spikeinterface.core import BaseRecording, get_chunk_with_margin
-from spikeinterface.core.job_tools import TimeSeriesChunkExecutor, fix_job_kwargs, _shared_job_kwargs_doc
+from spikeinterface.core.job_tools import TimeSeriesChunkExecutor, fix_job_kwargs
 from spikeinterface.core import get_channel_distances
 from spikeinterface.core.core_tools import ms_to_samples, samples_to_ms
 
@@ -32,7 +32,6 @@
 
 
 class PipelineNode:
-
     # If False (general case) then compute(traces_chunk, *node_input_args)
     # If True then compute(traces_chunk, start_frame, end_frame, segment_index, max_margin, *node_input_args)
     _compute_has_extended_signature = False
@@ -89,7 +88,6 @@ def compute(self, chunk, start_frame, end_frame, segment_index, max_margin, *arg
 
 
 class PeakSource(PipelineNode):
-
     # this is an important hack : this force a node.compute() before the machininery is started
     # this trigger eventually some numba jit compilation and avoid compilation racing
     # between processes or threads
@@ -627,9 +625,9 @@ def check_graph(nodes, check_for_peak_source=True):
         node_parents = node.parents if node.parents else []
         for parent in node_parents:
             assert parent in nodes, f"Node {node} has parent {parent} that was not passed in nodes"
-            assert (
-                nodes.index(parent) < i
-            ), f"Nodes are ordered incorrectly: {node} before {parent} in the pipeline definition."
+            assert nodes.index(parent) < i, (
+                f"Nodes are ordered incorrectly: {node} before {parent} in the pipeline definition."
+            )
 
     return nodes
 
diff --git a/src/spikeinterface/core/npzfolder.py b/src/spikeinterface/core/npzfolder.py
index e22c6fa6ae..696a4217da 100644
--- a/src/spikeinterface/core/npzfolder.py
+++ b/src/spikeinterface/core/npzfolder.py
@@ -1,5 +1,3 @@
 """
 This file is for backwards compatibility with the old npz folder structure.
 """
-
-from .sortingfolder import NpzFolderSorting
diff --git a/src/spikeinterface/core/old_api_utils.py b/src/spikeinterface/core/old_api_utils.py
index fd04745632..888529a4fb 100644
--- a/src/spikeinterface/core/old_api_utils.py
+++ b/src/spikeinterface/core/old_api_utils.py
@@ -355,7 +355,7 @@ def copy_properties(oldapi_extractor, new_extractor, skip_properties=None):
             new_extractor.set_property(
                 key=property_name, values=property_values, ids=property_ids, missing_value=missing_value
             )
-        except Exception as e:
+        except Exception:
             warnings.warn(f"Property {property_name} cannot be ported to new API due to missing values.")
 
 
diff --git a/src/spikeinterface/core/sorting_tools.py b/src/spikeinterface/core/sorting_tools.py
index f62fccafd7..98e4c2e45b 100644
--- a/src/spikeinterface/core/sorting_tools.py
+++ b/src/spikeinterface/core/sorting_tools.py
@@ -436,14 +436,14 @@ def random_spikes_selection(
 
             elif method == "percentage":
                 if percentage is None or not (0 < percentage <= 1):
-                    raise ValueError(f"percentage must be in the interval (0, 1]")
+                    raise ValueError("percentage must be in the interval (0, 1]")
 
                 rng_size = min(max_spikes_per_unit, int(all_unit_indices.size * percentage))
                 selected_unit_indices = rng.choice(all_unit_indices, size=rng_size, replace=False, shuffle=False)
 
             elif method == "maximum_rate":
                 if maximum_rate is None:
-                    raise ValueError(f"maximum_rate must be defined")
+                    raise ValueError("maximum_rate must be defined")
 
                 t_duration = np.sum(get_segment_durations(sorting)[0])
                 rng_size = min(int(t_duration * maximum_rate), max_spikes_per_unit, all_unit_indices.size)
@@ -699,7 +699,6 @@ def set_properties_after_merging(
     default_missing_values = BaseExtractor.default_missing_property_values
 
     for key in prop_keys:
-
         parent_values = sorting_pre_merge.get_property(key)
 
         # propagate keep values
@@ -1042,9 +1041,9 @@ def generate_unit_ids_for_split(old_unit_ids, unit_splits, new_unit_ids=None, ne
             # then only doing a consistency check
             assert len(split_unit) == len(new_split_ids), "new_unit_ids should have the same len as unit_splits.values"
             # new_unit_ids can also be part of old_unit_ids only inside the same group:
-            assert all(
-                new_split_id not in old_unit_ids for new_split_id in new_split_ids
-            ), "new_unit_ids already exists but outside the split groups"
+            assert all(new_split_id not in old_unit_ids for new_split_id in new_split_ids), (
+                "new_unit_ids already exists but outside the split groups"
+            )
     else:
         dtype = old_unit_ids.dtype
         if np.issubdtype(dtype, np.integer) and new_id_strategy == "split":
@@ -1145,9 +1144,9 @@ def _get_ids_after_splitting(old_unit_ids, split_units, new_unit_ids):
 
     assert len(new_unit_ids) == len(split_units), "new_unit_ids should have the same len as merge_unit_groups"
     for new_unit_in_split, unit_to_split in zip(new_unit_ids, split_units.keys()):
-        assert len(new_unit_in_split) == len(
-            split_units[unit_to_split]
-        ), "new_unit_ids should have the same len as split_units values"
+        assert len(new_unit_in_split) == len(split_units[unit_to_split]), (
+            "new_unit_ids should have the same len as split_units values"
+        )
 
     all_unit_ids = list(old_unit_ids.copy())
     for split_unit, split_new_units in zip(split_units, new_unit_ids):
@@ -1181,12 +1180,12 @@ def remap_unit_indices_in_vector(vector, all_old_unit_ids, all_new_unit_ids, kee
     """
     all_old_unit_ids = np.asarray(all_old_unit_ids)
     all_new_unit_ids = np.asarray(all_new_unit_ids)
-    assert (
-        all_old_unit_ids.size == np.unique(all_old_unit_ids).size
-    ), "remap_unit_indices_in_vector: all_old_unit_ids not unique"
-    assert (
-        all_new_unit_ids.size == np.unique(all_new_unit_ids).size
-    ), "remap_unit_indices_in_vector: all_new_unit_ids not unique"
+    assert all_old_unit_ids.size == np.unique(all_old_unit_ids).size, (
+        "remap_unit_indices_in_vector: all_old_unit_ids not unique"
+    )
+    assert all_new_unit_ids.size == np.unique(all_new_unit_ids).size, (
+        "remap_unit_indices_in_vector: all_new_unit_ids not unique"
+    )
 
     if keep_old_unit_ids is None:
         keep_old_unit_ids = all_old_unit_ids
@@ -1272,7 +1271,6 @@ def estimate_segment_durations_from_spike_vector(
     durations = []
     ts = 1 / sampling_frequency
     for i, seg_idx in enumerate(segment_indices):
-
         if segment_t_starts is None:
             segment_start = 0.0
         else:
diff --git a/src/spikeinterface/core/sortinganalyzer.py b/src/spikeinterface/core/sortinganalyzer.py
index 1873b3134b..bb43cfdf6f 100644
--- a/src/spikeinterface/core/sortinganalyzer.py
+++ b/src/spikeinterface/core/sortinganalyzer.py
@@ -208,7 +208,6 @@ def create_sorting_analyzer(
 
     # Aggregate split recordings and sortings if they are provided as dicts
     if isinstance(sorting, dict) and isinstance(recording, dict):
-
         if sorting.keys() != recording.keys():
             raise ValueError(
                 f"Keys of `sorting`, {sorting.keys()}, and `recording`, {recording.keys()}, dicts do not match."
@@ -303,28 +302,28 @@ def create_sorting_analyzer(
                 **job_kwargs,
             )
     else:  # main_channel_indices provided as argument
-        assert (
-            len(main_channel_indices) == sorting.get_num_units()
-        ), "len(main_channel_indices) must equal the number of units in the `sorting`"
+        assert len(main_channel_indices) == sorting.get_num_units(), (
+            "len(main_channel_indices) must equal the number of units in the `sorting`"
+        )
         if sparsity is None and sparse:  # sparsity needs to be calculated
             sparsity_method = sparsity_kwargs.get("method", "radius")  # default method is radius
-            assert (
-                sparsity_method == "radius"
-            ), 'If you pass `main_channel_indices`, you need to use sparsity method "radius"'
+            assert sparsity_method == "radius", (
+                'If you pass `main_channel_indices`, you need to use sparsity method "radius"'
+            )
 
     # Handle sparsity
     if sparsity is not None:
         # some checks
         assert isinstance(sparsity, ChannelSparsity), "'sparsity' must be a ChannelSparsity object"
-        assert np.array_equal(
-            sorting.unit_ids, sparsity.unit_ids
-        ), "create_sorting_analyzer(): if external sparsity is given unit_ids must correspond"
-        assert np.array_equal(
-            recording.channel_ids, sparsity.channel_ids
-        ), "create_sorting_analyzer(): if external sparsity is given unit_ids must correspond"
-        assert all(
-            sparsity.mask[u, c] for u, c in enumerate(main_channel_indices)
-        ), "sparsity is not consistent with main_channel_indices"
+        assert np.array_equal(sorting.unit_ids, sparsity.unit_ids), (
+            "create_sorting_analyzer(): if external sparsity is given unit_ids must correspond"
+        )
+        assert np.array_equal(recording.channel_ids, sparsity.channel_ids), (
+            "create_sorting_analyzer(): if external sparsity is given unit_ids must correspond"
+        )
+        assert all(sparsity.mask[u, c] for u, c in enumerate(main_channel_indices)), (
+            "sparsity is not consistent with main_channel_indices"
+        )
     elif sparse:
         sparsity = estimate_sparsity(
             sorting,
@@ -540,9 +539,9 @@ def create(
         backend_options: dict[str, Any] | None = None,
     ):
         assert recording is not None, "To create a SortingAnalyzer you need to specify the recording"
-        assert (
-            main_channel_indices is not None
-        ), "To create a SortingAnalyzer you need to specify the main_channel_indices"
+        assert main_channel_indices is not None, (
+            "To create a SortingAnalyzer you need to specify the main_channel_indices"
+        )
 
         # some checks
         if sorting.sampling_frequency != recording.sampling_frequency:
@@ -997,7 +996,7 @@ def load_from_binary_folder(
                     try:
                         recording = load(filename, base_folder=folder)
                         break
-                    except:
+                    except Exception:
                         pass
 
         # Load recording attributes
@@ -1176,7 +1175,7 @@ def load_from_zarr(
             try:
                 zarr_root_a = zarr.open(str(folder), mode="a", **storage_options_kwargs)
                 zarr.consolidate_metadata(zarr_root_a.store)
-            except:
+            except Exception:
                 warnings.warn(
                     "The zarr store was not consolidated prior to v0.101.1. "
                     "This may lead to unexpected behavior in loading extensions. "
@@ -1219,7 +1218,7 @@ def load_from_zarr(
             if rec_dict is not None:
                 try:
                     recording = load(rec_dict, base_folder=folder)
-                except:
+                except Exception:
                     pass
 
         # Load recording attributes
@@ -1319,7 +1318,6 @@ def set_sorting_property(
             if self.format == "binary_folder":
                 np.save(self.folder / "sorting" / "properties" / f"{key}.npy", self.sorting.get_property(key))
             elif self.format == "zarr":
-
                 zarr_root = self._get_zarr_root(mode="r+")
                 prop_values = self.sorting.get_property(key)
                 if prop_values.dtype.kind == "O":
@@ -1991,7 +1989,6 @@ def merge_units(
 
         # remove units which do not pass the sparsity threshold
         if self.sparsity is not None and merging_mode == "soft":
-
             mergeable = self.are_units_mergeable(
                 merge_unit_groups,
                 sparsity_overlap=sparsity_overlap,
@@ -2196,7 +2193,7 @@ def get_sorting_provenance(self):
                     try:
                         sorting_provenance = load(filename, base_folder=self.folder)
                         break
-                    except:
+                    except Exception:
                         pass
         elif self.format == "zarr":
             zarr_root = self._get_zarr_root(mode="r")
@@ -2212,7 +2209,7 @@ def get_sorting_provenance(self):
                 # the original sorting folder
                 try:
                     sorting_provenance = load(sort_dict, base_folder=self.folder)
-                except:
+                except Exception:
                     pass
 
         return sorting_provenance
@@ -2351,9 +2348,9 @@ def compute(self, input, save=True, extension_params=None, verbose=False, **kwar
             extensions = {k: {} for k in input}
             if extension_params is not None:
                 for ext_name, ext_params in extension_params.items():
-                    assert (
-                        ext_name in input
-                    ), f"SortingAnalyzer.compute(): Parameters specified for {ext_name}, which is not in the specified {input}"
+                    assert ext_name in input, (
+                        f"SortingAnalyzer.compute(): Parameters specified for {ext_name}, which is not in the specified {input}"
+                    )
                     extensions[ext_name] = ext_params
             self.compute_several_extensions(extensions=extensions, save=save, verbose=verbose, **job_kwargs)
         else:
@@ -2409,9 +2406,9 @@ def compute_one_extension(self, extension_name, save=True, verbose=False, **kwar
 
         # check dependencies
         if extension_class.need_recording:
-            assert (
-                self.has_recording() or self.has_temporary_recording()
-            ), f"Extension {extension_name} requires the recording"
+            assert self.has_recording() or self.has_temporary_recording(), (
+                f"Extension {extension_name} requires the recording"
+            )
         required_dependencies = extension_class.get_required_dependencies(**params)
         for dependency_name in required_dependencies:
             if "|" in dependency_name:
@@ -2555,9 +2552,9 @@ def compute_several_extensions(
             try:
                 for extension_name, extension_params in extensions_with_pipeline.items():
                     extension_class = get_extension_class(extension_name)
-                    assert (
-                        self.has_recording() or self.has_temporary_recording()
-                    ), f"Extension {extension_name} requires the recording"
+                    assert self.has_recording() or self.has_temporary_recording(), (
+                        f"Extension {extension_name} requires the recording"
+                    )
 
                     extension_folder = self.folder / "extensions" / extension_name if gather_dest is not None else None
                     for variable_name in extension_class.nodepipeline_variables:
@@ -2613,7 +2610,6 @@ def compute_several_extensions(
                         extension_instance._save_run_info()
                         extension_instance._save_data()
                         if self.format == "zarr":
-
                             zarr.consolidate_metadata(self._get_zarr_root().store)
                     if not self._lazy and gather_mode != "memory":
                         # Materialize the data if not in lazy mode
@@ -2705,9 +2701,9 @@ def load_extension(self, extension_name: str):
             The loaded instance of the extension
 
         """
-        assert (
-            self.format != "memory"
-        ), "SortingAnalyzer.load_extension() does not work for format='memory' use SortingAnalyzer.get_extension() instead"
+        assert self.format != "memory", (
+            "SortingAnalyzer.load_extension() does not work for format='memory' use SortingAnalyzer.get_extension() instead"
+        )
 
         extension_class = get_extension_class(extension_name)
 
@@ -2733,7 +2729,6 @@ def _delete_extension_storage(self, extension_name) -> None:
             if extension_folder.is_dir():
                 shutil.rmtree(extension_folder)
         if self.format == "zarr":
-
             zarr_root = self._get_zarr_root(mode="r+")
             if extension_name in (root := zarr_root["extensions"]):
                 del root[extension_name]
@@ -2857,7 +2852,6 @@ def _sort_extensions_by_dependency(extensions):
 
     i = 0
     while i < len(extensions_list):
-
         extension = extensions_list[i]
         extension_params = extension_params_list[i]
 
@@ -2882,10 +2876,8 @@ def _sort_extensions_by_dependency(extensions):
         # Otherwise, should check the dependency which has just been moved => at position i
         did_nothing = True
         for dependency in dependencies:
-
             # if dependency is on the right, move it left of the current dependency
             if dependency in extensions_list[i:]:
-
                 dependency_arg = extensions_list.index(dependency)
 
                 extension_params_list.pop(dependency_arg)
@@ -2952,9 +2944,9 @@ def register_result_extension(extension_class):
 
     already_registered = any(extension_class is ext for ext in _possible_extensions)
     if not already_registered:
-        assert all(
-            extension_class.extension_name != ext.extension_name for ext in _possible_extensions
-        ), "Extension name already exists"
+        assert all(extension_class.extension_name != ext.extension_name for ext in _possible_extensions), (
+            "Extension name already exists"
+        )
 
         _possible_extensions.append(extension_class)
 
@@ -2991,7 +2983,7 @@ def get_extension_class(extension_name: str, auto_import=True):
         if extension_name in _builtin_extensions:
             module = _builtin_extensions[extension_name]
             if auto_import:
-                imported_module = importlib.import_module(module)
+                _ = importlib.import_module(module)
                 extensions_dict = {ext.extension_name: ext for ext in _possible_extensions}
             else:
                 raise ValueError(
@@ -3526,7 +3518,6 @@ def run(self, save=True, **kwargs):
             self._save_run_info()
             self._save_data()
             if self.format == "zarr":
-
                 zarr.consolidate_metadata(self.sorting_analyzer._get_zarr_root(mode="r+").store)
 
     def save(self):
@@ -3537,7 +3528,6 @@ def save(self):
         self._save_data()
 
         if self.format == "zarr":
-
             zarr.consolidate_metadata(self.sorting_analyzer._get_zarr_root(mode="r+").store)
 
     def _save_data(self):
@@ -3552,11 +3542,10 @@ def _save_data(self):
             import pandas as pd
 
             HAS_PANDAS = True
-        except:
+        except Exception:
             HAS_PANDAS = False
 
         if self.format == "binary_folder":
-
             extension_folder = self._get_binary_extension_folder()
             for ext_data_name, ext_data in self.data.items():
                 if isinstance(ext_data, dict):
@@ -3577,10 +3566,9 @@ def _save_data(self):
                     try:
                         with (extension_folder / f"{ext_data_name}.pkl").open("wb") as f:
                             pickle.dump(ext_data, f)
-                    except:
+                    except Exception:
                         raise Exception(f"Could not save {ext_data_name} as extension data")
         elif self.format == "zarr":
-
             saving_options = self.sorting_analyzer._backend_options.get("saving_options", {})
             extension_group = self._get_zarr_extension_group(mode="r+")
 
@@ -3626,7 +3614,7 @@ def _save_data(self):
                         write_pickle_array(
                             extension_group, ext_data_name, ext_data, compressors=saving_options["compressors"]
                         )
-                    except:
+                    except Exception:
                         raise Exception(f"Could not save {ext_data_name} as extension data")
 
     def _reset_extension_folder(self):
@@ -3650,7 +3638,6 @@ def _reset_extension_folder(self):
             extension_folder.mkdir(exist_ok=False, parents=True)
 
         elif self.format == "zarr":
-
             zarr_root = self.sorting_analyzer._get_zarr_root(mode="r+")
             _ = zarr_root["extensions"].create_group(self.extension_name, overwrite=True)
             zarr.consolidate_metadata(zarr_root.store)
@@ -3665,7 +3652,6 @@ def _delete_extension_folder(self):
                 shutil.rmtree(extension_folder)
 
         elif self.format == "zarr":
-
             zarr_root = self.sorting_analyzer._get_zarr_root(mode="r+")
             if self.extension_name in zarr_root["extensions"]:
                 del zarr_root["extensions"][self.extension_name]
@@ -3765,16 +3751,16 @@ def _save_run_info(self):
                 extension_group.attrs["run_info"] = run_info
 
     def get_pipeline_nodes(self):
-        assert (
-            self.use_nodepipeline
-        ), "AnalyzerExtension.get_pipeline_nodes() must be called only when use_nodepipeline=True"
+        assert self.use_nodepipeline, (
+            "AnalyzerExtension.get_pipeline_nodes() must be called only when use_nodepipeline=True"
+        )
         return self._get_pipeline_nodes()
 
     def get_data(self, *args, **kwargs):
         if self.run_info is not None:
-            assert self.run_info[
-                "run_completed"
-            ], f"You must run the extension {self.extension_name} before retrieving data"
+            assert self.run_info["run_completed"], (
+                f"You must run the extension {self.extension_name} before retrieving data"
+            )
         assert len(self.data) > 0, "Extension has been run but no data found."
         return self._get_data(*args, **kwargs)
 
diff --git a/src/spikeinterface/core/sortingfolder.py b/src/spikeinterface/core/sortingfolder.py
index fefe5c1229..5b528bf617 100644
--- a/src/spikeinterface/core/sortingfolder.py
+++ b/src/spikeinterface/core/sortingfolder.py
@@ -96,7 +96,7 @@ def write_sorting(
         # All properties, annotations, and probe information are already saved in the folder,
         # so we don't need to include them in the si_folder.json
         cached = NumpyFolderSorting(folder_path=folder_path, mmap_mode=mmap_mode)
-        si_folder_path = folder_path / f"si_folder.json"
+        si_folder_path = folder_path / "si_folder.json"
         cached.dump_to_json(
             file_path=si_folder_path,
             relative_to=folder_path,
@@ -176,7 +176,7 @@ def write_sorting(sorting, save_path):
         # make the si_folder file to make the load() easier
         cached = NpzFolderSorting(folder_path=save_path)
         cached._annotations = deepcopy({k: sorting._annotations[k] for k in sorting._annotations.keys()})
-        si_folder_path = save_path / f"si_folder.json"
+        si_folder_path = save_path / "si_folder.json"
         cached.dump_to_json(file_path=si_folder_path, relative_to=save_path, include_extra_metadata=False)
 
         return cached
diff --git a/src/spikeinterface/core/sparsity.py b/src/spikeinterface/core/sparsity.py
index 9863dfbb77..c109db5cd9 100644
--- a/src/spikeinterface/core/sparsity.py
+++ b/src/spikeinterface/core/sparsity.py
@@ -4,9 +4,7 @@
 
 from .basesorting import BaseSorting
 from .baserecording import BaseRecording
-from .sorting_tools import random_spikes_selection
 from .job_tools import _shared_job_kwargs_doc
-from .waveform_tools import estimate_templates_with_accumulator
 from .core_tools import ms_to_samples
 
 _sparsity_doc = """
@@ -475,9 +473,9 @@ def from_snr(
         from .sortinganalyzer import SortingAnalyzer
         from .template import Templates
 
-        assert (
-            templates_or_sorting_analyzer.sparsity is None
-        ), "To compute sparsity you need a dense SortingAnalyzer or Templates"
+        assert templates_or_sorting_analyzer.sparsity is None, (
+            "To compute sparsity you need a dense SortingAnalyzer or Templates"
+        )
 
         unit_ids = templates_or_sorting_analyzer.unit_ids
         channel_ids = templates_or_sorting_analyzer.channel_ids
@@ -526,9 +524,9 @@ def from_amplitude(cls, templates_or_sorting_analyzer, threshold, amplitude_mode
         from .sortinganalyzer import SortingAnalyzer
         from .template import Templates
 
-        assert (
-            templates_or_sorting_analyzer.sparsity is None
-        ), "To compute sparsity you need a dense SortingAnalyzer or Templates"
+        assert templates_or_sorting_analyzer.sparsity is None, (
+            "To compute sparsity you need a dense SortingAnalyzer or Templates"
+        )
 
         unit_ids = templates_or_sorting_analyzer.unit_ids
         channel_ids = templates_or_sorting_analyzer.channel_ids
@@ -625,9 +623,9 @@ def from_property(cls, sorting, recording, by_property):
         rec_by = recording.split_by(by_property)
         for unit_ind, unit_id in enumerate(sorting.unit_ids):
             unit_property = sorting.get_property(by_property)[unit_ind]
-            assert (
-                unit_property in rec_by.keys()
-            ), f"Unit property {unit_property} cannot be found in the recording properties"
+            assert unit_property in rec_by.keys(), (
+                f"Unit property {unit_property} cannot be found in the recording properties"
+            )
             chan_inds = recording.ids_to_indices(rec_by[unit_property].get_channel_ids())
             mask[unit_ind, chan_inds] = True
         return cls(mask, sorting.unit_ids, recording.channel_ids)
@@ -698,26 +696,26 @@ def compute_sparsity(
         "snr",
         "amplitude",
     ):
-        assert isinstance(
-            templates_or_sorting_analyzer, (Templates, SortingAnalyzer)
-        ), f"compute_sparsity(method='{method}') need Templates or SortingAnalyzer"
+        assert isinstance(templates_or_sorting_analyzer, (Templates, SortingAnalyzer)), (
+            f"compute_sparsity(method='{method}') need Templates or SortingAnalyzer"
+        )
         if isinstance(templates_or_sorting_analyzer, Templates):
-            assert (
-                peak_sign is not None
-            ), "When using `compute_sparsity` with a Templates object, `peak_sign` must be specified."
-            assert (
-                amplitude_mode is not None
-            ), "When using `compute_sparsity` with a Templates object, `amplitude_mode` must be specified."
+            assert peak_sign is not None, (
+                "When using `compute_sparsity` with a Templates object, `peak_sign` must be specified."
+            )
+            assert amplitude_mode is not None, (
+                "When using `compute_sparsity` with a Templates object, `amplitude_mode` must be specified."
+            )
     else:
-        assert isinstance(
-            templates_or_sorting_analyzer, SortingAnalyzer
-        ), f"compute_sparsity(method='{method}') need SortingAnalyzer"
-        assert (
-            peak_sign is None
-        ), "When using `compute_sparsity` with an analyzer, `peak_sign` must be None. The `peak_sign is set when you create the analyzer."
-        assert (
-            amplitude_mode is None
-        ), "When using `compute_sparsity` with an analyzer, `amplitude_mode` must be None. The `peak_mode` is set when you create the analyzer."
+        assert isinstance(templates_or_sorting_analyzer, SortingAnalyzer), (
+            f"compute_sparsity(method='{method}') need SortingAnalyzer"
+        )
+        assert peak_sign is None, (
+            "When using `compute_sparsity` with an analyzer, `peak_sign` must be None. The `peak_sign is set when you create the analyzer."
+        )
+        assert amplitude_mode is None, (
+            "When using `compute_sparsity` with an analyzer, `amplitude_mode` must be None. The `peak_mode` is set when you create the analyzer."
+        )
 
     if method == "best_channels":
         assert num_channels is not None, "For the 'best_channels' method, 'num_channels' needs to be given"
diff --git a/src/spikeinterface/core/testing.py b/src/spikeinterface/core/testing.py
index 6ad7458c37..ddea78d343 100644
--- a/src/spikeinterface/core/testing.py
+++ b/src/spikeinterface/core/testing.py
@@ -1,4 +1,3 @@
-import warnings
 import numpy as np
 from numpy.testing import assert_array_equal
 from .baserecording import BaseRecording
@@ -117,7 +116,6 @@ def check_sortings_equal(
         (None, max_spike_index - 30),
         (30, max_spike_index - 30),
     ]:
-
         slice1 = _slice_spikes(s1, start_frame, end_frame)
         slice2 = _slice_spikes(s2, start_frame, end_frame)
         assert np.array_equal(slice1, slice2)
diff --git a/src/spikeinterface/core/tests/test_analyzer_extension_core.py b/src/spikeinterface/core/tests/test_analyzer_extension_core.py
index 6423ce11ce..a903c15cb0 100644
--- a/src/spikeinterface/core/tests/test_analyzer_extension_core.py
+++ b/src/spikeinterface/core/tests/test_analyzer_extension_core.py
@@ -40,7 +40,7 @@ def get_sorting_analyzer(cache_folder, format="memory", sparse=True):
     elif format == "binary_folder":
         folder = cache_folder / f"test_ComputeWaveforms_{format}"
     elif format == "zarr":
-        folder = cache_folder / f"test_ComputeWaveforms.zarr"
+        folder = cache_folder / "test_ComputeWaveforms.zarr"
     if folder and folder.exists():
         shutil.rmtree(folder)
 
diff --git a/src/spikeinterface/core/tests/test_base.py b/src/spikeinterface/core/tests/test_base.py
index c81d24963c..57a50eb940 100644
--- a/src/spikeinterface/core/tests/test_base.py
+++ b/src/spikeinterface/core/tests/test_base.py
@@ -94,7 +94,7 @@ def test_name_and_repr():
     assert "MyRecording" not in str(test_recording2)
     assert test_recording2.__class__.__name__ in str(test_recording2)
     # above 10khz, sampling frequency is printed in kHz
-    assert f"kHz" in rec_str
+    assert "kHz" in rec_str
     # below 10khz sampling frequency is printed in Hz
     test_rec_low_fs = generate_recording(seed=0, durations=[2], sampling_frequency=5000)
     rec_str = str(test_rec_low_fs)
diff --git a/src/spikeinterface/core/tests/test_baserecording.py b/src/spikeinterface/core/tests/test_baserecording.py
index c20850a3e1..4bc180492d 100644
--- a/src/spikeinterface/core/tests/test_baserecording.py
+++ b/src/spikeinterface/core/tests/test_baserecording.py
@@ -11,12 +11,11 @@
 import numpy as np
 from numpy.testing import assert_raises
 
-from probeinterface import Probe, ProbeGroup, generate_linear_probe
+from probeinterface import Probe
 
 from spikeinterface.core import (
     BinaryRecordingExtractor,
     NumpyRecording,
-    load,
     get_default_zarr_compressor,
     load,
 )
diff --git a/src/spikeinterface/core/tests/test_basesorting.py b/src/spikeinterface/core/tests/test_basesorting.py
index 09c82a9ecb..b51882245c 100644
--- a/src/spikeinterface/core/tests/test_basesorting.py
+++ b/src/spikeinterface/core/tests/test_basesorting.py
@@ -17,13 +17,11 @@
     NpzFolderSorting,
     NumpyFolderSorting,
     generate_ground_truth_recording,
-    generate_sorting,
     create_sorting_npz,
     generate_sorting,
     load,
 )
 from spikeinterface.core.base import BaseExtractor, minimum_spike_dtype, unit_period_dtype
-from spikeinterface.core.basesorting import LEXSORT_UNIT_COMPACT
 from spikeinterface.core.testing import check_sorted_arrays_equal, check_sortings_equal
 
 
diff --git a/src/spikeinterface/core/tests/test_binaryfolder.py b/src/spikeinterface/core/tests/test_binaryfolder.py
index 049e613541..cca083b025 100644
--- a/src/spikeinterface/core/tests/test_binaryfolder.py
+++ b/src/spikeinterface/core/tests/test_binaryfolder.py
@@ -1,9 +1,5 @@
-import pytest
-
-from pathlib import Path
 import shutil
 
-import numpy as np
 
 from spikeinterface.core import load
 from spikeinterface.core import generate_recording
diff --git a/src/spikeinterface/core/tests/test_binaryrecordingextractor.py b/src/spikeinterface/core/tests/test_binaryrecordingextractor.py
index 853271066c..869b4a34da 100644
--- a/src/spikeinterface/core/tests/test_binaryrecordingextractor.py
+++ b/src/spikeinterface/core/tests/test_binaryrecordingextractor.py
@@ -6,7 +6,6 @@
 from spikeinterface.core import BinaryRecordingExtractor, MockRecording
 from spikeinterface.core.base import BaseExtractor
 from spikeinterface.core.numpyextractors import NumpyRecording
-from spikeinterface.core.core_tools import measure_memory_allocation
 
 
 def test_BinaryRecordingExtractor(create_cache_folder):
diff --git a/src/spikeinterface/core/tests/test_core_tools.py b/src/spikeinterface/core/tests/test_core_tools.py
index 7153991543..080ab750c9 100644
--- a/src/spikeinterface/core/tests/test_core_tools.py
+++ b/src/spikeinterface/core/tests/test_core_tools.py
@@ -1,6 +1,5 @@
 import platform
 import math
-from pathlib import Path
 import pytest
 import numpy as np
 
diff --git a/src/spikeinterface/core/tests/test_frameslicerecording.py b/src/spikeinterface/core/tests/test_frameslicerecording.py
index fa0b76862d..248e930b35 100644
--- a/src/spikeinterface/core/tests/test_frameslicerecording.py
+++ b/src/spikeinterface/core/tests/test_frameslicerecording.py
@@ -1,7 +1,6 @@
-import pytest
 import numpy as np
 
-from spikeinterface.core import FrameSliceRecording, NumpyRecording
+from spikeinterface.core import NumpyRecording
 
 
 def test_FrameSliceRecording():
diff --git a/src/spikeinterface/core/tests/test_jsonification.py b/src/spikeinterface/core/tests/test_jsonification.py
index 316dac3abc..9850156829 100644
--- a/src/spikeinterface/core/tests/test_jsonification.py
+++ b/src/spikeinterface/core/tests/test_jsonification.py
@@ -7,8 +7,6 @@
 from spikeinterface.core.core_tools import SIJsonEncoder
 from spikeinterface.core.generate import generate_recording, generate_sorting
 
-from pathlib import Path
-
 
 @pytest.fixture(scope="module")
 def numpy_generated_sorting():
diff --git a/src/spikeinterface/core/tests/test_loading.py b/src/spikeinterface/core/tests/test_loading.py
index 8d57a3412f..340a44674b 100644
--- a/src/spikeinterface/core/tests/test_loading.py
+++ b/src/spikeinterface/core/tests/test_loading.py
@@ -1,5 +1,6 @@
 import pytest
 import zarr
+import importlib.util
 
 import numpy as np
 from spikeinterface import (
@@ -16,13 +17,13 @@
 from spikeinterface.core.testing import check_recordings_equal, check_sortings_equal
 from spikeinterface.core.zarrextractors import ZarrRecordingExtractor
 
-try:
-    import s3fs
 
+if importlib.util.find_spec("s3fs") is not None:
     HAVE_S3 = True
-except ImportError:
+else:
     HAVE_S3 = False
 
+
 computed_extensions = ["waveforms", "templates", "noise_levels", "random_spikes"]
 
 
diff --git a/src/spikeinterface/core/tests/test_motion_core.py b/src/spikeinterface/core/tests/test_motion_core.py
index 28d1ef7385..506d2c1e79 100644
--- a/src/spikeinterface/core/tests/test_motion_core.py
+++ b/src/spikeinterface/core/tests/test_motion_core.py
@@ -1,5 +1,4 @@
 import pickle
-import shutil
 
 import numpy as np
 from spikeinterface.core.motion import Motion
diff --git a/src/spikeinterface/core/tests/test_node_pipeline.py b/src/spikeinterface/core/tests/test_node_pipeline.py
index a721fc3367..3ea66063ed 100644
--- a/src/spikeinterface/core/tests/test_node_pipeline.py
+++ b/src/spikeinterface/core/tests/test_node_pipeline.py
@@ -1,6 +1,5 @@
 import pytest
 import numpy as np
-from pathlib import Path
 import shutil
 
 from spikeinterface import create_sorting_analyzer, generate_ground_truth_recording
diff --git a/src/spikeinterface/core/tests/test_noise_levels_propagation.py b/src/spikeinterface/core/tests/test_noise_levels_propagation.py
index 98e7a929fd..6c97284efd 100644
--- a/src/spikeinterface/core/tests/test_noise_levels_propagation.py
+++ b/src/spikeinterface/core/tests/test_noise_levels_propagation.py
@@ -1,11 +1,7 @@
-import pytest
 from pathlib import Path
-import shutil
 
-from spikeinterface import set_global_tmp_folder, get_noise_levels
-from spikeinterface.core import generate_recording, concatenate_recordings, aggregate_channels
-
-import numpy as np
+from spikeinterface import get_noise_levels
+from spikeinterface.core import generate_recording, concatenate_recordings
 
 
 def test_skip_noise_levels_propagation(create_cache_folder):
diff --git a/src/spikeinterface/core/tests/test_npzsortingextractor.py b/src/spikeinterface/core/tests/test_npzsortingextractor.py
index 4d84ee9a4d..1e4cf470d1 100644
--- a/src/spikeinterface/core/tests/test_npzsortingextractor.py
+++ b/src/spikeinterface/core/tests/test_npzsortingextractor.py
@@ -1,6 +1,3 @@
-import pytest
-from pathlib import Path
-
 from spikeinterface.core import NpzSortingExtractor
 from spikeinterface.core import create_sorting_npz
 
diff --git a/src/spikeinterface/core/tests/test_read_python_safe.py b/src/spikeinterface/core/tests/test_read_python_safe.py
index 63d9a7d73f..1ad8f81861 100644
--- a/src/spikeinterface/core/tests/test_read_python_safe.py
+++ b/src/spikeinterface/core/tests/test_read_python_safe.py
@@ -6,7 +6,6 @@
 Run: pytest test_read_python_safe.py -v
 """
 
-import os
 import re
 import inspect
 from spikeinterface.core.core_tools import read_python
@@ -15,9 +14,7 @@
 def test_read_python_does_not_execute_config(tmp_path):
     marker = tmp_path / "pwned.txt"
     p = tmp_path / "params.py"
-    p.write_text(
-        "sample_rate = 30000\n" "dtype = 'int16'\n" "import os\n" f"os.system('echo x> {marker.as_posix()}')\n"
-    )
+    p.write_text(f"sample_rate = 30000\ndtype = 'int16'\nimport os\nos.system('echo x> {marker.as_posix()}')\n")
     md = read_python(str(p))
     assert not marker.exists(), "read_python executed code from the config file (CWE-95)"
     assert md.get("sample_rate") == 30000  # literal assignments still parse
diff --git a/src/spikeinterface/core/tests/test_recording_tools.py b/src/spikeinterface/core/tests/test_recording_tools.py
index 13d68e3b45..abeafe8e0c 100644
--- a/src/spikeinterface/core/tests/test_recording_tools.py
+++ b/src/spikeinterface/core/tests/test_recording_tools.py
@@ -1,5 +1,3 @@
-from pathlib import Path
-import platform
 import numpy as np
 
 from spikeinterface.core import NumpyRecording, generate_recording, MockRecording
diff --git a/src/spikeinterface/core/tests/test_segmentutils.py b/src/spikeinterface/core/tests/test_segmentutils.py
index e2c22fc24c..9e0b82377e 100644
--- a/src/spikeinterface/core/tests/test_segmentutils.py
+++ b/src/spikeinterface/core/tests/test_segmentutils.py
@@ -1,7 +1,6 @@
 import warnings
 
 import numpy as np
-import pytest
 from numpy.testing import assert_raises
 
 from spikeinterface.core import (
@@ -13,9 +12,7 @@
     concatenate_sortings,
     select_segment_recording,
     split_recording,
-    split_sorting,
 )
-from spikeinterface.core.testing import check_sorted_arrays_equal
 
 
 def test_append_concatenate_recordings():
diff --git a/src/spikeinterface/core/tests/test_sorting_folder.py b/src/spikeinterface/core/tests/test_sorting_folder.py
index 8d78a89ebd..5da96a5758 100644
--- a/src/spikeinterface/core/tests/test_sorting_folder.py
+++ b/src/spikeinterface/core/tests/test_sorting_folder.py
@@ -1,11 +1,10 @@
-import pytest
 import shutil
 
 import numpy as np
 
 from spikeinterface.core import NpzFolderSorting, NumpyFolderSorting
 from spikeinterface.core import generate_sorting
-from spikeinterface.core.testing import check_sorted_arrays_equal, check_sortings_equal
+from spikeinterface.core.testing import check_sortings_equal
 
 
 def test_NumpyFolderSorting(create_cache_folder):
diff --git a/src/spikeinterface/core/tests/test_sorting_tools.py b/src/spikeinterface/core/tests/test_sorting_tools.py
index 821b8b1631..fe624cb0b6 100644
--- a/src/spikeinterface/core/tests/test_sorting_tools.py
+++ b/src/spikeinterface/core/tests/test_sorting_tools.py
@@ -14,7 +14,6 @@
     _get_ids_after_merging,
     generate_unit_ids_for_merge_group,
     remap_unit_indices_in_vector,
-    set_properties_after_merging,
     set_properties_after_splits,
     reorder_spike_vector_by_unit_and_segment,
     get_segment_durations,
diff --git a/src/spikeinterface/core/tests/test_sortinganalyzer.py b/src/spikeinterface/core/tests/test_sortinganalyzer.py
index 50eb925444..f21499b151 100644
--- a/src/spikeinterface/core/tests/test_sortinganalyzer.py
+++ b/src/spikeinterface/core/tests/test_sortinganalyzer.py
@@ -646,7 +646,7 @@ def test_extension_params():
             try:
                 default_params = get_default_analyzer_extension_params(ext)
                 # print(ext, default_params)
-            except:
+            except Exception:
                 print(f"Failed to import {ext}")
 
 
@@ -1130,7 +1130,6 @@ def test_select_channels_sparse_waveforms_templates(dataset):
     selected_waveforms = analyzer_selected.get_extension("waveforms")
 
     for unit_index, unit_id in enumerate(sorting_analyzer.unit_ids):
-
         original_units_to_channels = sorting_analyzer.sparsity.unit_id_to_channel_ids[unit_id]
         selected_units_to_channels = analyzer_selected.sparsity.unit_id_to_channel_ids[unit_id]
 
@@ -1139,7 +1138,6 @@ def test_select_channels_sparse_waveforms_templates(dataset):
 
         for channel_id in select_channel_ids:
             if channel_id in original_units_to_channels:
-
                 # Check templates, which are dense
                 original_channel_index = original_id_index_map[channel_id]
                 selected_channel_index = selected_id_index_map[channel_id]
diff --git a/src/spikeinterface/core/tests/test_waveform_tools.py b/src/spikeinterface/core/tests/test_waveform_tools.py
index 6623c92046..24784538ea 100644
--- a/src/spikeinterface/core/tests/test_waveform_tools.py
+++ b/src/spikeinterface/core/tests/test_waveform_tools.py
@@ -5,7 +5,7 @@
 
 import numpy as np
 
-from spikeinterface.core import generate_recording, generate_sorting, generate_ground_truth_recording, ms_to_samples
+from spikeinterface.core import generate_recording, generate_ground_truth_recording, ms_to_samples
 from spikeinterface.core.waveform_tools import (
     extract_waveforms_to_buffers,
     extract_waveforms_to_single_buffer,
diff --git a/src/spikeinterface/core/time_series_tools.py b/src/spikeinterface/core/time_series_tools.py
index 4c4abc3492..fd22a46297 100644
--- a/src/spikeinterface/core/time_series_tools.py
+++ b/src/spikeinterface/core/time_series_tools.py
@@ -348,9 +348,9 @@ def _write_time_series_to_zarr(
 
     assert dataset_paths is not None, "Provide 'dataset_paths' to save data in zarr format"
     if dataset_timestamps_paths is not None:
-        assert (
-            len(dataset_timestamps_paths) == time_series.get_num_segments()
-        ), "dataset_timestamps_paths should have the same length as the number of segments in the time_series"
+        assert len(dataset_timestamps_paths) == time_series.get_num_segments(), (
+            "dataset_timestamps_paths should have the same length as the number of segments in the time_series"
+        )
     else:
         dataset_timestamps_paths = [None] * time_series.get_num_segments()
 
@@ -421,7 +421,6 @@ def _write_time_series_to_zarr(
 
 
 def _init_zarr_worker(time_series, zarr_datasets, dtype, zarr_timestamps_datasets=None):
-    import zarr
 
     # create a local dict per worker
     worker_ctx = {}
diff --git a/src/spikeinterface/core/unitsaggregationsorting.py b/src/spikeinterface/core/unitsaggregationsorting.py
index 3f650cd802..f18c458743 100644
--- a/src/spikeinterface/core/unitsaggregationsorting.py
+++ b/src/spikeinterface/core/unitsaggregationsorting.py
@@ -38,7 +38,7 @@ def __init__(self, sorting_list, renamed_unit_ids=None, sampling_frequency_max_d
         num_all_units = sum([sort.get_num_units() for sort in sorting_list])
         if renamed_unit_ids is not None:
             assert len(np.unique(renamed_unit_ids)) == num_all_units, (
-                "'renamed_unit_ids' doesn't have the right size" "or has duplicates!"
+                "'renamed_unit_ids' doesn't have the right sizeor has duplicates!"
             )
             unit_ids = list(renamed_unit_ids)
         else:
@@ -96,7 +96,6 @@ def __init__(self, sorting_list, renamed_unit_ids=None, sampling_frequency_max_d
         # Check if all the sortings have the same properties
         properties_set = set(np.concatenate([sorting.get_property_keys() for sorting in sorting_list]))
         for prop_name in properties_set:
-
             dtypes_per_sorting = []
             for sort in sorting_list:
                 if prop_name in sort.get_property_keys():
@@ -110,7 +109,6 @@ def __init__(self, sorting_list, renamed_unit_ids=None, sampling_frequency_max_d
 
             all_property_values = []
             for sort in sorting_list:
-
                 # If one of the sortings doesn't have the property, use the default missing property value
                 if prop_name not in sort.get_property_keys():
                     try:
@@ -118,7 +116,7 @@ def __init__(self, sorting_list, renamed_unit_ids=None, sampling_frequency_max_d
                             sort.get_num_units(),
                             BaseExtractor.default_missing_property_values[dtypes_per_sorting[0]],
                         )
-                    except:
+                    except Exception:
                         warnings.warn(f"Skipping property '{prop_name}: cannot inpute missing property values.'")
                         break
                 else:
diff --git a/src/spikeinterface/core/waveform_tools.py b/src/spikeinterface/core/waveform_tools.py
index a557c52ba6..d4ea6bc0db 100644
--- a/src/spikeinterface/core/waveform_tools.py
+++ b/src/spikeinterface/core/waveform_tools.py
@@ -10,12 +10,9 @@
 """
 
 from pathlib import Path
-import warnings
 
 import numpy as np
 
-from spikeinterface.core.baserecording import BaseRecording
-
 from .baserecording import BaseRecording
 from .job_tools import TimeSeriesChunkExecutor, _shared_job_kwargs_doc
 from .core_tools import make_shared_array
@@ -367,7 +364,6 @@ def _worker_distribute_buffers(segment_index, start_frame, end_frame, worker_dic
     num_samples = recording.get_num_samples(segment_index=segment_index)
 
     if l1 > l0:
-
         sub_spikes = in_seg_spikes[i0:i1]
         start = sub_spikes[0]["sample_index"] - nbefore
         end = sub_spikes[-1]["sample_index"] + nafter
@@ -1137,7 +1133,6 @@ def _init_worker_estimate_templates(
     worker_dict["sparsity_mask"] = sparsity_mask
 
     from multiprocessing.shared_memory import SharedMemory
-    import multiprocessing
 
     shm = SharedMemory(shm_name)
     waveform_accumulator_per_worker = np.ndarray(shape=shape, dtype=dtype, buffer=shm.buf)
@@ -1204,7 +1199,6 @@ def _worker_estimate_templates(segment_index, start_frame, end_frame, worker_dic
         unit_indices = sub_spikes["unit_index"]
 
         for sample_index, unit_index in zip(sample_indices, unit_indices):
-
             # sample_index < 0 only near the segment start, near the segment end wf is shorter
             wf_start = max(0, -sample_index)
             wf = traces[sample_index + wf_start : sample_index + offset, :]
@@ -1222,4 +1216,4 @@ def _worker_estimate_templates(segment_index, start_frame, end_frame, worker_dic
                 if waveform_squared_accumulator_per_worker is not None:
                     waveform_squared_accumulator_per_worker[
                         worker_index, unit_index, wf_start:wf_end, : wf.shape[1]
-                    ] += (wf**2)
+                    ] += wf**2
diff --git a/src/spikeinterface/core/waveforms_extractor_backwards_compatibility.py b/src/spikeinterface/core/waveforms_extractor_backwards_compatibility.py
index 56f2177e70..178e6b4546 100644
--- a/src/spikeinterface/core/waveforms_extractor_backwards_compatibility.py
+++ b/src/spikeinterface/core/waveforms_extractor_backwards_compatibility.py
@@ -255,9 +255,9 @@ def get_sampled_indices(self, unit_id):
         selected_spikes = []
         for segment_index in range(self.get_num_segments()):
             # inds = self.sorting_analyzer.get_selected_indices_in_spike_train(unit_id, segment_index)
-            assert self.sorting_analyzer.has_extension(
-                "random_spikes"
-            ), "get_sampled_indices() requires the 'random_spikes' extension."
+            assert self.sorting_analyzer.has_extension("random_spikes"), (
+                "get_sampled_indices() requires the 'random_spikes' extension."
+            )
             inds = self.sorting_analyzer.get_extension("random_spikes").get_selected_indices_in_spike_train(
                 unit_id, segment_index
             )
@@ -281,9 +281,9 @@ def get_waveforms(
         ext = self.sorting_analyzer.get_extension("waveforms")
         unit_index = self.sorting.id_to_index(unit_id)
 
-        assert self.sorting_analyzer.has_extension(
-            "random_spikes"
-        ), "get_sampled_indices() requires the 'random_spikes' extension."
+        assert self.sorting_analyzer.has_extension("random_spikes"), (
+            "get_sampled_indices() requires the 'random_spikes' extension."
+        )
 
         some_spikes = self.sorting_analyzer.get_extension("random_spikes").get_random_spikes()
 
@@ -291,9 +291,9 @@ def get_waveforms(
         wfs = ext.data["waveforms"][spike_mask, :, :]
 
         if sparsity is not None:
-            assert (
-                self.sorting_analyzer.sparsity is None
-            ), "Waveforms are alreayd sparse! Cannot apply an additional sparsity."
+            assert self.sorting_analyzer.sparsity is None, (
+                "Waveforms are alreayd sparse! Cannot apply an additional sparsity."
+            )
             wfs = wfs[:, :, sparsity.mask[self.sorting.id_to_index(unit_id)]]
 
         if force_dense:
@@ -475,12 +475,12 @@ def _read_old_waveforms_extractor_binary(folder, sorting):
     if (folder / "recording.json").exists():
         try:
             recording = load(folder / "recording.json", base_folder=folder)
-        except:
+        except Exception:
             pass
     elif (folder / "recording.pickle").exists():
         try:
             recording = load(folder / "recording.pickle", base_folder=folder)
-        except:
+        except Exception:
             pass
 
     # sorting
@@ -505,7 +505,6 @@ def _read_old_waveforms_extractor_binary(folder, sorting):
     # need to concatenate sampled_index and order it
     waveform_folder = folder / "waveforms"
     if waveform_folder.exists():
-
         spikes = sorting.to_spike_vector()
         random_spike_mask = np.zeros(spikes.size, dtype="bool")
 
@@ -686,7 +685,7 @@ def make_ext_params_up_to_date(ext, old_params, new_params):
 #     try:
 #         recording_dict = waveforms_root.attrs["recording"]
 #         recording = load(recording_dict, base_folder=folder)
-#     except:
+#     except Exception:
 #         pass
 
 #     # sorting
diff --git a/src/spikeinterface/core/zarrextractors.py b/src/spikeinterface/core/zarrextractors.py
index bfe70691ae..1746d59b95 100644
--- a/src/spikeinterface/core/zarrextractors.py
+++ b/src/spikeinterface/core/zarrextractors.py
@@ -13,7 +13,6 @@
 from .core_tools import (
     define_function_from_class,
     check_json,
-    is_path_remote,
     retrieve_importing_provenance,
     is_path_remote,
 )
@@ -165,9 +164,9 @@ def __init__(
             cr_by_segment = {}
         for segment_index in range(num_segments):
             trace_name = f"traces_seg{segment_index}"
-            assert (
-                len(channel_ids) == self._root[trace_name].shape[1]
-            ), f"Segment {segment_index} has the wrong number of channels!"
+            assert len(channel_ids) == self._root[trace_name].shape[1], (
+                f"Segment {segment_index} has the wrong number of channels!"
+            )
 
             time_kwargs = {}
             time_vector = self._root.get(f"times_seg{segment_index}", None)
@@ -943,7 +942,7 @@ def add_recording_to_zarr_group(
     channel_ids = recording.channel_ids
     if channel_ids.dtype.kind in ("U", "S"):
         channel_ids = channel_ids.astype("T")
-    arr = zarr_group.create_array(name="channel_ids", data=channel_ids, compressors=None)
+    _ = zarr_group.create_array(name="channel_ids", data=channel_ids, compressors=None)
     dataset_paths = [f"traces_seg{i}" for i in range(recording.get_num_segments())]
     dataset_timestamps_paths: list | None = None
     if any(recording.has_time_vector(i) for i in range(recording.get_num_segments())):
diff --git a/src/spikeinterface/curation/auto_merge.py b/src/spikeinterface/curation/auto_merge.py
index a31b841882..17a3eb28af 100644
--- a/src/spikeinterface/curation/auto_merge.py
+++ b/src/spikeinterface/curation/auto_merge.py
@@ -227,7 +227,6 @@ def compute_merge_unit_groups(
     outs = dict()
 
     for step in steps:
-
         if step in _required_extensions:
             for ext in _required_extensions[step]:
                 if sorting_analyzer.has_extension(ext):
@@ -374,7 +373,6 @@ def compute_merge_unit_groups(
             outs["pairs_decreased_score"] = pairs_decreased_score
 
         elif step == "slay_score":
-
             M_ij = compute_slay_matrix(
                 sorting_analyzer, params["k1"], params["k2"], templates_diff=outs["templates_diff"], pair_mask=pair_mask
             )
@@ -641,7 +639,6 @@ def auto_merge_units(
     }
 
     for to_launch, params in zip(to_be_launched, steps_params):
-
         if launch_mode == "presets":
             compute_merge_kwargs = {"preset": to_launch}
         elif launch_mode == "steps":
@@ -802,7 +799,7 @@ def smooth_correlogram(correlograms, bins, sigma_smooth_ms=0.6):
     """
     Smooths cross-correlogram with a Gaussian kernel.
     """
-    from scipy.signal import fftconvolve, butter, filtfilt
+    from scipy.signal import fftconvolve
 
     # OLD implementation : smooth correlogram by low pass filter
     # b, a = butter(N=2, Wn = correlogram_low_pass / (1e3 / bin_ms /2), btype="low")
@@ -1432,7 +1429,6 @@ def compute_xcorr_and_rp(sorting_analyzer: SortingAnalyzer, pair_mask: np.ndarra
 
     for unit_index_1, _ in enumerate(sorting_analyzer.unit_ids):
         for unit_index_2, _ in enumerate(sorting_analyzer.unit_ids):
-
             # Don't waste time computing the other metrics if units not candidates merges
             if not pair_mask[unit_index_1, unit_index_2]:
                 continue
diff --git a/src/spikeinterface/curation/curation_model.py b/src/spikeinterface/curation/curation_model.py
index 128bc0e6ba..f0e915aa02 100644
--- a/src/spikeinterface/curation/curation_model.py
+++ b/src/spikeinterface/curation/curation_model.py
@@ -1,7 +1,6 @@
-import warnings
 from typing import Literal, List
 from itertools import chain, combinations
-from pydantic import BaseModel, Field, model_validator, field_validator, field_serializer
+from pydantic import BaseModel, Field, model_validator, field_validator
 
 import numpy as np
 
@@ -504,7 +503,6 @@ def validate_sequential_curation(self):
                     )
 
         for curation_index in range(len(self.curation_steps))[:-1]:
-
             curation_1 = self.curation_steps[curation_index]
             curation_2 = self.curation_steps[curation_index + 1]
 
@@ -513,7 +511,7 @@ def validate_sequential_curation(self):
 
             if not (set(previous_model_final_ids) == set(next_model_initial_ids)):
                 raise ValueError(
-                    f"The initial unit_ids of curation {curation_index+1} do not match the final unit_ids of curation {curation_index}."
+                    f"The initial unit_ids of curation {curation_index + 1} do not match the final unit_ids of curation {curation_index}."
                 )
 
         return self
diff --git a/src/spikeinterface/curation/curationsorting.py b/src/spikeinterface/curation/curationsorting.py
index 1e0e8fc1d0..52b879fb64 100644
--- a/src/spikeinterface/curation/curationsorting.py
+++ b/src/spikeinterface/curation/curationsorting.py
@@ -119,7 +119,7 @@ def merge(self, units_to_merge, new_unit_id=None, delta_time_ms=0.4):
         if new_unit_id is None:
             new_unit_id = self._get_unused_id()[0]
         elif new_unit_id not in units_to_merge:
-            assert new_unit_id not in current_sorting.unit_ids, f"new_unit_id already exists!"
+            assert new_unit_id not in current_sorting.unit_ids, "new_unit_id already exists!"
         new_sorting = MergeUnitsSorting(
             sorting=current_sorting,
             units_to_merge=units_to_merge,
diff --git a/src/spikeinterface/curation/model_based_curation.py b/src/spikeinterface/curation/model_based_curation.py
index 69c7f75419..b1f1184d16 100644
--- a/src/spikeinterface/curation/model_based_curation.py
+++ b/src/spikeinterface/curation/model_based_curation.py
@@ -1,7 +1,6 @@
 from pathlib import Path
 import json
 import warnings
-import re
 from packaging.version import parse
 from copy import deepcopy
 
@@ -141,7 +140,7 @@ def predict_labels(
                 label_conversion = {}
                 for key, value in string_label_conversion.items():
                     label_conversion[int(key)] = value
-            except:
+            except Exception:
                 warnings.warn("Could not find `label_conversion` key in `model_info.json` file")
 
         metrics = _format_metric_dataframe(metrics)
@@ -190,13 +189,11 @@ def _check_params_for_classification(self, enforce_metric_params=False, model_in
         metric_extensions = [self.sorting_analyzer.get_extension(extension_name) for extension_name in extension_names]
 
         for metric_extension, extension_name in zip(metric_extensions, extension_names):
-
             # remove the 's' at the end of the extension name
             extension_name = extension_name[:-1]
             model_extension_params = model_info["metric_params"].get(extension_name + "_params")
 
             if metric_extension is not None and model_extension_params is not None:
-
                 metric_params = metric_extension.params["metric_params"]
 
                 inconsistent_metrics = []
@@ -450,7 +447,6 @@ def _load_model_from_folder(model_folder=None, model_name=None, trust_model=Fals
     """
 
     import skops.io as skio
-    from skops.io.exceptions import UntrustedTypesFoundException
 
     folder = Path(model_folder)
     assert folder.is_dir(), f"The folder {folder}, does not exist."
diff --git a/src/spikeinterface/curation/sortingview_curation.py b/src/spikeinterface/curation/sortingview_curation.py
index 657dcb9cde..7cde276936 100644
--- a/src/spikeinterface/curation/sortingview_curation.py
+++ b/src/spikeinterface/curation/sortingview_curation.py
@@ -74,7 +74,7 @@ def apply_sortingview_curation(
 
         try:
             curation_dict = ka.load_json(uri=uri_or_json)
-        except:
+        except Exception:
             raise Exception(f"Could not retrieve curation from SortingView uri: {uri_or_json}")
 
     if curation_dict is None:
diff --git a/src/spikeinterface/curation/tests/test_auto_merge.py b/src/spikeinterface/curation/tests/test_auto_merge.py
index cab508f4fb..1e611dba07 100644
--- a/src/spikeinterface/curation/tests/test_auto_merge.py
+++ b/src/spikeinterface/curation/tests/test_auto_merge.py
@@ -8,9 +8,6 @@
 
 from spikeinterface.curation.tests.common import (
     make_sorting_analyzer,
-    sorting_analyzer_for_curation,
-    sorting_analyzer_with_splits,
-    sorting_analyzer_multi_segment_for_curation,
 )
 
 
diff --git a/src/spikeinterface/curation/tests/test_bombcell_curation.py b/src/spikeinterface/curation/tests/test_bombcell_curation.py
index 768d28c143..6a3d9f2c6c 100644
--- a/src/spikeinterface/curation/tests/test_bombcell_curation.py
+++ b/src/spikeinterface/curation/tests/test_bombcell_curation.py
@@ -1,6 +1,4 @@
 import pytest
-from pathlib import Path
-from spikeinterface.curation.tests.common import sorting_analyzer_for_curation, trained_pipeline_path
 from spikeinterface.curation.bombcell_curation import bombcell_label_units
 
 
@@ -31,7 +29,6 @@ def test_bombcell_label_units_with_external_metrics(sorting_analyzer_with_metric
     sorting_analyzer = sorting_analyzer_with_metrics
 
     # Create external metrics DataFrame
-    import pandas as pd
 
     metrics_df = sorting_analyzer.get_metrics_extension_data()
 
diff --git a/src/spikeinterface/curation/tests/test_curation_model.py b/src/spikeinterface/curation/tests/test_curation_model.py
index 48102096a6..5005cfa3fc 100644
--- a/src/spikeinterface/curation/tests/test_curation_model.py
+++ b/src/spikeinterface/curation/tests/test_curation_model.py
@@ -1,7 +1,6 @@
 import pytest
 
 from pydantic import ValidationError
-import numpy as np
 
 from spikeinterface.curation.curation_model import Curation, SequentialCuration, LabelDefinition
 
diff --git a/src/spikeinterface/curation/tests/test_model_based_curation.py b/src/spikeinterface/curation/tests/test_model_based_curation.py
index 800817cdda..6cfb86fe9d 100644
--- a/src/spikeinterface/curation/tests/test_model_based_curation.py
+++ b/src/spikeinterface/curation/tests/test_model_based_curation.py
@@ -1,7 +1,6 @@
 import pytest
 from pathlib import Path
 
-from spikeinterface.curation.tests.common import sorting_analyzer_for_unitrefine_curation, trained_pipeline_path
 from spikeinterface.curation.model_based_curation import ModelBasedClassification
 from spikeinterface.curation import (
     model_based_label_units,
diff --git a/src/spikeinterface/curation/tests/test_remove_redundant.py b/src/spikeinterface/curation/tests/test_remove_redundant.py
index 43a7cd1951..6449b582fe 100644
--- a/src/spikeinterface/curation/tests/test_remove_redundant.py
+++ b/src/spikeinterface/curation/tests/test_remove_redundant.py
@@ -2,7 +2,7 @@
 
 from spikeinterface import create_sorting_analyzer
 from spikeinterface.core.generate import inject_some_duplicate_units
-from spikeinterface.curation.tests.common import make_sorting_analyzer, sorting_analyzer_for_curation
+from spikeinterface.curation.tests.common import make_sorting_analyzer
 
 from spikeinterface.curation import remove_redundant_units
 
diff --git a/src/spikeinterface/curation/tests/test_sortingview_curation.py b/src/spikeinterface/curation/tests/test_sortingview_curation.py
index 9b1305205a..9e4d579f62 100644
--- a/src/spikeinterface/curation/tests/test_sortingview_curation.py
+++ b/src/spikeinterface/curation/tests/test_sortingview_curation.py
@@ -4,16 +4,8 @@
 import importlib.util
 import numpy as np
 
-import spikeinterface as si
 from spikeinterface.core import generate_sorting
 import spikeinterface.extractors as se
-from spikeinterface import set_global_tmp_folder
-from spikeinterface.postprocessing import (
-    compute_correlograms,
-    compute_unit_locations,
-    compute_template_similarity,
-    compute_spike_amplitudes,
-)
 from spikeinterface.curation import apply_sortingview_curation
 
 parent_folder = Path(__file__).parent
diff --git a/src/spikeinterface/curation/tests/test_train_manual_curation.py b/src/spikeinterface/curation/tests/test_train_manual_curation.py
index 21df26128a..249605046c 100644
--- a/src/spikeinterface/curation/tests/test_train_manual_curation.py
+++ b/src/spikeinterface/curation/tests/test_train_manual_curation.py
@@ -1,6 +1,7 @@
 import pytest
 import numpy as np
-import tempfile, csv
+import tempfile
+import csv
 from pathlib import Path
 
 from spikeinterface.curation.tests.common import make_sorting_analyzer
diff --git a/src/spikeinterface/curation/tests/test_unitrefine_curation.py b/src/spikeinterface/curation/tests/test_unitrefine_curation.py
index 314fcb5878..99764fffd7 100644
--- a/src/spikeinterface/curation/tests/test_unitrefine_curation.py
+++ b/src/spikeinterface/curation/tests/test_unitrefine_curation.py
@@ -1,6 +1,5 @@
 import pytest
 
-from spikeinterface.curation.tests.common import sorting_analyzer_for_unitrefine_curation, trained_pipeline_path
 from spikeinterface.curation import unitrefine_label_units
 
 
diff --git a/src/spikeinterface/curation/threshold_metrics_curation.py b/src/spikeinterface/curation/threshold_metrics_curation.py
index b9b5ca1a86..9a76dbc3f4 100644
--- a/src/spikeinterface/curation/threshold_metrics_curation.py
+++ b/src/spikeinterface/curation/threshold_metrics_curation.py
@@ -3,7 +3,6 @@
 
 import numpy as np
 
-from spikeinterface.core.analyzer_extension_core import SortingAnalyzer
 
 from .curation_tools import is_threshold_disabled
 
diff --git a/src/spikeinterface/curation/train_manual_curation.py b/src/spikeinterface/curation/train_manual_curation.py
index e34951820a..d9b7dcc4eb 100644
--- a/src/spikeinterface/curation/train_manual_curation.py
+++ b/src/spikeinterface/curation/train_manual_curation.py
@@ -265,7 +265,6 @@ def load_and_preprocess_analyzers(self, analyzers, enforce_metric_params):
         metric_extensions = [analyzers[0].get_extension(extension_name) for extension_name in extension_names]
 
         for metric_extension, extension_name in zip(metric_extensions, extension_names):
-
             # remove the 's' at the end of the extension name
             extension_name = extension_name[:-1]
             if metric_extension is not None:
@@ -289,11 +288,9 @@ def _check_metrics_parameters(self, analyzers, enforce_metric_params):
         conflicting_metrics = []
         for analyzer_index_1, analyzer_1 in enumerate(analyzers):
             for analyzer_index_2, analyzer_2 in enumerate(analyzers):
-
                 if analyzer_index_1 <= analyzer_index_2:
                     continue
                 else:
-
                     metric_params_1 = {}
                     metric_params_2 = {}
 
@@ -389,7 +386,6 @@ def process_test_data_for_classification(self):
 
     def apply_scaling_imputation(self, imputation_strategy, scaling_technique, X_train, X_test, y_train, y_test):
         """Impute and scale the data using the specified techniques."""
-        from sklearn.experimental import enable_iterative_imputer
         from sklearn.impute import SimpleImputer, KNNImputer, IterativeImputer
         from sklearn.ensemble import HistGradientBoostingRegressor
         from sklearn.preprocessing import StandardScaler, MinMaxScaler, RobustScaler
@@ -587,14 +583,14 @@ def _save(self):
         import pandas as pd
 
         # export training data and labels
-        pd.DataFrame(self.X).to_csv(self.folder / f"training_data.csv", index_label="unit_id")
-        pd.DataFrame(self.y).to_csv(self.folder / f"labels.csv", index_label="unit_index")
+        pd.DataFrame(self.X).to_csv(self.folder / "training_data.csv", index_label="unit_id")
+        pd.DataFrame(self.y).to_csv(self.folder / "labels.csv", index_label="unit_index")
 
         self.requirements["scikit-learn"] = sklearn.__version__
 
         # Dump to skops if folder is provided
-        dump(self.best_pipeline, self.folder / f"best_model.skops")
-        self.test_accuracies_df.to_csv(self.folder / f"model_accuracies.csv", float_format="%.4f")
+        dump(self.best_pipeline, self.folder / "best_model.skops")
+        self.test_accuracies_df.to_csv(self.folder / "model_accuracies.csv", float_format="%.4f")
 
         model_info = {}
         model_info["metric_params"] = self.metrics_params
@@ -629,7 +625,7 @@ def _train_and_evaluate(
                 random_state=self.seed,
                 **search_kwargs,
             )
-        except:
+        except Exception:
             if self.verbose is True:
                 print("BayesSearchCV from scikit-optimize not available, using RandomizedSearchCV")
             from sklearn.model_selection import RandomizedSearchCV
@@ -787,7 +783,7 @@ def try_to_get_metrics_from_analyzer(sorting_analyzer):
     for metric_extension in metric_extensions:
         try:
             metric_extensions_data.append(metric_extension.get_data())
-        except:
+        except Exception:
             metric_extensions_data.append(None)
 
     return metric_extensions_data
diff --git a/src/spikeinterface/exporters/tests/common.py b/src/spikeinterface/exporters/tests/common.py
index 3b85c11d54..d42c1b7253 100644
--- a/src/spikeinterface/exporters/tests/common.py
+++ b/src/spikeinterface/exporters/tests/common.py
@@ -1,5 +1,4 @@
 import pytest
-from pathlib import Path
 
 from spikeinterface.core import generate_ground_truth_recording, create_sorting_analyzer, compute_sparsity
 
@@ -23,7 +22,6 @@ def make_sorting_analyzer(sparse=True, with_group=False):
     )
 
     if with_group:
-
         # this is a bit painful. We need to figure out which units belong to which group
         initial_sorting_analyzer = create_sorting_analyzer(
             sorting=sorting, recording=recording, format="memory", sparse=True
diff --git a/src/spikeinterface/exporters/tests/test_export_to_ibl.py b/src/spikeinterface/exporters/tests/test_export_to_ibl.py
index c7be6911cc..9f1d24300a 100644
--- a/src/spikeinterface/exporters/tests/test_export_to_ibl.py
+++ b/src/spikeinterface/exporters/tests/test_export_to_ibl.py
@@ -4,7 +4,6 @@
 from spikeinterface.exporters import export_to_ibl_gui
 from spikeinterface.exporters.tests.common import (
     make_sorting_analyzer,
-    sorting_analyzer_sparse_for_export,
 )
 
 required_output_files = [
diff --git a/src/spikeinterface/exporters/tests/test_export_to_phy.py b/src/spikeinterface/exporters/tests/test_export_to_phy.py
index f46ecd3260..301c534fd0 100644
--- a/src/spikeinterface/exporters/tests/test_export_to_phy.py
+++ b/src/spikeinterface/exporters/tests/test_export_to_phy.py
@@ -8,9 +8,6 @@
 
 from spikeinterface.exporters.tests.common import (
     make_sorting_analyzer,
-    sorting_analyzer_dense_for_export,
-    sorting_analyzer_sparse_for_export,
-    sorting_analyzer_with_group_for_export,
 )
 
 
diff --git a/src/spikeinterface/exporters/tests/test_report.py b/src/spikeinterface/exporters/tests/test_report.py
index a2ee9e885c..9646ab6d9c 100644
--- a/src/spikeinterface/exporters/tests/test_report.py
+++ b/src/spikeinterface/exporters/tests/test_report.py
@@ -3,9 +3,6 @@
 from spikeinterface.exporters import export_report
 from spikeinterface.exporters.tests.common import (
     make_sorting_analyzer,
-    sorting_analyzer_dense_for_export,
-    sorting_analyzer_sparse_for_export,
-    sorting_analyzer_with_group_for_export,
 )
 
 
diff --git a/src/spikeinterface/exporters/to_phy.py b/src/spikeinterface/exporters/to_phy.py
index c6ea703770..40dae800f1 100644
--- a/src/spikeinterface/exporters/to_phy.py
+++ b/src/spikeinterface/exporters/to_phy.py
@@ -79,9 +79,9 @@ def export_to_phy(
     assert isinstance(sorting_analyzer, SortingAnalyzer), "sorting_analyzer must be a SortingAnalyzer object"
     sorting = sorting_analyzer.sorting
 
-    assert (
-        sorting_analyzer.get_num_segments() == 1
-    ), f"Export to phy only works with one segment, your extractor has {sorting_analyzer.get_num_segments()} segments"
+    assert sorting_analyzer.get_num_segments() == 1, (
+        f"Export to phy only works with one segment, your extractor has {sorting_analyzer.get_num_segments()} segments"
+    )
     num_chans = sorting_analyzer.get_num_channels()
     fs = sorting_analyzer.sampling_frequency
 
@@ -159,7 +159,7 @@ def export_to_phy(
     with (output_folder / "params.py").open("w") as f:
         if use_relative_path:
             if copy_binary:
-                f.write(f"dat_path = r'recording.dat'\n")
+                f.write("dat_path = r'recording.dat'\n")
             elif rec_path == "None":
                 f.write(f"dat_path = {rec_path}\n")
             else:
@@ -168,7 +168,7 @@ def export_to_phy(
             f.write(f"dat_path = r'{str(rec_path)}'\n")
         f.write(f"n_channels_dat = {num_chans}\n")
         f.write(f"dtype = '{dtype_str}'\n")
-        f.write(f"offset = 0\n")
+        f.write("offset = 0\n")
         f.write(f"sample_rate = {fs}\n")
         f.write(f"hp_filtered = {sorting_analyzer.is_filtered()}")
 
diff --git a/src/spikeinterface/extractors/cbin_ibl.py b/src/spikeinterface/extractors/cbin_ibl.py
index adf04f366a..0a47d7efab 100644
--- a/src/spikeinterface/extractors/cbin_ibl.py
+++ b/src/spikeinterface/extractors/cbin_ibl.py
@@ -1,6 +1,5 @@
 from pathlib import Path
 import re
-import warnings
 import numpy as np
 
 import probeinterface
@@ -142,9 +141,9 @@ def __init__(self, folder_path=None, load_sync_channel=False, stream_name="ap",
             # snippets downloaded from IBL have the .stream.cbin suffix
             cbin_stream_files = list(folder_path.glob(f"*.{stream_name}.stream.cbin"))
             curr_cbin_files = cbin_stream_files if len(cbin_stream_files) > len(cbin_files) else cbin_files
-            assert (
-                len(curr_cbin_files) == 1
-            ), f"There should only be one `*.cbin` file in the folder, but {print(curr_cbin_files)} have been found"
+            assert len(curr_cbin_files) == 1, (
+                f"There should only be one `*.cbin` file in the folder, but {print(curr_cbin_files)} have been found"
+            )
             cbin_file_path = curr_cbin_files[0]
         else:
             cbin_file_path = Path(cbin_file_path)
@@ -274,7 +273,7 @@ def extract_stream_info(meta_file, meta):
         gain_factor = float(meta["imAiRangeMax"]) / max_int
         channel_gains = gain_factor * per_channel_gain * 1e6
     else:
-        raise NotImplementedError("This meta file version of spikeglx" " is not implemented")
+        raise NotImplementedError("This meta file version of spikeglx is not implemented")
 
     info = {}
     info["fname"] = fname
diff --git a/src/spikeinterface/extractors/extractor_classes.py b/src/spikeinterface/extractors/extractor_classes.py
index 21c383309f..c12561331b 100644
--- a/src/spikeinterface/extractors/extractor_classes.py
+++ b/src/spikeinterface/extractors/extractor_classes.py
@@ -5,21 +5,16 @@
     NumpyRecording,
     NpzSortingExtractor,
     NumpySorting,
-    read_binary,
-    read_zarr,
     read_npz_sorting,
 )
 
 from spikeinterface.core.zarrextractors import (
     ZarrRecordingExtractor,
     ZarrSortingExtractor,
-    read_zarr_array,
 )
 
 # sorting/recording/event from neo
 from .neoextractors import *
-from .neoextractors import read_neuroscope
-from .neoextractors.intan import read_split_intan_files, IntanSplitFilesRecordingExtractor
 
 # non-NEO objects implemented in neo folder
 # keep for reference Currently pulling from neoextractor __init__
@@ -30,7 +25,6 @@
     NwbRecordingExtractor,
     NwbSortingExtractor,
     NwbTimeSeriesExtractor,
-    read_nwb,
     read_nwb_recording,
     read_nwb_sorting,
     read_nwb_timeseries,
diff --git a/src/spikeinterface/extractors/klustaextractors.py b/src/spikeinterface/extractors/klustaextractors.py
index d18c8d831f..604e31bad5 100644
--- a/src/spikeinterface/extractors/klustaextractors.py
+++ b/src/spikeinterface/extractors/klustaextractors.py
@@ -61,7 +61,7 @@ def __init__(self, file_or_folder_path, exclude_cluster_groups=None):
             config_file = [f for f in klustafolder.iterdir() if f.suffix == ".prm"][0]
             config = read_python(str(config_file))
             sampling_frequency = config["traces"]["sample_rate"]
-        except Exception as e:
+        except Exception:
             print("Could not load sampling frequency info")
 
         kf_reader = h5py.File(kwikfile, "r")
@@ -96,9 +96,9 @@ def __init__(self, file_or_folder_path, exclude_cluster_groups=None):
                     "cluster_group"
                 ]
 
-                assert (
-                    cluster_group in self.default_cluster_groups.keys()
-                ), f'cluster_group not in "default_dict: {cluster_group}'
+                assert cluster_group in self.default_cluster_groups.keys(), (
+                    f'cluster_group not in "default_dict: {cluster_group}'
+                )
                 cluster_group_name = self.default_cluster_groups[cluster_group]
 
                 if cluster_group_name.lower() in cs_to_exclude:
diff --git a/src/spikeinterface/extractors/mdaextractors.py b/src/spikeinterface/extractors/mdaextractors.py
index 12a7474df7..acc3a1790e 100644
--- a/src/spikeinterface/extractors/mdaextractors.py
+++ b/src/spikeinterface/extractors/mdaextractors.py
@@ -43,8 +43,7 @@ def __init__(self, folder_path, raw_fname="raw.mda", params_fname="params.json",
         dtype = self._diskreadmda.dt()
         num_channels = self._diskreadmda.N1()
         assert geom.shape[0] == self._diskreadmda.N1(), (
-            f"Incompatible dimensions between geom.csv and timeseries "
-            f"file: {geom.shape[0]} <> {self._diskreadmda.N1()}"
+            f"Incompatible dimensions between geom.csv and timeseries file: {geom.shape[0]} <> {self._diskreadmda.N1()}"
         )
         sampling_frequency = float(self._dataset_params["samplerate"])
         BaseRecording.__init__(
@@ -102,7 +101,7 @@ def write_recording(
         """
         job_kwargs = fix_job_kwargs(job_kwargs)
         assert recording.get_num_segments() == 1, (
-            "MdaRecording.write_recording() can only write a single segment " "recording"
+            "MdaRecording.write_recording() can only write a single segment recording"
         )
         save_path = Path(save_path)
         save_path.mkdir(parents=True, exist_ok=True)
@@ -434,7 +433,7 @@ def _read_chunk_1d(self, i, N):
             tmp_fname = _download_bytes_to_tmpfile(self._path, offset, offset + self._header.num_bytes_per_entry * N)
             try:
                 ret = self._read_chunk_1d_helper(tmp_fname, N, offset=0)
-            except:
+            except Exception:
                 ret = None
             return ret
         return self._read_chunk_1d_helper(self._path, N, offset=offset)
@@ -482,7 +481,7 @@ def _read_header(path):
             raise Exception("Problem downloading bytes from " + path)
         try:
             ret = _read_header(tmp_fname)
-        except:
+        except Exception:
             ret = None
         Path(tmp_fname).unlink()
         return ret
diff --git a/src/spikeinterface/extractors/neoextractors/neo_utils.py b/src/spikeinterface/extractors/neoextractors/neo_utils.py
index 9a0a01e50a..1bc1e486eb 100644
--- a/src/spikeinterface/extractors/neoextractors/neo_utils.py
+++ b/src/spikeinterface/extractors/neoextractors/neo_utils.py
@@ -1,6 +1,3 @@
-from .neobaseextractor import NeoBaseRecordingExtractor
-
-
 def get_neo_streams(extractor_name, *args, **kwargs):
     """Returns the NEO streams (stream names and stream ids) associated to a dataset.
     For multi-stream datasets, the `stream_id` or `stream_name` arguments can be used
@@ -57,7 +54,7 @@ def get_neo_extractor(extractor_name):
     from spikeinterface.extractors.neoextractors import neo_recording_class_dict
 
     assert extractor_name in neo_recording_class_dict, (
-        f"{extractor_name} not an extractor name:" f"\n{list(neo_recording_class_dict.keys())}"
+        f"{extractor_name} not an extractor name:\n{list(neo_recording_class_dict.keys())}"
     )
     neo_extractor = neo_recording_class_dict[extractor_name]
     return neo_extractor
diff --git a/src/spikeinterface/extractors/neoextractors/spike2.py b/src/spikeinterface/extractors/neoextractors/spike2.py
index 6283176def..e41dac547d 100644
--- a/src/spikeinterface/extractors/neoextractors/spike2.py
+++ b/src/spikeinterface/extractors/neoextractors/spike2.py
@@ -2,7 +2,7 @@
 
 from spikeinterface.core.core_tools import define_function_from_class
 
-from .neobaseextractor import NeoBaseRecordingExtractor, NeoBaseSortingExtractor
+from .neobaseextractor import NeoBaseRecordingExtractor
 
 
 class Spike2RecordingExtractor(NeoBaseRecordingExtractor):
diff --git a/src/spikeinterface/extractors/nwbextractors.py b/src/spikeinterface/extractors/nwbextractors.py
index e103c06392..199850f0db 100644
--- a/src/spikeinterface/extractors/nwbextractors.py
+++ b/src/spikeinterface/extractors/nwbextractors.py
@@ -420,8 +420,6 @@ def _retrieve_electrodes_indices_from_electrical_series_backend(open_file, elect
     """
     if "electrodes" not in electrical_series:
         if backend == "zarr":
-            import zarr
-
             # links must be resolved
             zarr_links = electrical_series.attrs.get("_LINKS", electrical_series.attrs.get("zarr_link", []))
             electrodes_path = None
@@ -658,9 +656,7 @@ def _locate_units_table(self, backend):
             return self.file[self.unit_table_path]
         except KeyError:
             available = _find_neurodata_type_from_backend(self.file, neurodata_type="Units", backend=backend)
-            raise ValueError(
-                f"{self.unit_table_path} not found in the NWB file!" f"Available options are: {available}."
-            )
+            raise ValueError(f"{self.unit_table_path} not found in the NWB file!Available options are: {available}.")
 
     @staticmethod
     def available_units_tables(file_path, stream_mode=None, storage_options=None):
@@ -838,7 +834,7 @@ def _locate_electrical_series(self, backend):
         except KeyError:
             available = _find_neurodata_type_from_backend(self.file, neurodata_type="ElectricalSeries", backend=backend)
             raise ValueError(
-                f"{self.electrical_series_path} not found in the NWB file!" f"Available options are: {available}."
+                f"{self.electrical_series_path} not found in the NWB file!Available options are: {available}."
             )
 
     # --- electrodes table ----------------------------------------------------------------------
diff --git a/src/spikeinterface/extractors/phykilosortextractors.py b/src/spikeinterface/extractors/phykilosortextractors.py
index 95cc7c9c64..011c52fe18 100644
--- a/src/spikeinterface/extractors/phykilosortextractors.py
+++ b/src/spikeinterface/extractors/phykilosortextractors.py
@@ -17,7 +17,7 @@
 from spikeinterface.core.core_tools import define_function_from_class
 from spikeinterface.core.base import minimum_spike_dtype
 
-from spikeinterface.postprocessing import ComputeSpikeAmplitudes, ComputeSpikeLocations
+from spikeinterface.postprocessing import ComputeSpikeLocations
 from probeinterface import read_prb, Probe, ProbeGroup
 
 
@@ -164,7 +164,6 @@ def __init__(
             del cluster_info["id"]
 
         if remove_empty_units:
-
             unique_unit_ids_list = [int(clust) for clust in unique_unit_ids]
             cluster_info = cluster_info.query(f"cluster_id in {unique_unit_ids_list}")
 
@@ -573,7 +572,6 @@ def _make_templates(
 
     # Used for kilosort 2, 2.5 and 3
     else:
-
         warnings.warn("Can't extract `ms_before` and `ms_after` from Kilosort output. Guessing a sensible value.")
 
         samples_in_templates = np.shape(new_templates)[1]
diff --git a/src/spikeinterface/extractors/sinapsrecordingextractors.py b/src/spikeinterface/extractors/sinapsrecordingextractors.py
index 3e50a17fb0..b3e55437bb 100644
--- a/src/spikeinterface/extractors/sinapsrecordingextractors.py
+++ b/src/spikeinterface/extractors/sinapsrecordingextractors.py
@@ -276,7 +276,7 @@ def get_sinaps_probe(probe_type: str) -> Probe:
 
     try:
         probe = get_probe(manufacturer="sinaps-research-platform", probe_name=f"{probe_type}")
-    except:
+    except Exception:
         # check if custom version of probe was used such as "p256s1_camera"
         if "_" in probe_type:
             probe_type = probe_type.split("_")[0]
@@ -287,7 +287,7 @@ def get_sinaps_probe(probe_type: str) -> Probe:
 
         try:
             probe = get_probe(manufacturer="sinaps-research-platform", probe_name=f"{probe_type}")
-        except:
+        except Exception:
             warnings.warn(
                 f"Could not load probe information for {probe_type}. Probe needs to be linked manually with rec.set_probe()"
             )
@@ -322,13 +322,13 @@ def parse_sinaps_meta(meta_file: str | Path) -> dict:
                 val = val.replace("\n", "")
                 try:
                     val = int(val)
-                except:
+                except Exception:
                     pass
                 try:
                     val = ast.literal_eval(val)
                     if isinstance(val, tuple):
                         val = float(str(val[0]) + "." + str(val[1]))
-                except:
+                except Exception:
                     pass
                 sinaps_info[key] = val
     return sinaps_info
diff --git a/src/spikeinterface/extractors/tests/test_cbin_ibl_extractors.py b/src/spikeinterface/extractors/tests/test_cbin_ibl_extractors.py
index bc508979b9..b3f6036373 100644
--- a/src/spikeinterface/extractors/tests/test_cbin_ibl_extractors.py
+++ b/src/spikeinterface/extractors/tests/test_cbin_ibl_extractors.py
@@ -3,7 +3,7 @@
 
 import numpy as np
 
-from spikeinterface.extractors.extractor_classes import CompressedBinaryIblExtractor, read_cbin_ibl
+from spikeinterface.extractors.extractor_classes import CompressedBinaryIblExtractor
 
 from spikeinterface.extractors.cbin_ibl import (
     _get_saved_channel_indices,
@@ -13,7 +13,7 @@
     extract_stream_info,
 )
 
-from spikeinterface.extractors.tests.common_tests import RecordingCommonTestSuite, SortingCommonTestSuite
+from spikeinterface.extractors.tests.common_tests import RecordingCommonTestSuite
 
 
 class CompressedBinaryIblExtractorTest(RecordingCommonTestSuite, unittest.TestCase):
diff --git a/src/spikeinterface/extractors/tests/test_iblextractors.py b/src/spikeinterface/extractors/tests/test_iblextractors.py
index eb87b34829..f09ebf8354 100644
--- a/src/spikeinterface/extractors/tests/test_iblextractors.py
+++ b/src/spikeinterface/extractors/tests/test_iblextractors.py
@@ -1,4 +1,3 @@
-import sys
 from re import escape
 from unittest import TestCase
 
@@ -27,7 +26,7 @@ def setUpClass(cls):
                 silent=True,
                 cache_dir=None,
             )
-        except:
+        except Exception:
             print("Skipping test due to server being down.")
             pytest.skip("Skipping test due to server being down.")
         try:
@@ -124,7 +123,7 @@ def setUpClass(cls):
                 silent=True,
                 cache_dir=None,
             )
-        except:
+        except Exception:
             pytest.skip("Skipping test due to server being down.")
         cls.recording = read_ibl_recording(eid=cls.eid, stream_name="probe00.ap", load_sync_channel=True, one=cls.one)
         cls.small_scaled_trace = cls.recording.get_traces(start_frame=5, end_frame=26, return_in_uV=True)
@@ -200,7 +199,7 @@ def test_ibl_sorting_extractor(self):
                 silent=True,
                 cache_dir=None,
             )
-        except:
+        except Exception:
             pytest.skip("Skipping test due to server being down.")
         sorting = read_ibl_sorting(pid=PID, one=one, revision="2023-12-05")
         assert len(sorting.unit_ids) == 733
diff --git a/src/spikeinterface/extractors/tests/test_neoextractors.py b/src/spikeinterface/extractors/tests/test_neoextractors.py
index 228409b8f9..d7833c90cd 100644
--- a/src/spikeinterface/extractors/tests/test_neoextractors.py
+++ b/src/spikeinterface/extractors/tests/test_neoextractors.py
@@ -2,7 +2,6 @@
 import platform
 import subprocess
 import os
-from packaging import version
 import importlib.util
 
 import pytest
@@ -37,7 +36,6 @@
     AxonaRecordingExtractor,
     Plexon2EventExtractor,
     MaxwellRecordingExtractor,
-    CedRecordingExtractor,
     AlphaOmegaRecordingExtractor,
     Spike2RecordingExtractor,
     EDFRecordingExtractor,
diff --git a/src/spikeinterface/extractors/tests/test_nwbextractors.py b/src/spikeinterface/extractors/tests/test_nwbextractors.py
index b442216d86..b61eb1f4b8 100644
--- a/src/spikeinterface/extractors/tests/test_nwbextractors.py
+++ b/src/spikeinterface/extractors/tests/test_nwbextractors.py
@@ -627,7 +627,7 @@ def test_sorting_extraction_start_time(tmp_path, use_pynwb):
 def test_sorting_extraction_start_time_from_series(tmp_path, use_pynwb):
     from pynwb import NWBHDF5IO
     from pynwb.testing.mock.file import mock_NWBFile
-    from pynwb.ecephys import ElectricalSeries, LFP, FilteredEphys
+    from pynwb.ecephys import ElectricalSeries
 
     from pynwb.testing.mock.ecephys import mock_electrodes
 
@@ -860,7 +860,7 @@ def test_sorting_electrical_series_path_and_time_base_are_mutually_exclusive(tmp
             **extra_kwarg,
         )
     expected_error = (
-        "Provide either 'electrical_series_path' or the time base ('sampling_frequency' and " "'t_start'), not both."
+        "Provide either 'electrical_series_path' or the time base ('sampling_frequency' and 't_start'), not both."
     )
     assert str(exc_info.value) == expected_error
 
diff --git a/src/spikeinterface/extractors/tests/test_nwbextractors_streaming.py b/src/spikeinterface/extractors/tests/test_nwbextractors_streaming.py
index 7d43253acf..bc5ff1c823 100644
--- a/src/spikeinterface/extractors/tests/test_nwbextractors_streaming.py
+++ b/src/spikeinterface/extractors/tests/test_nwbextractors_streaming.py
@@ -10,7 +10,7 @@
 
 from spikeinterface import load
 from spikeinterface.core.testing import check_recordings_equal
-from spikeinterface.core.testing import check_recordings_equal, check_sortings_equal
+from spikeinterface.core.testing import check_sortings_equal
 from spikeinterface.extractors.extractor_classes import NwbRecordingExtractor, NwbSortingExtractor
 
 py_version = sys.version_info
diff --git a/src/spikeinterface/extractors/yassextractors.py b/src/spikeinterface/extractors/yassextractors.py
index 38efeae996..e03a0ba969 100644
--- a/src/spikeinterface/extractors/yassextractors.py
+++ b/src/spikeinterface/extractors/yassextractors.py
@@ -25,7 +25,7 @@ class YassSortingExtractor(BaseSorting):
     def __init__(self, folder_path):
         try:
             import yaml
-        except:
+        except Exception:
             raise ImportError(self.installation_mesg)
 
         folder_path = Path(folder_path)
diff --git a/src/spikeinterface/generation/drifting_generator.py b/src/spikeinterface/generation/drifting_generator.py
index f217dda1b3..1d3cda2e16 100644
--- a/src/spikeinterface/generation/drifting_generator.py
+++ b/src/spikeinterface/generation/drifting_generator.py
@@ -124,8 +124,8 @@ def make_one_displacement_vector(
 
     t_start_drift = 0.0 if t_start_drift is None else t_start_drift
     t_end_drift = duration if t_end_drift is None else t_end_drift
-    assert t_start_drift < duration, f"'t_start_drift' must preceed 'duration'!"
-    assert t_end_drift <= duration, f"'t_end_drift' must preceed 'duration'!"
+    assert t_start_drift < duration, "'t_start_drift' must preceed 'duration'!"
+    assert t_end_drift <= duration, "'t_end_drift' must preceed 'duration'!"
     start_drift_index = int(t_start_drift * displacement_sampling_frequency)
     end_drift_index = int(t_end_drift * displacement_sampling_frequency)
 
@@ -133,7 +133,6 @@ def make_one_displacement_vector(
     displacement_vector = np.zeros(num_samples, dtype="float32")
 
     if drift_mode == "zigzag":
-
         times = np.arange(end_drift_index - start_drift_index) / displacement_sampling_frequency
 
         freq = 1.0 / period_s
@@ -455,9 +454,9 @@ def generate_drifting_recording(
         num_units = sorting.get_num_units()
         sampling_frequency = sorting.sampling_frequency
         if sorting._recording is not None:
-            assert (
-                sorting.get_total_duration() == duration
-            ), "Sorting should have the same duration as the generated data"
+            assert sorting.get_total_duration() == duration, (
+                "Sorting should have the same duration as the generated data"
+            )
 
     # probe
     if probe is None:
diff --git a/src/spikeinterface/metrics/quality/pca_metrics.py b/src/spikeinterface/metrics/quality/pca_metrics.py
index 45df10a833..2e2eba034a 100644
--- a/src/spikeinterface/metrics/quality/pca_metrics.py
+++ b/src/spikeinterface/metrics/quality/pca_metrics.py
@@ -31,7 +31,7 @@ def _mahalanobis_metrics_function(sorting_analyzer, unit_ids, tmp_data, **metric
 
         try:
             isolation_distance, l_ratio = mahalanobis_metrics(pcs_flat, labels, unit_id)
-        except:
+        except Exception:
             isolation_distance = np.nan
             l_ratio = np.nan
 
@@ -71,7 +71,7 @@ def _d_prime_metric_function(sorting_analyzer, unit_ids, tmp_data, **metric_para
 
         try:
             d_prime = d_prime_metric(pcs_flat, labels, unit_id)
-        except:
+        except Exception:
             d_prime = np.nan
 
         d_prime_dict[unit_id] = d_prime
@@ -94,7 +94,7 @@ def _nn_one_unit(args):
 
     try:
         nn_hit_rate, nn_miss_rate = nearest_neighbors_metrics(pcs_flat, labels, unit_id, **metric_params)
-    except:
+    except Exception:
         nn_hit_rate = np.nan
         nn_miss_rate = np.nan
 
@@ -116,7 +116,7 @@ def _nearest_neighbor_metric_function(sorting_analyzer, unit_ids, tmp_data, **me
 
         try:
             nn_hit_rate, nn_miss_rate = nearest_neighbors_metrics(pcs_flat, labels, unit_id, **metric_params)
-        except:
+        except Exception:
             nn_hit_rate = np.nan
             nn_miss_rate = np.nan
 
@@ -176,7 +176,7 @@ def _nn_advanced_one_unit(args):
             seed=seed,
             **nn_isolation_params,
         )
-    except:
+    except Exception:
         nn_isolation, nn_unit_id = np.nan, np.nan
 
     # NN Noise Overlap
@@ -189,7 +189,7 @@ def _nn_advanced_one_unit(args):
             seed=seed,
             **nn_noise_params,
         )
-    except:
+    except Exception:
         nn_noise_overlap = np.nan
 
     return unit_id, nn_isolation, nn_unit_id, nn_noise_overlap
@@ -321,7 +321,7 @@ def _silhouette_metric_function(sorting_analyzer, unit_ids, tmp_data, **metric_p
                 silhouette_value = simplified_silhouette_score(pcs_flat, labels, unit_id)
             else:  # method == "full"
                 silhouette_value = silhouette_score(pcs_flat, labels, unit_id)
-        except:
+        except Exception:
             silhouette_value = np.nan
 
         silhouette_dict[unit_id] = silhouette_value
diff --git a/src/spikeinterface/metrics/quality/tests/test_metrics_functions.py b/src/spikeinterface/metrics/quality/tests/test_metrics_functions.py
index 2b8302e6d3..5a2742ad26 100644
--- a/src/spikeinterface/metrics/quality/tests/test_metrics_functions.py
+++ b/src/spikeinterface/metrics/quality/tests/test_metrics_functions.py
@@ -780,7 +780,7 @@ def test_unit_structure_in_output(small_sorting_analyzer):
         metric_fun = metric.metric_function
         try:
             qm_param = qm_params[metric_name]
-        except:
+        except Exception:
             qm_param = {}
 
         result_all = metric_fun(sorting_analyzer=small_sorting_analyzer, **qm_param)
@@ -796,7 +796,6 @@ def test_unit_structure_in_output(small_sorting_analyzer):
 
         else:
             for result_ind, result in enumerate(result_sub):
-
                 assert list(result_all[result_ind].keys()) == ["#3", "#9", "#4"], error
                 assert result_sub[result_ind].keys() == set(["#4", "#9"]), error
 
diff --git a/src/spikeinterface/metrics/template/tests/test_template_metrics.py b/src/spikeinterface/metrics/template/tests/test_template_metrics.py
index 30314615d1..75204e543d 100644
--- a/src/spikeinterface/metrics/template/tests/test_template_metrics.py
+++ b/src/spikeinterface/metrics/template/tests/test_template_metrics.py
@@ -6,7 +6,7 @@
     compute_template_metrics,
     get_single_channel_template_metric_names,
 )
-from spikeinterface.metrics.template.metrics import single_channel_metrics, multi_channel_metrics
+from spikeinterface.metrics.template.metrics import single_channel_metrics
 
 template_metrics = get_single_channel_template_metric_names()
 
@@ -137,7 +137,6 @@ def test_save_template_metrics(small_sorting_analyzer, create_cache_folder):
 
 
 class TestTemplateMetrics(AnalyzerExtensionCommonTestSuite):
-
     @pytest.mark.parametrize(
         "params",
         [
diff --git a/src/spikeinterface/postprocessing/amplitude_scalings.py b/src/spikeinterface/postprocessing/amplitude_scalings.py
index 3b6653f70c..ea838646fc 100644
--- a/src/spikeinterface/postprocessing/amplitude_scalings.py
+++ b/src/spikeinterface/postprocessing/amplitude_scalings.py
@@ -93,17 +93,17 @@ def _get_pipeline_nodes(self):
         # if ms_before / ms_after are set in params then the original templates are shorten
         if self.params["ms_before"] is not None:
             cut_out_before = ms_to_samples(self.params["ms_before"], self.sorting_analyzer.sampling_frequency)
-            assert (
-                cut_out_before <= nbefore
-            ), f"`ms_before` must be smaller than `ms_before` used in ComputeTemplates: {nbefore}"
+            assert cut_out_before <= nbefore, (
+                f"`ms_before` must be smaller than `ms_before` used in ComputeTemplates: {nbefore}"
+            )
         else:
             cut_out_before = nbefore
 
         if self.params["ms_after"] is not None:
             cut_out_after = ms_to_samples(self.params["ms_after"], self.sorting_analyzer.sampling_frequency)
-            assert (
-                cut_out_after <= nafter
-            ), f"`ms_after` must be smaller than `ms_after` used in templates: {templates_ext.params['ms_after']}"
+            assert cut_out_after <= nafter, (
+                f"`ms_after` must be smaller than `ms_after` used in templates: {templates_ext.params['ms_after']}"
+            )
         else:
             cut_out_after = nafter
 
@@ -120,9 +120,9 @@ def _get_pipeline_nodes(self):
             sparsity = self.params["sparsity"]
             # assert provided sparsity is sparser than the one in the waveform extractor
             waveform_sparsity = self.sorting_analyzer.sparsity
-            assert np.all(
-                np.sum(waveform_sparsity.mask, 1) - np.sum(sparsity.mask, 1) > 0
-            ), "The provided sparsity needs to be sparser than the one in the waveform extractor!"
+            assert np.all(np.sum(waveform_sparsity.mask, 1) - np.sum(sparsity.mask, 1) > 0), (
+                "The provided sparsity needs to be sparser than the one in the waveform extractor!"
+            )
         elif not self.sorting_analyzer.is_sparse() and self.params["sparsity"] is not None:
             sparsity = self.params["sparsity"]
         else:
@@ -189,9 +189,9 @@ def __init__(
             self._offsets = None
         self._dtype = np.float32
         spike_retriever = find_parent_of_type(parents, SpikeRetriever)
-        assert isinstance(
-            spike_retriever, SpikeRetriever
-        ), "SpikeAmplitudeNode needs a single SpikeRetriever as a parent"
+        assert isinstance(spike_retriever, SpikeRetriever), (
+            "SpikeAmplitudeNode needs a single SpikeRetriever as a parent"
+        )
         assert spike_retriever.include_spikes_in_margin, "Need SpikeRetriever with include_spikes_in_margin=True"
         if not handle_collisions:
             self._margin = max(nbefore, nafter)
@@ -659,7 +659,6 @@ def fit_collision(
     y = local_waveform.T.flatten()
     X = np.zeros((len(y), len(collision)))
     for i, spike in enumerate(collision):
-
         # float64 like X, so templates are not truncated to the dtype of unscaled integer or float16 traces
         full_template = np.zeros(local_waveform.shape)
 
@@ -716,7 +715,7 @@ def _plot_collisions(sorting_analyzer, sparsity=None, num_collisions=None):
 
     # TODO: this is broken, sac no longer (06/06/2024)
     # has _extension_data and its collisions attribute is unused
-    collisions = sac._extension_data[f"collisions"]
+    collisions = sac._extension_data["collisions"]
     collision_keys = list(collisions.keys())
     num_collisions = num_collisions or len(collisions)
     num_collisions = min(num_collisions, len(collisions))
diff --git a/src/spikeinterface/postprocessing/localization_tools.py b/src/spikeinterface/postprocessing/localization_tools.py
index 60746c11e9..a23019f955 100644
--- a/src/spikeinterface/postprocessing/localization_tools.py
+++ b/src/spikeinterface/postprocessing/localization_tools.py
@@ -1,5 +1,3 @@
-from typing import Literal
-
 import warnings
 import importlib.util
 
diff --git a/src/spikeinterface/postprocessing/noise_level.py b/src/spikeinterface/postprocessing/noise_level.py
index 59ede21fcb..84c6a3ae7e 100644
--- a/src/spikeinterface/postprocessing/noise_level.py
+++ b/src/spikeinterface/postprocessing/noise_level.py
@@ -1,3 +1,2 @@
 # "noise_levels" extensions is now in core
 # this is kept name space compatibility but should be removed soon
-from spikeinterface.core.analyzer_extension_core import ComputeNoiseLevels, compute_noise_levels
diff --git a/src/spikeinterface/postprocessing/principal_component.py b/src/spikeinterface/postprocessing/principal_component.py
index 225b37c9f0..60f398f4d2 100644
--- a/src/spikeinterface/postprocessing/principal_component.py
+++ b/src/spikeinterface/postprocessing/principal_component.py
@@ -394,9 +394,9 @@ def run_for_all_spikes(self, file_path=None, verbose=False, **job_kwargs):
         p = self.params
         sorting_analyzer = self.sorting_analyzer
         sorting = sorting_analyzer.sorting
-        assert (
-            sorting_analyzer.has_recording() or sorting_analyzer.has_temporary_recording()
-        ), "To compute PCA projections for all spikes, the sorting analyzer needs the recording"
+        assert sorting_analyzer.has_recording() or sorting_analyzer.has_temporary_recording(), (
+            "To compute PCA projections for all spikes, the sorting analyzer needs the recording"
+        )
         recording = sorting_analyzer.recording
 
         # assert sorting.get_num_segments() == 1
@@ -578,7 +578,7 @@ def _transform_waveforms(self, spikes, waveforms, pca_model, progress_bar):
                     try:
                         proj = pca_model.transform(wfs[:, :, wf_ind])
                         pca_projection[:, :, wf_ind][spike_mask, :] = proj
-                    except:
+                    except Exception:
                         # this could happen if len(wfs) is less then n_comp for a channel
                         project_on_non_fitted = True
             if project_on_non_fitted:
diff --git a/src/spikeinterface/postprocessing/template_similarity.py b/src/spikeinterface/postprocessing/template_similarity.py
index ef40671b1f..a65bd8fb54 100644
--- a/src/spikeinterface/postprocessing/template_similarity.py
+++ b/src/spikeinterface/postprocessing/template_similarity.py
@@ -1,5 +1,4 @@
 import numpy as np
-import warnings
 from itertools import chain
 import importlib.util
 from spikeinterface.core.core_tools import slice_rows, materialize_array
@@ -259,7 +258,6 @@ def _compute_similarity_matrix_numpy(
 
 
 if HAVE_NUMBA:
-
     from math import sqrt
     from numba import jit, typed, prange
 
@@ -304,7 +302,6 @@ def _compute_similarity_matrix_numba(
         for src_unit in range(num_templates):
             start = src_unit if same_array else 0
             for tgt_unit in range(start, other_num_templates):
-
                 if support == "intersection":
                     ch = np.where(sparsity_mask[src_unit] & other_sparsity_mask[tgt_unit])[0].astype(np.uint16)
 
@@ -417,12 +414,12 @@ def compute_similarity_with_templates_array(
     if method not in all_metrics:
         raise ValueError(f"compute_template_similarity (method {method}) not exists")
 
-    assert (
-        templates_array.shape[1] == other_templates_array.shape[1]
-    ), "The number of samples in the templates should be the same for both arrays"
-    assert (
-        templates_array.shape[2] == other_templates_array.shape[2]
-    ), "The number of channels in the templates should be the same for both arrays"
+    assert templates_array.shape[1] == other_templates_array.shape[1], (
+        "The number of samples in the templates should be the same for both arrays"
+    )
+    assert templates_array.shape[2] == other_templates_array.shape[2], (
+        "The number of channels in the templates should be the same for both arrays"
+    )
     # num_templates = templates_array.shape[0]
     num_samples = templates_array.shape[1]
     # num_channels = templates_array.shape[2]
diff --git a/src/spikeinterface/postprocessing/tests/test_multi_extensions.py b/src/spikeinterface/postprocessing/tests/test_multi_extensions.py
index 17f51fd1ce..b863037cdc 100644
--- a/src/spikeinterface/postprocessing/tests/test_multi_extensions.py
+++ b/src/spikeinterface/postprocessing/tests/test_multi_extensions.py
@@ -1,6 +1,5 @@
 import pytest
 
-import time
 import numpy as np
 
 from spikeinterface import (
diff --git a/src/spikeinterface/postprocessing/unit_locations.py b/src/spikeinterface/postprocessing/unit_locations.py
index 7cd94d7ee9..da4e39730c 100644
--- a/src/spikeinterface/postprocessing/unit_locations.py
+++ b/src/spikeinterface/postprocessing/unit_locations.py
@@ -1,7 +1,7 @@
 import numpy as np
 from itertools import chain
 
-from spikeinterface.core.core_tools import slice_rows, materialize_array
+from spikeinterface.core.core_tools import slice_rows
 from spikeinterface.core.sortinganalyzer import register_result_extension, AnalyzerExtension
 from .localization_tools import _unit_location_methods
 
diff --git a/src/spikeinterface/postprocessing/valid_unit_periods.py b/src/spikeinterface/postprocessing/valid_unit_periods.py
index da28b20e00..d24f206e2b 100644
--- a/src/spikeinterface/postprocessing/valid_unit_periods.py
+++ b/src/spikeinterface/postprocessing/valid_unit_periods.py
@@ -137,9 +137,9 @@ def _set_params(
 
         # subperiods
         assert period_mode in ("absolute", "relative"), f"Invalid subperiod_size_mode: {period_mode}"
-        assert (
-            period_duration_s_absolute > 0 or period_target_num_spikes > 0
-        ), "Either period_duration_s_absolute or period_target_num_spikes must be positive."
+        assert period_duration_s_absolute > 0 or period_target_num_spikes > 0, (
+            "Either period_duration_s_absolute or period_target_num_spikes must be positive."
+        )
         assert isinstance(period_target_num_spikes, (int)), "period_target_num_spikes must be an integer."
 
         # user_defined_periods formatting
@@ -147,7 +147,7 @@ def _set_params(
         if user_defined_periods is not None:
             try:
                 user_defined_periods = np.asarray(user_defined_periods)
-            except Exception as e:
+            except Exception:
                 raise ValueError(
                     (
                         "user_defined_periods must be some (n_periods, 3) [unit, good_period_start, good_period_end] "
@@ -362,12 +362,10 @@ def _run(self, unit_ids=None, verbose=False, **job_kwargs):
 
     def _compute_valid_periods(self, sorting_analyzer, unit_ids=None, **job_kwargs):
         if self.params["method"] == "user_defined":
-
             # directly use user defined periods
             return self.user_defined_periods, None, None, None
 
         elif self.params["method"] in ["false_positives_and_negatives", "combined"]:
-
             # dict: unit_id -> list of subperiod, each subperiod is an array of dtype unit_period_dtype with 4 fields
             all_periods, all_periods_w_margins = compute_subperiods(
                 sorting_analyzer,
@@ -394,7 +392,7 @@ def _compute_valid_periods(self, sorting_analyzer, unit_ids=None, **job_kwargs):
 
             # Each item is one computation of fp and fn for one period and one unit
             items = [(period,) for period in all_periods_w_margins]
-            job_name = f"computing false positives and negatives"
+            job_name = "computing false positives and negatives"
 
             # parallel
             with ProcessPoolExecutor(
diff --git a/src/spikeinterface/preprocessing/decimate.py b/src/spikeinterface/preprocessing/decimate.py
index 147e685118..16bd21445d 100644
--- a/src/spikeinterface/preprocessing/decimate.py
+++ b/src/spikeinterface/preprocessing/decimate.py
@@ -70,7 +70,7 @@ def __init__(
         # Original sampling frequency
         self._orig_samp_freq = recording.get_sampling_frequency()
         if not isinstance(decimation_factor, int) or decimation_factor <= 0:
-            raise ValueError(f"Expecting strictly positive integer for `decimation_factor` arg")
+            raise ValueError("Expecting strictly positive integer for `decimation_factor` arg")
         self._decimation_factor = decimation_factor
         if not isinstance(decimation_offset, int) or decimation_offset < 0:
             raise ValueError("Expecting a nonnegative integer for `decimation_offset` arg")
@@ -79,8 +79,8 @@ def __init__(
         )
         if decimation_offset >= decimation_factor or decimation_offset >= parent_min_n_samp:
             raise ValueError(
-                f"Expecting `decimation_offset` < `decimation_factor` and `decimation_offset` < parent_segment.get_num_samples() for all segments. "
-                f"Consider combining DecimateRecording with FrameSliceRecording for fine control on the recording start/end frames."
+                "Expecting `decimation_offset` < `decimation_factor` and `decimation_offset` < parent_segment.get_num_samples() for all segments. "
+                "Consider combining DecimateRecording with FrameSliceRecording for fine control on the recording start/end frames."
             )
         self._decimation_offset = decimation_offset
         decimated_sampling_frequency = self._orig_samp_freq / self._decimation_factor
@@ -179,9 +179,7 @@ def get_traces(self, start_frame, end_frame, channel_indices):
                 parent_start_frame,
                 parent_end_frame,
                 channel_indices,
-            )[
-                :: self._decimation_factor
-            ].astype(self._dtype)
+            )[:: self._decimation_factor].astype(self._dtype)
 
         return get_polyphase_resampled_traces(
             self._parent_segment,
diff --git a/src/spikeinterface/preprocessing/deepinterpolation/tests/test_deepinterpolation.py b/src/spikeinterface/preprocessing/deepinterpolation/tests/test_deepinterpolation.py
index 8d2558531f..1d99788525 100644
--- a/src/spikeinterface/preprocessing/deepinterpolation/tests/test_deepinterpolation.py
+++ b/src/spikeinterface/preprocessing/deepinterpolation/tests/test_deepinterpolation.py
@@ -11,7 +11,6 @@
 from spikeinterface.preprocessing import depth_order, zscore
 
 from spikeinterface.preprocessing.deepinterpolation import train_deepinterpolation, deepinterpolate
-from spikeinterface.preprocessing.deepinterpolation.train import train_deepinterpolation_process
 
 tensorflow_spec = importlib.util.find_spec("tensorflow")
 deepinter_spec = importlib.util.find_spec("deepinterpolation")
diff --git a/src/spikeinterface/preprocessing/interpolate_bad_channels.py b/src/spikeinterface/preprocessing/interpolate_bad_channels.py
index f2ae77f3d7..a5eb206f70 100644
--- a/src/spikeinterface/preprocessing/interpolate_bad_channels.py
+++ b/src/spikeinterface/preprocessing/interpolate_bad_channels.py
@@ -8,7 +8,6 @@
     detect_bad_channels,
     _get_all_detect_bad_channel_kwargs,
 )
-from inspect import signature
 
 
 class InterpolateBadChannelsRecording(BasePreprocessor):
diff --git a/src/spikeinterface/preprocessing/motion.py b/src/spikeinterface/preprocessing/motion.py
index 388605c166..2629b118c1 100644
--- a/src/spikeinterface/preprocessing/motion.py
+++ b/src/spikeinterface/preprocessing/motion.py
@@ -12,7 +12,6 @@
 from spikeinterface.core import get_noise_levels, fix_job_kwargs
 from spikeinterface.core.job_tools import _shared_job_kwargs_doc
 from spikeinterface.core.core_tools import SIJsonEncoder
-from spikeinterface.core.job_tools import _shared_job_kwargs_doc
 from spikeinterface.core import BaseRecording
 
 motion_options_preset = {
@@ -336,7 +335,7 @@ def compute_motion(
     from spikeinterface.sortingcomponents.peak_selection import select_peaks
     from spikeinterface.sortingcomponents.peak_localization import localize_peaks, peak_localization_methods
     from spikeinterface.core.node_pipeline import ExtractDenseWaveforms, run_node_pipeline
-    from spikeinterface.sortingcomponents.motion.motion_estimation import estimate_motion, estimate_motion_methods
+    from spikeinterface.sortingcomponents.motion.motion_estimation import estimate_motion
 
     # get preset params and update if necessary
     detect_kwargs, select_kwargs, localize_peaks_kwargs, estimate_motion_kwargs = _update_motion_kwargs(
@@ -643,7 +642,6 @@ def load_motion_info(folder):
     if (folder / "motion").is_dir():
         motion = Motion.load(folder / "motion")
     else:
-
         is_legacy_format = True
         required_files = ["spatial_bins.npy", "temporal_bins.npy", "motion.npy"]
         for required_file in required_files:
@@ -651,7 +649,6 @@ def load_motion_info(folder):
                 is_legacy_format = False
 
         if is_legacy_format:
-
             warnings.warn("Trying to load Motion from the legacy format")
 
             spatial_bins_um = np.load(folder / "spatial_bins.npy")
@@ -661,7 +658,6 @@ def load_motion_info(folder):
             motion = Motion(displacement=displacement, temporal_bins_s=temporal_bins_s, spatial_bins_um=spatial_bins_um)
 
         else:
-
             warnings.warn("No `motion` object in folder. `motion_info` is loaded with `motion` equal to `None`.")
 
             motion = None
diff --git a/src/spikeinterface/preprocessing/pipeline.py b/src/spikeinterface/preprocessing/pipeline.py
index b75cae49f8..4ee81f3de0 100644
--- a/src/spikeinterface/preprocessing/pipeline.py
+++ b/src/spikeinterface/preprocessing/pipeline.py
@@ -5,7 +5,7 @@
 from spikeinterface.core.core_tools import is_dict_extractor, is_path_remote
 from spikeinterface.core.zarrextractors import super_zarr_open
 from spikeinterface.core.zarr_tools import read_encoded_array
-from spikeinterface.preprocessing.preprocessing_classes import preprocessor_dict, _all_preprocesser_dict
+from spikeinterface.preprocessing.preprocessing_classes import preprocessor_dict
 
 pp_names_to_functions = {preprocessor.__name__: preprocessor for preprocessor in preprocessor_dict.values()}
 
@@ -30,9 +30,9 @@ def __init__(self, preprocessor_list_or_dict):
                 preprocessor_list.append(step)
         elif isinstance(preprocessor_list_or_dict, list):
             preprocessor_list = preprocessor_list_or_dict
-            assert all(
-                isinstance(step, dict) and "name" in step for step in preprocessor_list
-            ), "Each step in the preprocessor list must be a dict with 'name' key."
+            assert all(isinstance(step, dict) and "name" in step for step in preprocessor_list), (
+                "Each step in the preprocessor list must be a dict with 'name' key."
+            )
 
         for step in preprocessor_list:
             if "params" not in step:
@@ -321,7 +321,6 @@ def _make_pipeline_list_from_recording_dict(recording_dict):
 
     preprocessing_list = []
     for preprocessor in pipeline_dict_from_file:
-
         preprocessor_class_name = preprocessor.split(".")[-1]
 
         preprocessor_function = preprocessor_dict.get(preprocessor_class_name)
@@ -391,7 +390,6 @@ def _get_all_kwargs_and_values(my_pipeline):
 
     all_kwargs_list = []
     for preprocessor in my_pipeline.preprocessor_list:
-
         preprocessor_name = preprocessor["name"].split(".")[-1]
         pp_function = my_pipeline.function_names_to_functions[preprocessor["name"].split(".")[-1]]
         signature = inspect.signature(pp_function)
@@ -407,7 +405,7 @@ def _get_all_kwargs_and_values(my_pipeline):
                         default_value = None
                     else:
                         default_value = default_value[-1]
-                except:
+                except Exception:
                     default_value = None
 
                 preprocessor_index = my_pipeline.preprocessor_list.index(preprocessor)
diff --git a/src/spikeinterface/preprocessing/resample.py b/src/spikeinterface/preprocessing/resample.py
index 10783062ed..6dd8c9c3b4 100644
--- a/src/spikeinterface/preprocessing/resample.py
+++ b/src/spikeinterface/preprocessing/resample.py
@@ -1,5 +1,4 @@
 import numpy as np
-import warnings
 
 from spikeinterface.core.core_tools import define_function_handling_dict_from_class
 
diff --git a/src/spikeinterface/preprocessing/tests/test_astype.py b/src/spikeinterface/preprocessing/tests/test_astype.py
index d1d1b11f43..88c80e414a 100644
--- a/src/spikeinterface/preprocessing/tests/test_astype.py
+++ b/src/spikeinterface/preprocessing/tests/test_astype.py
@@ -1,9 +1,4 @@
-import pytest
-from pathlib import Path
-import shutil
-
-from spikeinterface import set_global_tmp_folder, NumpyRecording
-from spikeinterface.core import generate_recording
+from spikeinterface import NumpyRecording
 
 from spikeinterface.preprocessing import astype
 
diff --git a/src/spikeinterface/preprocessing/tests/test_common_reference.py b/src/spikeinterface/preprocessing/tests/test_common_reference.py
index 139213056f..9a5b81d9c8 100644
--- a/src/spikeinterface/preprocessing/tests/test_common_reference.py
+++ b/src/spikeinterface/preprocessing/tests/test_common_reference.py
@@ -1,4 +1,3 @@
-import operator
 import pytest
 
 from spikeinterface.core import generate_recording, NumpyRecording
@@ -6,7 +5,6 @@
 from spikeinterface.preprocessing import common_reference
 
 import numpy as np
-from tqdm import trange
 
 
 def _generate_test_recording():
diff --git a/src/spikeinterface/preprocessing/tests/test_detect_artifacts.py b/src/spikeinterface/preprocessing/tests/test_detect_artifacts.py
index 81f934300a..0f524af3b0 100644
--- a/src/spikeinterface/preprocessing/tests/test_detect_artifacts.py
+++ b/src/spikeinterface/preprocessing/tests/test_detect_artifacts.py
@@ -1,6 +1,6 @@
 import numpy as np
 
-from spikeinterface.core import generate_recording, NumpyRecording
+from spikeinterface.core import NumpyRecording
 from spikeinterface.preprocessing import (
     detect_artifact_periods,
     detect_saturation_periods,
@@ -41,7 +41,6 @@ def test_detect_artifact_by_envelope(debug_plots):
     )
 
     if debug_plots:
-        import matplotlib
         import matplotlib.pyplot as plt
 
         plt.plot(envelope.get_traces(), color="r", lw=3)
@@ -151,7 +150,6 @@ def test_detect_saturation_periods(debug_plots):
     offset = 0
 
     if debug_plots:
-        import matplotlib
         import matplotlib.pyplot as plt
 
         plt.plot(data_seg_1)
@@ -206,12 +204,12 @@ def test_detect_saturation_periods(debug_plots):
     for seg_periods, seg_offset in zip([seg_1_periods, seg_2_periods], offsets):
         slow_period_idx = np.argmin(np.abs(seg_periods["start_sample_index"] - start_slow_artifact))
         slow_period = seg_periods[slow_period_idx]
-        assert (
-            slow_period["start_sample_index"] >= start_rising_sample + tolerance_samples
-        ), "Slow artifact period starts in the rising phase"
-        assert (
-            slow_period["end_sample_index"] <= stop_falling_sample + seg_offset - tolerance_samples
-        ), "Slow artifact period ends in the falling phase"
+        assert slow_period["start_sample_index"] >= start_rising_sample + tolerance_samples, (
+            "Slow artifact period starts in the rising phase"
+        )
+        assert slow_period["end_sample_index"] <= stop_falling_sample + seg_offset - tolerance_samples, (
+            "Slow artifact period ends in the falling phase"
+        )
 
     # Just do a quick test that a threshold slightly over the sat value is not detected.
     # In this case we only see the derivative threshold detection. We do not play around with this
diff --git a/src/spikeinterface/preprocessing/tests/test_filter.py b/src/spikeinterface/preprocessing/tests/test_filter.py
index 3b47d0eb1a..42d6619671 100644
--- a/src/spikeinterface/preprocessing/tests/test_filter.py
+++ b/src/spikeinterface/preprocessing/tests/test_filter.py
@@ -2,7 +2,6 @@
 
 import numpy as np
 from spikeinterface.core import generate_recording
-from spikeinterface import NumpyRecording, set_global_tmp_folder
 
 from spikeinterface.preprocessing import filter, bandpass_filter, notch_filter, causal_filter
 
diff --git a/src/spikeinterface/preprocessing/tests/test_pipeline.py b/src/spikeinterface/preprocessing/tests/test_pipeline.py
index 1ea89ec749..9cd54ad9fc 100644
--- a/src/spikeinterface/preprocessing/tests/test_pipeline.py
+++ b/src/spikeinterface/preprocessing/tests/test_pipeline.py
@@ -6,8 +6,6 @@
 from spikeinterface.preprocessing import (
     apply_preprocessing_pipeline,
     preprocessor_dict,
-    bandpass_filter,
-    common_reference,
     whiten,
     detect_and_remove_bad_channels,
     bandpass_filter,
@@ -45,7 +43,6 @@ def test_pipeline_equiv_to_step():
 
     for rec in [single_group_rec, rec_groups.split_by("group")]:
         for _, pp_wrapper in preprocessor_dict.items():
-
             pp_name = pp_wrapper.__name__
             pp_class = pp_names_to_functions[pp_name]
 
diff --git a/src/spikeinterface/preprocessing/tests/test_preprocessing_tools.py b/src/spikeinterface/preprocessing/tests/test_preprocessing_tools.py
index db3df0b7ab..55d4b61037 100644
--- a/src/spikeinterface/preprocessing/tests/test_preprocessing_tools.py
+++ b/src/spikeinterface/preprocessing/tests/test_preprocessing_tools.py
@@ -1,5 +1,3 @@
-import pytest
-
 import numpy as np
 
 from spikeinterface.preprocessing import get_spatial_interpolation_kernel
@@ -13,7 +11,6 @@ def test_get_spatial_interpolation_kernel():
     target_location[:, 1] = np.linspace(0, 130, 4)
 
     for method in ("kriging", "idw", "nearest"):
-
         kernel = get_spatial_interpolation_kernel(
             source_location, target_location, method=method, force_extrapolate=False
         )
diff --git a/src/spikeinterface/preprocessing/tests/test_remove_artifacts.py b/src/spikeinterface/preprocessing/tests/test_remove_artifacts.py
index 85ba61cdd4..716f173fbb 100644
--- a/src/spikeinterface/preprocessing/tests/test_remove_artifacts.py
+++ b/src/spikeinterface/preprocessing/tests/test_remove_artifacts.py
@@ -1,5 +1,3 @@
-import pytest
-
 import numpy as np
 
 from spikeinterface.core import generate_recording
diff --git a/src/spikeinterface/preprocessing/tests/test_resample.py b/src/spikeinterface/preprocessing/tests/test_resample.py
index de5f19def4..bfcd27f71e 100644
--- a/src/spikeinterface/preprocessing/tests/test_resample.py
+++ b/src/spikeinterface/preprocessing/tests/test_resample.py
@@ -143,7 +143,7 @@ def test_resample_freq_domain():
         fig, ax = plt.subplots(nrows=1, ncols=1, figsize=[10, 7])
 
         xf, nyf = get_fft(parent_rec.get_traces().ravel(), parent_rec.get_sampling_frequency())
-        _ = ax.plot(xf, nyf, color="k", alpha=0.8, label=f"original")
+        _ = ax.plot(xf, nyf, color="k", alpha=0.8, label="original")
 
         for i, rec in enumerate(resamp_recs):
             rs_rate = int(rec.get_sampling_frequency())
diff --git a/src/spikeinterface/preprocessing/tests/test_silence_periods.py b/src/spikeinterface/preprocessing/tests/test_silence_periods.py
index d3531f1a0f..5b8598aee7 100644
--- a/src/spikeinterface/preprocessing/tests/test_silence_periods.py
+++ b/src/spikeinterface/preprocessing/tests/test_silence_periods.py
@@ -1,5 +1,3 @@
-import pytest
-
 from spikeinterface.core import generate_recording
 from spikeinterface.core import get_noise_levels
 from spikeinterface.core.base import base_period_dtype
diff --git a/src/spikeinterface/preprocessing/tests/testing_tools.py b/src/spikeinterface/preprocessing/tests/testing_tools.py
index 2257039d43..244a421fe3 100644
--- a/src/spikeinterface/preprocessing/tests/testing_tools.py
+++ b/src/spikeinterface/preprocessing/tests/testing_tools.py
@@ -1,8 +1,2 @@
-import numpy as np
-
-from spikeinterface import NumpyRecording
-
-from probeinterface import generate_linear_probe
-
 if __name__ == "__main__":
     pass
diff --git a/src/spikeinterface/sorters/basesorter.py b/src/spikeinterface/sorters/basesorter.py
index f25fe33e92..233de7ee46 100644
--- a/src/spikeinterface/sorters/basesorter.py
+++ b/src/spikeinterface/sorters/basesorter.py
@@ -195,7 +195,7 @@ def set_params_to_folder(
         invalid_parameters = [k for k in new_params.keys() if k not in valid_parameters]
 
         if invalid_parameters:
-            error_msg = f"Invalid parameters: {invalid_parameters} \n" f"Valid parameters are: {valid_parameters}"
+            error_msg = f"Invalid parameters: {invalid_parameters} \nValid parameters are: {valid_parameters}"
             raise ValueError(error_msg)
 
         params.update(new_params)
@@ -278,7 +278,7 @@ def run_from_folder(cls, output_folder, raise_error, verbose):
             t1 = time.perf_counter()
             run_time = float(t1 - t0)
             has_error = False
-        except Exception as err:
+        except Exception:
             has_error = True
             run_time = None
             log["error"] = True
diff --git a/src/spikeinterface/sorters/external/dartsort.py b/src/spikeinterface/sorters/external/dartsort.py
index daad3ec555..8e66f7929b 100644
--- a/src/spikeinterface/sorters/external/dartsort.py
+++ b/src/spikeinterface/sorters/external/dartsort.py
@@ -1,4 +1,5 @@
 from pathlib import Path
+import importlib.util
 
 import numpy as np
 
@@ -44,14 +45,7 @@ def _dynamic_params(cls):
 
     @classmethod
     def is_installed(cls):
-        try:
-            import dartsort
-
-            HAVE_DARTSORT = True
-        except ImportError:
-            HAVE_DARTSORT = False
-
-        return HAVE_DARTSORT
+        return importlib.util.find_spec("dartsort") is not None
 
     @staticmethod
     def get_sorter_version():
diff --git a/src/spikeinterface/sorters/external/hdsort.py b/src/spikeinterface/sorters/external/hdsort.py
index 07d59332d2..0be747b72b 100644
--- a/src/spikeinterface/sorters/external/hdsort.py
+++ b/src/spikeinterface/sorters/external/hdsort.py
@@ -52,7 +52,7 @@ class HDSortSorter(BaseSorter):
 
     _params_description = {
         "detect_threshold": "Threshold for spike detection",
-        "detect_sign": "Use -1 (negative) or 1 (positive) depending " "on the sign of the spikes in the recording",
+        "detect_sign": "Use -1 (negative) or 1 (positive) depending on the sign of the spikes in the recording",
         "filter": "Enable or disable filter",
         "parfor": "If True, the Matlab parfor is used",
         "freq_min": "High-pass filter cutoff frequency",
@@ -248,7 +248,7 @@ def _get_result_from_folder(cls, sorter_output_folder):
     def write_hdsort_input_format(cls, recording, save_path, chunk_memory="500M"):
         try:
             import h5py
-        except:
+        except Exception:
             raise Exception("To use HDSort, install h5py: pip install h5py")
 
         # check if already in write format
diff --git a/src/spikeinterface/sorters/external/rt_sort.py b/src/spikeinterface/sorters/external/rt_sort.py
index 76ab5cc413..99f486c6c7 100644
--- a/src/spikeinterface/sorters/external/rt_sort.py
+++ b/src/spikeinterface/sorters/external/rt_sort.py
@@ -1,6 +1,5 @@
 import importlib.util
 import os
-import numpy as np
 
 from ..basesorter import BaseSorter
 
@@ -116,7 +115,7 @@ class RTSortSorter(BaseSorter):
     This implementation in SpikeInterface only implements RT-Sort's offline sorting.
     For more information see https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0312438"""
 
-    installation_mesg = f"""\nTo use RTSort run:\n
+    installation_mesg = """\nTo use RTSort run:\n
        >>> pip install git+https://github.com/braingeneers/braindance#egg=braindance[rt-sort]
 
     Additionally, install PyTorch (https://pytorch.org/get-started/locally/) with any version of CUDA as the compute platform.
diff --git a/src/spikeinterface/sorters/external/tests/test_combinato.py b/src/spikeinterface/sorters/external/tests/test_combinato.py
index 248cf9274d..304f523f18 100644
--- a/src/spikeinterface/sorters/external/tests/test_combinato.py
+++ b/src/spikeinterface/sorters/external/tests/test_combinato.py
@@ -1,6 +1,6 @@
 from spikeinterface.sorters import CombinatoSorter
 
-import os, getpass
+import getpass
 
 if getpass.getuser() == "samuel":
     combinato_path = "/home/samuel/Documents/SpikeInterface/combinato/"
diff --git a/src/spikeinterface/sorters/external/tests/test_hdsort.py b/src/spikeinterface/sorters/external/tests/test_hdsort.py
index d8495339d3..0894a3655e 100644
--- a/src/spikeinterface/sorters/external/tests/test_hdsort.py
+++ b/src/spikeinterface/sorters/external/tests/test_hdsort.py
@@ -1,6 +1,6 @@
 from spikeinterface.sorters import HDSortSorter
 
-import os, getpass
+import getpass
 
 if getpass.getuser() == "samuel":
     hdsort_path = "/home/samuel/Documents/SpikeInterface/HDsort/"
diff --git a/src/spikeinterface/sorters/external/tests/test_ironclust.py b/src/spikeinterface/sorters/external/tests/test_ironclust.py
index 54edae6976..7642bc8f7e 100644
--- a/src/spikeinterface/sorters/external/tests/test_ironclust.py
+++ b/src/spikeinterface/sorters/external/tests/test_ironclust.py
@@ -1,4 +1,5 @@
-import os, getpass
+import os
+import getpass
 
 if getpass.getuser() == "samuel":
     ironclust_path = "/home/samuel/Documents/SpikeInterface/ironclust/"
diff --git a/src/spikeinterface/sorters/external/tests/test_kilosort2_5.py b/src/spikeinterface/sorters/external/tests/test_kilosort2_5.py
index 58d9114930..8f7c7939a5 100644
--- a/src/spikeinterface/sorters/external/tests/test_kilosort2_5.py
+++ b/src/spikeinterface/sorters/external/tests/test_kilosort2_5.py
@@ -1,6 +1,6 @@
 from spikeinterface.sorters import Kilosort2_5Sorter
 
-import os, getpass
+import getpass
 
 if getpass.getuser() == "samuel":
     kilosort2_5_path = "/home/samuel/Documents/SpikeInterface/Kilosort2.5"
diff --git a/src/spikeinterface/sorters/external/tests/test_singularity_containers_gpu.py b/src/spikeinterface/sorters/external/tests/test_singularity_containers_gpu.py
index eb238abdf4..aa3e683199 100644
--- a/src/spikeinterface/sorters/external/tests/test_singularity_containers_gpu.py
+++ b/src/spikeinterface/sorters/external/tests/test_singularity_containers_gpu.py
@@ -1,5 +1,4 @@
 import os
-import shutil
 
 import pytest
 
diff --git a/src/spikeinterface/sorters/external/tests/test_tridesclous.py b/src/spikeinterface/sorters/external/tests/test_tridesclous.py
index 95c663a20e..b00512879e 100644
--- a/src/spikeinterface/sorters/external/tests/test_tridesclous.py
+++ b/src/spikeinterface/sorters/external/tests/test_tridesclous.py
@@ -1,7 +1,6 @@
 import unittest
 
 import pytest
-from spikeinterface.extractors import toy_example
 from spikeinterface.sorters import TridesclousSorter
 from spikeinterface.sorters.tests.common_tests import SorterCommonTestSuite
 
diff --git a/src/spikeinterface/sorters/external/tests/test_waveclus.py b/src/spikeinterface/sorters/external/tests/test_waveclus.py
index 71af12d99f..4d3335a6dd 100644
--- a/src/spikeinterface/sorters/external/tests/test_waveclus.py
+++ b/src/spikeinterface/sorters/external/tests/test_waveclus.py
@@ -1,4 +1,5 @@
-import os, getpass
+import os
+import getpass
 
 if getpass.getuser() == "samuel":
     waveclus_path = "/home/samuel/Documents/SpikeInterface/wave_clus/"
diff --git a/src/spikeinterface/sorters/external/waveclus.py b/src/spikeinterface/sorters/external/waveclus.py
index 2d498616b7..41277667b6 100644
--- a/src/spikeinterface/sorters/external/waveclus.py
+++ b/src/spikeinterface/sorters/external/waveclus.py
@@ -194,7 +194,7 @@ def _run_from_folder(cls, sorter_output_folder, params, verbose):
             """
         else:
             source_dir = Path(__file__).parent
-            shutil.copy(str(source_dir / f"waveclus_master.m"), str(sorter_output_folder))
+            shutil.copy(str(source_dir / "waveclus_master.m"), str(sorter_output_folder))
 
             sorter_path = Path(cls.waveclus_path).absolute()
             if "win" in sys.platform and sys.platform != "darwin":
diff --git a/src/spikeinterface/sorters/internal/lupin.py b/src/spikeinterface/sorters/internal/lupin.py
index 8f83bf3352..799a88071c 100644
--- a/src/spikeinterface/sorters/internal/lupin.py
+++ b/src/spikeinterface/sorters/internal/lupin.py
@@ -12,7 +12,7 @@
 
 from spikeinterface.core.job_tools import fix_job_kwargs
 
-from spikeinterface.preprocessing import bandpass_filter, common_reference, zscore, whiten
+from spikeinterface.preprocessing import bandpass_filter, common_reference, whiten
 from spikeinterface.core.base import minimum_spike_dtype
 
 from spikeinterface.sortingcomponents.tools import cache_preprocessing, clean_cache_preprocessing
@@ -177,7 +177,6 @@ def _run_from_folder(cls, sorter_output_folder, params, verbose):
         # preprocessing
         if params["apply_preprocessing"]:
             if params["apply_motion_correction"]:
-
                 rec_for_motion = recording_raw
                 if params["preprocessing_dict"] is None:
                     rec_for_motion = bandpass_filter(
diff --git a/src/spikeinterface/sorters/internal/si_based.py b/src/spikeinterface/sorters/internal/si_based.py
index 3860e60fb5..64dc035085 100644
--- a/src/spikeinterface/sorters/internal/si_based.py
+++ b/src/spikeinterface/sorters/internal/si_based.py
@@ -1,4 +1,4 @@
-from spikeinterface.core import load, NumpyRecording
+from spikeinterface.core import load
 
 from spikeinterface.sorters import BaseSorter
 
diff --git a/src/spikeinterface/sorters/internal/simplesorter.py b/src/spikeinterface/sorters/internal/simplesorter.py
index 0c7414171d..d0b89fe9fb 100644
--- a/src/spikeinterface/sorters/internal/simplesorter.py
+++ b/src/spikeinterface/sorters/internal/simplesorter.py
@@ -1,9 +1,8 @@
 from .si_based import ComponentsBasedSorter
 
-from spikeinterface.core import BaseRecording, get_noise_levels, extract_waveforms, NumpySorting
+from spikeinterface.core import get_noise_levels, NumpySorting
 from spikeinterface.core.job_tools import fix_job_kwargs
-from spikeinterface.sortingcomponents.tools import cache_preprocessing
-from spikeinterface.preprocessing import bandpass_filter, common_reference, zscore
+from spikeinterface.preprocessing import bandpass_filter, zscore
 
 import numpy as np
 
diff --git a/src/spikeinterface/sorters/internal/spyking_circus2.py b/src/spikeinterface/sorters/internal/spyking_circus2.py
index 06b804b305..a9188259bf 100644
--- a/src/spikeinterface/sorters/internal/spyking_circus2.py
+++ b/src/spikeinterface/sorters/internal/spyking_circus2.py
@@ -1,6 +1,7 @@
 from .si_based import ComponentsBasedSorter
 
 import shutil
+import importlib.util
 import numpy as np
 
 from spikeinterface.core import NumpySorting
@@ -90,8 +91,6 @@ class Spykingcircus2Sorter(ComponentsBasedSorter):
 
     @classmethod
     def is_installed(cls):
-        import importlib.util
-
         spykingcircus2_deps = ["scipy", "numba", "hdbscan"]
 
         for package_name in spykingcircus2_deps:
@@ -107,9 +106,9 @@ def get_sorter_version(cls):
     @classmethod
     def _run_from_folder(cls, sorter_output_folder, params, verbose):
 
-        try:
-            import torch
-        except ImportError:
+        if importlib.util.find_spec("torch") is not None:
+            HAVE_TORCH = True
+        else:
             HAVE_TORCH = False
             print("spykingcircus2 could benefit from using torch. Consider installing it")
 
@@ -231,7 +230,7 @@ def _run_from_folder(cls, sorter_output_folder, params, verbose):
         n_peaks_per_channel = selection_params.get("n_peaks_per_channel", 5000)
         min_n_peaks = selection_params.get("min_n_peaks", 100000)
         skip_peaks = not params["multi_units_only"] and selection_method == "uniform"
-        skip_peaks = skip_peaks and not deterministic and not (matching_method is None)
+        skip_peaks = skip_peaks and not deterministic and matching_method is not None
         max_n_peaks = n_peaks_per_channel * num_channels
         n_peaks = max(min_n_peaks, max_n_peaks)
         selection_params["n_peaks"] = n_peaks
diff --git a/src/spikeinterface/sorters/internal/tests/test_lupin.py b/src/spikeinterface/sorters/internal/tests/test_lupin.py
index f838f9f4eb..fca6208bc7 100644
--- a/src/spikeinterface/sorters/internal/tests/test_lupin.py
+++ b/src/spikeinterface/sorters/internal/tests/test_lupin.py
@@ -1,10 +1,9 @@
 import unittest
 
-import pytest
 
 from spikeinterface.sorters.tests.common_tests import SorterCommonTestSuite
 
-from spikeinterface.sorters import LupinSorter, run_sorter
+from spikeinterface.sorters import LupinSorter
 
 from pathlib import Path
 
diff --git a/src/spikeinterface/sorters/internal/tests/test_tridesclous2.py b/src/spikeinterface/sorters/internal/tests/test_tridesclous2.py
index 6431532b87..18d58e55ab 100644
--- a/src/spikeinterface/sorters/internal/tests/test_tridesclous2.py
+++ b/src/spikeinterface/sorters/internal/tests/test_tridesclous2.py
@@ -1,6 +1,5 @@
 import unittest
 
-import pytest
 
 from spikeinterface.sorters.tests.common_tests import SorterCommonTestSuite
 
diff --git a/src/spikeinterface/sorters/internal/tridesclous2.py b/src/spikeinterface/sorters/internal/tridesclous2.py
index 56a506b293..20d6c4e6e3 100644
--- a/src/spikeinterface/sorters/internal/tridesclous2.py
+++ b/src/spikeinterface/sorters/internal/tridesclous2.py
@@ -1,6 +1,3 @@
-import shutil
-import importlib
-
 from .si_based import ComponentsBasedSorter
 
 from copy import deepcopy
@@ -10,13 +7,12 @@
     NumpySorting,
     estimate_templates_with_accumulator,
     Templates,
-    compute_sparsity,
     ms_to_samples,
 )
 
 from spikeinterface.core.job_tools import fix_job_kwargs
 
-from spikeinterface.preprocessing import bandpass_filter, common_reference, zscore, whiten
+from spikeinterface.preprocessing import bandpass_filter, common_reference, whiten
 from spikeinterface.core.base import minimum_spike_dtype
 
 from spikeinterface.sortingcomponents.tools import cache_preprocessing, clean_cache_preprocessing
@@ -142,7 +138,6 @@ def _run_from_folder(cls, sorter_output_folder, params, verbose):
         # preprocessing
         if params["apply_preprocessing"]:
             if params["apply_motion_correction"]:
-
                 rec_for_motion = recording_raw
                 if params["preprocessing_dict"] is None:
                     rec_for_motion = bandpass_filter(
diff --git a/src/spikeinterface/sorters/runsorter.py b/src/spikeinterface/sorters/runsorter.py
index 9b0e6855f5..c0923f0342 100644
--- a/src/spikeinterface/sorters/runsorter.py
+++ b/src/spikeinterface/sorters/runsorter.py
@@ -144,7 +144,6 @@ def run_sorter(
     )
 
     if isinstance(recording, dict):
-
         all_kwargs = common_kwargs
         all_kwargs.update(
             dict(
@@ -186,8 +185,7 @@ def run_sorter(
 
             if not has_singularity():
                 raise RuntimeError(
-                    "Singularity is not installed. Install singularity "
-                    "on this machine to run sorting with singularity."
+                    "Singularity is not installed. Install singularity on this machine to run sorting with singularity."
                 )
 
             if not has_spython():
@@ -482,9 +480,9 @@ def run_sorter_container(
             print(f"installation_mode='auto' switching to installation_mode: '{installation_mode}'")
 
     if installation_mode == "folder":
-        assert (
-            spikeinterface_folder_source is not None
-        ), "for installation_mode='folder', spikeinterface_folder_source must be provided"
+        assert spikeinterface_folder_source is not None, (
+            "for installation_mode='folder', spikeinterface_folder_source must be provided"
+        )
         host_folder_source = Path(spikeinterface_folder_source)
 
     if installation_mode == "dev":
@@ -552,7 +550,7 @@ def run_sorter_container(
 
     if need_si_install or installation_mode == "dev":
         # update pip in container
-        cmd = f"pip install --user --upgrade pip"
+        cmd = "pip install --user --upgrade pip"
         res_output = container_client.run_command(cmd)
 
         if installation_mode == "pypi":
@@ -678,7 +676,7 @@ def run_sorter_container(
         if with_output:
             try:
                 sorting = SorterClass.get_result_from_folder(folder)
-            except Exception as e:
+            except Exception:
                 try:
                     sorting = load(in_container_sorting_folder)
                 except FileNotFoundError:
diff --git a/src/spikeinterface/sorters/sorterlist.py b/src/spikeinterface/sorters/sorterlist.py
index f536967b3b..71f16f1d6c 100644
--- a/src/spikeinterface/sorters/sorterlist.py
+++ b/src/spikeinterface/sorters/sorterlist.py
@@ -7,7 +7,7 @@
 from .external.kilosort2 import Kilosort2Sorter
 from .external.kilosort2_5 import Kilosort2_5Sorter
 from .external.kilosort3 import Kilosort3Sorter
-from .external.kilosort4 import Kilosort4Sorter, read_kilosort4_motion
+from .external.kilosort4 import Kilosort4Sorter
 from .external.pykilosort import PyKilosortSorter
 from .external.klusta import KlustaSorter
 from .external.mountainsort4 import Mountainsort4Sorter
diff --git a/src/spikeinterface/sorters/tests/test_runsorter_dependency_checks.py b/src/spikeinterface/sorters/tests/test_runsorter_dependency_checks.py
index 12ef8caafd..cae63fbe50 100644
--- a/src/spikeinterface/sorters/tests/test_runsorter_dependency_checks.py
+++ b/src/spikeinterface/sorters/tests/test_runsorter_dependency_checks.py
@@ -1,7 +1,7 @@
 import pytest
 import platform
 from spikeinterface import generate_ground_truth_recording
-from spikeinterface.sorters.utils import has_spython, has_docker_python, has_docker, has_singularity
+from spikeinterface.sorters.utils import has_spython, has_docker_python
 from spikeinterface.sorters import run_sorter
 import sys
 
@@ -71,11 +71,11 @@ def uninstall_python_dependency(self, request):
 
         try:
             if dep_name == "spython":
-                import spython
+                pass
             else:
-                import docker
+                pass
             dependency_installed = True
-        except:
+        except Exception:
             dependency_installed = False
 
         if dependency_installed:
@@ -120,7 +120,7 @@ def test_no_singularity_error_raised(self, recording, monkeypatch):
         return False. Then, test the expected error is raised when the dependency
         is not found.
         """
-        monkeypatch.setattr(f"spikeinterface.sorters.runsorter.has_singularity", _monkeypatch_return_false)
+        monkeypatch.setattr("spikeinterface.sorters.runsorter.has_singularity", _monkeypatch_return_false)
 
         with pytest.raises(RuntimeError) as e:
             run_sorter("kilosort2_5", recording, singularity_image=True)
@@ -132,8 +132,8 @@ def test_no_spython_error_raised(self, recording, monkeypatch):
         See `test_no_singularity_error_raised()`.
         """
         # make sure singularity test returns true as that comes first
-        monkeypatch.setattr(f"spikeinterface.sorters.runsorter.has_singularity", _monkeypatch_return_true)
-        monkeypatch.setattr(f"spikeinterface.sorters.runsorter.has_spython", _monkeypatch_return_false)
+        monkeypatch.setattr("spikeinterface.sorters.runsorter.has_singularity", _monkeypatch_return_true)
+        monkeypatch.setattr("spikeinterface.sorters.runsorter.has_spython", _monkeypatch_return_false)
 
         with pytest.raises(RuntimeError) as e:
             run_sorter("kilosort2_5", recording, singularity_image=True)
@@ -144,7 +144,7 @@ def test_no_docker_error_raised(self, recording, monkeypatch):
         """
         See `test_no_singularity_error_raised()`.
         """
-        monkeypatch.setattr(f"spikeinterface.sorters.runsorter.has_docker", _monkeypatch_return_false)
+        monkeypatch.setattr("spikeinterface.sorters.runsorter.has_docker", _monkeypatch_return_false)
 
         with pytest.raises(RuntimeError) as e:
             run_sorter("kilosort2_5", recording, docker_image=True)
@@ -156,8 +156,8 @@ def test_as_no_docker_python_error_raised(self, recording, monkeypatch):
         See `test_no_singularity_error_raised()`.
         """
         # make sure docker test returns true as that comes first
-        monkeypatch.setattr(f"spikeinterface.sorters.runsorter.has_docker", _monkeypatch_return_true)
-        monkeypatch.setattr(f"spikeinterface.sorters.runsorter.has_docker_python", _monkeypatch_return_false)
+        monkeypatch.setattr("spikeinterface.sorters.runsorter.has_docker", _monkeypatch_return_true)
+        monkeypatch.setattr("spikeinterface.sorters.runsorter.has_docker_python", _monkeypatch_return_false)
 
         with pytest.raises(RuntimeError) as e:
             run_sorter("kilosort2_5", recording, docker_image=True)
diff --git a/src/spikeinterface/sorters/utils/misc.py b/src/spikeinterface/sorters/utils/misc.py
index 162c8f07c2..66e6710260 100644
--- a/src/spikeinterface/sorters/utils/misc.py
+++ b/src/spikeinterface/sorters/utils/misc.py
@@ -52,7 +52,7 @@ def get_git_commit(git_folder, shorten=True):
         commit = check_output(["git", "rev-parse", "HEAD"], cwd=git_folder).decode("utf8").strip()
         if shorten:
             commit = commit[:12]
-    except:
+    except Exception:
         commit = None
     return commit
 
diff --git a/src/spikeinterface/sorters/utils/shellscript.py b/src/spikeinterface/sorters/utils/shellscript.py
index abd2eaf0b1..5659466b78 100644
--- a/src/spikeinterface/sorters/utils/shellscript.py
+++ b/src/spikeinterface/sorters/utils/shellscript.py
@@ -106,7 +106,7 @@ def wait(self, timeout=None) -> int | None:
         try:
             retcode = self._process.wait(timeout=timeout)
             return retcode
-        except:
+        except Exception:
             return None
 
     def cleanup(self) -> None:
@@ -133,7 +133,7 @@ def stop(self) -> None:
             try:
                 self._process.wait(timeout=0.02)
                 return
-            except:
+            except Exception:
                 pass
 
     def kill(self) -> None:
@@ -144,7 +144,7 @@ def kill(self) -> None:
         self._process.send_signal(signal.SIGKILL)
         try:
             self._process.wait(timeout=1)
-        except:
+        except Exception:
             print("WARNING: unable to kill shell script.")
             pass
 
@@ -157,7 +157,7 @@ def stopWithSignal(self, sig, timeout) -> bool:
         try:
             self._process.wait(timeout=timeout)
             return True
-        except:
+        except Exception:
             return False
 
     def elapsedTimeSinceStart(self) -> float | None:
@@ -208,7 +208,7 @@ def _rmdir_with_retries(dirname, num_retries, delay_between_tries=1):
         try:
             shutil.rmtree(dirname)
             break
-        except:
+        except Exception:
             if retry_num < num_retries:
                 print(f"Retrying to remove directory: {dirname}")
                 time.sleep(delay_between_tries)
diff --git a/src/spikeinterface/sortingcomponents/clustering/cleaning_tools.py b/src/spikeinterface/sortingcomponents/clustering/cleaning_tools.py
index 4f10f51b73..589cc936e6 100644
--- a/src/spikeinterface/sortingcomponents/clustering/cleaning_tools.py
+++ b/src/spikeinterface/sortingcomponents/clustering/cleaning_tools.py
@@ -5,7 +5,6 @@
 import numpy as np
 from spikeinterface.core.job_tools import fix_job_kwargs
 from spikeinterface.postprocessing import check_equal_template_with_distribution_overlap
-from spikeinterface.core import NumpySorting
 
 
 def _split_waveforms(
@@ -50,7 +49,6 @@ def _split_waveforms(
 
     if debug:
         import matplotlib.pyplot as plt
-        import umap
 
         fig, ax = plt.subplots()
 
@@ -229,9 +227,6 @@ def auto_split_clustering(
     Internally used by PositionAndPCAClustering for the second step.
     """
 
-    import sklearn.decomposition
-    import hdbscan
-
     split_peak_labels = -1 * np.ones(peak_labels.size, dtype=np.int64)
     nb_clusters = 0
     main_channels = {}
@@ -589,11 +584,9 @@ def detect_mixtures(templates, method_kwargs={}, job_kwargs={}, tmp_folder=None,
     DEBUG = False
     sub_recording = None  # we only do a sub recording if we have data to iterate through
     while keep_searching:
-
         keep_searching = False
 
         for i in list(set(range(nb_templates)).difference(ignore_inds)):
-
             ## Could be speed up by only computing the values for templates that are
             ## nearby
 
@@ -642,7 +635,6 @@ def detect_mixtures(templates, method_kwargs={}, job_kwargs={}, tmp_folder=None,
                         import matplotlib.pyplot as plt
 
                         fig, axes = plt.subplots(1, 2)
-                        from spikeinterface.widgets import plot_traces
 
                         # plot_traces(sub_recording, ax=axes[0])
                         axes[1].plot(templates_array[i].flatten(), label=f"{ref_norm}")
diff --git a/src/spikeinterface/sortingcomponents/clustering/graph_clustering.py b/src/spikeinterface/sortingcomponents/clustering/graph_clustering.py
index bea9cda7a2..92472b03d7 100644
--- a/src/spikeinterface/sortingcomponents/clustering/graph_clustering.py
+++ b/src/spikeinterface/sortingcomponents/clustering/graph_clustering.py
@@ -1,5 +1,3 @@
-from pathlib import Path
-
 import numpy as np
 
 
diff --git a/src/spikeinterface/sortingcomponents/clustering/itersplit_tools.py b/src/spikeinterface/sortingcomponents/clustering/itersplit_tools.py
index d34ca8bb4e..a4d2a77a3b 100644
--- a/src/spikeinterface/sortingcomponents/clustering/itersplit_tools.py
+++ b/src/spikeinterface/sortingcomponents/clustering/itersplit_tools.py
@@ -11,7 +11,7 @@
 from .tools import aggregate_sparse_features, FeaturesLoader
 
 if importlib.util.find_spec("numba") is not None:
-    import numba
+    pass
 else:
     pass
 # isocut requires numba
@@ -364,7 +364,7 @@ def split(
                 ax.plot(flatten_wfs[mask].T, color=colors[k], alpha=0.1)
                 if k > -1:
                     ax.plot(np.median(flatten_wfs[mask].T, axis=1), color=colors[k], lw=2)
-                ax.set_xlabel(f"PCA features")
+                ax.set_xlabel("PCA features")
 
                 ax = axs[3]
                 if n_pca_features == 1:
diff --git a/src/spikeinterface/sortingcomponents/clustering/main.py b/src/spikeinterface/sortingcomponents/clustering/main.py
index 46052fa5ae..c8b8a60a27 100644
--- a/src/spikeinterface/sortingcomponents/clustering/main.py
+++ b/src/spikeinterface/sortingcomponents/clustering/main.py
@@ -1,4 +1,4 @@
-from spikeinterface.core.job_tools import fix_job_kwargs, _shared_job_kwargs_doc
+from spikeinterface.core.job_tools import fix_job_kwargs
 
 import copy
 from ..tools import make_multi_method_doc
@@ -39,9 +39,9 @@ def find_clusters_from_peaks(
     """
     job_kwargs = fix_job_kwargs(job_kwargs)
 
-    assert (
-        method in clustering_methods
-    ), f"Method for clustering do not exists, should be in {list(clustering_methods.keys())}"
+    assert method in clustering_methods, (
+        f"Method for clustering do not exists, should be in {list(clustering_methods.keys())}"
+    )
 
     method_class = clustering_methods[method]
     params = copy.deepcopy(method_class._default_params.copy())
diff --git a/src/spikeinterface/sortingcomponents/clustering/positions.py b/src/spikeinterface/sortingcomponents/clustering/positions.py
index b94f6607cb..93e57c27d1 100644
--- a/src/spikeinterface/sortingcomponents/clustering/positions.py
+++ b/src/spikeinterface/sortingcomponents/clustering/positions.py
@@ -1,5 +1,4 @@
 # """Sorting components: clustering"""
-from pathlib import Path
 import importlib.util
 
 import numpy as np
diff --git a/src/spikeinterface/sortingcomponents/clustering/tests/test_itersplit_tool.py b/src/spikeinterface/sortingcomponents/clustering/tests/test_itersplit_tool.py
index 35e2678d13..1476606ec5 100644
--- a/src/spikeinterface/sortingcomponents/clustering/tests/test_itersplit_tool.py
+++ b/src/spikeinterface/sortingcomponents/clustering/tests/test_itersplit_tool.py
@@ -1,8 +1,3 @@
-import pytest
-
-from spikeinterface.sortingcomponents.clustering.itersplit_tools import split_clusters
-
-
 # TODO
 def test_split():
     pass
diff --git a/src/spikeinterface/sortingcomponents/clustering/tests/test_merging_tools.py b/src/spikeinterface/sortingcomponents/clustering/tests/test_merging_tools.py
index e462985450..77b1049b7b 100644
--- a/src/spikeinterface/sortingcomponents/clustering/tests/test_merging_tools.py
+++ b/src/spikeinterface/sortingcomponents/clustering/tests/test_merging_tools.py
@@ -1,11 +1,3 @@
-import pytest
-
-from spikeinterface.sortingcomponents.clustering.merging_tools import (
-    merge_peak_labels_from_features,
-    merge_peak_labels_from_templates,
-)
-
-
 # TODO
 def test_merge():
     pass
diff --git a/src/spikeinterface/sortingcomponents/clustering/tools.py b/src/spikeinterface/sortingcomponents/clustering/tools.py
index 2fb05bbc6b..1df339400f 100644
--- a/src/spikeinterface/sortingcomponents/clustering/tools.py
+++ b/src/spikeinterface/sortingcomponents/clustering/tools.py
@@ -1,5 +1,4 @@
 from pathlib import Path
-from typing import Any
 import numpy as np
 
 from spikeinterface.core import Templates, estimate_templates, fix_job_kwargs
diff --git a/src/spikeinterface/sortingcomponents/matching/circus.py b/src/spikeinterface/sortingcomponents/matching/circus.py
index cb133e435f..28bf9fc840 100644
--- a/src/spikeinterface/sortingcomponents/matching/circus.py
+++ b/src/spikeinterface/sortingcomponents/matching/circus.py
@@ -406,7 +406,6 @@ def compute_matching(self, traces, start_frame, end_frame, segment_index):
         do_loop = True
 
         while do_loop:
-
             best_cluster_inds = np.argmax(scalar_products, axis=0, keepdims=True)
             products = np.take_along_axis(scalar_products, best_cluster_inds, axis=0)
 
@@ -419,7 +418,6 @@ def compute_matching(self, traces, start_frame, end_frame, segment_index):
                 break
 
             for peak_index in peak_indices:
-
                 best_cluster_ind = best_cluster_inds[0, peak_index]
 
                 if num_selection > 0:
@@ -640,9 +638,9 @@ def __init__(
 
         assert HAVE_SKLEARN, "CircusPeeler needs sklearn to work"
 
-        assert (use_sparse_matrix_threshold >= 0) and (
-            use_sparse_matrix_threshold <= 1
-        ), f"use_sparse_matrix_threshold should be in [0, 1]"
+        assert (use_sparse_matrix_threshold >= 0) and (use_sparse_matrix_threshold <= 1), (
+            "use_sparse_matrix_threshold should be in [0, 1]"
+        )
 
         self.num_channels = recording.get_num_channels()
         self.num_samples = templates.num_samples
@@ -770,7 +768,7 @@ def compute_matching(self, traces, start_frame, end_frame, segment_index):
             is_valid_nn = np.searchsorted(peak_data, [-neighbor_window, neighbor_window + 1])
             idx_neighbor = peak_data[is_valid_nn[0] : is_valid_nn[1]] + neighbor_window
 
-            if not best_cluster_ind in cached_overlaps.keys():
+            if best_cluster_ind not in cached_overlaps.keys():
                 cached_overlaps[best_cluster_ind] = self.overlaps[best_cluster_ind].toarray()
 
             to_add = -best_amplitude * cached_overlaps[best_cluster_ind][:, idx_neighbor]
diff --git a/src/spikeinterface/sortingcomponents/matching/main.py b/src/spikeinterface/sortingcomponents/matching/main.py
index 0b054c0638..babe76de73 100644
--- a/src/spikeinterface/sortingcomponents/matching/main.py
+++ b/src/spikeinterface/sortingcomponents/matching/main.py
@@ -1,5 +1,4 @@
 import numpy as np
-import warnings
 
 from .method_list import *
 
diff --git a/src/spikeinterface/sortingcomponents/matching/nearest.py b/src/spikeinterface/sortingcomponents/matching/nearest.py
index 7ca2c3ece4..e67eefe916 100644
--- a/src/spikeinterface/sortingcomponents/matching/nearest.py
+++ b/src/spikeinterface/sortingcomponents/matching/nearest.py
@@ -1,16 +1,13 @@
 """Sorting components: template matching."""
 
 import numpy as np
-from spikeinterface.core.template_tools import get_template_extremum_channel
-from spikeinterface.core import get_noise_levels, get_channel_distances
-from spikeinterface.core.sparsity import compute_sparsity
+from spikeinterface.core import get_channel_distances
 
 
 from .base import BaseTemplateMatching, _base_matching_dtype
 
 
 class NearestTemplatesPeeler(BaseTemplateMatching):
-
     name = "nearest"
     need_noise_levels = True
     # this is because numba
@@ -153,16 +150,18 @@ def compute_matching(self, traces, start_frame, end_frame, segment_index):
 
 
 class NearestTemplatesSVDPeeler(NearestTemplatesPeeler):
-
     name = "nearest-svd"
     need_noise_levels = True
-    params_doc = NearestTemplatesPeeler.params_doc + """
+    params_doc = (
+        NearestTemplatesPeeler.params_doc
+        + """
     svd_model : The svd model used to project the waveforms
         The radius to use to select neighbour channels for locally exclusive detection.
     svd_radius_um : float
         The radius in um of the local neighboorhood used, centered on every detected peaks, to compute
         the distances with all the templates in the SVD space
     """
+    )
 
     def __init__(
         self,
diff --git a/src/spikeinterface/sortingcomponents/matching/tests/test_template_matching.py b/src/spikeinterface/sortingcomponents/matching/tests/test_template_matching.py
index 0fb3e6bc61..90767007d7 100644
--- a/src/spikeinterface/sortingcomponents/matching/tests/test_template_matching.py
+++ b/src/spikeinterface/sortingcomponents/matching/tests/test_template_matching.py
@@ -1,6 +1,5 @@
 import pytest
 import numpy as np
-from pathlib import Path
 
 from spikeinterface import NumpySorting, create_sorting_analyzer, compute_sparsity, get_noise_levels
 
@@ -93,9 +92,6 @@ def test_find_spikes_from_templates(method, sorting_analyzer):
     DEBUG = False
 
     if DEBUG:
-        import matplotlib.pyplot as plt
-        import spikeinterface.full as si
-
         sorting_analyzer.compute("waveforms")
         sorting_analyzer.compute("templates")
 
diff --git a/src/spikeinterface/sortingcomponents/matching/tests/test_wobble.py b/src/spikeinterface/sortingcomponents/matching/tests/test_wobble.py
index 36d5452933..f3a7a2e4f9 100644
--- a/src/spikeinterface/sortingcomponents/matching/tests/test_wobble.py
+++ b/src/spikeinterface/sortingcomponents/matching/tests/test_wobble.py
@@ -1,6 +1,5 @@
 from types import SimpleNamespace
 
-import pytest
 import numpy as np
 
 from spikeinterface.sortingcomponents.matching import wobble
@@ -326,7 +325,6 @@ def test_compute_scale_amplitudes():
     rng = np.random.default_rng(seed)
     num_spikes = rng.integers(0, 100)
     norm_peaks = rng.random(num_spikes)
-    num_jittered = rng.integers(1, 100)
     peak_window_size = rng.integers(1, 100)
     high_resolution_conv = rng.random((peak_window_size, num_spikes))
     scale_min = rng.random() * 10
diff --git a/src/spikeinterface/sortingcomponents/motion/decentralized.py b/src/spikeinterface/sortingcomponents/motion/decentralized.py
index 076d3658de..509841e6f6 100644
--- a/src/spikeinterface/sortingcomponents/motion/decentralized.py
+++ b/src/spikeinterface/sortingcomponents/motion/decentralized.py
@@ -3,7 +3,7 @@
 from tqdm.auto import tqdm, trange
 
 from spikeinterface.core.motion import Motion
-from .motion_utils import get_spatial_windows, get_spatial_bin_edges, make_2d_motion_histogram, scipy_conv1d
+from .motion_utils import get_spatial_windows, get_spatial_bin_edges, make_2d_motion_histogram
 
 from .dredge import normxcorr1d
 
@@ -328,7 +328,7 @@ def compute_pairwise_displacement(
     if conv_engine == "torch":
         import torch
 
-    assert conv_engine in ("torch", "numpy"), f"'conv_engine' must be 'torch' or 'numpy'"
+    assert conv_engine in ("torch", "numpy"), "'conv_engine' must be 'torch' or 'numpy'"
     size = motion_hist.shape[0]
     pairwise_displacement = np.zeros((size, size), dtype="float32")
 
@@ -509,7 +509,6 @@ def jac(p):
         displacement = res.x
 
     elif convergence_method == "lsqr_robust":
-
         if sparse_mask is not None:
             I, J = np.nonzero(sparse_mask > 0)
         elif pairwise_displacement_weight is not None:
diff --git a/src/spikeinterface/sortingcomponents/motion/medicine.py b/src/spikeinterface/sortingcomponents/motion/medicine.py
index 8be18f7502..0cfc44f5a1 100644
--- a/src/spikeinterface/sortingcomponents/motion/medicine.py
+++ b/src/spikeinterface/sortingcomponents/motion/medicine.py
@@ -1,11 +1,7 @@
 import numpy as np
 
-import tempfile
-import shutil
-from pathlib import Path
 
 from spikeinterface.core.motion import Motion
-from spikeinterface.sortingcomponents.motion.motion_utils import get_spatial_windows
 
 
 class MedicineRegistration:
diff --git a/src/spikeinterface/sortingcomponents/motion/motion_estimation.py b/src/spikeinterface/sortingcomponents/motion/motion_estimation.py
index 7e48ef146e..6f309281d7 100644
--- a/src/spikeinterface/sortingcomponents/motion/motion_estimation.py
+++ b/src/spikeinterface/sortingcomponents/motion/motion_estimation.py
@@ -1,5 +1,4 @@
 import warnings
-import numpy as np
 
 
 from spikeinterface.sortingcomponents.tools import make_multi_method_doc
diff --git a/src/spikeinterface/sortingcomponents/motion/motion_utils.py b/src/spikeinterface/sortingcomponents/motion/motion_utils.py
index c58322d2c6..ab08326c56 100644
--- a/src/spikeinterface/sortingcomponents/motion/motion_utils.py
+++ b/src/spikeinterface/sortingcomponents/motion/motion_utils.py
@@ -1,7 +1,6 @@
 import warnings
 
 import numpy as np
-from spikeinterface.core.core_tools import check_json
 
 
 def get_spatial_windows(
@@ -58,8 +57,6 @@ def get_spatial_windows(
     Here by default we use gaussian window.
 
     """
-    n = spatial_bin_centers.size
-
     if rigid:
         # win_shape = 'rect' is forced
         windows, window_centers = get_rigid_windows(spatial_bin_centers)
diff --git a/src/spikeinterface/sortingcomponents/motion/tests/test_drege.py b/src/spikeinterface/sortingcomponents/motion/tests/test_drege.py
index 8133c1fa6b..202ae63a64 100644
--- a/src/spikeinterface/sortingcomponents/motion/tests/test_drege.py
+++ b/src/spikeinterface/sortingcomponents/motion/tests/test_drege.py
@@ -1,6 +1,3 @@
-import pytest
-
-
 def test_dredge_online_lfp():
     pass
 
diff --git a/src/spikeinterface/sortingcomponents/motion/tests/test_motion_estimation.py b/src/spikeinterface/sortingcomponents/motion/tests/test_motion_estimation.py
index 1ba43e6a13..adff080792 100644
--- a/src/spikeinterface/sortingcomponents/motion/tests/test_motion_estimation.py
+++ b/src/spikeinterface/sortingcomponents/motion/tests/test_motion_estimation.py
@@ -6,7 +6,7 @@
 from spikeinterface import get_noise_levels
 from spikeinterface.core.node_pipeline import ExtractDenseWaveforms, run_node_pipeline
 from spikeinterface.sortingcomponents.motion import estimate_motion
-from spikeinterface.sortingcomponents.peak_detection import detect_peaks, detect_peak_methods
+from spikeinterface.sortingcomponents.peak_detection import detect_peak_methods
 from spikeinterface.sortingcomponents.peak_localization.method_list import LocalizeCenterOfMass
 from spikeinterface.sortingcomponents.tests.common import make_dataset
 
diff --git a/src/spikeinterface/sortingcomponents/peak_detection/main.py b/src/spikeinterface/sortingcomponents/peak_detection/main.py
index 4332acac0f..0fc554efea 100644
--- a/src/spikeinterface/sortingcomponents/peak_detection/main.py
+++ b/src/spikeinterface/sortingcomponents/peak_detection/main.py
@@ -2,7 +2,7 @@
 
 from .method_list import detect_peak_methods
 
-from spikeinterface.core.job_tools import split_job_kwargs, fix_job_kwargs
+from spikeinterface.core.job_tools import fix_job_kwargs
 
 from ..tools import make_multi_method_doc
 
diff --git a/src/spikeinterface/sortingcomponents/peak_detection/tests/test_peak_detection.py b/src/spikeinterface/sortingcomponents/peak_detection/tests/test_peak_detection.py
index 25b9d9515a..7f25299476 100644
--- a/src/spikeinterface/sortingcomponents/peak_detection/tests/test_peak_detection.py
+++ b/src/spikeinterface/sortingcomponents/peak_detection/tests/test_peak_detection.py
@@ -327,7 +327,7 @@ def test_detect_peaks_locally_exclusive(recording, job_kwargs, torch_job_kwargs)
         assert np.isclose(np.array(len(peaks_local_numba)), np.array(len(peaks_local_torch)), rtol=0.1)
 
     if HAVE_PYOPENCL:
-        peaks_local_cl = detect_peaks(
+        _ = detect_peaks(
             recording,
             method="locally_exclusive_cl",
             method_kwargs=dict(
diff --git a/src/spikeinterface/sortingcomponents/peak_localization/grid.py b/src/spikeinterface/sortingcomponents/peak_localization/grid.py
index c55b6b712e..94bcd38af2 100644
--- a/src/spikeinterface/sortingcomponents/peak_localization/grid.py
+++ b/src/spikeinterface/sortingcomponents/peak_localization/grid.py
@@ -4,7 +4,6 @@
 
 from spikeinterface.core.node_pipeline import (
     find_parent_of_type,
-    PipelineNode,
     WaveformsNode,
 )
 
diff --git a/src/spikeinterface/sortingcomponents/peak_localization/main.py b/src/spikeinterface/sortingcomponents/peak_localization/main.py
index d75f4a8a55..1cb8d8629d 100644
--- a/src/spikeinterface/sortingcomponents/peak_localization/main.py
+++ b/src/spikeinterface/sortingcomponents/peak_localization/main.py
@@ -4,7 +4,7 @@
 from .method_list import peak_localization_methods
 from ..tools import make_multi_method_doc
 
-from spikeinterface.core.job_tools import split_job_kwargs, fix_job_kwargs
+from spikeinterface.core.job_tools import fix_job_kwargs
 
 
 from spikeinterface.core.node_pipeline import (
@@ -30,9 +30,9 @@ def get_localization_pipeline_nodes(
     seed=None,
 ):
 
-    assert (
-        method in peak_localization_methods
-    ), f"Method {method} is not supported. Choose from {peak_localization_methods.keys()}"
+    assert method in peak_localization_methods, (
+        f"Method {method} is not supported. Choose from {peak_localization_methods.keys()}"
+    )
 
     assert method_kwargs is not None
 
@@ -152,9 +152,9 @@ def localize_peaks(
 
     job_kwargs = fix_job_kwargs(job_kwargs)
 
-    assert (
-        method in peak_localization_methods
-    ), f"Method {method} is not supported. Choose from {peak_localization_methods.keys()}"
+    assert method in peak_localization_methods, (
+        f"Method {method} is not supported. Choose from {peak_localization_methods.keys()}"
+    )
 
     peak_source = PeakRetriever(recording, peaks)
 
diff --git a/src/spikeinterface/sortingcomponents/peak_localization/tests/test_peak_localization.py b/src/spikeinterface/sortingcomponents/peak_localization/tests/test_peak_localization.py
index 9db0588f6d..15d0476e65 100644
--- a/src/spikeinterface/sortingcomponents/peak_localization/tests/test_peak_localization.py
+++ b/src/spikeinterface/sortingcomponents/peak_localization/tests/test_peak_localization.py
@@ -1,6 +1,3 @@
-import pytest
-import numpy as np
-
 from spikeinterface.sortingcomponents.peak_detection import detect_peaks
 from spikeinterface.sortingcomponents.peak_localization import localize_peaks
 
diff --git a/src/spikeinterface/sortingcomponents/tests/test_peak_selection.py b/src/spikeinterface/sortingcomponents/tests/test_peak_selection.py
index e9d8f1987b..94db8bc510 100644
--- a/src/spikeinterface/sortingcomponents/tests/test_peak_selection.py
+++ b/src/spikeinterface/sortingcomponents/tests/test_peak_selection.py
@@ -1,4 +1,3 @@
-import pytest
 import numpy as np
 
 
@@ -52,37 +51,37 @@ def test_select_peaks():
     ]
     for method in select_methods:
         selected_peaks = select_peaks(peaks, method=method, **select_kwargs)
-        assert (
-            selected_peaks.size <= n_peaks
-        ), "selected_peaks is not the right size when return_indices=False, select_per_channel=False"
+        assert selected_peaks.size <= n_peaks, (
+            "selected_peaks is not the right size when return_indices=False, select_per_channel=False"
+        )
 
         selected_peaks = select_peaks(peaks, recording=recording, method=method, margin=(10, 10), **select_kwargs)
-        assert (
-            selected_peaks.size <= n_peaks
-        ), "selected_peaks is not the right size when return_indices=False, select_per_channel=False"
+        assert selected_peaks.size <= n_peaks, (
+            "selected_peaks is not the right size when return_indices=False, select_per_channel=False"
+        )
 
         selected_peaks = select_peaks(peaks, method=method, select_per_channel=True, **select_kwargs)
-        assert selected_peaks.size <= (
-            n_peaks * recording.get_num_channels()
-        ), "selected_peaks is not the right size when return_indices=False, select_per_channel=True"
+        assert selected_peaks.size <= (n_peaks * recording.get_num_channels()), (
+            "selected_peaks is not the right size when return_indices=False, select_per_channel=True"
+        )
 
         selected_peaks, selected_indices = select_peaks(peaks, method=method, return_indices=True, **select_kwargs)
-        assert (
-            selected_peaks.size <= n_peaks
-        ), "selected_peaks is not the right size when return_indices=True, select_per_channel=False"
-        assert np.all(
-            selected_peaks == peaks[selected_indices]
-        ), "selection_indices differ from selected_peaks when select_per_channel=False"
+        assert selected_peaks.size <= n_peaks, (
+            "selected_peaks is not the right size when return_indices=True, select_per_channel=False"
+        )
+        assert np.all(selected_peaks == peaks[selected_indices]), (
+            "selection_indices differ from selected_peaks when select_per_channel=False"
+        )
 
         selected_peaks, selected_indices = select_peaks(
             peaks, method=method, return_indices=True, select_per_channel=True, **select_kwargs
         )
-        assert selected_peaks.size <= (
-            n_peaks * recording.get_num_channels()
-        ), "selected_peaks is not the right size when return_indices=True, select_per_channel=True"
-        assert np.all(
-            selected_peaks == peaks[selected_indices]
-        ), "selection_indices differ from selected_peaks when select_per_channel=True"
+        assert selected_peaks.size <= (n_peaks * recording.get_num_channels()), (
+            "selected_peaks is not the right size when return_indices=True, select_per_channel=True"
+        )
+        assert np.all(selected_peaks == peaks[selected_indices]), (
+            "selection_indices differ from selected_peaks when select_per_channel=True"
+        )
 
 
 if __name__ == "__main__":
diff --git a/src/spikeinterface/sortingcomponents/waveforms/features_from_peaks.py b/src/spikeinterface/sortingcomponents/waveforms/features_from_peaks.py
index 0c7ffe7447..ec750d8c95 100644
--- a/src/spikeinterface/sortingcomponents/waveforms/features_from_peaks.py
+++ b/src/spikeinterface/sortingcomponents/waveforms/features_from_peaks.py
@@ -6,7 +6,6 @@
 from spikeinterface.core import get_channel_distances
 from spikeinterface.sortingcomponents.peak_localization.method_list import (
     LocalizeCenterOfMass,
-    LocalizeMonopolarTriangulation,
 )
 from spikeinterface.core.node_pipeline import (
     run_node_pipeline,
@@ -70,9 +69,9 @@ def compute_features_from_peaks(
         extract_dense_waveforms,
     ]
     for feature_name in feature_list:
-        assert (
-            feature_name in _features_class.keys()
-        ), f"Feature {feature_name} in 'feature_list' is not possible. Possible features are {list(_features_class.keys())}"
+        assert feature_name in _features_class.keys(), (
+            f"Feature {feature_name} in 'feature_list' is not possible. Possible features are {list(_features_class.keys())}"
+        )
         Class = _features_class[feature_name]
         params = feature_params.get(feature_name, {}).copy()
         node = Class(recording, parents=[peak_retriever, extract_dense_waveforms], **params)
diff --git a/src/spikeinterface/sortingcomponents/waveforms/neural_network_denoiser.py b/src/spikeinterface/sortingcomponents/waveforms/neural_network_denoiser.py
index 7a889780b9..b5d6a45a03 100644
--- a/src/spikeinterface/sortingcomponents/waveforms/neural_network_denoiser.py
+++ b/src/spikeinterface/sortingcomponents/waveforms/neural_network_denoiser.py
@@ -82,9 +82,9 @@ def __init__(
                 self.denoiser, model_relative_path = self.load_model(
                     model_folder=model_folder, repo_id=repo_id, model_name=model_name, spike_size=spike_size
                 )
-            except RuntimeError as e:
+            except RuntimeError:
                 raise ValueError(
-                    f"Failed to load model. Check consistency between waveform node shapes and model output layer"
+                    "Failed to load model. Check consistency between waveform node shapes and model output layer"
                 )
 
             self.assert_model_and_waveform_temporal_match(
@@ -122,7 +122,7 @@ def assert_model_and_waveform_temporal_match(
             try:
                 filename = str(model_relative_path).replace(".pt", ".json")
                 json_file_path = hf_hub_download(repo_id=repo_id, filename=filename)
-            except Exception as e:
+            except Exception:
                 warnings.warn(f"Could not download json file from repo {repo_id}. Model might misbehave")
 
         if json_file_path is None or not Path(json_file_path).exists():
@@ -179,9 +179,9 @@ def load_model(
             else:
                 if model_name is not None:
                     raise ValueError(f"Multiple models found in {model_folder}. Please specify model_name")
-                assert (
-                    model_name is not None
-                ), "If there are multiple .pt files in the repo, you need to specify the model_name"
+                assert model_name is not None, (
+                    "If there are multiple .pt files in the repo, you need to specify the model_name"
+                )
                 filename = [f for f in pt_files if model_name in f]
                 if len(filename) == 0:
                     raise ValueError(f"Model {model_name} not found in repo {repo_id}")
@@ -199,9 +199,9 @@ def load_model(
             if len(pt_files) == 1:
                 filename = pt_files[0]
             else:
-                assert (
-                    model_name is not None
-                ), "If there are multiple .pt files in the repo, you need to specify the model_name"
+                assert model_name is not None, (
+                    "If there are multiple .pt files in the repo, you need to specify the model_name"
+                )
                 filename = [f for f in pt_files if model_name in f]
                 if len(filename) == 0:
                     raise ValueError(f"Model {model_name} not found in repo {repo_id}")
diff --git a/src/spikeinterface/sortingcomponents/waveforms/tests/test_features_from_peaks.py b/src/spikeinterface/sortingcomponents/waveforms/tests/test_features_from_peaks.py
index 736b040a26..79f48932c5 100644
--- a/src/spikeinterface/sortingcomponents/waveforms/tests/test_features_from_peaks.py
+++ b/src/spikeinterface/sortingcomponents/waveforms/tests/test_features_from_peaks.py
@@ -1,5 +1,3 @@
-import pytest
-
 from spikeinterface.sortingcomponents.waveforms.features_from_peaks import compute_features_from_peaks
 from spikeinterface.core import get_noise_levels
 from spikeinterface.sortingcomponents.peak_detection import detect_peaks
diff --git a/src/spikeinterface/sortingcomponents/waveforms/tests/test_hanning_filter.py b/src/spikeinterface/sortingcomponents/waveforms/tests/test_hanning_filter.py
index 1b006af429..83848881a1 100644
--- a/src/spikeinterface/sortingcomponents/waveforms/tests/test_hanning_filter.py
+++ b/src/spikeinterface/sortingcomponents/waveforms/tests/test_hanning_filter.py
@@ -1,6 +1,3 @@
-import pytest
-
-
 from spikeinterface.sortingcomponents.waveforms.hanning_filter import HanningFilter
 
 from spikeinterface.core.node_pipeline import (
diff --git a/src/spikeinterface/sortingcomponents/waveforms/tests/test_neural_network_denoiser.py b/src/spikeinterface/sortingcomponents/waveforms/tests/test_neural_network_denoiser.py
index b481a39ca6..d2cd517f86 100644
--- a/src/spikeinterface/sortingcomponents/waveforms/tests/test_neural_network_denoiser.py
+++ b/src/spikeinterface/sortingcomponents/waveforms/tests/test_neural_network_denoiser.py
@@ -83,7 +83,7 @@ def test_single_channel_yass_denoiser_wrong_shape(generated_recording_30khz, det
         recording, parents=[peak_retriever], nbefore=nbefore, nafter=nafter, return_output=True
     )
     with pytest.raises(ValueError):
-        yass_denoiser = SingleChannelDenoiser(
+        _ = SingleChannelDenoiser(
             recording,
             parents=[peak_retriever, waveform_extraction],
             repo_id="spikeinterface/waveform_denoiser",
@@ -96,4 +96,4 @@ def test_single_channel_yass_denoiser_wrong_shape(generated_recording_30khz, det
         model_name="yass_ibl",
     )
     with pytest.raises(ValueError):
-        yass_denoiser = SingleChannelDenoiser(recording, parents=[peak_retriever, waveform_extraction], model=model)
+        _ = SingleChannelDenoiser(recording, parents=[peak_retriever, waveform_extraction], model=model)
diff --git a/src/spikeinterface/sortingcomponents/waveforms/tests/test_savgol_denoiser.py b/src/spikeinterface/sortingcomponents/waveforms/tests/test_savgol_denoiser.py
index 651b681078..fc2787a3d6 100644
--- a/src/spikeinterface/sortingcomponents/waveforms/tests/test_savgol_denoiser.py
+++ b/src/spikeinterface/sortingcomponents/waveforms/tests/test_savgol_denoiser.py
@@ -1,6 +1,3 @@
-import pytest
-
-
 from spikeinterface.sortingcomponents.waveforms.savgol_denoiser import SavGolDenoiser
 
 from spikeinterface.core.node_pipeline import (
diff --git a/src/spikeinterface/sortingcomponents/waveforms/tests/test_temporal_pca.py b/src/spikeinterface/sortingcomponents/waveforms/tests/test_temporal_pca.py
index dc01ab3431..e3d99a5e1d 100644
--- a/src/spikeinterface/sortingcomponents/waveforms/tests/test_temporal_pca.py
+++ b/src/spikeinterface/sortingcomponents/waveforms/tests/test_temporal_pca.py
@@ -180,9 +180,6 @@ def test_initialization_with_wrong_parents_failure(generated_recording, model_pa
     recording = generated_recording
     model_folder_path = model_path_of_trained_pca
     dummy_parent = PipelineNode(recording)
-    extract_waveforms = ExtractSparseWaveforms(
-        recording=recording, ms_before=1, ms_after=1, radius_um=40, return_output=True
-    )
 
     match_error = f"TemporalPCA should have a single {WaveformsNode.__name__} in its parents"
 
diff --git a/src/spikeinterface/widgets/all_amplitudes_distributions.py b/src/spikeinterface/widgets/all_amplitudes_distributions.py
index b3cf2cfc02..c4d3eb4b69 100644
--- a/src/spikeinterface/widgets/all_amplitudes_distributions.py
+++ b/src/spikeinterface/widgets/all_amplitudes_distributions.py
@@ -55,7 +55,6 @@ def __init__(
         BaseWidget.__init__(self, plot_data, backend=backend, **backend_kwargs)
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
-        import matplotlib.pyplot as plt
         from .utils_matplotlib import make_mpl_figure
 
         dp = to_attr(data_plot)
diff --git a/src/spikeinterface/widgets/amplitudes.py b/src/spikeinterface/widgets/amplitudes.py
index 1983253299..6091214a66 100644
--- a/src/spikeinterface/widgets/amplitudes.py
+++ b/src/spikeinterface/widgets/amplitudes.py
@@ -159,7 +159,6 @@ def plot_figpack(self, data_plot, **backend_kwargs):
             make_serializable,
             handle_display_and_url,
             import_figpack_or_sortingview,
-            generate_unit_table_view,
         )
 
         use_sortingview = backend_kwargs.get("use_sortingview", False)
diff --git a/src/spikeinterface/widgets/autocorrelograms.py b/src/spikeinterface/widgets/autocorrelograms.py
index d83afeb259..1380d0119f 100644
--- a/src/spikeinterface/widgets/autocorrelograms.py
+++ b/src/spikeinterface/widgets/autocorrelograms.py
@@ -16,7 +16,6 @@ def __init__(self, *args, **kargs):
         )
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
-        import matplotlib.pyplot as plt
         from .utils_matplotlib import make_mpl_figure
 
         dp = to_attr(data_plot)
@@ -46,7 +45,6 @@ def plot_figpack(self, data_plot, **backend_kwargs):
             make_serializable,
             handle_display_and_url,
             import_figpack_or_sortingview,
-            generate_unit_table_view,
         )
 
         use_sortingview = backend_kwargs.get("use_sortingview", False)
diff --git a/src/spikeinterface/widgets/bombcell_curation.py b/src/spikeinterface/widgets/bombcell_curation.py
index 38b4e6c751..3f06b88684 100644
--- a/src/spikeinterface/widgets/bombcell_curation.py
+++ b/src/spikeinterface/widgets/bombcell_curation.py
@@ -85,7 +85,6 @@ def _get_metrics_for_unit_label(self, unit_label, thresholds):
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
         import matplotlib.pyplot as plt
-        import pandas as pd
 
         dp = to_attr(data_plot)
         metrics = dp.metrics
@@ -239,8 +238,7 @@ def plot_bombcell_unit_labeling_all(
     dict
         Dictionary with keys 'histograms', 'waveforms', 'upset' containing widget objects.
     """
-    from pathlib import Path
-    from spikeinterface.curation import bombcell_get_default_thresholds, save_bombcell_results
+    from spikeinterface.curation import bombcell_get_default_thresholds
 
     if thresholds is None:
         thresholds = bombcell_get_default_thresholds()
diff --git a/src/spikeinterface/widgets/collision.py b/src/spikeinterface/widgets/collision.py
index ce1f263cce..ad02f36b08 100644
--- a/src/spikeinterface/widgets/collision.py
+++ b/src/spikeinterface/widgets/collision.py
@@ -67,7 +67,6 @@ def __init__(
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
         import matplotlib.pyplot as plt
-        import sklearn
         import matplotlib
 
         from .utils_matplotlib import make_mpl_figure
@@ -87,7 +86,6 @@ def plot_matplotlib(self, data_plot, **backend_kwargs):
         template_inds = [all_unit_ids.index(u) for u in dp.unit_ids]
 
         templates_array = dp.templates_array[template_inds, :, :].copy()
-        flat_templates = templates_array.reshape(templates_array.shape[0], -1)
 
         similarity_matrix, _ = compute_similarity_with_templates_array(
             templates_array,
@@ -107,8 +105,6 @@ def plot_matplotlib(self, data_plot, **backend_kwargs):
         fs = comp.sorting1.get_sampling_frequency()
         lags = comp.bins / fs * 1000
 
-        n = len(dp.unit_ids)
-
         similarities, recall_scores, pair_names = comp.compute_collision_by_similarity(
             similarity_matrix, unit_ids=dp.unit_ids, good_only=dp.good_only, min_accuracy=dp.min_accuracy
         )
@@ -239,7 +235,6 @@ def __init__(
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
         import matplotlib.pyplot as plt
-        import sklearn
         import matplotlib
 
         from .utils_matplotlib import make_mpl_figure
diff --git a/src/spikeinterface/widgets/comparison.py b/src/spikeinterface/widgets/comparison.py
index d111124522..2784cd09a2 100644
--- a/src/spikeinterface/widgets/comparison.py
+++ b/src/spikeinterface/widgets/comparison.py
@@ -27,7 +27,6 @@ def __init__(self, gt_comparison, count_text=True, unit_ticks=True, backend=None
         BaseWidget.__init__(self, plot_data, backend=backend, **backend_kwargs)
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
-        import matplotlib.pyplot as plt
         from .utils_matplotlib import make_mpl_figure
 
         dp = to_attr(data_plot)
@@ -108,7 +107,6 @@ def __init__(
         BaseWidget.__init__(self, plot_data, backend=backend, **backend_kwargs)
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
-        import matplotlib.pyplot as plt
         from .utils_matplotlib import make_mpl_figure
 
         dp = to_attr(data_plot)
diff --git a/src/spikeinterface/widgets/crosscorrelograms.py b/src/spikeinterface/widgets/crosscorrelograms.py
index 438239ab88..ed818b7800 100644
--- a/src/spikeinterface/widgets/crosscorrelograms.py
+++ b/src/spikeinterface/widgets/crosscorrelograms.py
@@ -86,7 +86,6 @@ def __init__(
         BaseWidget.__init__(self, plot_data, backend=backend, **backend_kwargs)
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
-        import matplotlib.pyplot as plt
         from .utils_matplotlib import make_mpl_figure
 
         dp = to_attr(data_plot)
@@ -131,7 +130,6 @@ def plot_figpack(self, data_plot, **backend_kwargs):
             make_serializable,
             handle_display_and_url,
             import_figpack_or_sortingview,
-            generate_unit_table_view,
         )
 
         use_sortingview = backend_kwargs.get("use_sortingview", False)
diff --git a/src/spikeinterface/widgets/drift_templates.py b/src/spikeinterface/widgets/drift_templates.py
index dda0371e52..297c24d287 100644
--- a/src/spikeinterface/widgets/drift_templates.py
+++ b/src/spikeinterface/widgets/drift_templates.py
@@ -69,7 +69,7 @@ def plot_ipywidgets(self, data_plot, **backend_kwargs):
             max=arr.shape[0] - 1,
             readout=False,
             continuous_update=True,
-            layout=widgets.Layout(width=f"100%"),
+            layout=widgets.Layout(width="100%"),
         )
 
         self.widget = widgets.AppLayout(
diff --git a/src/spikeinterface/widgets/isi_distribution.py b/src/spikeinterface/widgets/isi_distribution.py
index 65bda2341e..6e6c1e1cbd 100644
--- a/src/spikeinterface/widgets/isi_distribution.py
+++ b/src/spikeinterface/widgets/isi_distribution.py
@@ -1,5 +1,4 @@
 import numpy as np
-from warnings import warn
 
 from spikeinterface.core import SortingAnalyzer, BaseSorting
 
@@ -48,7 +47,6 @@ def __init__(
         BaseWidget.__init__(self, plot_data, backend=backend, **backend_kwargs)
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
-        import matplotlib.pyplot as plt
         from .utils_matplotlib import make_mpl_figure
 
         dp = to_attr(data_plot)
diff --git a/src/spikeinterface/widgets/metrics.py b/src/spikeinterface/widgets/metrics.py
index 0631dc52c9..23317fdc4e 100644
--- a/src/spikeinterface/widgets/metrics.py
+++ b/src/spikeinterface/widgets/metrics.py
@@ -82,7 +82,6 @@ def __init__(
         BaseWidget.__init__(self, plot_data, backend=backend, **backend_kwargs)
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
-        import matplotlib.pyplot as plt
         from .utils_matplotlib import make_mpl_figure
 
         dp = to_attr(data_plot)
@@ -376,9 +375,9 @@ def __init__(
             for category, subdict in thresholds.items():
                 assert isinstance(subdict, dict), "Each category in thresholds should be a dict of metric thresholds."
                 for metric_name, thresh in subdict.items():
-                    assert isinstance(thresh, dict) and (
-                        "greater" in thresh or "less" in thresh
-                    ), "Each threshold entry should be a dict with 'greater' and/or 'less' keys."
+                    assert isinstance(thresh, dict) and ("greater" in thresh or "less" in thresh), (
+                        "Each threshold entry should be a dict with 'greater' and/or 'less' keys."
+                    )
                     flat_thresholds[metric_name] = thresh
 
         if metrics_to_plot is None:
diff --git a/src/spikeinterface/widgets/multicomparison.py b/src/spikeinterface/widgets/multicomparison.py
index 38d1b28e54..b0878914f7 100644
--- a/src/spikeinterface/widgets/multicomparison.py
+++ b/src/spikeinterface/widgets/multicomparison.py
@@ -1,8 +1,6 @@
 import numpy as np
-from warnings import warn
 
 from .base import BaseWidget, to_attr
-from .utils import get_unit_colors
 
 
 class MultiCompGraphWidget(BaseWidget):
@@ -228,7 +226,6 @@ def __init__(
         BaseWidget.__init__(self, plot_data, backend=backend, **backend_kwargs)
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
-        import matplotlib.colors as mpl_colors
         import matplotlib.pyplot as plt
         from .utils_matplotlib import make_mpl_figure
 
diff --git a/src/spikeinterface/widgets/peak_activity.py b/src/spikeinterface/widgets/peak_activity.py
index f7582b4042..117df2073a 100644
--- a/src/spikeinterface/widgets/peak_activity.py
+++ b/src/spikeinterface/widgets/peak_activity.py
@@ -204,6 +204,6 @@ def _plot_one_bin(
             artists = artists + (im,)
 
         if with_color_bar:
-            self.cbar = self.figure.colorbar(im, ax=self.ax, label=f"Peak rate (Hz)")
+            self.cbar = self.figure.colorbar(im, ax=self.ax, label="Peak rate (Hz)")
 
         return artists
diff --git a/src/spikeinterface/widgets/peaks_on_probe.py b/src/spikeinterface/widgets/peaks_on_probe.py
index ea707c30ed..8f19b4a7eb 100644
--- a/src/spikeinterface/widgets/peaks_on_probe.py
+++ b/src/spikeinterface/widgets/peaks_on_probe.py
@@ -79,12 +79,10 @@ def plot_matplotlib(self, data_plot, **backend_kwargs):
             dp.peaks,
             dp.peak_locations,
         )
-        fs = dp.recording.get_sampling_frequency()
         num_plots = len(peaks)
 
         # Set the maximum time to the end time of the longest segment
         if dp.time_range is None:
-
             time_range = self._get_min_and_max_times_in_recording(dp.recording)
         else:
             time_range = dp.time_range
@@ -98,7 +96,6 @@ def plot_matplotlib(self, data_plot, **backend_kwargs):
 
         # Plot each passed peaks / peak_locations over the probe on a separate subplot
         for ax_idx, (peaks_to_plot, peak_locs_to_plot) in enumerate(zip(peaks, peak_locations)):
-
             ax = self.axes[ax_idx]
             plot_probe_map(dp.recording, ax=ax)
 
@@ -138,7 +135,7 @@ def plot_matplotlib(self, data_plot, **backend_kwargs):
 
             ax.set_ylim(ylim[0], ylim[1])
 
-        self.figure.suptitle(f"Peaks on Probe Plot")
+        self.figure.suptitle("Peaks on Probe Plot")
 
     def _get_peaks_time_mask(self, recording, time_range, peaks_to_plot):
         """
@@ -152,7 +149,6 @@ def _get_peaks_time_mask(self, recording, time_range, peaks_to_plot):
         time_mask = np.zeros(peaks_to_plot.size, dtype=bool)
 
         for seg_idx in range(recording.get_num_segments()):
-
             segment = recording.select_segments(seg_idx)
 
             t_start_sample = segment.time_to_sample_index(time_range[0])
@@ -175,7 +171,6 @@ def _get_min_and_max_times_in_recording(self, recording):
         t_starts = []
         t_stops = []
         for seg_idx in range(recording.get_num_segments()):
-
             segment = recording.select_segments(seg_idx)
 
             t_starts.append(segment.sample_index_to_time(0))
diff --git a/src/spikeinterface/widgets/potential_merges.py b/src/spikeinterface/widgets/potential_merges.py
index 370efa57eb..ce4e23e2f7 100644
--- a/src/spikeinterface/widgets/potential_merges.py
+++ b/src/spikeinterface/widgets/potential_merges.py
@@ -1,5 +1,4 @@
 import numpy as np
-from warnings import warn
 
 from .base import BaseWidget, default_backend_kwargs
 
diff --git a/src/spikeinterface/widgets/probe_map.py b/src/spikeinterface/widgets/probe_map.py
index 53f18af814..afc6224756 100644
--- a/src/spikeinterface/widgets/probe_map.py
+++ b/src/spikeinterface/widgets/probe_map.py
@@ -41,7 +41,6 @@ def __init__(
         BaseWidget.__init__(self, plot_data, backend=backend, **backend_kwargs)
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
-        import matplotlib.pyplot as plt
         from .utils_matplotlib import make_mpl_figure
         from probeinterface.plotting import get_auto_lims, plot_probe
 
diff --git a/src/spikeinterface/widgets/rasters.py b/src/spikeinterface/widgets/rasters.py
index e302674845..eda75cef9e 100644
--- a/src/spikeinterface/widgets/rasters.py
+++ b/src/spikeinterface/widgets/rasters.py
@@ -1,10 +1,9 @@
 import numpy as np
-from warnings import warn
 
 from spikeinterface.core import SortingAnalyzer, BaseSorting
 from spikeinterface.core.sorting_tools import get_segment_durations
 
-from .base import BaseWidget, to_attr, default_backend_kwargs
+from .base import BaseWidget, to_attr
 from .utils import (
     get_some_colors,
     validate_segment_indices,
@@ -185,8 +184,6 @@ def __init__(
         BaseWidget.__init__(self, plot_data, backend=backend, **backend_kwargs)
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
-        import matplotlib.pyplot as plt
-        from matplotlib.colors import Normalize
         from .utils_matplotlib import make_mpl_figure
 
         dp = to_attr(data_plot)
@@ -267,10 +264,8 @@ def plot_matplotlib(self, data_plot, **backend_kwargs):
 
         # Add segment boundary lines if provided and handle x limits
         if dp.segment_start_stop_times is not None:
-
             segment_times = np.array(list(dp.segment_start_stop_times.values()))
             if len(segment_times) > 1:
-
                 segment_times = segment_times - dp.segment_time_offsets[:, None]
                 self._set_segment_time_ticks(scatter_ax, segment_times, dp.segment_time_offsets)
 
@@ -471,7 +466,7 @@ def __init__(
         if isinstance(sorting_analyzer_or_sorting, SortingAnalyzer):
             if not sorting_analyzer_or_sorting.has_extension("unit_locations"):
                 if sort_by_depth:
-                    raise AttributeError(f"'unit_locations' necessary for `sort_by_depth=True`")
+                    raise AttributeError("'unit_locations' necessary for `sort_by_depth=True`")
             else:
                 depths = sorting_analyzer_or_sorting.get_extension("unit_locations").get_data(outputs="numpy")
                 s_args_depths = np.argsort(depths[:, 1])
diff --git a/src/spikeinterface/widgets/spike_locations.py b/src/spikeinterface/widgets/spike_locations.py
index f589d86896..af2956522c 100644
--- a/src/spikeinterface/widgets/spike_locations.py
+++ b/src/spikeinterface/widgets/spike_locations.py
@@ -106,7 +106,6 @@ def __init__(
         BaseWidget.__init__(self, plot_data, backend=backend, **backend_kwargs)
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
-        import matplotlib.pyplot as plt
         from .utils_matplotlib import make_mpl_figure
         from matplotlib.lines import Line2D
 
diff --git a/src/spikeinterface/widgets/spike_locations_by_time.py b/src/spikeinterface/widgets/spike_locations_by_time.py
index 5b35888852..c1f3b7d277 100644
--- a/src/spikeinterface/widgets/spike_locations_by_time.py
+++ b/src/spikeinterface/widgets/spike_locations_by_time.py
@@ -114,7 +114,6 @@ def __init__(
         BaseWidget.__init__(self, plot_data, backend=backend, **backend_kwargs)
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
-        import matplotlib.pyplot as plt
         from .utils_matplotlib import make_mpl_figure
 
         dp = to_attr(data_plot)
@@ -167,7 +166,7 @@ def plot_matplotlib(self, data_plot, **backend_kwargs):
 
         scatter_ax.set_xlim(0, dp.total_duration)
         scatter_ax.set_xlabel("Times [s]")
-        scatter_ax.set_ylabel(f"Location [um]")
+        scatter_ax.set_ylabel("Location [um]")
         scatter_ax.spines["top"].set_visible(False)
         scatter_ax.spines["right"].set_visible(False)
         self.figure.subplots_adjust(bottom=0.1, top=0.9, left=0.1)
diff --git a/src/spikeinterface/widgets/spikes_on_traces.py b/src/spikeinterface/widgets/spikes_on_traces.py
index b28fe25e9d..86e1a26faf 100644
--- a/src/spikeinterface/widgets/spikes_on_traces.py
+++ b/src/spikeinterface/widgets/spikes_on_traces.py
@@ -1,5 +1,3 @@
-import warnings
-
 import numpy as np
 
 from .base import BaseWidget, to_attr
@@ -147,8 +145,6 @@ def __init__(
         BaseWidget.__init__(self, plot_data, backend=backend, **backend_kwargs)
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
-        import matplotlib.pyplot as plt
-        from .utils_matplotlib import make_mpl_figure
 
         from matplotlib.patches import Ellipse
         from matplotlib.lines import Line2D
@@ -237,7 +233,6 @@ def plot_matplotlib(self, data_plot, **backend_kwargs):
                                 label_set = True
 
     def plot_ipywidgets(self, data_plot, **backend_kwargs):
-        import matplotlib.pyplot as plt
         import ipywidgets.widgets as widgets
         from IPython.display import display
         from .utils_ipywidgets import check_ipywidget_backend, UnitSelector
@@ -254,8 +249,6 @@ def plot_ipywidgets(self, data_plot, **backend_kwargs):
         backend_kwargs_ts = backend_kwargs.copy()
         backend_kwargs_ts["width_cm"] = ratios[1] * backend_kwargs_ts["width_cm"]
         backend_kwargs_ts["display"] = False
-        height_cm = backend_kwargs["height_cm"]
-        width_cm = backend_kwargs["width_cm"]
 
         # plot timeseries
         self._traces_widget = TracesWidget(
diff --git a/src/spikeinterface/widgets/template_similarity.py b/src/spikeinterface/widgets/template_similarity.py
index 749afe0334..a9283d40b3 100644
--- a/src/spikeinterface/widgets/template_similarity.py
+++ b/src/spikeinterface/widgets/template_similarity.py
@@ -63,7 +63,6 @@ def __init__(
         BaseWidget.__init__(self, plot_data, backend=backend, **backend_kwargs)
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
-        import matplotlib.pyplot as plt
         from .utils_matplotlib import make_mpl_figure
 
         dp = to_attr(data_plot)
diff --git a/src/spikeinterface/widgets/tests/test_widgets.py b/src/spikeinterface/widgets/tests/test_widgets.py
index 8ece826de9..fcac517d46 100644
--- a/src/spikeinterface/widgets/tests/test_widgets.py
+++ b/src/spikeinterface/widgets/tests/test_widgets.py
@@ -37,7 +37,6 @@
 
 
 class TestWidgets(unittest.TestCase):
-
     @classmethod
     def setUpClass(cls):
 
@@ -759,7 +758,6 @@ def test_plot_bombcell_labels_upset(self):
 
 if __name__ == "__main__":
     # unittest.main()
-    import matplotlib.pyplot as plt
 
     TestWidgets.setUpClass()
     mytest = TestWidgets()
diff --git a/src/spikeinterface/widgets/tests/test_widgets_utils.py b/src/spikeinterface/widgets/tests/test_widgets_utils.py
index c1905f3ac8..144fae8de9 100644
--- a/src/spikeinterface/widgets/tests/test_widgets_utils.py
+++ b/src/spikeinterface/widgets/tests/test_widgets_utils.py
@@ -5,24 +5,23 @@
     get_some_colors,
     validate_segment_indices,
 )
-import numpy as np
 
 
 def test_get_some_colors():
     keys = ["a", "b", "c", "d"]
 
-    colors = get_some_colors(keys, color_engine="auto")
+    _ = get_some_colors(keys, color_engine="auto")
     # print(colors)
 
-    colors = get_some_colors(keys, color_engine="distinctipy")
+    _ = get_some_colors(keys, color_engine="distinctipy")
     # print(colors)
 
-    colors = get_some_colors(keys, color_engine="matplotlib", shuffle=None)
+    _ = get_some_colors(keys, color_engine="matplotlib", shuffle=None)
     # print(colors)
-    colors = get_some_colors(keys, color_engine="matplotlib", shuffle=False)
-    colors = get_some_colors(keys, color_engine="matplotlib", shuffle=True)
+    _ = get_some_colors(keys, color_engine="matplotlib", shuffle=False)
+    _ = get_some_colors(keys, color_engine="matplotlib", shuffle=True)
 
-    colors = get_some_colors(keys, color_engine="colorsys")
+    _ = get_some_colors(keys, color_engine="colorsys")
     # print(colors)
 
 
diff --git a/src/spikeinterface/widgets/traces.py b/src/spikeinterface/widgets/traces.py
index 62f221b6ca..8106e7e1d3 100644
--- a/src/spikeinterface/widgets/traces.py
+++ b/src/spikeinterface/widgets/traces.py
@@ -141,7 +141,7 @@ def __init__(
         time_range = np.array(time_range, dtype=np.float64)
         if time_range[1] > t_end:
             warnings.warn(
-                "You have selected a time after the end of the segment. The range will be clipped to " f"{t_end}"
+                f"You have selected a time after the end of the segment. The range will be clipped to {t_end}"
             )
             time_range[1] = t_end
 
@@ -209,9 +209,9 @@ def __init__(
             if isinstance(clim, tuple):
                 clims = {layer_key: clim for layer_key in layer_keys}
             elif isinstance(clim, dict):
-                assert all(
-                    layer_key in clim for layer_key in layer_keys
-                ), f"all recordings must be a key in `clim` if `clim` is a dict. Provide keys {layer_keys} in clim"
+                assert all(layer_key in clim for layer_key in layer_keys), (
+                    f"all recordings must be a key in `clim` if `clim` is a dict. Provide keys {layer_keys} in clim"
+                )
                 clims = clim
             else:
                 raise TypeError(f"'clim' can be None, tuple, or dict! Unsupported type {type(clim)}")
@@ -220,9 +220,9 @@ def __init__(
         if events is not None:
             num_segments = rec0.get_num_segments()
             if num_segments > 1:
-                assert (
-                    len(events) == num_segments
-                ), f"events must be a list with the events for each of the {num_segments} segments"
+                assert len(events) == num_segments, (
+                    f"events must be a list with the events for each of the {num_segments} segments"
+                )
                 evensts_w_dtype = events
             else:
                 if isinstance(events, np.ndarray):
@@ -272,7 +272,6 @@ def __init__(
         BaseWidget.__init__(self, plot_data, backend=backend, **backend_kwargs)
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
-        import matplotlib.pyplot as plt
         from matplotlib.ticker import MaxNLocator
         from .utils_matplotlib import make_mpl_figure
 
@@ -283,7 +282,7 @@ def plot_matplotlib(self, data_plot, **backend_kwargs):
         if self.cb is not None:
             try:
                 self.cb.remove()
-            except:
+            except Exception:
                 pass
 
         ax = self.ax
@@ -618,7 +617,7 @@ def plot_figpack(self, data_plot, **backend_kwargs):
 
         if not dp.order_channel_by_depth:
             warnings.warn(
-                "It is recommended to set 'order_channel_by_depth' to True " "when using the sortingview backend"
+                "It is recommended to set 'order_channel_by_depth' to True when using the sortingview backend"
             )
 
         tiled_layers = []
@@ -673,9 +672,9 @@ def _get_trace_list(recordings, channel_ids, segment_index, time_range=None, ret
     rec0 = recordings[k0]
 
     if return_in_uV:
-        assert all(
-            rec.has_scaleable_traces() for rec in recordings.values()
-        ), "Some recording layers do not have scaled traces. Use `return_in_uV=False`"
+        assert all(rec.has_scaleable_traces() for rec in recordings.values()), (
+            "Some recording layers do not have scaled traces. Use `return_in_uV=False`"
+        )
 
     assert time_range is not None or frame_range is not None, "You must provide either time_range or frame_range"
 
diff --git a/src/spikeinterface/widgets/unit_depths.py b/src/spikeinterface/widgets/unit_depths.py
index 6f6b24cc07..cd113cfca6 100644
--- a/src/spikeinterface/widgets/unit_depths.py
+++ b/src/spikeinterface/widgets/unit_depths.py
@@ -54,7 +54,6 @@ def __init__(self, sorting_analyzer, unit_colors=None, depth_axis=1, backend=Non
         BaseWidget.__init__(self, plot_data, backend=backend, **backend_kwargs)
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
-        import matplotlib.pyplot as plt
         from .utils_matplotlib import make_mpl_figure
 
         dp = to_attr(data_plot)
diff --git a/src/spikeinterface/widgets/unit_labels.py b/src/spikeinterface/widgets/unit_labels.py
index 348f0e3b8d..40a028ca8c 100644
--- a/src/spikeinterface/widgets/unit_labels.py
+++ b/src/spikeinterface/widgets/unit_labels.py
@@ -2,7 +2,6 @@
 
 import numpy as np
 
-from spikeinterface.curation.curation_tools import is_threshold_disabled
 from .base import BaseWidget, to_attr
 
 
@@ -38,9 +37,9 @@ def __init__(
         self.check_extensions(sorting_analyzer, "templates")
         if labels_order is not None:
             assert len(labels_order) == len(np.unique(unit_labels)), "labels_order length must match unique unit types"
-            assert all(
-                [label in np.unique(unit_labels) for label in labels_order]
-            ), "All labels in labels_order must be present in unit_labels"
+            assert all([label in np.unique(unit_labels) for label in labels_order]), (
+                "All labels in labels_order must be present in unit_labels"
+            )
         else:
             labels_order = np.unique(unit_labels)
         plot_data = dict(
diff --git a/src/spikeinterface/widgets/unit_locations.py b/src/spikeinterface/widgets/unit_locations.py
index 7d88a523d4..4785f36251 100644
--- a/src/spikeinterface/widgets/unit_locations.py
+++ b/src/spikeinterface/widgets/unit_locations.py
@@ -109,7 +109,6 @@ def __init__(
         BaseWidget.__init__(self, data_plot, backend=backend, **backend_kwargs)
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
-        import matplotlib.pyplot as plt
         from .utils_matplotlib import make_mpl_figure
         from probeinterface.plotting import plot_probe
 
diff --git a/src/spikeinterface/widgets/unit_presence.py b/src/spikeinterface/widgets/unit_presence.py
index 72a9603544..0baf14914d 100644
--- a/src/spikeinterface/widgets/unit_presence.py
+++ b/src/spikeinterface/widgets/unit_presence.py
@@ -1,5 +1,4 @@
 import numpy as np
-from warnings import warn
 
 from spikeinterface.core import SortingAnalyzer, BaseSorting
 from .base import BaseWidget, to_attr
@@ -55,7 +54,6 @@ def __init__(
         BaseWidget.__init__(self, data_plot, backend=backend, **backend_kwargs)
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
-        import matplotlib.pyplot as plt
         from .utils_matplotlib import make_mpl_figure
 
         dp = to_attr(data_plot)
diff --git a/src/spikeinterface/widgets/unit_probe_map.py b/src/spikeinterface/widgets/unit_probe_map.py
index 944331ad92..eb6a219295 100644
--- a/src/spikeinterface/widgets/unit_probe_map.py
+++ b/src/spikeinterface/widgets/unit_probe_map.py
@@ -59,7 +59,6 @@ def __init__(
         BaseWidget.__init__(self, data_plot, backend=backend, **backend_kwargs)
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
-        import matplotlib.pyplot as plt
         from .utils_matplotlib import make_mpl_figure
         from probeinterface.plotting import plot_probe
 
diff --git a/src/spikeinterface/widgets/unit_summary.py b/src/spikeinterface/widgets/unit_summary.py
index 821260eba7..e0ac78d66b 100644
--- a/src/spikeinterface/widgets/unit_summary.py
+++ b/src/spikeinterface/widgets/unit_summary.py
@@ -80,7 +80,6 @@ def __init__(
         BaseWidget.__init__(self, plot_data, backend=backend, **backend_kwargs)
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
-        import matplotlib.pyplot as plt
         from .utils_matplotlib import make_mpl_figure
 
         dp = to_attr(data_plot)
diff --git a/src/spikeinterface/widgets/unit_valid_periods.py b/src/spikeinterface/widgets/unit_valid_periods.py
index 7c54e93fdc..5835497174 100644
--- a/src/spikeinterface/widgets/unit_valid_periods.py
+++ b/src/spikeinterface/widgets/unit_valid_periods.py
@@ -59,7 +59,6 @@ def __init__(
         BaseWidget.__init__(self, data_plot, backend=backend, **backend_kwargs)
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
-        import matplotlib.pyplot as plt
         from .utils_matplotlib import make_mpl_figure
 
         dp = to_attr(data_plot)
diff --git a/src/spikeinterface/widgets/unit_waveforms.py b/src/spikeinterface/widgets/unit_waveforms.py
index 5f9da5dc97..cfdd27b93e 100644
--- a/src/spikeinterface/widgets/unit_waveforms.py
+++ b/src/spikeinterface/widgets/unit_waveforms.py
@@ -6,7 +6,6 @@
 from .utils import get_unit_colors
 
 from spikeinterface.core import ChannelSparsity, SortingAnalyzer, Templates
-from spikeinterface.core.basesorting import BaseSorting
 
 
 class UnitWaveformsWidget(BaseWidget):
@@ -236,7 +235,6 @@ def __init__(
         BaseWidget.__init__(self, plot_data, backend=backend, **backend_kwargs)
 
     def plot_matplotlib(self, data_plot, **backend_kwargs):
-        import matplotlib.pyplot as plt
         from .utils_matplotlib import make_mpl_figure
 
         dp = to_attr(data_plot)
@@ -548,12 +546,12 @@ def _get_template_shadings(self, unit_ids, templates_percentile_shading):
             if isinstance(templates_percentile_shading, (int, float)):
                 templates_percentile_shading = [templates_percentile_shading, 100 - templates_percentile_shading]
             else:
-                assert isinstance(
-                    templates_percentile_shading, (list, tuple)
-                ), "'templates_percentile_shading' should be a float, a list/tuple of floats, or None!"
-                assert (
-                    np.mod(len(templates_percentile_shading), 2) == 0
-                ), "'templates_percentile_shading' should be a have an even number of elements."
+                assert isinstance(templates_percentile_shading, (list, tuple)), (
+                    "'templates_percentile_shading' should be a float, a list/tuple of floats, or None!"
+                )
+                assert np.mod(len(templates_percentile_shading), 2) == 0, (
+                    "'templates_percentile_shading' should be a have an even number of elements."
+                )
             templates_shading = []
             for percentile in templates_percentile_shading:
                 template_percentile = self.templates_ext.get_templates(
diff --git a/src/spikeinterface/widgets/utils.py b/src/spikeinterface/widgets/utils.py
index 82c35dafc0..824579179c 100644
--- a/src/spikeinterface/widgets/utils.py
+++ b/src/spikeinterface/widgets/utils.py
@@ -226,8 +226,8 @@ def array_to_image(
                 font = ImageFont.truetype("/usr/share/fonts/truetype/freefont/FreeMono.ttf", fontsize)
             else:
                 font = ImageFont.truetype("arial.ttf", fontsize)
-        except:
-            print(f"Could not load font to use in scalebar. Scalebar will not be drawn.")
+        except Exception:
+            print("Could not load font to use in scalebar. Scalebar will not be drawn.")
             font = None
 
         if font is not None:
diff --git a/src/spikeinterface/widgets/utils_ipywidgets.py b/src/spikeinterface/widgets/utils_ipywidgets.py
index 25c67d36bd..7da6bec865 100644
--- a/src/spikeinterface/widgets/utils_ipywidgets.py
+++ b/src/spikeinterface/widgets/utils_ipywidgets.py
@@ -8,9 +8,9 @@ def check_ipywidget_backend():
     import matplotlib
 
     mpl_backend = matplotlib.get_backend()
-    assert (
-        "ipympl" in mpl_backend or "widget" in mpl_backend
-    ), "To use the 'ipywidgets' backend, you have to set %matplotlib widget"
+    assert "ipympl" in mpl_backend or "widget" in mpl_backend, (
+        "To use the 'ipywidgets' backend, you have to set %matplotlib widget"
+    )
 
 
 class TimeSlider(W.HBox):
@@ -80,7 +80,7 @@ def __init__(self, durations, sampling_frequency, frame_range, rec0=None, t_star
             max=self.frame_limits[self.segment_index] - 1,
             readout=False,
             continuous_update=False,
-            layout=W.Layout(width=f"70%"),
+            layout=W.Layout(width="70%"),
         )
 
         self.slider.observe(self.slider_moved, names="value", type="change")
@@ -184,7 +184,7 @@ def update_time(self, new_frame=None, new_time=None, update_slider=False, update
     def time_label_changed(self, change=None):
         try:
             new_time = float(self.time_label.value)
-        except:
+        except Exception:
             new_time = None
         if new_time is not None:
             self.update_time(new_time=new_time, update_slider=True)
diff --git a/src/spikeinterface/widgets/widget_list.py b/src/spikeinterface/widgets/widget_list.py
index 6cd6bbfd23..988019fbac 100644
--- a/src/spikeinterface/widgets/widget_list.py
+++ b/src/spikeinterface/widgets/widget_list.py
@@ -38,7 +38,7 @@
 from .collision import ComparisonCollisionBySimilarityWidget, StudyComparisonCollisionBySimilarityWidget
 from .unit_labels import WaveformOverlayByLabelWidget
 from .unit_valid_periods import ValidUnitPeriodsWidget
-from .bombcell_curation import BombcellUpsetPlotWidget, plot_bombcell_unit_labeling_all
+from .bombcell_curation import BombcellUpsetPlotWidget
 
 widget_list = [
     AgreementMatrixWidget,

From db3d47962d17082675cae0a104107f855865e5d7 Mon Sep 17 00:00:00 2001
From: Alessio Buccino <alejoe9187@gmail.com>
Date: Mon, 9 Nov 2026 14:56:25 +0100
Subject: [PATCH 07/30] fix: extractors ruff checks

---
 pyproject.toml                                |  4 +-
 .../extractors/combinatoextractors.py         |  1 -
 .../extractors/extractor_classes.py           |  2 +-
 .../extractors/mdaextractors.py               | 10 ++--
 .../extractors/neuropixels_utils.py           | 60 +++++++++----------
 5 files changed, 37 insertions(+), 40 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 6762671368..170fa857ef 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -58,8 +58,8 @@ select = ['E4', 'E7', 'E9', 'F']
 exclude = ["**/tests/**", "**/test_*.py", "**/conftest.py"]
 ignore = ['E741', 'E731', 'F821']
 [tool.ruff.lint.per-file-ignores]
-"**/__init__.py" = ["F401"]
-"src/spikeinterface/core/testing_tools.py" = ["E402", "F403"]
+"**/__init__.py" = ['F401', 'F403']
+"src/spikeinterface/core/testing_tools.py" = ['E402', 'F403']
 
 [project.urls]
 homepage = "https://github.com/SpikeInterface/spikeinterface"
diff --git a/src/spikeinterface/extractors/combinatoextractors.py b/src/spikeinterface/extractors/combinatoextractors.py
index 5ecc5cdf24..011af94ba9 100644
--- a/src/spikeinterface/extractors/combinatoextractors.py
+++ b/src/spikeinterface/extractors/combinatoextractors.py
@@ -56,7 +56,6 @@ def __init__(self, folder_path, sampling_frequency=None, user="simple", det_sign
         unit_counter = 0
         spiketrains = {}
         metadata = {}
-        unsorted = []
         with h5py.File(det_file, mode="r") as fdet:
             for sign, sfile in sort_cat_files:
                 with h5py.File(sfile, mode="r") as f:
diff --git a/src/spikeinterface/extractors/extractor_classes.py b/src/spikeinterface/extractors/extractor_classes.py
index c12561331b..e46ebbf0a2 100644
--- a/src/spikeinterface/extractors/extractor_classes.py
+++ b/src/spikeinterface/extractors/extractor_classes.py
@@ -14,7 +14,7 @@
 )
 
 # sorting/recording/event from neo
-from .neoextractors import *
+from .neoextractors import neo_recording_extractors_dict, neo_sorting_extractors_dict, neo_event_extractors_dict
 
 # non-NEO objects implemented in neo folder
 # keep for reference Currently pulling from neoextractor __init__
diff --git a/src/spikeinterface/extractors/mdaextractors.py b/src/spikeinterface/extractors/mdaextractors.py
index acc3a1790e..b5b744e568 100644
--- a/src/spikeinterface/extractors/mdaextractors.py
+++ b/src/spikeinterface/extractors/mdaextractors.py
@@ -489,7 +489,6 @@ def _read_header(path):
     f = open(path, "rb")
     try:
         dt_code = _read_int32(f)
-        num_bytes_per_entry = _read_int32(f)
         num_dims = _read_int32(f)
         uses64bitdims = False
         if num_dims < 0:
@@ -688,7 +687,7 @@ def _writemda(X, fname, dt):
         print(f"Unexpected data type: {dt}")
         return False
 
-    if type(fname) == str:
+    if type(fname) is str:
         f = open(fname, "wb")
     else:
         f = fname
@@ -705,13 +704,13 @@ def _writemda(X, fname, dt):
         bytes0 = X.astype(dt).tobytes(order="F")
         f.write(bytes0)
 
-        if type(fname) == str:
+        if type(fname) is str:
             f.close()
         return True
     except Exception as e:  # catch *all* exceptions
         traceback.print_exc()
         print(e)
-        if type(fname) == str:
+        if type(fname) is str:
             f.close()
         return False
 
@@ -790,7 +789,7 @@ def appendmda(X, path):
 
 
 def file_extension(fname):
-    if type(fname) == str:
+    if type(fname) is str:
         filename, ext = os.path.splitext(fname)
         return ext
     else:
@@ -816,7 +815,6 @@ def _write_int64(f, val):
 def _header_from_file(f):
     try:
         dt_code = _read_int32(f)
-        num_bytes_per_entry = _read_int32(f)
         num_dims = _read_int32(f)
         uses64bitdims = False
         if num_dims < 0:
diff --git a/src/spikeinterface/extractors/neuropixels_utils.py b/src/spikeinterface/extractors/neuropixels_utils.py
index df66230548..115a43be4b 100644
--- a/src/spikeinterface/extractors/neuropixels_utils.py
+++ b/src/spikeinterface/extractors/neuropixels_utils.py
@@ -90,33 +90,33 @@ def compute_saturation_threshold_from_probe(probe: Probe, stream_name: str) -> f
     return None
 
 
-def synchronize_neuropixel_streams(recording_ref, recording_other):
-    """
-    Use the last "sync" channel from spikeglx or openephys neuropixels to synchronize
-    recordings.
-
-    Method used :
-      1. detect pulse times on both streams.
-      2. make a linear regression from "other" to "ref".
-          The slope is nclose to 1 and corresponds to the sample rate correction
-          The intercept is close to 0 and corresponds to the delta time start
-
-    """
-    # This will be done very very soon, I promise.
-    raise NotImplementedError
-
-    synhcro_chan_id = recording_ref.channel_ids[-1]
-    trig_ref = recording_ref.get_traces(channel_ids=[synhcro_chan_id], return_in_uV=False)
-    trig_ref = trig_ref[:, 0]
-    times_ref = recording_ref.get_times()
-
-    synhcro_chan_id = recording_other.channel_ids[-1]
-    trig_other = recording_other.get_traces(channel_ids=[synhcro_chan_id], return_in_uV=False)
-    trig_other = trig_other[:, 0]
-    times_other = recording_other.get_times()
-
-    # import matplotlib.pyplot as plt
-    # fig, ax = plt.subplots()
-    # ax.plot(times_ref, trig_ref)
-    # ax.plot(times_other, trig_other)
-    # plt.show()
+# def synchronize_neuropixel_streams(recording_ref, recording_other):
+#     """
+#     Use the last "sync" channel from spikeglx or openephys neuropixels to synchronize
+#     recordings.
+
+#     Method used :
+#       1. detect pulse times on both streams.
+#       2. make a linear regression from "other" to "ref".
+#           The slope is nclose to 1 and corresponds to the sample rate correction
+#           The intercept is close to 0 and corresponds to the delta time start
+
+#     """
+#     # This will be done very very soon, I promise.
+#     raise NotImplementedError
+
+#     synhcro_chan_id = recording_ref.channel_ids[-1]
+#     trig_ref = recording_ref.get_traces(channel_ids=[synhcro_chan_id], return_in_uV=False)
+#     trig_ref = trig_ref[:, 0]
+#     times_ref = recording_ref.get_times()
+
+#     synhcro_chan_id = recording_other.channel_ids[-1]
+#     trig_other = recording_other.get_traces(channel_ids=[synhcro_chan_id], return_in_uV=False)
+#     trig_other = trig_other[:, 0]
+#     times_other = recording_other.get_times()
+
+#     # import matplotlib.pyplot as plt
+#     # fig, ax = plt.subplots()
+#     # ax.plot(times_ref, trig_ref)
+#     # ax.plot(times_other, trig_other)
+#     # plt.show()

From a1fd4487c2fd03076b232ad62434815135e61993 Mon Sep 17 00:00:00 2001
From: Alessio Buccino <alejoe9187@gmail.com>
Date: Mon, 9 Nov 2026 14:59:03 +0100
Subject: [PATCH 08/30] fix: sorters ruff checks

---
 src/spikeinterface/sorters/external/combinato.py       | 3 +--
 src/spikeinterface/sorters/external/hdsort.py          | 1 -
 src/spikeinterface/sorters/external/ironclust.py       | 2 --
 src/spikeinterface/sorters/external/kilosort4.py       | 6 ++----
 src/spikeinterface/sorters/external/waveclus.py        | 2 +-
 src/spikeinterface/sorters/external/yass.py            | 2 +-
 src/spikeinterface/sorters/internal/spyking_circus2.py | 6 +-----
 7 files changed, 6 insertions(+), 16 deletions(-)

diff --git a/src/spikeinterface/sorters/external/combinato.py b/src/spikeinterface/sorters/external/combinato.py
index 94fe33b70a..0d9457cfd8 100644
--- a/src/spikeinterface/sorters/external/combinato.py
+++ b/src/spikeinterface/sorters/external/combinato.py
@@ -52,7 +52,7 @@ class CombinatoSorter(BaseSorter):
     }
 
     _params_description = {
-        "detect_sign": "Use -1 (negative) or 1 (positive) depending " "on the sign of the spikes in the recording",
+        "detect_sign": "Use -1 (negative) or 1 (positive) depending on the sign of the spikes in the recording",
         "MaxClustersPerTemp": "How many clusters can be selected at one temperature",
         "MinSpikesPerClusterMultiSelect": "How many spikes does a cluster need to be selected",
         "RecursiveDepth": "How many clustering recursions should be run (1 do not recurse)",
@@ -125,7 +125,6 @@ def _setup_recording(cls, recording, sorter_output_folder, params, verbose):
         # Generate h5 files in the dataset directory
         chan_ids = recording.get_channel_ids()
         assert len(chan_ids) == 1, "combinato is a single-channel recording"
-        chid = chan_ids[0]
         vcFile_h5 = str(sorter_output_folder / ("recording.h5"))
         with h5py.File(vcFile_h5, mode="w") as f:
             f.create_dataset("sr", data=[recording.get_sampling_frequency()], dtype="float32")
diff --git a/src/spikeinterface/sorters/external/hdsort.py b/src/spikeinterface/sorters/external/hdsort.py
index 0be747b72b..ae4954785c 100644
--- a/src/spikeinterface/sorters/external/hdsort.py
+++ b/src/spikeinterface/sorters/external/hdsort.py
@@ -294,7 +294,6 @@ def write_hdsort_input_format(cls, recording, save_path, chunk_memory="500M"):
                     mapping[i] = (ch, x[i], y[i], i)
                 ephys.create_dataset("mapping", data=mapping)
                 # save traces
-                segment_index = 0
                 write_to_h5_dataset_format(
                     recording,
                     dataset_path="/ephys/signal",
diff --git a/src/spikeinterface/sorters/external/ironclust.py b/src/spikeinterface/sorters/external/ironclust.py
index e79324a0f8..ac0f0d05d5 100644
--- a/src/spikeinterface/sorters/external/ironclust.py
+++ b/src/spikeinterface/sorters/external/ironclust.py
@@ -161,8 +161,6 @@ def _check_apply_filter_in_params(cls, params):
 
     @classmethod
     def _setup_recording(cls, recording, sorter_output_folder, params, verbose):
-        p = params
-
         dataset_dir = sorter_output_folder / "ironclust_dataset"
         # Generate three files in the dataset directory: raw.mda, geom.csv, params.json
         MdaRecordingExtractor.write_recording(
diff --git a/src/spikeinterface/sorters/external/kilosort4.py b/src/spikeinterface/sorters/external/kilosort4.py
index ea5e596b79..e52b084484 100644
--- a/src/spikeinterface/sorters/external/kilosort4.py
+++ b/src/spikeinterface/sorters/external/kilosort4.py
@@ -182,9 +182,7 @@ def _run_from_folder(cls, sorter_output_folder, params, verbose):
 
         if version.parse(cls.get_sorter_version()) < version.parse("4.0.16"):
             raise RuntimeError(
-                "Kilosort versions before 4.0.16 are not supported"
-                "in SpikeInterface. "
-                "Please upgrade Kilosort version."
+                "Kilosort versions before 4.0.16 are not supportedin SpikeInterface. Please upgrade Kilosort version."
             )
 
         # setup kilosort's console and file log handlers
@@ -212,7 +210,7 @@ def _run_from_folder(cls, sorter_output_folder, params, verbose):
             # find the stream handler
             stream_handler = None
             for handler in logger.handlers:
-                if type(handler) == logging.StreamHandler:
+                if type(handler) is logging.StreamHandler:
                     stream_handler = handler
                     break
 
diff --git a/src/spikeinterface/sorters/external/waveclus.py b/src/spikeinterface/sorters/external/waveclus.py
index 41277667b6..df38dfc0f6 100644
--- a/src/spikeinterface/sorters/external/waveclus.py
+++ b/src/spikeinterface/sorters/external/waveclus.py
@@ -290,7 +290,7 @@ def _generate_par_file(params, sorter_output_folder):
         }
         par_input = {}
         for key, value in p.items():
-            if type(value) == bool:
+            if type(value) is bool:
                 value = f"{value}".lower()
             if key in par_renames:
                 key = par_renames[key]
diff --git a/src/spikeinterface/sorters/external/yass.py b/src/spikeinterface/sorters/external/yass.py
index 1a1b40b324..77373e8ad9 100644
--- a/src/spikeinterface/sorters/external/yass.py
+++ b/src/spikeinterface/sorters/external/yass.py
@@ -163,7 +163,7 @@ def _setup_recording(cls, recording, sorter_output_folder, params, verbose):
         # to yaml
         fname_config = sorter_output_folder / "config.yaml"
         with open(fname_config, "w") as file:
-            documents = yaml.dump(merge_params, file)
+            _ = yaml.dump(merge_params, file)
 
         # RunNN training on existing
         neural_nets_path = p["neural_nets_path"]
diff --git a/src/spikeinterface/sorters/internal/spyking_circus2.py b/src/spikeinterface/sorters/internal/spyking_circus2.py
index a9188259bf..f62c9f6259 100644
--- a/src/spikeinterface/sorters/internal/spyking_circus2.py
+++ b/src/spikeinterface/sorters/internal/spyking_circus2.py
@@ -106,10 +106,7 @@ def get_sorter_version(cls):
     @classmethod
     def _run_from_folder(cls, sorter_output_folder, params, verbose):
 
-        if importlib.util.find_spec("torch") is not None:
-            HAVE_TORCH = True
-        else:
-            HAVE_TORCH = False
+        if importlib.util.find_spec("torch") is None:
             print("spykingcircus2 could benefit from using torch. Consider installing it")
 
         # this is imported only on demand because numba import are too heavy
@@ -406,7 +403,6 @@ def _run_from_folder(cls, sorter_output_folder, params, verbose):
 
             del more_outs
 
-            before_clean_ids = templates.unit_ids.copy()
             cleaning_kwargs["max_std_per_channel"] = max_std_per_channel
             cleaning_kwargs["verbose"] = verbose
             templates = clean_templates(templates, noise_levels=noise_levels, **cleaning_kwargs)

From a7408a32632fd9f739aadeb12811f57643f4177b Mon Sep 17 00:00:00 2001
From: Alessio Buccino <alejoe9187@gmail.com>
Date: Mon, 9 Nov 2026 15:02:23 +0100
Subject: [PATCH 09/30] fix: postprocessing ruff checks

---
 src/spikeinterface/postprocessing/amplitude_scalings.py  | 4 +---
 src/spikeinterface/postprocessing/localization_tools.py  | 3 ---
 src/spikeinterface/postprocessing/principal_component.py | 2 +-
 3 files changed, 2 insertions(+), 7 deletions(-)

diff --git a/src/spikeinterface/postprocessing/amplitude_scalings.py b/src/spikeinterface/postprocessing/amplitude_scalings.py
index ea838646fc..6e555c512e 100644
--- a/src/spikeinterface/postprocessing/amplitude_scalings.py
+++ b/src/spikeinterface/postprocessing/amplitude_scalings.py
@@ -107,8 +107,6 @@ def _get_pipeline_nodes(self):
         else:
             cut_out_after = nafter
 
-        extremum_channels_indices = self.sorting_analyzer.get_main_channels(outputs="index", with_dict=True)
-
         # collisions
         handle_collisions = self.params["handle_collisions"]
         delta_collision_ms = self.params["delta_collision_ms"]
@@ -722,7 +720,7 @@ def _plot_collisions(sorting_analyzer, sparsity=None, num_collisions=None):
 
     for i in range(num_collisions):
         overlapping_spikes = collisions[collision_keys[i]]
-        ax = _plot_one_collision(
+        _ = _plot_one_collision(
             sorting_analyzer, collision_keys[i], overlapping_spikes, spikes, scalings=scalings, sparsity=sparsity
         )
 
diff --git a/src/spikeinterface/postprocessing/localization_tools.py b/src/spikeinterface/postprocessing/localization_tools.py
index a23019f955..06af4a46bd 100644
--- a/src/spikeinterface/postprocessing/localization_tools.py
+++ b/src/spikeinterface/postprocessing/localization_tools.py
@@ -108,9 +108,6 @@ def compute_monopolar_triangulation(
         for i, unit_id in enumerate(unit_ids):
             chan_inds = sparsity.unit_id_to_channel_indices[unit_id]
             neighbours_mask[i, chan_inds] = True
-        enforce_decrease_radial_parents = make_radial_order_parents(contact_locations, neighbours_mask)
-
-        best_channels = sorting_analyzer_or_templates.get_main_channels(outputs="index", with_dict=True)
 
     unit_location = np.zeros((unit_ids.size, 4), dtype="float64")
     for i, unit_id in enumerate(unit_ids):
diff --git a/src/spikeinterface/postprocessing/principal_component.py b/src/spikeinterface/postprocessing/principal_component.py
index 60f398f4d2..63bc0ee26d 100644
--- a/src/spikeinterface/postprocessing/principal_component.py
+++ b/src/spikeinterface/postprocessing/principal_component.py
@@ -422,7 +422,7 @@ def run_for_all_spikes(self, file_path=None, verbose=False, **job_kwargs):
 
         num_spikes = sorting.to_spike_vector().size
         shape = (num_spikes, p["n_components"], max_channels_per_template)
-        all_pcs = np.lib.format.open_memmap(filename=file_path, mode="w+", dtype="float32", shape=shape)
+        _ = np.lib.format.open_memmap(filename=file_path, mode="w+", dtype="float32", shape=shape)
         all_pcs_args = dict(filename=file_path, mode="r+", dtype="float32", shape=shape)
 
         waveforms_ext = self.sorting_analyzer.get_extension("waveforms")

From 16ae6cf5be159460300c601b9579fce431106b54 Mon Sep 17 00:00:00 2001
From: Alessio Buccino <alejoe9187@gmail.com>
Date: Mon, 9 Nov 2026 15:04:48 +0100
Subject: [PATCH 10/30] fix: exporters ruff checks

---
 src/spikeinterface/exporters/report.py | 11 ++++-------
 1 file changed, 4 insertions(+), 7 deletions(-)

diff --git a/src/spikeinterface/exporters/report.py b/src/spikeinterface/exporters/report.py
index ae1341afbc..95a184917c 100644
--- a/src/spikeinterface/exporters/report.py
+++ b/src/spikeinterface/exporters/report.py
@@ -71,12 +71,9 @@ def export_report(
         )
 
     # load or compute correlograms
-    if sorting_analyzer.has_extension("correlograms"):
-        correlograms, bins = sorting_analyzer.get_extension("correlograms").get_data()
-    elif force_computation:
-        correlograms, bins = compute_correlograms(sorting_analyzer, window_ms=100.0, bin_ms=1.0)
+    if not sorting_analyzer.has_extension("correlograms") and force_computation:
+        _ = compute_correlograms(sorting_analyzer, window_ms=100.0, bin_ms=1.0)
     else:
-        correlograms = None
         warnings.warn(
             "export_report(): correlograms will not be exported. Use sorting_analyzer.compute('correlograms') if you want to include them."
         )
@@ -107,13 +104,13 @@ def export_report(
 
     # global figures
     fig = plt.figure(figsize=(20, 10))
-    w = sw.plot_unit_locations(sorting_analyzer, figure=fig, unit_colors=unit_colors)
+    _ = sw.plot_unit_locations(sorting_analyzer, figure=fig, unit_colors=unit_colors)
     fig.savefig(output_folder / f"unit_locations.{format}")
     if not show_figures:
         plt.close(fig)
 
     fig, ax = plt.subplots(figsize=(20, 10))
-    sw.plot_unit_depths(sorting_analyzer, ax=ax, unit_colors=unit_colors)
+    _ = sw.plot_unit_depths(sorting_analyzer, ax=ax, unit_colors=unit_colors)
     fig.savefig(output_folder / f"unit_depths.{format}")
     if not show_figures:
         plt.close(fig)

From 866597f6f66f0c37e13fe28f73168e3802737424 Mon Sep 17 00:00:00 2001
From: Alessio Buccino <alejoe9187@gmail.com>
Date: Mon, 9 Nov 2026 15:07:15 +0100
Subject: [PATCH 11/30] fix: benchmark ruff checks

---
 src/spikeinterface/benchmark/benchmark_base.py             | 3 +--
 .../benchmark/benchmark_motion_estimation.py               | 2 +-
 src/spikeinterface/benchmark/benchmark_peak_detection.py   | 7 +------
 .../benchmark/benchmark_peak_localization.py               | 4 ----
 4 files changed, 3 insertions(+), 13 deletions(-)

diff --git a/src/spikeinterface/benchmark/benchmark_base.py b/src/spikeinterface/benchmark/benchmark_base.py
index ebf4b0dde5..e301019699 100644
--- a/src/spikeinterface/benchmark/benchmark_base.py
+++ b/src/spikeinterface/benchmark/benchmark_base.py
@@ -477,7 +477,6 @@ def compute_results(self, case_keys=None, verbose=False, **result_params):
         if case_keys is None:
             case_keys = list(self.cases.keys())
 
-        job_keys = []
         for key in case_keys:
             if verbose:
                 print("### Compute result", key, "###")
@@ -543,7 +542,7 @@ def compute_metrics(self, case_keys=None, metric_names=["snr", "firing_rate"], f
                 qm_ext = sorting_analyzer.compute("quality_metrics", metric_names=metric_names, **job_kwargs)
 
             # TODO remove this metics CSV file!!!!
-            metrics = qm_ext.get_data()
+            # _ = qm_ext.get_data()
             # metrics.to_csv(filename, sep="\t", index=True)
 
     def get_metrics(self, key):
diff --git a/src/spikeinterface/benchmark/benchmark_motion_estimation.py b/src/spikeinterface/benchmark/benchmark_motion_estimation.py
index b864b34bba..d42be84a88 100644
--- a/src/spikeinterface/benchmark/benchmark_motion_estimation.py
+++ b/src/spikeinterface/benchmark/benchmark_motion_estimation.py
@@ -351,7 +351,7 @@ def plot_summary_errors(self, case_keys=None, show_legend=True, figsize=(15, 5))
                         parts[k].set_color(c)
             axes[2].plot(motion.spatial_bins_um, depth_error, label=label, color=c)
 
-        ax0 = ax = axes[0]
+        ax = axes[0]
         ax.set_xlabel("Time [s]")
         ax.set_ylabel("Error [μm]")
         if show_legend:
diff --git a/src/spikeinterface/benchmark/benchmark_peak_detection.py b/src/spikeinterface/benchmark/benchmark_peak_detection.py
index 4c84304a63..671080b0a7 100644
--- a/src/spikeinterface/benchmark/benchmark_peak_detection.py
+++ b/src/spikeinterface/benchmark/benchmark_peak_detection.py
@@ -17,7 +17,6 @@
 
 
 class PeakDetectionBenchmark(Benchmark):
-
     def __init__(self, recording, gt_sorting, params, gt_peaks, exhaustive_gt=True, delta_t_ms=0.2):
         self.recording = recording
         self.gt_sorting = gt_sorting
@@ -233,9 +232,7 @@ def plot_mean_deltas(self, case_keys=None, figsize=(15, 5), ax=None):
         import matplotlib.pyplot as plt
 
         if ax is None:
-            fig, ax = plt.subplots(1, figsize=figsize)
-        else:
-            fig = ax.get_figure()
+            _, ax = plt.subplots(1, figsize=figsize)
 
         results = {}
         labels = []
@@ -283,7 +280,6 @@ def plot_template_similarities(self, case_keys=None, metric="l2", figsize=(15, 5
             fig = ax.get_figure()
 
         for key in case_keys:
-
             import sklearn.metrics
 
             gt_templates = self.get_result(key)["gt_templates"]
@@ -292,7 +288,6 @@ def plot_template_similarities(self, case_keys=None, metric="l2", figsize=(15, 5
             distances = np.zeros(num_templates)
 
             for i in range(num_templates):
-
                 a = gt_templates[i].flatten()
                 b = found_templates[i].flatten()
 
diff --git a/src/spikeinterface/benchmark/benchmark_peak_localization.py b/src/spikeinterface/benchmark/benchmark_peak_localization.py
index 054ef3f38d..199df36930 100644
--- a/src/spikeinterface/benchmark/benchmark_peak_localization.py
+++ b/src/spikeinterface/benchmark/benchmark_peak_localization.py
@@ -91,14 +91,12 @@ def plot_comparison_positions(self, case_keys=None):
             metrics = analyzer.get_extension("quality_metrics").get_data()
             snrs = metrics["snr"].values
             result = self.get_result(key)
-            norms = np.linalg.norm(result["templates"].templates_array, axis=(1, 2))
 
             coordinates = self.benchmarks[key].gt_positions[:, :2].copy()
             coordinates[:, 0] -= coordinates[:, 0].mean()
             coordinates[:, 1] -= coordinates[:, 1].mean()
             distances_to_center = np.linalg.norm(coordinates, axis=1)
             zdx = np.argsort(distances_to_center)
-            idx = np.argsort(norms)
 
             wdx = np.argsort(snrs)
 
@@ -252,14 +250,12 @@ def plot_comparison_positions(self, case_keys=None):
             metrics = analyzer.get_extension("quality_metrics").get_data()
             snrs = metrics["snr"].values
             result = self.get_result(key)
-            norms = np.linalg.norm(result["templates"].templates_array, axis=(1, 2))
 
             coordinates = self.benchmarks[key].gt_positions[:, :2].copy()
             coordinates[:, 0] -= coordinates[:, 0].mean()
             coordinates[:, 1] -= coordinates[:, 1].mean()
             distances_to_center = np.linalg.norm(coordinates, axis=1)
             zdx = np.argsort(distances_to_center)
-            idx = np.argsort(norms)
 
             wdx = np.argsort(snrs)
 

From 747f5ef2cb5183a3f72e62ba12dd0c03378fe68a Mon Sep 17 00:00:00 2001
From: Alessio Buccino <alejoe9187@gmail.com>
Date: Mon, 9 Nov 2026 15:08:10 +0100
Subject: [PATCH 12/30] fix: widgets ruff checks

---
 src/spikeinterface/widgets/base.py | 9 +++++----
 1 file changed, 5 insertions(+), 4 deletions(-)

diff --git a/src/spikeinterface/widgets/base.py b/src/spikeinterface/widgets/base.py
index 646e46a7a7..e6d75222e5 100644
--- a/src/spikeinterface/widgets/base.py
+++ b/src/spikeinterface/widgets/base.py
@@ -1,10 +1,11 @@
-global default_backend_
-default_backend_ = "matplotlib"
-
 from spikeinterface.core import SortingAnalyzer, BaseSorting
 from spikeinterface.core.waveforms_extractor_backwards_compatibility import MockWaveformExtractor
 
 
+global default_backend_
+default_backend_ = "matplotlib"
+
+
 def get_default_plotter_backend():
     """Return the default backend for spikeinterface widgets.
     The default backend is "matplotlib" at init.
@@ -105,7 +106,7 @@ def check_backend(self, backend):
         if backend is None:
             backend = get_default_plotter_backend()
         assert backend in self.get_possible_backends(), (
-            f"{backend} backend not available! Available backends are: " f"{self.get_possible_backends()}"
+            f"{backend} backend not available! Available backends are: {self.get_possible_backends()}"
         )
         return backend
 

From 64df25f218c4ca00ff68284391798178c86d1fea Mon Sep 17 00:00:00 2001
From: Alessio Buccino <alejoe9187@gmail.com>
Date: Mon, 9 Nov 2026 15:09:12 +0100
Subject: [PATCH 13/30] fix: curation ruff checks

---
 src/spikeinterface/curation/remove_duplicated_spikes.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/spikeinterface/curation/remove_duplicated_spikes.py b/src/spikeinterface/curation/remove_duplicated_spikes.py
index f8716ba54a..e494e43ddb 100644
--- a/src/spikeinterface/curation/remove_duplicated_spikes.py
+++ b/src/spikeinterface/curation/remove_duplicated_spikes.py
@@ -80,9 +80,9 @@ def get_unit_spike_train(self, unit_id, start_frame: int | None = None, end_fram
 
         spike_train = np.delete(spike_train, self._duplicated_spikes[unit_id])
 
-        if start_frame == None:
+        if start_frame is None:
             start_frame = 0
-        if end_frame == None:
+        if end_frame is None:
             end_frame = spike_train[-1] if len(spike_train) > 0 else 0
 
         start = np.searchsorted(spike_train, start_frame, side="left")

From 8cd4a5ec01d536ed49460856fdcb2fe5dabbac2f Mon Sep 17 00:00:00 2001
From: Alessio Buccino <alejoe9187@gmail.com>
Date: Mon, 9 Nov 2026 15:09:57 +0100
Subject: [PATCH 14/30] fix: comparison ruff checks

---
 src/spikeinterface/comparison/basecomparison.py  | 2 +-
 src/spikeinterface/comparison/comparisontools.py | 1 -
 2 files changed, 1 insertion(+), 2 deletions(-)

diff --git a/src/spikeinterface/comparison/basecomparison.py b/src/spikeinterface/comparison/basecomparison.py
index d532f59a2d..4202d31335 100644
--- a/src/spikeinterface/comparison/basecomparison.py
+++ b/src/spikeinterface/comparison/basecomparison.py
@@ -186,7 +186,7 @@ def _clean_graph(self):
                         if edge_to_remove[0] in nodes_duplicate:
                             node_to_remove = edge_to_remove[0]
                         else:
-                            node_to_removed = edge_to_remove[1]
+                            node_to_remove = edge_to_remove[1]
                         if node_to_remove in sg.nodes:
                             sg.remove_node(node_to_remove)
                             print(f"Removed node: {node_to_remove}")
diff --git a/src/spikeinterface/comparison/comparisontools.py b/src/spikeinterface/comparison/comparisontools.py
index 90e807f45d..356976e47c 100644
--- a/src/spikeinterface/comparison/comparisontools.py
+++ b/src/spikeinterface/comparison/comparisontools.py
@@ -911,7 +911,6 @@ def make_matching_events(times1, times2, delta):
 
     mask2 = membership_sorted[inds] == 2
     inds2 = inds[mask2]
-    n2 = np.sum(mask2)
     matching_event[n1:]["index1"] = spike_index_sorted[inds2 + 1]
     matching_event[n1:]["index2"] = spike_index_sorted[inds2]
     matching_event[n1:]["delta_frame"] = times_concat_sorted[inds2] - times_concat_sorted[inds2 + 1]

From c15ac9935e8b4e77ef0cc7dbf8bca9164f6cf8ed Mon Sep 17 00:00:00 2001
From: Alessio Buccino <alejoe9187@gmail.com>
Date: Mon, 9 Nov 2026 15:17:30 +0100
Subject: [PATCH 15/30] fix: sortingcomponents ruff checks

---
 .../clustering/cleaning_tools.py              |  2 --
 .../clustering/graph_clustering.py            |  1 -
 .../clustering/itersplit_tools.py             |  1 -
 .../clustering/merging_tools.py               |  7 +----
 .../clustering/random_projections.py          | 15 +++++-----
 .../sortingcomponents/matching/circus.py      |  5 ++--
 .../sortingcomponents/matching/main.py        |  2 +-
 .../sortingcomponents/matching/nearest.py     | 12 --------
 .../sortingcomponents/matching/tdc_peeler.py  |  4 ---
 .../peak_detection/locally_exclusive.py       | 30 +++++++++++--------
 .../peak_detection/matched_filtering.py       |  8 +++--
 11 files changed, 36 insertions(+), 51 deletions(-)

diff --git a/src/spikeinterface/sortingcomponents/clustering/cleaning_tools.py b/src/spikeinterface/sortingcomponents/clustering/cleaning_tools.py
index 589cc936e6..6825b68a72 100644
--- a/src/spikeinterface/sortingcomponents/clustering/cleaning_tools.py
+++ b/src/spikeinterface/sortingcomponents/clustering/cleaning_tools.py
@@ -120,7 +120,6 @@ def _split_waveforms_nested(
         # hdbscan on pca
         clustering = hdbscan.hdbscan(local_feature, **hdbscan_params)
         active_labels_with_noise = clustering[0]
-        cluster_probability = clustering[2]
         (persistent_clusters,) = np.nonzero(clustering[2] > probability_thr)
         active_labels_with_noise[~np.isin(active_labels_with_noise, persistent_clusters)] = -1
 
@@ -500,7 +499,6 @@ def remove_duplicates(
         idx = np.argsort(channel_norms)[::-1]
         explained_norms = np.cumsum(channel_norms[idx] / total_norm)
         channel = np.searchsorted(explained_norms, sparsify_threshold)
-        active_channels = np.sort(idx[:channel])
         templates[t, :, idx[channel:]] = 0
 
     from sklearn.metrics.pairwise import cosine_similarity
diff --git a/src/spikeinterface/sortingcomponents/clustering/graph_clustering.py b/src/spikeinterface/sortingcomponents/clustering/graph_clustering.py
index 92472b03d7..197f5674ae 100644
--- a/src/spikeinterface/sortingcomponents/clustering/graph_clustering.py
+++ b/src/spikeinterface/sortingcomponents/clustering/graph_clustering.py
@@ -70,7 +70,6 @@ def main_function(cls, recording, peaks, params, job_kwargs=dict()):
         radius_um = peaks_svd["radius_um"]
         motion = peaks_svd["motion"]
         seed = params["seed"]
-        verbose = params["verbose"]
         clustering_kwargs = params["clusterer"].copy()
         graph_kwargs = params["graph_kwargs"].copy()
 
diff --git a/src/spikeinterface/sortingcomponents/clustering/itersplit_tools.py b/src/spikeinterface/sortingcomponents/clustering/itersplit_tools.py
index a4d2a77a3b..c2c56cf214 100644
--- a/src/spikeinterface/sortingcomponents/clustering/itersplit_tools.py
+++ b/src/spikeinterface/sortingcomponents/clustering/itersplit_tools.py
@@ -352,7 +352,6 @@ def split(
             if final_features.shape[1] == 1:
                 final_features = np.hstack((final_features, np.zeros_like(final_features)))
 
-            sl = slice(None, None, 100)
             for k in np.unique(possible_labels):
                 mask = possible_labels == k
                 ax = axs[0]
diff --git a/src/spikeinterface/sortingcomponents/clustering/merging_tools.py b/src/spikeinterface/sortingcomponents/clustering/merging_tools.py
index 9cc4bd18a3..1b9194d504 100644
--- a/src/spikeinterface/sortingcomponents/clustering/merging_tools.py
+++ b/src/spikeinterface/sortingcomponents/clustering/merging_tools.py
@@ -7,6 +7,7 @@
 import numpy as np
 
 from spikeinterface.core.job_tools import get_poolexecutor, fix_job_kwargs
+from .tools import aggregate_sparse_features, FeaturesLoader
 
 numba_spec = importlib.util.find_spec("numba")
 networkx_spec = importlib.util.find_spec("networkx")
@@ -20,7 +21,6 @@
 else:
     pass
 
-from .tools import aggregate_sparse_features, FeaturesLoader
 
 DEBUG = False
 
@@ -45,10 +45,6 @@ def merge_peak_labels_from_features(
 
     job_kwargs = fix_job_kwargs(job_kwargs)
 
-    features = FeaturesLoader.from_dict_or_folder(features_dict_or_folder)
-    # sparse_wfs = features["sparse_wfs"]
-    # sparse_mask = features["sparse_mask"]
-
     labels_set, pair_mask, pair_shift, pair_values = find_merge_pairs_from_features(
         peaks,
         peak_labels,
@@ -443,7 +439,6 @@ def merge(
             is_merge = l0 >= l1
             merge_value = l0 - l1
         elif criteria == "distrib_overlap":
-
             lim0 = min(np.min(feat0), np.min(feat1))
             lim1 = max(np.max(feat0), np.max(feat1))
             bin_size = (lim1 - lim0) / 200.0
diff --git a/src/spikeinterface/sortingcomponents/clustering/random_projections.py b/src/spikeinterface/sortingcomponents/clustering/random_projections.py
index cd451f4d07..24966fd348 100644
--- a/src/spikeinterface/sortingcomponents/clustering/random_projections.py
+++ b/src/spikeinterface/sortingcomponents/clustering/random_projections.py
@@ -4,13 +4,6 @@
 import importlib
 import numpy as np
 
-hdbscan_spec = importlib.util.find_spec("hdbscan")
-if hdbscan_spec is not None:
-    HAVE_HDBSCAN = True
-    import hdbscan
-else:
-    HAVE_HDBSCAN = False
-
 from spikeinterface.core.base import minimum_spike_dtype
 from spikeinterface.core.core_tools import ms_to_samples
 from spikeinterface.core.waveform_tools import estimate_templates
@@ -25,6 +18,14 @@
 )
 
 
+hdbscan_spec = importlib.util.find_spec("hdbscan")
+if hdbscan_spec is not None:
+    HAVE_HDBSCAN = True
+    import hdbscan
+else:
+    HAVE_HDBSCAN = False
+
+
 class RandomProjectionClustering:
     """
     hdbscan clustering on peak_locations previously done by localize_peaks()
diff --git a/src/spikeinterface/sortingcomponents/matching/circus.py b/src/spikeinterface/sortingcomponents/matching/circus.py
index 28bf9fc840..9e537ca33c 100644
--- a/src/spikeinterface/sortingcomponents/matching/circus.py
+++ b/src/spikeinterface/sortingcomponents/matching/circus.py
@@ -3,6 +3,9 @@
 import numpy as np
 import importlib.util
 
+from .base import BaseTemplateMatching
+
+
 spike_dtype = [
     ("sample_index", "int64"),
     ("channel_index", "int64"),
@@ -23,8 +26,6 @@
 else:
     HAVE_TORCH = False
 
-from .base import BaseTemplateMatching
-
 
 def compress_templates(
     templates_array, approx_rank, remove_mean=False, return_new_templates=True
diff --git a/src/spikeinterface/sortingcomponents/matching/main.py b/src/spikeinterface/sortingcomponents/matching/main.py
index babe76de73..46dae15ad7 100644
--- a/src/spikeinterface/sortingcomponents/matching/main.py
+++ b/src/spikeinterface/sortingcomponents/matching/main.py
@@ -1,6 +1,6 @@
 import numpy as np
 
-from .method_list import *
+from .method_list import matching_methods
 
 from spikeinterface.core.node_pipeline import run_node_pipeline
 
diff --git a/src/spikeinterface/sortingcomponents/matching/nearest.py b/src/spikeinterface/sortingcomponents/matching/nearest.py
index e67eefe916..5221f66e81 100644
--- a/src/spikeinterface/sortingcomponents/matching/nearest.py
+++ b/src/spikeinterface/sortingcomponents/matching/nearest.py
@@ -72,18 +72,6 @@ def __init__(
             self.neighborhood_mask = np.ones((num_channels, num_templates), dtype=bool)
 
         if support_radius_um is not None:
-            if not templates.are_templates_sparse():
-                from spikeinterface.core.sparsity import compute_sparsity
-
-                sparsity = compute_sparsity(
-                    templates,
-                    method="radius",
-                    radius_um=sparsity_radius_um,
-                    peak_sign=self.peak_sign,
-                )
-            else:
-                sparsity = templates.sparsity
-
             channel_locations = recording.get_channel_locations()
             channel_distances = np.linalg.norm(channel_locations[:, None] - channel_locations[np.newaxis, :], axis=2)
             self.sparsity_support_mask = channel_distances <= self.support_radius_um
diff --git a/src/spikeinterface/sortingcomponents/matching/tdc_peeler.py b/src/spikeinterface/sortingcomponents/matching/tdc_peeler.py
index cff99020fd..3101af0485 100644
--- a/src/spikeinterface/sortingcomponents/matching/tdc_peeler.py
+++ b/src/spikeinterface/sortingcomponents/matching/tdc_peeler.py
@@ -418,7 +418,6 @@ def compute_matching(self, traces, start_frame, end_frame, segment_index):
 
         all_spikes = []
         for start, stop, channel_motions in loop:
-
             local_residuals = residuals[start:stop]
 
             spikes_in_time_bin = []
@@ -782,7 +781,6 @@ def get_neighbors_spikes(sample_inds, chan_inds, delta_sample, near_chan_mask):
 
     neighbors_spikes_inds = []
     for i in range(sample_inds.size):
-
         inds = np.flatnonzero(np.abs(sample_inds - sample_inds[i]) < delta_sample)
         neighb = []
         for ind in inds:
@@ -817,7 +815,6 @@ def fit_one_amplitude_with_neighbors(
         amplitude = np.sum(template.flatten() * wf.flatten()) / template_norms[cluster_index]
 
     else:
-
         lim0 = min(start, np.min(neighbors_spikes["sample_index"]) - nbefore)
         lim1 = max(stop, np.max(neighbors_spikes["sample_index"]) + nafter)
 
@@ -833,7 +830,6 @@ def fit_one_amplitude_with_neighbors(
 
         num_spikes_to_fit = 1 + np.sum(mask_not_fitted)
         x = np.zeros((lim1 - lim0, num_chans, num_spikes_to_fit), dtype="float32")
-        wanted_channel_mask = chan_sparsity_mask
         construct_prediction_sparse(
             np.array([local_spike]),
             x[:, :, 0],
diff --git a/src/spikeinterface/sortingcomponents/peak_detection/locally_exclusive.py b/src/spikeinterface/sortingcomponents/peak_detection/locally_exclusive.py
index bafb526a8c..d25007c02c 100644
--- a/src/spikeinterface/sortingcomponents/peak_detection/locally_exclusive.py
+++ b/src/spikeinterface/sortingcomponents/peak_detection/locally_exclusive.py
@@ -1,18 +1,18 @@
 import numpy as np
 import importlib.util
 
+from spikeinterface.core.node_pipeline import (
+    PeakDetector,
+)
+from spikeinterface.core.recording_tools import get_channel_distances
+from .by_channel import ByChannelTorchPeakDetector, ByChannelPeakDetector
+
 numba_spec = importlib.util.find_spec("numba")
 if numba_spec is not None:
     HAVE_NUMBA = True
 else:
     HAVE_NUMBA = False
 
-from spikeinterface.core.node_pipeline import (
-    PeakDetector,
-)
-from spikeinterface.core.recording_tools import get_channel_distances
-from .by_channel import ByChannelTorchPeakDetector
-
 torch_spec = importlib.util.find_spec("torch")
 if torch_spec is not None:
     torch_nn_functional_spec = importlib.util.find_spec("torch.nn")
@@ -29,8 +29,6 @@
 else:
     HAVE_PYOPENCL = False
 
-from .by_channel import ByChannelPeakDetector
-
 
 class LocallyExclusivePeakDetector(PeakDetector):
     """Detect peaks using the "locally exclusive" method."""
@@ -42,10 +40,13 @@ class LocallyExclusivePeakDetector(PeakDetector):
 
     # this is because numba
     need_first_call_before_pipeline = True
-    params_doc = ByChannelPeakDetector.params_doc + """
+    params_doc = (
+        ByChannelPeakDetector.params_doc
+        + """
     radius_um: float
         The radius to use to select neighbour channels for locally exclusive detection.
     """
+    )
 
     def __init__(
         self,
@@ -148,7 +149,6 @@ def detect_peaks_numba_locally_exclusive_on_chunk(
         keep_peak = np.ones(npeaks, dtype="bool")
         next_start = 0
         for i in range(npeaks):
-
             if (samples_inds[i] < exclude_sweep_size + 1) or (
                 samples_inds[i] >= (num_samples - exclude_sweep_size - 1)
             ):
@@ -195,10 +195,13 @@ class LocallyExclusiveTorchPeakDetector(ByChannelTorchPeakDetector):
     engine = "torch"
     need_noise_levels = True
     preferred_mp_context = "spawn"
-    params_doc = ByChannelPeakDetector.params_doc + """
+    params_doc = (
+        ByChannelPeakDetector.params_doc
+        + """
     radius_um: float
         The radius to use to select neighbour channels for locally exclusive detection.
     """
+    )
 
     def __init__(
         self,
@@ -265,10 +268,13 @@ class LocallyExclusiveOpenCLPeakDetector(LocallyExclusivePeakDetector):
     engine = "opencl"
     preferred_mp_context = None
     need_noise_levels = True
-    params_doc = LocallyExclusiveTorchPeakDetector.params_doc + """
+    params_doc = (
+        LocallyExclusiveTorchPeakDetector.params_doc
+        + """
     opencl_context_kwargs: None or dict
        kwargs to create the opencl context
     """
+    )
 
     def __init__(
         self,
diff --git a/src/spikeinterface/sortingcomponents/peak_detection/matched_filtering.py b/src/spikeinterface/sortingcomponents/peak_detection/matched_filtering.py
index a7ce981ed3..13849cf700 100644
--- a/src/spikeinterface/sortingcomponents/peak_detection/matched_filtering.py
+++ b/src/spikeinterface/sortingcomponents/peak_detection/matched_filtering.py
@@ -8,6 +8,7 @@
 from spikeinterface.core.node_pipeline import PeakDetector
 from spikeinterface.core.recording_tools import get_channel_distances, get_random_data_chunks
 from spikeinterface.postprocessing.localization_tools import get_convolution_weights
+from .by_channel import ByChannelPeakDetector
 
 numba_spec = importlib.util.find_spec("numba")
 if numba_spec is not None:
@@ -15,8 +16,6 @@
 else:
     HAVE_NUMBA = False
 
-from .by_channel import ByChannelPeakDetector
-
 
 class MatchedFilteringPeakDetector(PeakDetector):
     """Detect peaks using the 'matched_filtering' method."""
@@ -25,7 +24,9 @@ class MatchedFilteringPeakDetector(PeakDetector):
     engine = "numba"
     need_noise_levels = False
     preferred_mp_context = None
-    params_doc = ByChannelPeakDetector.params_doc + """
+    params_doc = (
+        ByChannelPeakDetector.params_doc
+        + """
     radius_um : float
         The radius to use to select neighbour channels for locally exclusive detection.
     prototype : array
@@ -37,6 +38,7 @@ class MatchedFilteringPeakDetector(PeakDetector):
         in order to know how to estimate the positions. One argument is mode that could
         be either gaussian_2d (KS like) or exponential_3d (default)
     """
+    )
 
     def __init__(
         self,

From b53cf58e782fc70289e29c5f66cb4d4a1d3b907f Mon Sep 17 00:00:00 2001
From: Alessio Buccino <alejoe9187@gmail.com>
Date: Mon, 9 Nov 2026 15:20:11 +0100
Subject: [PATCH 16/30] lint: all ruff fixed

---
 installation_tips/check_your_install.py | 2 +-
 pyproject.toml                          | 3 ++-
 2 files changed, 3 insertions(+), 2 deletions(-)

diff --git a/installation_tips/check_your_install.py b/installation_tips/check_your_install.py
index cdaa702e8d..1778f6bdac 100644
--- a/installation_tips/check_your_install.py
+++ b/installation_tips/check_your_install.py
@@ -69,7 +69,7 @@ def open_sigui():
     folder = f"./analyzer_with_{sorter_name}"
     analyzer = si.load_sorting_analyzer(folder)
 
-    win = run_mainwindow(analyzer, start_app=True)
+    _ = run_mainwindow(analyzer, start_app=True)
 
 
 def _clean():
diff --git a/pyproject.toml b/pyproject.toml
index 170fa857ef..6224c5411c 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -55,10 +55,11 @@ exclude = ["spikeinterface.*.tests"]
 line-length = 120
 [tool.ruff.lint]
 select = ['E4', 'E7', 'E9', 'F']
-exclude = ["**/tests/**", "**/test_*.py", "**/conftest.py"]
+exclude = ["**/tests/**", "**/test_*.py", "**/conftest.py", "examples/**", "doc/conf.py"]
 ignore = ['E741', 'E731', 'F821']
 [tool.ruff.lint.per-file-ignores]
 "**/__init__.py" = ['F401', 'F403']
+"src/spikeinterface/full.py" = ['F403']
 "src/spikeinterface/core/testing_tools.py" = ['E402', 'F403']
 
 [project.urls]

From 3477781100deaa0556ed4f3412e212c1e3283be8 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Mon, 9 Nov 2026 14:20:30 +0000
Subject: [PATCH 17/30] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 .../benchmark_motion_interpolation.py         |  2 -
 .../tests/test_benchmark_clustering.py        |  1 -
 .../tests/test_benchmark_peak_detection.py    |  1 -
 .../comparison/tests/test_comparisontools.py  |  5 +-
 src/spikeinterface/core/baseevent.py          | 12 ++--
 src/spikeinterface/core/channelslice.py       | 26 ++++-----
 .../core/frameslicerecording.py               |  6 +-
 src/spikeinterface/core/frameslicesorting.py  | 12 ++--
 src/spikeinterface/core/generate.py           | 12 ++--
 src/spikeinterface/core/globals.py            |  2 +-
 src/spikeinterface/core/job_tools.py          |  2 +-
 src/spikeinterface/core/numpyextractors.py    |  6 +-
 src/spikeinterface/core/operatorrecordings.py | 18 +++---
 src/spikeinterface/core/segmentutils.py       | 26 ++++-----
 src/spikeinterface/core/template.py           | 12 ++--
 src/spikeinterface/core/template_tools.py     |  6 +-
 src/spikeinterface/core/testing_tools.py      |  2 +-
 .../test_channelsaggregationrecording.py      |  1 -
 .../core/tests/test_generate.py               | 12 ++--
 .../core/tests/test_time_handling.py          |  7 ---
 .../tests/test_unitsaggregationsorting.py     |  1 -
 ...forms_extractor_backwards_compatibility.py |  1 -
 src/spikeinterface/core/zarr_tools.py         |  6 +-
 .../curation/bombcell_curation.py             |  6 +-
 .../curation/curation_format.py               | 12 ++--
 .../curation/mergeunitssorting.py             |  2 +-
 .../curation/remove_excess_spikes.py          |  6 +-
 .../curation/splitunitsorting.py              | 20 +++----
 .../curation/tests/test_curation_format.py    |  1 -
 .../curation/tests/test_curationsorting.py    | 12 ++--
 .../cellexplorersortingextractor.py           |  6 +-
 .../extractors/iblextractors.py               |  8 +--
 .../extractors/matlabhelpers.py               |  3 +-
 .../extractors/mcsh5extractors.py             |  8 +--
 .../extractors/neoextractors/intan.py         |  2 +-
 .../neoextractors/neobaseextractor.py         | 16 +++---
 .../extractors/neoextractors/neuroscope.py    | 33 ++++++-----
 .../extractors/shybridextractors.py           |  4 +-
 src/spikeinterface/generation/drift_tools.py  | 55 +++++++++----------
 src/spikeinterface/generation/hybrid_tools.py | 24 ++++----
 src/spikeinterface/generation/noise_tools.py  |  6 +-
 .../generation/template_database.py           | 12 ++--
 .../metrics/quality/misc_metrics.py           |  9 +--
 .../tests/test_quality_metric_calculator.py   |  1 -
 .../metrics/template/template_metrics.py      |  1 -
 .../postprocessing/spike_amplitudes.py        |  6 +-
 .../tests/test_amplitude_scalings.py          |  1 -
 .../postprocessing/tests/test_correlograms.py | 12 ++--
 .../tests/test_extension_merges.py            |  2 -
 .../postprocessing/tests/test_isi.py          |  1 -
 .../tests/test_principal_component.py         |  3 -
 .../tests/test_spike_amplitudes.py            |  1 -
 .../tests/test_spike_locations.py             |  1 -
 .../tests/test_template_similarity.py         |  2 -
 .../tests/test_unit_locations.py              |  2 -
 .../tests/test_valid_unit_periods.py          |  1 -
 .../preprocessing/average_across_direction.py |  1 -
 .../preprocessing/common_reference.py         | 12 ++--
 .../deepinterpolation/deepinterpolation.py    | 18 +++---
 .../deepinterpolation/generators.py           | 12 ++--
 .../preprocessing/detect_artifacts.py         |  6 +-
 .../preprocessing/directional_derivative.py   |  1 -
 .../preprocessing/highpass_spatial_filter.py  | 12 ++--
 .../preprocessing/phase_shift.py              |  6 +-
 src/spikeinterface/preprocessing/rectify.py   |  1 -
 .../preprocessing/remove_artifacts.py         | 12 ++--
 .../tests/test_detect_bad_channels.py         | 12 ++--
 src/spikeinterface/preprocessing/whiten.py    |  6 +-
 .../preprocessing/zero_channel_pad.py         |  9 ++-
 src/spikeinterface/sorters/container_tools.py |  5 +-
 .../sorters/external/herdingspikes.py         |  6 +-
 .../sorters/external/kilosort.py              |  6 +-
 .../sorters/external/kilosort2.py             |  6 +-
 .../sorters/external/kilosort2_5.py           |  6 +-
 .../sorters/external/kilosort3.py             |  6 +-
 .../sorters/external/kilosortbase.py          |  6 +-
 .../sorters/external/mountainsort4.py         |  4 +-
 .../sorters/external/tridesclous.py           |  2 +-
 src/spikeinterface/sorters/launcher.py        |  2 +-
 .../sorters/tests/test_launcher.py            |  1 -
 .../clustering/graph_tools.py                 |  3 -
 .../clustering/isosplit_isocut.py             |  3 -
 .../clustering/iterative_isosplit.py          |  1 -
 .../sortingcomponents/matching/base.py        |  6 +-
 .../sortingcomponents/matching/wobble.py      |  6 +-
 .../sortingcomponents/motion/dredge.py        |  2 -
 .../motion/motion_interpolation.py            |  3 +-
 .../peak_localization/base.py                 |  1 -
 .../sortingcomponents/peak_selection.py       |  2 +-
 .../waveforms/waveform_thresholder.py         |  2 +-
 src/spikeinterface/widgets/motion.py          | 12 ++--
 91 files changed, 301 insertions(+), 356 deletions(-)

diff --git a/src/spikeinterface/benchmark/benchmark_motion_interpolation.py b/src/spikeinterface/benchmark/benchmark_motion_interpolation.py
index c5e0143961..3e96013e7b 100644
--- a/src/spikeinterface/benchmark/benchmark_motion_interpolation.py
+++ b/src/spikeinterface/benchmark/benchmark_motion_interpolation.py
@@ -95,7 +95,6 @@ def compute_result(self, exhaustive_gt=True, merging_score=0.2):
 
 
 class MotionInterpolationStudy(BenchmarkStudy):
-
     benchmark_class = MotionInterpolationBenchmark
 
     def create_benchmark(self, key):
@@ -133,7 +132,6 @@ def plot_sorting_accuracy(
 
         if mode == "ordered_accuracy":
             if ax is None:
-
                 fig, ax = plt.subplots(figsize=figsize)
             else:
                 fig = ax.figure
diff --git a/src/spikeinterface/benchmark/tests/test_benchmark_clustering.py b/src/spikeinterface/benchmark/tests/test_benchmark_clustering.py
index 971c410807..01ba792fc7 100644
--- a/src/spikeinterface/benchmark/tests/test_benchmark_clustering.py
+++ b/src/spikeinterface/benchmark/tests/test_benchmark_clustering.py
@@ -26,7 +26,6 @@ def test_benchmark_clustering(create_cache_folder):
 
     peaks = {}
     for dataset, gt_analyzer in datasets.items():
-
         # recording, gt_sorting = datasets[dataset]
 
         # sorting_analyzer = create_sorting_analyzer(gt_sorting, recording, format="memory", sparse=False)
diff --git a/src/spikeinterface/benchmark/tests/test_benchmark_peak_detection.py b/src/spikeinterface/benchmark/tests/test_benchmark_peak_detection.py
index 462ede4375..95f48e9214 100644
--- a/src/spikeinterface/benchmark/tests/test_benchmark_peak_detection.py
+++ b/src/spikeinterface/benchmark/tests/test_benchmark_peak_detection.py
@@ -23,7 +23,6 @@ def test_benchmark_peak_detection(create_cache_folder):
 
     peaks = {}
     for dataset in datasets.keys():
-
         recording, gt_sorting = datasets[dataset]
 
         sorting_analyzer = create_sorting_analyzer(gt_sorting, recording, format="memory", sparse=False, **job_kwargs)
diff --git a/src/spikeinterface/comparison/tests/test_comparisontools.py b/src/spikeinterface/comparison/tests/test_comparisontools.py
index 43288415d1..a32bef49ae 100644
--- a/src/spikeinterface/comparison/tests/test_comparisontools.py
+++ b/src/spikeinterface/comparison/tests/test_comparisontools.py
@@ -80,7 +80,10 @@ def test_make_match_count_matrix_with_mismatched_sortings():
     delta_frames = 10
 
     sorting1, sorting2 = make_sorting(
-        [100, 200, 300, 400], [0, 0, 1, 0], [500, 600, 700, 800], [0, 0, 1, 0]  # Completely different spike times
+        [100, 200, 300, 400],
+        [0, 0, 1, 0],
+        [500, 600, 700, 800],
+        [0, 0, 1, 0],  # Completely different spike times
     )
 
     match_event_count = make_match_count_matrix(sorting1, sorting2, delta_frames)
diff --git a/src/spikeinterface/core/baseevent.py b/src/spikeinterface/core/baseevent.py
index 2e73774c04..78e542705f 100644
--- a/src/spikeinterface/core/baseevent.py
+++ b/src/spikeinterface/core/baseevent.py
@@ -26,16 +26,16 @@ def __init__(self, channel_ids, structured_dtype):
         if not isinstance(structured_dtype, dict):
             structured_dtype = {chan_id: structured_dtype for chan_id in channel_ids}
         else:
-            assert all(
-                chan_id in structured_dtype for chan_id in channel_ids
-            ), "Missing some channel_ids from structured_dtype dict keys"
+            assert all(chan_id in structured_dtype for chan_id in channel_ids), (
+                "Missing some channel_ids from structured_dtype dict keys"
+            )
 
         # check dtype fields (if present)
         for _, dtype in structured_dtype.items():
             if dtype.names is not None:
-                assert (
-                    "time" in dtype.names or "timestamp" in dtype.names
-                ), "The event dtype need to have the 'time' or 'timestamp' field"
+                assert "time" in dtype.names or "timestamp" in dtype.names, (
+                    "The event dtype need to have the 'time' or 'timestamp' field"
+                )
 
         self.structured_dtype = structured_dtype
 
diff --git a/src/spikeinterface/core/channelslice.py b/src/spikeinterface/core/channelslice.py
index 13cac8db8d..e1af49a3c2 100644
--- a/src/spikeinterface/core/channelslice.py
+++ b/src/spikeinterface/core/channelslice.py
@@ -17,9 +17,9 @@ def __init__(self, recording, channel_ids=None, renamed_channel_ids=None):
         if renamed_channel_ids is None:
             renamed_channel_ids = channel_ids
         else:
-            assert len(renamed_channel_ids) == len(
-                np.unique(renamed_channel_ids)
-            ), "renamed_channel_ids must be unique!"
+            assert len(renamed_channel_ids) == len(np.unique(renamed_channel_ids)), (
+                "renamed_channel_ids must be unique!"
+            )
 
         self._channel_ids = np.asarray(channel_ids)
         self._renamed_channel_ids = np.asarray(renamed_channel_ids)
@@ -29,16 +29,16 @@ def __init__(self, recording, channel_ids=None, renamed_channel_ids=None):
         # some checks
         # We use lists to compare numpy scalar types as their python versions (e.g. int vs int64())
         channel_ids_not_in_parents = [id for id in self._channel_ids.tolist() if id not in parents_chan_ids.tolist()]
-        assert (
-            len(channel_ids_not_in_parents) == 0
-        ), f"ChannelSliceRecording : channel ids {channel_ids_not_in_parents} are not all in parent ids {parents_chan_ids}"
-
-        assert len(self._channel_ids) == len(
-            self._renamed_channel_ids
-        ), "ChannelSliceRecording: renamed channel_ids must be the same size"
-        assert (
-            self._channel_ids.size == np.unique(self._channel_ids).size
-        ), "ChannelSliceRecording : channel_ids are not unique"
+        assert len(channel_ids_not_in_parents) == 0, (
+            f"ChannelSliceRecording : channel ids {channel_ids_not_in_parents} are not all in parent ids {parents_chan_ids}"
+        )
+
+        assert len(self._channel_ids) == len(self._renamed_channel_ids), (
+            "ChannelSliceRecording: renamed channel_ids must be the same size"
+        )
+        assert self._channel_ids.size == np.unique(self._channel_ids).size, (
+            "ChannelSliceRecording : channel_ids are not unique"
+        )
 
         sampling_frequency = recording.get_sampling_frequency()
 
diff --git a/src/spikeinterface/core/frameslicerecording.py b/src/spikeinterface/core/frameslicerecording.py
index bc7913e505..6bb606f5ad 100644
--- a/src/spikeinterface/core/frameslicerecording.py
+++ b/src/spikeinterface/core/frameslicerecording.py
@@ -34,9 +34,9 @@ def __init__(self, recording, start_frame=None, end_frame=None):
 
         assert start_frame >= 0, f"{start_frame=} must be positive"
         assert start_frame < end_frame, f"{start_frame=} must be smaller than 'end_frame' {end_frame=}!"
-        assert (
-            end_frame <= samples_in_recording
-        ), f"{end_frame=} must be smaller than or equal to {samples_in_recording=}"
+        assert end_frame <= samples_in_recording, (
+            f"{end_frame=} must be smaller than or equal to {samples_in_recording=}"
+        )
 
         BaseRecording.__init__(
             self,
diff --git a/src/spikeinterface/core/frameslicesorting.py b/src/spikeinterface/core/frameslicesorting.py
index 2d3195e8a5..6d0a99ad46 100644
--- a/src/spikeinterface/core/frameslicesorting.py
+++ b/src/spikeinterface/core/frameslicesorting.py
@@ -46,12 +46,12 @@ def __init__(self, parent_sorting, start_frame=None, end_frame=None, check_spike
             parent_n_samples = parent_sorting._recording.get_total_samples()
             if end_frame is None:
                 end_frame = parent_n_samples
-            assert (
-                end_frame <= parent_n_samples
-            ), f"`end_frame` should be smaller than the sortings' total number of samples {parent_n_samples}."
-            assert (
-                start_frame <= parent_n_samples
-            ), "`start_frame` should be smaller than the sortings' total number of samples."
+            assert end_frame <= parent_n_samples, (
+                f"`end_frame` should be smaller than the sortings' total number of samples {parent_n_samples}."
+            )
+            assert start_frame <= parent_n_samples, (
+                "`start_frame` should be smaller than the sortings' total number of samples."
+            )
             if check_spike_frames and has_exceeding_spikes(parent_sorting, parent_sorting._recording):
                 raise ValueError(
                     "The sorting object has spikes whose times go beyond the recording duration."
diff --git a/src/spikeinterface/core/generate.py b/src/spikeinterface/core/generate.py
index 4b06058048..b0c3ad4318 100644
--- a/src/spikeinterface/core/generate.py
+++ b/src/spikeinterface/core/generate.py
@@ -372,9 +372,9 @@ def __init__(
         self.added_spikes_from_new_mask = np.zeros(len(spikes), dtype=bool)
 
         if added_spikes_existing_units is not None and len(added_spikes_existing_units) > 0:
-            assert (
-                added_spikes_existing_units.dtype == minimum_spike_dtype
-            ), "added_spikes_existing_units should be a spike vector"
+            assert added_spikes_existing_units.dtype == minimum_spike_dtype, (
+                "added_spikes_existing_units should be a spike vector"
+            )
             spikes = np.concatenate((spikes, added_spikes_existing_units))
             self.added_spikes_from_existing_mask = np.concatenate(
                 (self.added_spikes_from_existing_mask, np.ones(len(added_spikes_existing_units), dtype=bool))
@@ -384,9 +384,9 @@ def __init__(
             )
 
         if added_spikes_new_units is not None and len(added_spikes_new_units) > 0:
-            assert (
-                added_spikes_new_units.dtype == minimum_spike_dtype
-            ), "added_spikes_new_units should be a spike vector"
+            assert added_spikes_new_units.dtype == minimum_spike_dtype, (
+                "added_spikes_new_units should be a spike vector"
+            )
             spikes = np.concatenate((spikes, added_spikes_new_units))
             self.added_spikes_from_existing_mask = np.concatenate(
                 (self.added_spikes_from_existing_mask, np.zeros(len(added_spikes_new_units), dtype=bool))
diff --git a/src/spikeinterface/core/globals.py b/src/spikeinterface/core/globals.py
index 2712f4db3a..8bfa0f7a06 100644
--- a/src/spikeinterface/core/globals.py
+++ b/src/spikeinterface/core/globals.py
@@ -131,7 +131,7 @@ def set_global_job_kwargs(**job_kwargs):
     global global_job_kwargs
     for k in job_kwargs:
         assert k in job_keys, (
-            f"{k} is not a valid job keyword argument. " f"Available keyword arguments are: {list(job_keys)}"
+            f"{k} is not a valid job keyword argument. Available keyword arguments are: {list(job_keys)}"
         )
     global_job_kwargs.update(job_kwargs)
     global global_job_kwargs_set
diff --git a/src/spikeinterface/core/job_tools.py b/src/spikeinterface/core/job_tools.py
index 59af6fd254..1c3a62b9da 100644
--- a/src/spikeinterface/core/job_tools.py
+++ b/src/spikeinterface/core/job_tools.py
@@ -144,7 +144,7 @@ def fix_job_kwargs(runtime_job_kwargs):
 
     for k in runtime_job_kwargs:
         assert k in job_keys, (
-            f"{k} is not a valid job keyword argument. " f"Available keyword arguments are: {list(job_keys)}"
+            f"{k} is not a valid job keyword argument. Available keyword arguments are: {list(job_keys)}"
         )
 
     # remove mutually exclusive from global job kwargs
diff --git a/src/spikeinterface/core/numpyextractors.py b/src/spikeinterface/core/numpyextractors.py
index 1419db82cc..ae2569bee0 100644
--- a/src/spikeinterface/core/numpyextractors.py
+++ b/src/spikeinterface/core/numpyextractors.py
@@ -36,9 +36,9 @@ def __init__(self, traces_list, sampling_frequency, t_starts=None, channel_ids=N
             all_elements_are_list = all(isinstance(e, list) for e in traces_list)
             if all_elements_are_list:
                 traces_list = [np.array(trace) for trace in traces_list]
-            assert all(
-                isinstance(e, np.ndarray) for e in traces_list
-            ), f"must give a list of numpy array but gave {traces_list[0]}"
+            assert all(isinstance(e, np.ndarray) for e in traces_list), (
+                f"must give a list of numpy array but gave {traces_list[0]}"
+            )
         else:
             assert isinstance(traces_list, np.ndarray), "must give a list of numpy array"
             traces_list = [traces_list]
diff --git a/src/spikeinterface/core/operatorrecordings.py b/src/spikeinterface/core/operatorrecordings.py
index 63332bffa1..5e05922c2e 100644
--- a/src/spikeinterface/core/operatorrecordings.py
+++ b/src/spikeinterface/core/operatorrecordings.py
@@ -7,17 +7,17 @@ class BaseOperatorRecording(BaseRecording):
 
     def __init__(self, recording1, recording2, operator: str):
         assert operator in ["add", "subtract"], "Operator must be 'add' or 'subtract'"
-        assert all(
-            isinstance(rec, BaseRecording) for rec in [recording1, recording2]
-        ), "'recordings' must be a list of RecordingExtractor"
+        assert all(isinstance(rec, BaseRecording) for rec in [recording1, recording2]), (
+            "'recordings' must be a list of RecordingExtractor"
+        )
 
         rec_attrs2 = get_rec_attributes(recording2)
-        assert do_recording_attributes_match(
-            recording1, rec_attrs2
-        ), "Both recordings must have the same sampling frequency and channel ids"
-        assert self.are_times_kwargs_compatible(
-            recording1, recording2
-        ), "Both recordings must have the same time parameters"
+        assert do_recording_attributes_match(recording1, rec_attrs2), (
+            "Both recordings must have the same sampling frequency and channel ids"
+        )
+        assert self.are_times_kwargs_compatible(recording1, recording2), (
+            "Both recordings must have the same time parameters"
+        )
 
         channel_ids = recording1.channel_ids
         sampling_frequency = recording1.sampling_frequency
diff --git a/src/spikeinterface/core/segmentutils.py b/src/spikeinterface/core/segmentutils.py
index 90218a55bb..0c57e6f7ba 100644
--- a/src/spikeinterface/core/segmentutils.py
+++ b/src/spikeinterface/core/segmentutils.py
@@ -236,9 +236,9 @@ def __init__(self, recording: BaseRecording, segment_indices: int | list[int]):
             segment_indices = [segment_indices]
 
         num_segments = recording.get_num_segments()
-        assert all(
-            0 <= s < num_segments for s in segment_indices
-        ), f"'segment_index' must be between 0 and {num_segments - 1}"
+        assert all(0 <= s < num_segments for s in segment_indices), (
+            f"'segment_index' must be between 0 and {num_segments - 1}"
+        )
 
         for segment_index in segment_indices:
             rec_seg = recording.segments[segment_index]
@@ -363,12 +363,12 @@ def __init__(self, sorting_list, total_samples_list=None, ignore_times=True, sam
                 "Some concatenated sortings don't have a registered recording. "
                 "Call sorting.register_recording() or set `total_samples_list` kwarg."
             )
-            assert len(total_samples_list) == len(
-                sorting_list
-            ), "`total_samples_list` should have the same number of elements as `sorting_list`"
-            assert all(
-                [s.get_num_segments() == 1 for s in sorting_list]
-            ), "All sortings are expected to be monosegment."
+            assert len(total_samples_list) == len(sorting_list), (
+                "`total_samples_list` should have the same number of elements as `sorting_list`"
+            )
+            assert all([s.get_num_segments() == 1 for s in sorting_list]), (
+                "All sortings are expected to be monosegment."
+            )
             assert ignore_times, (
                 "Concatenating sortings without registered recordings: "
                 "Use ignore_times=True to ignore time information."
@@ -550,7 +550,7 @@ def __init__(self, parent_sorting: BaseSorting, recording_or_recording_list=None
             recording_list = recording_or_recording_list.recording_list
         else:
             raise TypeError(
-                "'recording_or_recording_list' must be a list of recordings, " "ConcatenateSegmentRecording, or None"
+                "'recording_or_recording_list' must be a list of recordings, ConcatenateSegmentRecording, or None"
             )
 
         num_samples = [0]
@@ -593,9 +593,9 @@ def __init__(self, sorting: BaseSorting, segment_indices: int | list[int]):
             segment_indices = [segment_indices]
 
         num_segments = sorting.get_num_segments()
-        assert all(
-            0 <= s < num_segments for s in segment_indices
-        ), f"'segment_index' must be between 0 and {num_segments - 1}"
+        assert all(0 <= s < num_segments for s in segment_indices), (
+            f"'segment_index' must be between 0 and {num_segments - 1}"
+        )
 
         for segment_index in segment_indices:
             sort_seg = sorting.segments[segment_index]
diff --git a/src/spikeinterface/core/template.py b/src/spikeinterface/core/template.py
index a170dd4e02..07462137c4 100644
--- a/src/spikeinterface/core/template.py
+++ b/src/spikeinterface/core/template.py
@@ -101,17 +101,17 @@ def __post_init__(self):
             self.channel_ids = np.arange(self.num_channels)
         else:
             self.channel_ids = np.asarray(self.channel_ids)
-            assert (
-                len(self.channel_ids) == self.num_channels
-            ), f"length of channel ids {len(self.channel_ids)} must be equal to the number of channels {self.num_channels}"
+            assert len(self.channel_ids) == self.num_channels, (
+                f"length of channel ids {len(self.channel_ids)} must be equal to the number of channels {self.num_channels}"
+            )
 
         if self.unit_ids is None:
             self.unit_ids = np.arange(self.num_units)
         else:
             self.unit_ids = np.asarray(self.unit_ids)
-            assert (
-                self.unit_ids.size == self.num_units
-            ), f"length of units ids {self.unit_ids.size} must be equal to the number of units {self.num_units}"
+            assert self.unit_ids.size == self.num_units, (
+                f"length of units ids {self.unit_ids.size} must be equal to the number of units {self.num_units}"
+            )
 
         if self.sparsity_mask is not None:
             self.sparsity = ChannelSparsity(
diff --git a/src/spikeinterface/core/template_tools.py b/src/spikeinterface/core/template_tools.py
index 4b46b4689e..353a654806 100644
--- a/src/spikeinterface/core/template_tools.py
+++ b/src/spikeinterface/core/template_tools.py
@@ -129,9 +129,9 @@ def get_template_amplitudes(
     """
 
     if isinstance(templates_or_sorting_analyzer, SortingAnalyzer):
-        assert (
-            peak_sign is None
-        ), "get_template_amplitudes() peak_sign is now contained in SortingAnalyzer, should be None here"
+        assert peak_sign is None, (
+            "get_template_amplitudes() peak_sign is now contained in SortingAnalyzer, should be None here"
+        )
         if peak_sign is None:
             peak_sign = templates_or_sorting_analyzer.peak_sign
         if peak_mode is None:
diff --git a/src/spikeinterface/core/testing_tools.py b/src/spikeinterface/core/testing_tools.py
index 101dfaea46..82be0f58d6 100644
--- a/src/spikeinterface/core/testing_tools.py
+++ b/src/spikeinterface/core/testing_tools.py
@@ -1,7 +1,7 @@
 import warnings
 
 warnings.warn(
-    "The 'testing_tools' submodule is deprecated. " "Use spikeinterface.core.generate instead",
+    "The 'testing_tools' submodule is deprecated. Use spikeinterface.core.generate instead",
     FutureWarning,
     stacklevel=2,
 )
diff --git a/src/spikeinterface/core/tests/test_channelsaggregationrecording.py b/src/spikeinterface/core/tests/test_channelsaggregationrecording.py
index 4702acca93..a851925724 100644
--- a/src/spikeinterface/core/tests/test_channelsaggregationrecording.py
+++ b/src/spikeinterface/core/tests/test_channelsaggregationrecording.py
@@ -40,7 +40,6 @@ def test_channelsaggregationrecording():
     ]
 
     for recordings_list in recordings_list_possibilities:
-
         # test num channels
         recording_agg = aggregate_channels(recordings_list)
         assert len(recording_agg.get_channel_ids()) == 3 * num_channels
diff --git a/src/spikeinterface/core/tests/test_generate.py b/src/spikeinterface/core/tests/test_generate.py
index 66f84a2914..d8945699a3 100644
--- a/src/spikeinterface/core/tests/test_generate.py
+++ b/src/spikeinterface/core/tests/test_generate.py
@@ -118,9 +118,9 @@ def test_memory_sorting_generator():
     memory_usage_MiB = after_instanciation_MiB - before_instanciation_MiB
     ratio = memory_usage_MiB / before_instanciation_MiB
     expected_allocation_MiB = 0
-    assert (
-        ratio <= 1.0 + relative_tolerance
-    ), f"SortingGenerator wrong memory {memory_usage_MiB} instead of {expected_allocation_MiB}"
+    assert ratio <= 1.0 + relative_tolerance, (
+        f"SortingGenerator wrong memory {memory_usage_MiB} instead of {expected_allocation_MiB}"
+    )
 
 
 def test_sorting_generator_consisency_across_calls():
@@ -192,9 +192,9 @@ def test_noise_generator_memory():
     memory_usage_MiB = after_instanciation_MiB - before_instanciation_MiB
     expected_allocation_MiB = dtype.itemsize * num_channels * noise_block_size / bytes_to_MiB_factor
     ratio = expected_allocation_MiB / expected_allocation_MiB
-    assert (
-        ratio <= 1.0 + relative_tolerance
-    ), f"MockRecording with 'tile_pregenerated' wrong memory {memory_usage_MiB} instead of {expected_allocation_MiB}"
+    assert ratio <= 1.0 + relative_tolerance, (
+        f"MockRecording with 'tile_pregenerated' wrong memory {memory_usage_MiB} instead of {expected_allocation_MiB}"
+    )
 
     # case 2: no preallocation very few memory (under 2 MiB)
     before_instanciation_MiB = measure_memory_allocation() / bytes_to_MiB_factor
diff --git a/src/spikeinterface/core/tests/test_time_handling.py b/src/spikeinterface/core/tests/test_time_handling.py
index 2f3cc1a6bf..eb872a6f4a 100644
--- a/src/spikeinterface/core/tests/test_time_handling.py
+++ b/src/spikeinterface/core/tests/test_time_handling.py
@@ -55,7 +55,6 @@ def _get_time_vector_recording(self, raw_recording):
         times_recording = raw_recording.clone()
         all_time_vectors = []
         for segment_index in range(raw_recording.get_num_segments()):
-
             t_start = segment_index + 1 * 100
             t_stop = t_start + raw_recording.get_duration(segment_index) + segment_index + 1
 
@@ -80,7 +79,6 @@ def _get_t_start_recording(self, raw_recording):
 
         all_t_starts = []
         for segment_index in range(raw_recording.get_num_segments()):
-
             t_start = (segment_index + 1) * 100
 
             all_t_starts.append(t_start + t_start_recording.get_times(segment_index))
@@ -110,7 +108,6 @@ def test_has_time_vector(self, time_vector_recording):
         raw_recording, times_recording, _ = time_vector_recording
 
         for segment_idx in range(raw_recording.get_num_segments()):
-
             assert raw_recording.has_time_vector(segment_idx) is False
             assert times_recording.has_time_vector(segment_idx) is True
 
@@ -169,7 +166,6 @@ def test_times_propagated_to_sorting(self, request, fixture_name):
             recording_for_durations=raw_recording, recording_to_attach=times_recording
         )
         for segment_index in range(raw_recording.get_num_segments()):
-
             if fixture_name == "time_vector_recording":
                 assert sorting.has_time_vector(segment_index=segment_index)
 
@@ -187,7 +183,6 @@ def test_time_sample_converters(self, request, fixture_name):
         assert "Provide 'segment_index'" in str(e)
 
         for segment_index in range(times_recording.get_num_segments()):
-
             sample_index = np.random.randint(low=0, high=times_recording.get_num_samples(segment_index))
             time_ = times_recording.sample_index_to_time(sample_index, segment_index=segment_index)
 
@@ -258,7 +253,6 @@ def test_get_durations(self, time_vector_recording, t_start_recording):
         all_raw_durations = []
         all_vector_durations = []
         for segment_index in range(raw_recording.get_num_segments()):
-
             # Test before `t_start` and `t_start` (`t_start` is just an offset,
             # should not affect duration).
             raw_duration = all_t_starts[segment_index][-1] - all_t_starts[segment_index][0] + ts
@@ -342,7 +336,6 @@ def test_shift_times_different_segments(self, request, fixture_name, shift):
         # For each segment, shift the segment only and check the
         # times are updated as expected.
         for idx in range(num_segments):
-
             scaler = idx + 2
             times_recording.shift_times(shift * scaler, segment_index=idx)
 
diff --git a/src/spikeinterface/core/tests/test_unitsaggregationsorting.py b/src/spikeinterface/core/tests/test_unitsaggregationsorting.py
index c04c66d60c..f648a25407 100644
--- a/src/spikeinterface/core/tests/test_unitsaggregationsorting.py
+++ b/src/spikeinterface/core/tests/test_unitsaggregationsorting.py
@@ -26,7 +26,6 @@ def test_unitsaggregationsorting_spiketrains():
 
     # test spike trains
     for segment_index in range(sorting1.get_num_segments()):
-
         spiketrain1 = sorting1.get_unit_spike_train(unit_ids[1], segment_index=segment_index)
         assert np.all(spiketrain1 == sorting_agg.get_unit_spike_train(unit_ids[1], segment_index=segment_index))
 
diff --git a/src/spikeinterface/core/tests/test_waveforms_extractor_backwards_compatibility.py b/src/spikeinterface/core/tests/test_waveforms_extractor_backwards_compatibility.py
index efb3de7464..dbb64090e1 100644
--- a/src/spikeinterface/core/tests/test_waveforms_extractor_backwards_compatibility.py
+++ b/src/spikeinterface/core/tests/test_waveforms_extractor_backwards_compatibility.py
@@ -61,7 +61,6 @@ def test_extract_waveforms(create_cache_folder):
     print(we_mock)
 
     for we in (we_old, we_mock):
-
         selected_spikes = we.get_sampled_indices(unit_id=sorting.unit_ids[0])
         # print(selected_spikes.size, selected_spikes.dtype)
 
diff --git a/src/spikeinterface/core/zarr_tools.py b/src/spikeinterface/core/zarr_tools.py
index 41ff57a358..a12c4ceec2 100644
--- a/src/spikeinterface/core/zarr_tools.py
+++ b/src/spikeinterface/core/zarr_tools.py
@@ -61,9 +61,9 @@ def adjust_chunks_shards_and_job_kwargs(
     if shards is not None:
         assert len(shards) == len(chunks), "Shards and chunks must have the same number of dimensions"
         for dim in range(len(chunks)):
-            assert (
-                shards[dim] >= chunks[dim] and shards[dim] % chunks[dim] == 0
-            ), "Shard size must be a multiple of chunk size"
+            assert shards[dim] >= chunks[dim] and shards[dim] % chunks[dim] == 0, (
+                "Shard size must be a multiple of chunk size"
+            )
         # When sharding is used, chunk_size in job_kwargs is used to determine the number of samples per chunk to
         # write in each job. Each process will write all chunks in a shard.
         job_kwargs["chunk_size"] = shards[0]
diff --git a/src/spikeinterface/curation/bombcell_curation.py b/src/spikeinterface/curation/bombcell_curation.py
index f41b25f8e8..a16a1904c2 100644
--- a/src/spikeinterface/curation/bombcell_curation.py
+++ b/src/spikeinterface/curation/bombcell_curation.py
@@ -245,9 +245,9 @@ def bombcell_label_units(
         if external_metrics is None:
             raise ValueError("Either sorting_analyzer or external_metrics must be provided")
         if isinstance(external_metrics, list):
-            assert all(
-                isinstance(df, pd.DataFrame) for df in external_metrics
-            ), "All items in external_metrics must be DataFrames"
+            assert all(isinstance(df, pd.DataFrame) for df in external_metrics), (
+                "All items in external_metrics must be DataFrames"
+            )
             combined_metrics = pd.concat(external_metrics, axis=1)
         else:
             combined_metrics = external_metrics
diff --git a/src/spikeinterface/curation/curation_format.py b/src/spikeinterface/curation/curation_format.py
index cf5b952376..84ae86ed47 100644
--- a/src/spikeinterface/curation/curation_format.py
+++ b/src/spikeinterface/curation/curation_format.py
@@ -190,12 +190,12 @@ def apply_curation(
     curated_sorting_or_analyzer : Sorting | SortingAnalyzer
         The curated object.
     """
-    assert isinstance(
-        sorting_or_analyzer, (BaseSorting, SortingAnalyzer)
-    ), f"`sorting_or_analyzer` must be a Sorting or a SortingAnalyzer, not an object of type {type(sorting_or_analyzer)}"
-    assert isinstance(
-        curation_dict_or_model, (dict, list, Curation, SequentialCuration)
-    ), f"`curation_dict_or_model` must be a dict, Curation or a SequentialCuration not an object of type {type(curation_dict_or_model)}"
+    assert isinstance(sorting_or_analyzer, (BaseSorting, SortingAnalyzer)), (
+        f"`sorting_or_analyzer` must be a Sorting or a SortingAnalyzer, not an object of type {type(sorting_or_analyzer)}"
+    )
+    assert isinstance(curation_dict_or_model, (dict, list, Curation, SequentialCuration)), (
+        f"`curation_dict_or_model` must be a dict, Curation or a SequentialCuration not an object of type {type(curation_dict_or_model)}"
+    )
     if isinstance(curation_dict_or_model, dict):
         curation_model = Curation(**curation_dict_or_model)
     elif isinstance(curation_dict_or_model, list):
diff --git a/src/spikeinterface/curation/mergeunitssorting.py b/src/spikeinterface/curation/mergeunitssorting.py
index 314a1a417e..4d8fdddb82 100644
--- a/src/spikeinterface/curation/mergeunitssorting.py
+++ b/src/spikeinterface/curation/mergeunitssorting.py
@@ -59,7 +59,7 @@ def __init__(self, sorting, units_to_merge, new_unit_ids=None, properties_policy
         # some checks
         for ids in units_to_merge:
             assert all(u in parents_unit_ids for u in ids), "units to merge are not all in parent"
-        assert properties_policy in ("keep", "remove"), "properties_policy must be " "keep" " or " "remove" ""
+        assert properties_policy in ("keep", "remove"), "properties_policy must be keep or remove"
 
         # new units are put at the end
         unit_ids = keep_unit_ids + list(new_unit_ids)
diff --git a/src/spikeinterface/curation/remove_excess_spikes.py b/src/spikeinterface/curation/remove_excess_spikes.py
index a2b8ebb20a..13c2c761f4 100644
--- a/src/spikeinterface/curation/remove_excess_spikes.py
+++ b/src/spikeinterface/curation/remove_excess_spikes.py
@@ -25,9 +25,9 @@ class RemoveExcessSpikesSorting(BaseSorting):
     def __init__(self, sorting: BaseSorting, recording: BaseRecording) -> None:
         super().__init__(sorting.get_sampling_frequency(), sorting.unit_ids)
 
-        assert (
-            sorting.get_num_segments() == recording.get_num_segments()
-        ), "The sorting and recording objects must have the same number of samples!"
+        assert sorting.get_num_segments() == recording.get_num_segments(), (
+            "The sorting and recording objects must have the same number of samples!"
+        )
 
         self._parent_sorting = sorting
         self._num_samples = np.empty(sorting.get_num_segments(), dtype=np.int64)
diff --git a/src/spikeinterface/curation/splitunitsorting.py b/src/spikeinterface/curation/splitunitsorting.py
index 087a808b02..a7af7c8994 100644
--- a/src/spikeinterface/curation/splitunitsorting.py
+++ b/src/spikeinterface/curation/splitunitsorting.py
@@ -38,9 +38,9 @@ def __init__(self, sorting, split_unit_id, indices_list, new_unit_ids=None, prop
         if type(indices_list) is not list:
             indices_list = [indices_list]
         parents_unit_ids = sorting.unit_ids
-        assert sorting.get_num_segments() == len(
-            indices_list
-        ), "The length of indices_list must be the same as parent_sorting.get_num_segments"
+        assert sorting.get_num_segments() == len(indices_list), (
+            "The length of indices_list must be the same as parent_sorting.get_num_segments"
+        )
         split_unit_indices = np.unique([np.unique(v) for v in indices_list])
         tot_splits = len(split_unit_indices)
         unchanged_units = parents_unit_ids[parents_unit_ids != split_unit_id]
@@ -63,12 +63,10 @@ def __init__(self, sorting, split_unit_id, indices_list, new_unit_ids=None, prop
             assert len(new_unit_ids) <= tot_splits, "indices_list has more id indices than the length of new_unit_ids"
 
         assert split_unit_id in parents_unit_ids, "Unit to split must be in parent sorting"
-        assert properties_policy == "keep" or properties_policy == "remove", (
-            "properties_policy must be " "keep" " or " "remove" ""
+        assert properties_policy == "keep" or properties_policy == "remove", "properties_policy must be keep or remove"
+        assert not any(np.isin(new_unit_ids, unchanged_units)), (
+            "new_unit_ids should be new unit ids or no more than one unit id can be found in split_unit_id"
         )
-        assert not any(
-            np.isin(new_unit_ids, unchanged_units)
-        ), "new_unit_ids should be new unit ids or no more than one unit id can be found in split_unit_id"
 
         sampling_frequency = sorting.get_sampling_frequency()
         units_ids = np.concatenate([unchanged_units, new_unit_ids])
@@ -76,9 +74,9 @@ def __init__(self, sorting, split_unit_id, indices_list, new_unit_ids=None, prop
         self._parent_sorting = sorting
 
         BaseSorting.__init__(self, sampling_frequency, units_ids)
-        assert all(
-            np.isin(unchanged_units, self.unit_ids)
-        ), "new_unit_ids should have a compatible format with the parent ids"
+        assert all(np.isin(unchanged_units, self.unit_ids)), (
+            "new_unit_ids should have a compatible format with the parent ids"
+        )
 
         for si, parent_segment in enumerate(self._parent_sorting.segments):
             sub_segment = SplitSortingUnitSegment(parent_segment, split_unit_id, indices_zero_based[si], new_unit_ids)
diff --git a/src/spikeinterface/curation/tests/test_curation_format.py b/src/spikeinterface/curation/tests/test_curation_format.py
index 40e0a9b2b7..a837e510bd 100644
--- a/src/spikeinterface/curation/tests/test_curation_format.py
+++ b/src/spikeinterface/curation/tests/test_curation_format.py
@@ -234,7 +234,6 @@ def test_to_from_json_file(tmp_path):
     for curation_index, curation_dict in enumerate(
         [curation_ids_int, curation_ids_str, curation_ids_int_dict, curation_with_splits]
     ):
-
         temp_filepath = tmp_path / f"data_{curation_index}.json"
 
         with open(temp_filepath, "w") as f:
diff --git a/src/spikeinterface/curation/tests/test_curationsorting.py b/src/spikeinterface/curation/tests/test_curationsorting.py
index cca3407ef5..95a87fc1d1 100644
--- a/src/spikeinterface/curation/tests/test_curationsorting.py
+++ b/src/spikeinterface/curation/tests/test_curationsorting.py
@@ -56,9 +56,9 @@ def test_split_merge():
             all(parent_sort.get_unit_spike_train(4, segment_index=i) == merged.get_unit_spike_train(4, segment_index=i))
             == True
         ), "splir or merge error"
-    assert parent_sort.get_unit_property(4, "someprop") == merged.get_unit_property(
-        4, "someprop"
-    ), "property wasn't kept"
+    assert parent_sort.get_unit_property(4, "someprop") == merged.get_unit_property(4, "someprop"), (
+        "property wasn't kept"
+    )
     # 1d
     assert merged.get_unit_property(4, "some_str_prop") == "", "error with array property"
     assert merged.get_unit_property(4, "some_prop_to_keep") == 1, "error with array property"
@@ -67,9 +67,9 @@ def test_split_merge():
     # 2d
     assert np.array_equal(merged.get_unit_property(4, "some_array_prop_to_keep"), [1, 1]), "error with array property"
     assert np.all(np.isnan(merged.get_unit_property(4, "some_array_prop_to_remove"))), "error with array property"
-    assert np.array_equal(
-        merged.get_unit_property(4, "some_array_prop_to_none"), [None, None]
-    ), "error with array property"
+    assert np.array_equal(merged.get_unit_property(4, "some_array_prop_to_none"), [None, None]), (
+        "error with array property"
+    )
 
     merged_with_dups = MergeUnitsSorting(
         parent_sort, new_unit_ids=[8], units_to_merge=[[0, 1]], properties_policy="remove", delta_time_ms=0.5
diff --git a/src/spikeinterface/extractors/cellexplorersortingextractor.py b/src/spikeinterface/extractors/cellexplorersortingextractor.py
index 8659baded8..953c9c315a 100644
--- a/src/spikeinterface/extractors/cellexplorersortingextractor.py
+++ b/src/spikeinterface/extractors/cellexplorersortingextractor.py
@@ -157,9 +157,9 @@ def _retrieve_sampling_frequency_from_session_info_file(self) -> float:
             self.session_info_file_path = self.session_path / f"{self.session_id}.sessionInfo.mat"
 
         self.session_info_file_path = Path(self.session_info_file_path).absolute()
-        assert (
-            self.session_info_file_path.is_file()
-        ), f"No {self.session_id}.sessionInfo.mat file found in the {self.session_path}!, can't inferr sampling rate, please pass the sampling rate at initialization"
+        assert self.session_info_file_path.is_file(), (
+            f"No {self.session_id}.sessionInfo.mat file found in the {self.session_path}!, can't inferr sampling rate, please pass the sampling rate at initialization"
+        )
 
         session_info_mat = read_mat(self.session_info_file_path)
         rates = session_info_mat["sessionInfo"]["rates"]
diff --git a/src/spikeinterface/extractors/iblextractors.py b/src/spikeinterface/extractors/iblextractors.py
index 8a57e40ec3..69c072931b 100644
--- a/src/spikeinterface/extractors/iblextractors.py
+++ b/src/spikeinterface/extractors/iblextractors.py
@@ -172,9 +172,9 @@ def __init__(
         else:
             stream_names = IblRecordingExtractor.get_stream_names(eid=eid, cache_folder=cache_folder, one=one)
             if len(stream_names) > 1:
-                assert (
-                    stream_name is not None
-                ), f"Multiple streams found for session. Please specify a stream name from {stream_names}."
+                assert stream_name is not None, (
+                    f"Multiple streams found for session. Please specify a stream name from {stream_names}."
+                )
                 assert stream_name in stream_names, (
                     f"The `stream_name` '{stream_name}' is not available for this experiment {eid}! "
                     f"Please choose one of {stream_names}."
@@ -320,7 +320,7 @@ class IblSortingExtractor(BaseSorting):
         The loaded data.
     """
 
-    installation_mesg = "IBL extractors require ibllib as a dependency." " To install, run: \n\n pip install ibllib\n\n"
+    installation_mesg = "IBL extractors require ibllib as a dependency. To install, run: \n\n pip install ibllib\n\n"
 
     def __init__(
         self, pid: str, good_clusters_only: bool = False, load_unit_properties: bool = True, one=None, **kwargs
diff --git a/src/spikeinterface/extractors/matlabhelpers.py b/src/spikeinterface/extractors/matlabhelpers.py
index f7ffb45065..8ffe31d665 100644
--- a/src/spikeinterface/extractors/matlabhelpers.py
+++ b/src/spikeinterface/extractors/matlabhelpers.py
@@ -18,7 +18,8 @@
 
 class MatlabHelper:
     installation_mesg = (
-        "To use the MATSortingExtractor install h5py and scipy: " "\n\n pip install h5py scipy\n\n"
+        "To use the MATSortingExtractor install h5py and scipy: "
+        "\n\n pip install h5py scipy\n\n"
     )  # error message when not installed
 
     def __init__(self, file_path):
diff --git a/src/spikeinterface/extractors/mcsh5extractors.py b/src/spikeinterface/extractors/mcsh5extractors.py
index 3e295f33b4..df0004f09a 100644
--- a/src/spikeinterface/extractors/mcsh5extractors.py
+++ b/src/spikeinterface/extractors/mcsh5extractors.py
@@ -111,7 +111,7 @@ def openMCSH5File(filename, stream_id):
     stream_name = "Stream_" + str(stream_id)
     analog_stream_names = list(rf.require_group("/Data/Recording_0/AnalogStream").keys())
     assert stream_name in analog_stream_names, (
-        f"Specified stream does not exist. " f"Available streams: {analog_stream_names}"
+        f"Specified stream does not exist. Available streams: {analog_stream_names}"
     )
 
     stream = rf.require_group("/Data/Recording_0/AnalogStream/" + stream_name)
@@ -141,9 +141,9 @@ def openMCSH5File(filename, stream_id):
     timestep_avg = np.mean(TimeVals[1:] - TimeVals[0:-1])
     timestep_min = np.min(TimeVals[1:] - TimeVals[0:-1])
     timestep_max = np.min(TimeVals[1:] - TimeVals[0:-1])
-    assert all(
-        np.abs(np.array((timestep_min, timestep_max)) - timestep_avg) / timestep_avg < 1e-6
-    ), "Time steps vary by more than 1 ppm"
+    assert all(np.abs(np.array((timestep_min, timestep_max)) - timestep_avg) / timestep_avg < 1e-6), (
+        "Time steps vary by more than 1 ppm"
+    )
     samplingRate = 1.0 / timestep_avg
 
     mcs_info = {
diff --git a/src/spikeinterface/extractors/neoextractors/intan.py b/src/spikeinterface/extractors/neoextractors/intan.py
index 877f7f33b2..4f0fd31ea5 100644
--- a/src/spikeinterface/extractors/neoextractors/intan.py
+++ b/src/spikeinterface/extractors/neoextractors/intan.py
@@ -156,7 +156,7 @@ def __init__(
 
         if mode not in ("append", "concatenate"):
             mode_error = (
-                "Possible options for the `mode` argument are 'concatenate' or 'append', you have entered " f"{mode}."
+                f"Possible options for the `mode` argument are 'concatenate' or 'append', you have entered {mode}."
             )
             raise ValueError(mode_error)
 
diff --git a/src/spikeinterface/extractors/neoextractors/neobaseextractor.py b/src/spikeinterface/extractors/neoextractors/neobaseextractor.py
index b9832f7fe8..7e70adcbda 100644
--- a/src/spikeinterface/extractors/neoextractors/neobaseextractor.py
+++ b/src/spikeinterface/extractors/neoextractors/neobaseextractor.py
@@ -230,9 +230,9 @@ def __init__(
 
         if use_names_as_ids:
             chan_names = signal_channels["name"]
-            assert (
-                chan_names.size == np.unique(chan_names).size
-            ), "use_names_as_ids=True is not possible, channel names are not unique"
+            assert chan_names.size == np.unique(chan_names).size, (
+                "use_names_as_ids=True is not possible, channel names are not unique"
+            )
             chan_ids = chan_names
         else:
             # unique in all cases
@@ -577,9 +577,7 @@ def _infer_t_start_from_signal_stream(self, segment_index: int, stream_id: str |
 
         if len(unique_t_starts) == 0:
             t_start = None
-            warning_message = (
-                "No stream ids with corresponding sampling frequency found \n " "Setting t_start to None. \n"
-            )
+            warning_message = "No stream ids with corresponding sampling frequency found \n Setting t_start to None. \n"
             warnings.warn(warning_message)
 
         if len(unique_t_starts) == 1:
@@ -671,9 +669,9 @@ def __init__(self, block_index=None, use_names_as_ids: bool = False, **neo_kwarg
 
         if use_names_as_ids:
             channel_ids = event_channels["name"]
-            assert (
-                event_channels.size == np.unique(channel_ids).size
-            ), "use_name_as_ids=True is not possible, channel names are not unique"
+            assert event_channels.size == np.unique(channel_ids).size, (
+                "use_name_as_ids=True is not possible, channel names are not unique"
+            )
         else:
             channel_ids = event_channels["id"]
 
diff --git a/src/spikeinterface/extractors/neoextractors/neuroscope.py b/src/spikeinterface/extractors/neoextractors/neuroscope.py
index 7064ea1303..bc02faa0e3 100644
--- a/src/spikeinterface/extractors/neoextractors/neuroscope.py
+++ b/src/spikeinterface/extractors/neoextractors/neuroscope.py
@@ -188,21 +188,20 @@ def __init__(
     ):
         from lxml import etree as et
 
-        assert not (
-            folder_path is None and resfile_path is None and clufile_path is None
-        ), "Either pass a single folder_path location, or a pair of resfile_path and clufile_path! None received."
+        assert not (folder_path is None and resfile_path is None and clufile_path is None), (
+            "Either pass a single folder_path location, or a pair of resfile_path and clufile_path! None received."
+        )
 
         if resfile_path is not None:
             assert clufile_path is not None, "If passing resfile_path or clufile_path, both are required!"
             resfile_path = Path(resfile_path)
             clufile_path = Path(clufile_path)
-            assert (
-                resfile_path.is_file() and clufile_path.is_file()
-            ), f"The resfile_path ({resfile_path}) and clufile_path ({clufile_path}) must be .res and .clu files!"
+            assert resfile_path.is_file() and clufile_path.is_file(), (
+                f"The resfile_path ({resfile_path}) and clufile_path ({clufile_path}) must be .res and .clu files!"
+            )
 
             assert folder_path is None, (
-                "Pass either a single folder_path location, "
-                "or a pair of resfile_path and clufile_path! All received."
+                "Pass either a single folder_path location, or a pair of resfile_path and clufile_path! All received."
             )
             folder_path_passed = False
             folder_path = resfile_path.parent
@@ -225,9 +224,9 @@ def __init__(
             folder_path_passed = True  # flag for setting kwargs for proper dumping
 
         if exclude_shanks is not None:  # dumping checks do not like having an empty list as default
-            assert all(
-                [isinstance(x, (int, np.integer)) and x >= 0 for x in exclude_shanks]
-            ), "Optional argument 'exclude_shanks' must contain positive integers only!"
+            assert all([isinstance(x, (int, np.integer)) and x >= 0 for x in exclude_shanks]), (
+                "Optional argument 'exclude_shanks' must contain positive integers only!"
+            )
         else:
             exclude_shanks = []
         xml_file_path = _handle_xml_file_path(folder_path=folder_path, initial_xml_file_path=xml_file_path)
@@ -248,9 +247,9 @@ def __init__(
 
         resfile_names = [x.name[: x.name.find(".res")] for x in res_files]
         clufile_names = [x.name[: x.name.find(".clu")] for x in clu_files]
-        assert np.all(
-            r == c for (r, c) in zip(resfile_names, clufile_names)
-        ), "Some of the .res.%i and .clu.%i files do not share the same name!"
+        assert np.all(r == c for (r, c) in zip(resfile_names, clufile_names)), (
+            "Some of the .res.%i and .clu.%i files do not share the same name!"
+        )
 
         all_unit_ids = []
         all_spiketrains = []
@@ -272,9 +271,9 @@ def __init__(
                 n_clu = clu[0]
                 clu = np.delete(clu, 0)
                 unique_ids = np.unique(clu)
-                assert (
-                    len(unique_ids) == n_clu
-                ), "First value of .clu file ({clufile_path}) does not match number of unique IDs!"
+                assert len(unique_ids) == n_clu, (
+                    "First value of .clu file ({clufile_path}) does not match number of unique IDs!"
+                )
                 unit_map = dict(zip(unique_ids, list(range(1, n_clu + 1))))
 
                 if 0 in unique_ids:
diff --git a/src/spikeinterface/extractors/shybridextractors.py b/src/spikeinterface/extractors/shybridextractors.py
index eca7d46724..9aa7439fab 100644
--- a/src/spikeinterface/extractors/shybridextractors.py
+++ b/src/spikeinterface/extractors/shybridextractors.py
@@ -41,9 +41,7 @@ class SHYBRIDRecordingExtractor(BinaryRecordingExtractor):
         Loaded data.
     """
 
-    installation_mesg = (
-        "To use the SHYBRID extractors, install SHYBRID and pyyaml: " "\n\n pip install shybrid pyyaml\n\n"
-    )
+    installation_mesg = "To use the SHYBRID extractors, install SHYBRID and pyyaml: \n\n pip install shybrid pyyaml\n\n"
 
     def __init__(self, file_path):
         if HAVE_SHYBRID:
diff --git a/src/spikeinterface/generation/drift_tools.py b/src/spikeinterface/generation/drift_tools.py
index 6b95ac3834..da0e85cc32 100644
--- a/src/spikeinterface/generation/drift_tools.py
+++ b/src/spikeinterface/generation/drift_tools.py
@@ -71,7 +71,6 @@ def interpolate_templates(
             template = templates_array[template_index, sample_index, :]
 
             if interpolation_method == "thin_plate":
-
                 if "neighbors" not in interpolation_kwargs:
                     # If neighbors it not passed, `RBFInterpolator` uses all channels.
                     # This works poorly for standard ephys template interpolation.
@@ -389,9 +388,9 @@ def __init__(
     ):
         from scipy.spatial import distance
 
-        assert isinstance(
-            drifting_templates, DriftingTemplates
-        ), "drifting_templates must be a DriftingTemplates object"
+        assert isinstance(drifting_templates, DriftingTemplates), (
+            "drifting_templates must be a DriftingTemplates object"
+        )
         self.drifting_templates = drifting_templates
 
         if parent_recording is None:
@@ -419,15 +418,15 @@ def __init__(
             amplitude_vector = amplitude_factor
 
         if parent_recording is not None:
-            assert (
-                parent_recording.get_num_segments() == sorting.get_num_segments()
-            ), "parent_recording must have the same number of segments as sorting"
-            assert (
-                parent_recording.get_sampling_frequency() == sorting.get_sampling_frequency()
-            ), "parent_recording must have the same sampling frequency as sorting"
-            assert (
-                parent_recording.get_num_channels() == drifting_templates.num_channels
-            ), "parent_recording must have the same number of channels as templates"
+            assert parent_recording.get_num_segments() == sorting.get_num_segments(), (
+                "parent_recording must have the same number of segments as sorting"
+            )
+            assert parent_recording.get_sampling_frequency() == sorting.get_sampling_frequency(), (
+                "parent_recording must have the same sampling frequency as sorting"
+            )
+            assert parent_recording.get_num_channels() == drifting_templates.num_channels, (
+                "parent_recording must have the same number of channels as templates"
+            )
             parent_recording.copy_metadata(self)
 
         if num_samples is None:
@@ -441,29 +440,29 @@ def __init__(
             num_samples = [num_samples]
 
         # check drift vector shape and length
-        assert (
-            len(displacement_vectors) == sorting.get_num_segments()
-        ), "displacement_vectors must have the same number of segments as sorting"
+        assert len(displacement_vectors) == sorting.get_num_segments(), (
+            "displacement_vectors must have the same number of segments as sorting"
+        )
         if displacement_unit_factor is None:
             displacement_unit_factor = np.ones(sorting.get_num_units(), dtype="float32")
-        assert displacement_unit_factor.shape[0] == len(
-            sorting.unit_ids
-        ), "displacement_unit_factor must have the same number of units as sorting"
+        assert displacement_unit_factor.shape[0] == len(sorting.unit_ids), (
+            "displacement_unit_factor must have the same number of units as sorting"
+        )
         # displacement_vectors_indices = []
         for num_segment in range(sorting.get_num_segments()):
             duration = displacement_vectors[num_segment].shape[0] / displacement_sampling_frequency
-            assert (
-                duration >= num_samples[num_segment] / sorting.get_sampling_frequency()
-            ), "displacement_vectors duration must span the entire recording segment"
-            assert (
-                displacement_vectors[num_segment].shape[2] == displacement_unit_factor.shape[1]
-            ), "displacement_vectors and displacement_unit_factor must have the same number of motions"
+            assert duration >= num_samples[num_segment] / sorting.get_sampling_frequency(), (
+                "displacement_vectors duration must span the entire recording segment"
+            )
+            assert displacement_vectors[num_segment].shape[2] == displacement_unit_factor.shape[1], (
+                "displacement_vectors and displacement_unit_factor must have the same number of motions"
+            )
 
         # TODO SharedMem for templates
         if mode == "precompute":
-            assert (
-                drifting_templates.templates_array_moved is not None
-            ), "drifting_templates must have precomputed displacements"
+            assert drifting_templates.templates_array_moved is not None, (
+                "drifting_templates must have precomputed displacements"
+            )
             displacements = drifting_templates.displacements
 
             # compute the displacement indices
diff --git a/src/spikeinterface/generation/hybrid_tools.py b/src/spikeinterface/generation/hybrid_tools.py
index 426699f743..7fad61ee48 100644
--- a/src/spikeinterface/generation/hybrid_tools.py
+++ b/src/spikeinterface/generation/hybrid_tools.py
@@ -121,9 +121,9 @@ def select_templates(
     Templates
         The selected templates
     """
-    assert (
-        min_amplitude is not None or max_amplitude is not None or min_depth is not None or max_depth is not None
-    ), "At least one of min_amplitude, max_amplitude, min_depth, max_depth should be provided"
+    assert min_amplitude is not None or max_amplitude is not None or min_depth is not None or max_depth is not None, (
+        "At least one of min_amplitude, max_amplitude, min_depth, max_depth should be provided"
+    )
     # get template amplitudes and depth
     main_channel_indices = templates.get_main_channels(outputs="index", with_dict=False)
 
@@ -400,9 +400,9 @@ def generate_hybrid_recording(
     durations = num_samples / sampling_frequency
     channel_locations = probe.contact_positions
 
-    assert (
-        templates is not None or sorting is not None or generate_sorting_kwargs is not None
-    ), "Provide templates or sorting or generate_sorting_kwargs"
+    assert templates is not None or sorting is not None or generate_sorting_kwargs is not None, (
+        "Provide templates or sorting or generate_sorting_kwargs"
+    )
 
     # check num_units
     num_units = None
@@ -444,9 +444,9 @@ def generate_hybrid_recording(
         from spikeinterface.postprocessing.localization_tools import compute_monopolar_triangulation
 
         assert isinstance(templates, Templates), "templates should be a Templates object"
-        assert (
-            templates.num_channels == recording.get_num_channels()
-        ), "templates and recording should have the same number of channels"
+        assert templates.num_channels == recording.get_num_channels(), (
+            "templates and recording should have the same number of channels"
+        )
         nbefore = templates.nbefore
         nafter = templates.nafter
         unit_locations = compute_monopolar_triangulation(templates, peak_sign="both", peak_mode="extremum")
@@ -485,9 +485,9 @@ def generate_hybrid_recording(
     num_spikes = sorting.to_spike_vector().size
     sorting.set_property("gt_unit_locations", unit_locations)
 
-    assert (nbefore + nafter) == templates_array.shape[
-        1
-    ], "templates and ms_before, ms_after should have the same length"
+    assert (nbefore + nafter) == templates_array.shape[1], (
+        "templates and ms_before, ms_after should have the same length"
+    )
 
     if templates_array.ndim == 3:
         upsample_vector = None
diff --git a/src/spikeinterface/generation/noise_tools.py b/src/spikeinterface/generation/noise_tools.py
index 7fbecf0c9b..3820c55b20 100644
--- a/src/spikeinterface/generation/noise_tools.py
+++ b/src/spikeinterface/generation/noise_tools.py
@@ -81,9 +81,9 @@ def __init__(
         num_segments = len(durations)
 
         if cov_matrix is not None:
-            assert (
-                cov_matrix.shape[0] == cov_matrix.shape[1] == num_channels
-            ), "cov_matrix should have a size (num_channels, num_channels)"
+            assert cov_matrix.shape[0] == cov_matrix.shape[1] == num_channels, (
+                "cov_matrix should have a size (num_channels, num_channels)"
+            )
 
         # very important here when multiprocessing and dump/load
         seed = _ensure_seed(seed)
diff --git a/src/spikeinterface/generation/template_database.py b/src/spikeinterface/generation/template_database.py
index 83fb42fe38..999f46ebf3 100644
--- a/src/spikeinterface/generation/template_database.py
+++ b/src/spikeinterface/generation/template_database.py
@@ -109,12 +109,12 @@ def query_templates_from_database(template_df: "pandas.DataFrame", verbose: bool
         current_channel_locations = templates.get_channel_locations()
         current_sampling_frequency = templates.sampling_frequency
 
-        assert (
-            current_nbefore == nbefore
-        ), f"Number of samples before the peak is not consistent across datasets: {current_nbefore} != {nbefore}"
-        assert (
-            current_sampling_frequency == sampling_frequency
-        ), f"Sampling frequency is not consistent across datasets: {current_sampling_frequency} != {sampling_frequency}"
+        assert current_nbefore == nbefore, (
+            f"Number of samples before the peak is not consistent across datasets: {current_nbefore} != {nbefore}"
+        )
+        assert current_sampling_frequency == sampling_frequency, (
+            f"Sampling frequency is not consistent across datasets: {current_sampling_frequency} != {sampling_frequency}"
+        )
         assert np.array_equal(
             current_channel_locations - current_channel_locations[0],
             channel_locations - channel_locations[0],
diff --git a/src/spikeinterface/metrics/quality/misc_metrics.py b/src/spikeinterface/metrics/quality/misc_metrics.py
index 9c5c3fa258..016a2d24f9 100644
--- a/src/spikeinterface/metrics/quality/misc_metrics.py
+++ b/src/spikeinterface/metrics/quality/misc_metrics.py
@@ -88,7 +88,7 @@ def compute_presence_ratios(
     mean_fr_ratio_thresh = float(mean_fr_ratio_thresh)
     if mean_fr_ratio_thresh < 0:
         raise ValueError(
-            f"Expected positive float for `mean_fr_ratio_thresh` param." f"Provided value: {mean_fr_ratio_thresh}"
+            f"Expected positive float for `mean_fr_ratio_thresh` param.Provided value: {mean_fr_ratio_thresh}"
         )
     if mean_fr_ratio_thresh > 1:
         warnings.warn("`mean_fr_ratio_thres` parameter above 1 might lead to low presence ratios.")
@@ -96,11 +96,10 @@ def compute_presence_ratios(
     presence_ratios = {}
     if total_samples < bin_duration_samples:
         warnings.warn(
-            f"Bin duration of {bin_duration_s}s is larger than recording duration. " f"Presence ratios are set to NaN."
+            f"Bin duration of {bin_duration_s}s is larger than recording duration. Presence ratios are set to NaN."
         )
         presence_ratios = {unit_id: np.nan for unit_id in unit_ids}
     else:
-
         for unit_id in unit_ids:
             if num_spikes[unit_id] == 0:
                 presence_ratios[unit_id] = np.nan
@@ -1240,9 +1239,7 @@ def compute_drift_metrics(
 
     segment_samples = [sorting_analyzer.get_num_samples(i) for i in range(sorting_analyzer.get_num_segments())]
     data = spike_locations_by_unit[unit_ids[0]]
-    assert direction in data.dtype.names, (
-        f"Direction {direction} is invalid. Available directions: " f"{data.dtype.names}"
-    )
+    assert direction in data.dtype.names, f"Direction {direction} is invalid. Available directions: {data.dtype.names}"
     bin_edges_for_units = compute_bin_edges_per_unit(
         sorting, segment_samples=segment_samples, periods=periods, bin_duration_s=interval_s, concatenated=False
     )
diff --git a/src/spikeinterface/metrics/quality/tests/test_quality_metric_calculator.py b/src/spikeinterface/metrics/quality/tests/test_quality_metric_calculator.py
index 823d53f347..34b94f625b 100644
--- a/src/spikeinterface/metrics/quality/tests/test_quality_metric_calculator.py
+++ b/src/spikeinterface/metrics/quality/tests/test_quality_metric_calculator.py
@@ -261,7 +261,6 @@ def test_quality_metrics_with_periods():
 
 
 if __name__ == "__main__":
-
     sorting_analyzer = get_sorting_analyzer()
     print(sorting_analyzer)
 
diff --git a/src/spikeinterface/metrics/template/template_metrics.py b/src/spikeinterface/metrics/template/template_metrics.py
index a23343d0ec..dd79983949 100644
--- a/src/spikeinterface/metrics/template/template_metrics.py
+++ b/src/spikeinterface/metrics/template/template_metrics.py
@@ -88,7 +88,6 @@ def _handle_backward_compatibility_on_load(self):
 
         # For backwards compatibility - this reformats metrics_kwargs as metric_params
         if (metrics_kwargs := self.params.get("metrics_kwargs")) is not None:
-
             metric_params = {}
             for metric_name in self.params["metric_names"]:
                 metric_params[metric_name] = deepcopy(metrics_kwargs)
diff --git a/src/spikeinterface/postprocessing/spike_amplitudes.py b/src/spikeinterface/postprocessing/spike_amplitudes.py
index 3c2020a64e..0621419835 100644
--- a/src/spikeinterface/postprocessing/spike_amplitudes.py
+++ b/src/spikeinterface/postprocessing/spike_amplitudes.py
@@ -75,9 +75,9 @@ def __init__(
             self._gains = None
             self._offsets = None
         spike_retriever = find_parent_of_type(parents, SpikeRetriever)
-        assert isinstance(
-            spike_retriever, SpikeRetriever
-        ), "SpikeAmplitudeNode needs a single SpikeRetriever as a parent"
+        assert isinstance(spike_retriever, SpikeRetriever), (
+            "SpikeAmplitudeNode needs a single SpikeRetriever as a parent"
+        )
         # put peak_shifts in vector way
         self._peak_shifts = np.array(list(peak_shifts.values()), dtype="int64")
         self._margin = np.max(np.abs(self._peak_shifts))
diff --git a/src/spikeinterface/postprocessing/tests/test_amplitude_scalings.py b/src/spikeinterface/postprocessing/tests/test_amplitude_scalings.py
index cb523038df..d5f0bf947a 100644
--- a/src/spikeinterface/postprocessing/tests/test_amplitude_scalings.py
+++ b/src/spikeinterface/postprocessing/tests/test_amplitude_scalings.py
@@ -139,7 +139,6 @@ def test_unit_pair_overlap_matrix_matches_naive_reference():
 
 
 class TestAmplitudeScalingsExtension(AnalyzerExtensionCommonTestSuite):
-
     @pytest.mark.parametrize("params", [dict(handle_collisions=True), dict(handle_collisions=False)])
     def test_extension(self, params):
         self.run_extension_tests(ComputeAmplitudeScalings, params)
diff --git a/src/spikeinterface/postprocessing/tests/test_correlograms.py b/src/spikeinterface/postprocessing/tests/test_correlograms.py
index 5b3410ed39..96503d7840 100644
--- a/src/spikeinterface/postprocessing/tests/test_correlograms.py
+++ b/src/spikeinterface/postprocessing/tests/test_correlograms.py
@@ -647,9 +647,9 @@ def test_acgs_3d_original_implementation(window_ms, bin_ms, num_firing_rate_quan
     )
 
     assert np.allclose(npyx_3dacg, acg_3d, rtol=1e-2, atol=1e-2), "3D-ACG result does not match original implementation"
-    assert np.allclose(
-        npyx_quantiles, firing_rate_quantiles, rtol=1e-5, atol=1e-5
-    ), "3D-ACG quantiles do not match original implementation"
+    assert np.allclose(npyx_quantiles, firing_rate_quantiles, rtol=1e-5, atol=1e-5), (
+        "3D-ACG quantiles do not match original implementation"
+    )
 
 
 # Check in the case where we have segments
@@ -693,6 +693,6 @@ def test_acgs_3d_original_implementation_with_segments(window_ms, bin_ms, num_fi
     )
 
     # Use a less strict tolerance here as we are only simulating a single segment
-    assert np.allclose(
-        npyx_3dacg, acg_3d, rtol=5e-2, atol=5e-2
-    ), f"3D-ACG result for {segments} segments does not match original implementation with concatenated times"
+    assert np.allclose(npyx_3dacg, acg_3d, rtol=5e-2, atol=5e-2), (
+        f"3D-ACG result for {segments} segments does not match original implementation with concatenated times"
+    )
diff --git a/src/spikeinterface/postprocessing/tests/test_extension_merges.py b/src/spikeinterface/postprocessing/tests/test_extension_merges.py
index e4f858223e..ca47d7dd26 100644
--- a/src/spikeinterface/postprocessing/tests/test_extension_merges.py
+++ b/src/spikeinterface/postprocessing/tests/test_extension_merges.py
@@ -27,7 +27,6 @@ def test_correlograms_merge():
 
     for new_id_strategy in ["append", "take_first", "user"]:
         for merge_unit_groups, new_unit_id in zip(trial_merges, new_unit_ids):
-
             # first, compute the correlograms of the merged units using the merge method
             if new_id_strategy == "user":
                 merged_sorting_analyzer = sorting_analyzer.merge_units(
@@ -87,7 +86,6 @@ def test_acgs_3d_merge(sparse):
 
     for new_id_strategy in ["append", "take_first"]:
         for merge_unit_groups in trial_merges:
-
             merged_sorting_analyzer = sorting_analyzer.merge_units(
                 merge_unit_groups=merge_unit_groups, new_id_strategy=new_id_strategy
             )
diff --git a/src/spikeinterface/postprocessing/tests/test_isi.py b/src/spikeinterface/postprocessing/tests/test_isi.py
index b24a3b0405..f426569a33 100644
--- a/src/spikeinterface/postprocessing/tests/test_isi.py
+++ b/src/spikeinterface/postprocessing/tests/test_isi.py
@@ -15,7 +15,6 @@
 
 
 class TestComputeISIHistograms(AnalyzerExtensionCommonTestSuite):
-
     @pytest.mark.parametrize(
         "params",
         [
diff --git a/src/spikeinterface/postprocessing/tests/test_principal_component.py b/src/spikeinterface/postprocessing/tests/test_principal_component.py
index 879f4ff055..493f36e797 100644
--- a/src/spikeinterface/postprocessing/tests/test_principal_component.py
+++ b/src/spikeinterface/postprocessing/tests/test_principal_component.py
@@ -8,7 +8,6 @@
 
 
 class TestPrincipalComponentsExtension(AnalyzerExtensionCommonTestSuite):
-
     @pytest.mark.parametrize(
         "params",
         [
@@ -223,7 +222,6 @@ def test_select_channels_sparse_pca():
     selected_pca = analyzer_selected.get_extension("principal_components")
 
     for unit_id in sorting_analyzer.unit_ids:
-
         original_units_to_channels = sorting_analyzer.sparsity.unit_id_to_channel_ids[unit_id]
         selected_units_to_channels = analyzer_selected.sparsity.unit_id_to_channel_ids[unit_id]
 
@@ -232,7 +230,6 @@ def test_select_channels_sparse_pca():
 
         for channel_id in select_channel_ids:
             if channel_id in original_units_to_channels:
-
                 # Now check waveforms and PCs, which are sparse
                 channel_index_in_original = np.where(original_units_to_channels == channel_id)[0][0]
                 original_unit_pca = original_pca_one_unit[:, :, channel_index_in_original]
diff --git a/src/spikeinterface/postprocessing/tests/test_spike_amplitudes.py b/src/spikeinterface/postprocessing/tests/test_spike_amplitudes.py
index a68483a1b2..4ab77f2b0a 100644
--- a/src/spikeinterface/postprocessing/tests/test_spike_amplitudes.py
+++ b/src/spikeinterface/postprocessing/tests/test_spike_amplitudes.py
@@ -3,6 +3,5 @@
 
 
 class TestComputeSpikeAmplitudes(AnalyzerExtensionCommonTestSuite):
-
     def test_extension(self):
         self.run_extension_tests(ComputeSpikeAmplitudes, params=dict())
diff --git a/src/spikeinterface/postprocessing/tests/test_spike_locations.py b/src/spikeinterface/postprocessing/tests/test_spike_locations.py
index 3810a470be..33871d90dc 100644
--- a/src/spikeinterface/postprocessing/tests/test_spike_locations.py
+++ b/src/spikeinterface/postprocessing/tests/test_spike_locations.py
@@ -4,7 +4,6 @@
 
 
 class TestSpikeLocationsExtension(AnalyzerExtensionCommonTestSuite):
-
     @pytest.mark.parametrize(
         "params",
         [
diff --git a/src/spikeinterface/postprocessing/tests/test_template_similarity.py b/src/spikeinterface/postprocessing/tests/test_template_similarity.py
index fd963fa013..ef35858fbb 100644
--- a/src/spikeinterface/postprocessing/tests/test_template_similarity.py
+++ b/src/spikeinterface/postprocessing/tests/test_template_similarity.py
@@ -14,7 +14,6 @@
 )
 
 if importlib.util.find_spec("numba") is not None:
-
     HAVE_NUMBA = True
     from spikeinterface.postprocessing.template_similarity import _compute_similarity_matrix_numba
 else:
@@ -25,7 +24,6 @@
 
 
 class TestSimilarityExtension(AnalyzerExtensionCommonTestSuite):
-
     @pytest.mark.parametrize(
         "params",
         [
diff --git a/src/spikeinterface/postprocessing/tests/test_unit_locations.py b/src/spikeinterface/postprocessing/tests/test_unit_locations.py
index 5f0a90d966..4c7db3bbd3 100644
--- a/src/spikeinterface/postprocessing/tests/test_unit_locations.py
+++ b/src/spikeinterface/postprocessing/tests/test_unit_locations.py
@@ -7,7 +7,6 @@
 
 
 class TestUnitLocationsExtension(AnalyzerExtensionCommonTestSuite):
-
     @pytest.mark.parametrize(
         "params",
         [
@@ -60,7 +59,6 @@ def test_2d_and_3d_unit_localization():
     analyzer_2D.compute(["random_spikes", "templates"])
 
     for method in ["center_of_mass", "grid_convolution", "monopolar_triangulation", "max_channel"]:
-
         analyzer_2D.compute("unit_locations", method=method)
         analyzer_3D.compute("unit_locations", method=method)
         unit_locations_2D = analyzer_2D.get_extension("unit_locations").get_data()
diff --git a/src/spikeinterface/postprocessing/tests/test_valid_unit_periods.py b/src/spikeinterface/postprocessing/tests/test_valid_unit_periods.py
index 3ba057d059..a929f01881 100644
--- a/src/spikeinterface/postprocessing/tests/test_valid_unit_periods.py
+++ b/src/spikeinterface/postprocessing/tests/test_valid_unit_periods.py
@@ -7,7 +7,6 @@
 
 
 class TestComputeValidUnitPeriods(AnalyzerExtensionCommonTestSuite):
-
     @pytest.mark.parametrize(
         "params",
         [
diff --git a/src/spikeinterface/preprocessing/average_across_direction.py b/src/spikeinterface/preprocessing/average_across_direction.py
index f87a79e2b4..2fb1c36dcf 100644
--- a/src/spikeinterface/preprocessing/average_across_direction.py
+++ b/src/spikeinterface/preprocessing/average_across_direction.py
@@ -5,7 +5,6 @@
 
 
 class AverageAcrossDirectionRecording(BaseRecording):
-
     def __init__(
         self,
         recording: BaseRecording,
diff --git a/src/spikeinterface/preprocessing/common_reference.py b/src/spikeinterface/preprocessing/common_reference.py
index 6da823d0e4..9ca5143409 100644
--- a/src/spikeinterface/preprocessing/common_reference.py
+++ b/src/spikeinterface/preprocessing/common_reference.py
@@ -139,13 +139,13 @@ def __init__(
                 if np.isscalar(ref_channel_ids):
                     ref_channel_ids = [ref_channel_ids]
                 else:
-                    assert (
-                        len(ref_channel_ids) == 1
-                    ), "'ref_channel_ids' with no 'groups' must be a single channel id or a list of one element"
+                    assert len(ref_channel_ids) == 1, (
+                        "'ref_channel_ids' with no 'groups' must be a single channel id or a list of one element"
+                    )
                 ref_channel_ids = np.asarray(ref_channel_ids)
-                assert np.all(
-                    [ch in recording.channel_ids for ch in ref_channel_ids]
-                ), "Some 'ref_channel_ids' are wrong!"
+                assert np.all([ch in recording.channel_ids for ch in ref_channel_ids]), (
+                    "Some 'ref_channel_ids' are wrong!"
+                )
         elif reference == "local":
             assert groups is None, "With 'local' CAR, the group option should not be used."
             closest_inds, dist = get_closest_channels(recording)
diff --git a/src/spikeinterface/preprocessing/deepinterpolation/deepinterpolation.py b/src/spikeinterface/preprocessing/deepinterpolation/deepinterpolation.py
index e324048c5a..cc9802df90 100644
--- a/src/spikeinterface/preprocessing/deepinterpolation/deepinterpolation.py
+++ b/src/spikeinterface/preprocessing/deepinterpolation/deepinterpolation.py
@@ -64,9 +64,9 @@ def __init__(
         if parse(importlib.metadata.version("deepinterpolation")) < parse("0.2.0"):
             raise ImportError("DeepInterpolation version must be at least 0.2.0")
 
-        assert has_tf(
-            use_gpu, disable_tf_logger, memory_gpu
-        ), "To use DeepInterpolation, you first need to install `tensorflow`."
+        assert has_tf(use_gpu, disable_tf_logger, memory_gpu), (
+            "To use DeepInterpolation, you first need to install `tensorflow`."
+        )
 
         self.tf = import_tf(use_gpu, disable_tf_logger, memory_gpu=memory_gpu)
 
@@ -80,12 +80,12 @@ def __init__(
         # check shape (this will need to be done at inference)
         network_input_shape = model.get_config()["layers"][0]["config"]["batch_input_shape"]
         desired_shape = network_input_shape[1:3]
-        assert (
-            desired_shape[0] * desired_shape[1] == recording.get_num_channels()
-        ), "The desired shape of the network input must match the number of channels in the recording"
-        assert (
-            network_input_shape[-1] == pre_frame + post_frame
-        ), "The desired shape of the network input must match the pre and post frames"
+        assert desired_shape[0] * desired_shape[1] == recording.get_num_channels(), (
+            "The desired shape of the network input must match the number of channels in the recording"
+        )
+        assert network_input_shape[-1] == pre_frame + post_frame, (
+            "The desired shape of the network input must match the pre and post frames"
+        )
 
         self.model = model
         # add segment
diff --git a/src/spikeinterface/preprocessing/deepinterpolation/generators.py b/src/spikeinterface/preprocessing/deepinterpolation/generators.py
index dbf869997d..2520a62f39 100644
--- a/src/spikeinterface/preprocessing/deepinterpolation/generators.py
+++ b/src/spikeinterface/preprocessing/deepinterpolation/generators.py
@@ -28,9 +28,9 @@ def __init__(
             recordings = [recordings]
         self.recordings = recordings
         if len(recordings) > 1:
-            assert (
-                r.get_num_channels() == recordings[0].get_num_channels() for r in recordings[1:]
-            ), "All recordings must have the same number of channels"
+            assert (r.get_num_channels() == recordings[0].get_num_channels() for r in recordings[1:]), (
+                "All recordings must have the same number of channels"
+            )
 
         total_num_samples = sum([r.get_total_samples() for r in recordings])
         # In case of multiple recordings and/or multiple segments, we calculate the frame periods to be excluded (borders)
@@ -58,9 +58,9 @@ def __init__(
         )
         self.total_samples = int(total_valid_samples) if total_samples == -1 else total_samples
         assert len(desired_shape) == 2, "desired_shape should be 2D"
-        assert (
-            desired_shape[0] * desired_shape[1] == recording.get_num_channels()
-        ), f"The product of desired_shape dimensions should be the number of channels: {recording.get_num_channels()}"
+        assert desired_shape[0] * desired_shape[1] == recording.get_num_channels(), (
+            f"The product of desired_shape dimensions should be the number of channels: {recording.get_num_channels()}"
+        )
         self.desired_shape = desired_shape
 
         start_frame = start_frame if start_frame is not None else 0
diff --git a/src/spikeinterface/preprocessing/detect_artifacts.py b/src/spikeinterface/preprocessing/detect_artifacts.py
index 80aa88c73c..cbe5488bb9 100644
--- a/src/spikeinterface/preprocessing/detect_artifacts.py
+++ b/src/spikeinterface/preprocessing/detect_artifacts.py
@@ -671,9 +671,9 @@ def detect_artifact_periods(
             Array with dtype ``artifact_dtype`` describing each detected artifact
             period.
     """
-    assert (
-        method in _method_to_function
-    ), f"Method {method} not recognized. Valid methods are: {_method_to_function.keys()}"
+    assert method in _method_to_function, (
+        f"Method {method} not recognized. Valid methods are: {_method_to_function.keys()}"
+    )
     if method_kwargs is None:
         method_kwargs = dict()
 
diff --git a/src/spikeinterface/preprocessing/directional_derivative.py b/src/spikeinterface/preprocessing/directional_derivative.py
index f302708055..457c6edc69 100644
--- a/src/spikeinterface/preprocessing/directional_derivative.py
+++ b/src/spikeinterface/preprocessing/directional_derivative.py
@@ -5,7 +5,6 @@
 
 
 class DirectionalDerivativeRecording(BasePreprocessor):
-
     def __init__(
         self,
         recording: BaseRecording,
diff --git a/src/spikeinterface/preprocessing/highpass_spatial_filter.py b/src/spikeinterface/preprocessing/highpass_spatial_filter.py
index 979bb00908..838672ab4b 100644
--- a/src/spikeinterface/preprocessing/highpass_spatial_filter.py
+++ b/src/spikeinterface/preprocessing/highpass_spatial_filter.py
@@ -112,13 +112,13 @@ def __init__(
         # Fix channel padding and tapering
         n_channels = recording.get_num_channels()
         n_channel_pad = 0 if n_channel_pad is None else int(n_channel_pad)
-        assert (
-            n_channel_pad <= recording.get_num_channels()
-        ), "'n_channel_pad' must be less than the number of channels in recording."
+        assert n_channel_pad <= recording.get_num_channels(), (
+            "'n_channel_pad' must be less than the number of channels in recording."
+        )
         n_channel_taper = n_channel_pad if n_channel_taper is None else int(n_channel_taper)
-        assert (
-            n_channel_taper <= recording.get_num_channels()
-        ), "'n_channel_taper' must be less than the number of channels in recording."
+        assert n_channel_taper <= recording.get_num_channels(), (
+            "'n_channel_taper' must be less than the number of channels in recording."
+        )
 
         # Fix Automatic Gain Control options
         sampling_interval = 1 / recording.sampling_frequency
diff --git a/src/spikeinterface/preprocessing/phase_shift.py b/src/spikeinterface/preprocessing/phase_shift.py
index 273e828da3..949f200f30 100644
--- a/src/spikeinterface/preprocessing/phase_shift.py
+++ b/src/spikeinterface/preprocessing/phase_shift.py
@@ -69,9 +69,9 @@ def __init__(
             assert "inter_sample_shift" in recording.get_property_keys(), "'inter_sample_shift' is not a property!"
             sample_shifts = recording.get_property("inter_sample_shift")
         else:
-            assert (
-                len(inter_sample_shift) == recording.get_num_channels()
-            ), "the 'inter_sample_shift' must be same size at the num_channels "
+            assert len(inter_sample_shift) == recording.get_num_channels(), (
+                "the 'inter_sample_shift' must be same size at the num_channels "
+            )
             sample_shifts = np.asarray(inter_sample_shift)
 
         dtype = np.dtype(recording.get_dtype() if dtype is None else dtype)
diff --git a/src/spikeinterface/preprocessing/rectify.py b/src/spikeinterface/preprocessing/rectify.py
index 7bd91a16d9..1328e21dcf 100644
--- a/src/spikeinterface/preprocessing/rectify.py
+++ b/src/spikeinterface/preprocessing/rectify.py
@@ -6,7 +6,6 @@
 
 
 class RectifyRecording(BasePreprocessor):
-
     def __init__(self, recording):
         BasePreprocessor.__init__(self, recording)
         for parent_segment in recording.segments:
diff --git a/src/spikeinterface/preprocessing/remove_artifacts.py b/src/spikeinterface/preprocessing/remove_artifacts.py
index b20f1351b0..55584f3a13 100644
--- a/src/spikeinterface/preprocessing/remove_artifacts.py
+++ b/src/spikeinterface/preprocessing/remove_artifacts.py
@@ -125,9 +125,9 @@ def __init__(
         # some checks
         assert isinstance(list_triggers, list), "'list_triggers' must be a list (one per segment)"
         assert len(list_triggers) == num_seg, "'list_triggers' must have the same length as the number of segments"
-        assert all(
-            isinstance(list_triggers[i], (list, np.ndarray)) for i in range(num_seg)
-        ), "Each element of 'list_triggers' must be array-like"
+        assert all(isinstance(list_triggers[i], (list, np.ndarray)) for i in range(num_seg)), (
+            "Each element of 'list_triggers' must be array-like"
+        )
 
         if list_labels is not None:
             assert isinstance(list_labels, list), "'list_labels' must be a list (one per segment)"
@@ -163,9 +163,9 @@ def __init__(
                 for l in np.unique(labels):
                     assert l in artifacts.keys(), f"Artefacts are provided but label {l} has no value!"
             else:
-                assert (
-                    ms_before is not None and ms_after is not None
-                ), f"ms_before/after should not be None for mode {mode}"
+                assert ms_before is not None and ms_after is not None, (
+                    f"ms_before/after should not be None for mode {mode}"
+                )
                 sorting = NumpySorting.from_samples_and_labels(
                     list_triggers, list_labels, recording.get_sampling_frequency()
                 )
diff --git a/src/spikeinterface/preprocessing/tests/test_detect_bad_channels.py b/src/spikeinterface/preprocessing/tests/test_detect_bad_channels.py
index b9c3b83a6f..0de46b7c4f 100644
--- a/src/spikeinterface/preprocessing/tests/test_detect_bad_channels.py
+++ b/src/spikeinterface/preprocessing/tests/test_detect_bad_channels.py
@@ -113,13 +113,13 @@ def test_detect_bad_channels_std_mad():
     # Check that the number of segments is maintained after preprocessor
     assert np.array_equal(rec2.get_num_segments(), rec.get_num_segments()), "wrong numbber of segments."
     # Check that the size of the segments os maintained after preprocessor
-    assert np.array_equal(
-        *([r.get_num_frames(x) for x in range(rec.get_num_segments())] for r in [rec, rec2])
-    ), "wrong length of resulting segments."
+    assert np.array_equal(*([r.get_num_frames(x) for x in range(rec.get_num_segments())] for r in [rec, rec2])), (
+        "wrong length of resulting segments."
+    )
     # Check that locations are mantained
-    assert np.array_equal(
-        rec.get_channel_locations()[[0, 2, 3]], rec2.get_channel_locations()
-    ), "wrong channels locations."
+    assert np.array_equal(rec.get_channel_locations()[[0, 2, 3]], rec2.get_channel_locations()), (
+        "wrong channels locations."
+    )
 
 
 @pytest.mark.parametrize("pool_engine", ["thread", "process"])
diff --git a/src/spikeinterface/preprocessing/whiten.py b/src/spikeinterface/preprocessing/whiten.py
index d3fd699442..bbd30066a6 100644
--- a/src/spikeinterface/preprocessing/whiten.py
+++ b/src/spikeinterface/preprocessing/whiten.py
@@ -76,9 +76,9 @@ def __init__(
         dtype_ = fix_dtype(recording, dtype)
 
         if dtype_.kind == "i":
-            assert (
-                int_scale is not None
-            ), "For recording with dtype=int you must set the output dtype to float OR set a int_scale"
+            assert int_scale is not None, (
+                "For recording with dtype=int you must set the output dtype to float OR set a int_scale"
+            )
 
         if not apply_mean and regularize:
             raise ValueError("`apply_mean` must be `True` if regularising. `assume_centered` is fixed to `True`.")
diff --git a/src/spikeinterface/preprocessing/zero_channel_pad.py b/src/spikeinterface/preprocessing/zero_channel_pad.py
index 639e5ccced..fdcce72866 100644
--- a/src/spikeinterface/preprocessing/zero_channel_pad.py
+++ b/src/spikeinterface/preprocessing/zero_channel_pad.py
@@ -129,7 +129,6 @@ def get_num_samples(self):
 
 
 class ZeroChannelPaddedRecording(BaseRecording):
-
     def __init__(self, recording: BaseRecording, num_channels: int, channel_mapping: list | None = None):
         """Pads a recording with channels that contain only zero.
 
@@ -147,11 +146,11 @@ def __init__(self, recording: BaseRecording, num_channels: int, channel_mapping:
         BaseRecording.__init__(self, recording.get_sampling_frequency(), np.arange(num_channels), recording.get_dtype())
 
         if channel_mapping is not None:
-            assert (
-                len(channel_mapping) == recording.get_num_channels()
-            ), "The new mapping must be specified for all channels."
+            assert len(channel_mapping) == recording.get_num_channels(), (
+                "The new mapping must be specified for all channels."
+            )
             assert max(channel_mapping) < num_channels, (
-                "The new mapping cannot exceed total number of channels " "in the zero-chanenl-padded recording."
+                "The new mapping cannot exceed total number of channels in the zero-chanenl-padded recording."
             )
         else:
             if recording.has_probe():
diff --git a/src/spikeinterface/sorters/container_tools.py b/src/spikeinterface/sorters/container_tools.py
index a75ca57be7..df59f5b71b 100644
--- a/src/spikeinterface/sorters/container_tools.py
+++ b/src/spikeinterface/sorters/container_tools.py
@@ -102,7 +102,6 @@ def __init__(self, mode, container_image, volumes, py_user_base, extra_kwargs):
             elif Path(sif_file).exists():
                 singularity_image = sif_file
             else:
-
                 docker_image = Client.load("docker://" + container_image)
                 if docker_image and len(docker_image.tags) > 0:
                     tag = docker_image.tags[0]
@@ -116,7 +115,7 @@ def __init__(self, mode, container_image, volumes, py_user_base, extra_kwargs):
                 raise FileNotFoundError(f"Unable to locate container image {container_image}")
 
             # bin options
-            singularity_bind = ",".join([f'{volume_src}:{volume["bind"]}' for volume_src, volume in volumes.items()])
+            singularity_bind = ",".join([f"{volume_src}:{volume['bind']}" for volume_src, volume in volumes.items()])
             options = ["--bind", singularity_bind]
 
             # gpu options
@@ -278,6 +277,6 @@ def install_package_in_container(
         raise ValueError(f"install_package_incontainer, wrong installation_mode={installation_mode}")
 
     if isinstance(res_output, str) and "ERROR" in res_output.upper():
-        warnings.warn(f"pip install of {package_name} in container may have failed. " f"pip output:\n{res_output}")
+        warnings.warn(f"pip install of {package_name} in container may have failed. pip output:\n{res_output}")
 
     return res_output
diff --git a/src/spikeinterface/sorters/external/herdingspikes.py b/src/spikeinterface/sorters/external/herdingspikes.py
index 5f0bfa7dc1..c08907111d 100644
--- a/src/spikeinterface/sorters/external/herdingspikes.py
+++ b/src/spikeinterface/sorters/external/herdingspikes.py
@@ -128,9 +128,9 @@ def _run_from_folder(cls, sorter_output_folder, params, verbose):
         else:
             lightning_api = False
 
-        assert (
-            lightning_api
-        ), "HerdingSpikes version <0.4.1 is no longer supported. To upgrade, run:\n>>> pip install --upgrade herdingspikes"
+        assert lightning_api, (
+            "HerdingSpikes version <0.4.1 is no longer supported. To upgrade, run:\n>>> pip install --upgrade herdingspikes"
+        )
 
         recording = cls.load_recording_from_folder(sorter_output_folder.parent, with_warnings=False)
 
diff --git a/src/spikeinterface/sorters/external/kilosort.py b/src/spikeinterface/sorters/external/kilosort.py
index 1933be38d9..e80e439b17 100644
--- a/src/spikeinterface/sorters/external/kilosort.py
+++ b/src/spikeinterface/sorters/external/kilosort.py
@@ -256,9 +256,9 @@ def _get_specific_options(cls, ops, params) -> dict:
         ops["Th"] = params["Th"]  # threshold for detecting spikes on template-filtered data ([6 12 12])
         ops["lam"] = params["lam"]  # large means amplitudes are forced around the mean ([10 30 30])
         ops["nannealpasses"] = params["nannealpasses"]  # should be less than nfullpasses (4)
-        assert (
-            ops["nannealpasses"] < ops["nfullpasses"]
-        ), f"{ops['nannealpasses']=} should be less than {ops['nfullpasses']=}"
+        assert ops["nannealpasses"] < ops["nfullpasses"], (
+            f"{ops['nannealpasses']=} should be less than {ops['nfullpasses']=}"
+        )
         ops["momentum"] = params["momentum"]  # start with high momentum and anneal (1./[20 1000])
         ops["shuffle_clusters"] = params["shuffle_clusters"]  # allow merges and splits during optimization (1)
         ops["mergeT"] = params["mergeT"]  # upper threshold for merging (.1)
diff --git a/src/spikeinterface/sorters/external/kilosort2.py b/src/spikeinterface/sorters/external/kilosort2.py
index 6f4b0eec32..4ee92b5754 100644
--- a/src/spikeinterface/sorters/external/kilosort2.py
+++ b/src/spikeinterface/sorters/external/kilosort2.py
@@ -209,9 +209,9 @@ def _get_specific_options(cls, ops, params) -> dict:
         ops["skip_kilosort_preprocessing"] = params["skip_kilosort_preprocessing"]
         if params["skip_kilosort_preprocessing"]:
             ops["fproc"] = ops["fbinary"]
-            assert (
-                params["scaleproc"] is not None
-            ), "When skip_kilosort_preprocessing=True scaleproc must explicitly given"
+            assert params["scaleproc"] is not None, (
+                "When skip_kilosort_preprocessing=True scaleproc must explicitly given"
+            )
 
         # int16 scaling of whitened data, when None then scaleproc is set to 200.
         scaleproc = params["scaleproc"]
diff --git a/src/spikeinterface/sorters/external/kilosort2_5.py b/src/spikeinterface/sorters/external/kilosort2_5.py
index 06a1f07b11..23359796a1 100644
--- a/src/spikeinterface/sorters/external/kilosort2_5.py
+++ b/src/spikeinterface/sorters/external/kilosort2_5.py
@@ -232,9 +232,9 @@ def _get_specific_options(cls, ops, params) -> dict:
         ops["skip_kilosort_preprocessing"] = params["skip_kilosort_preprocessing"]
         if params["skip_kilosort_preprocessing"]:
             ops["fproc"] = ops["fbinary"]
-            assert (
-                params["scaleproc"] is not None
-            ), "When skip_kilosort_preprocessing=True scaleproc must explicitly given"
+            assert params["scaleproc"] is not None, (
+                "When skip_kilosort_preprocessing=True scaleproc must explicitly given"
+            )
 
         # int16 scaling of whitened data, when None then scaleproc is set to 200.
         scaleproc = params["scaleproc"]
diff --git a/src/spikeinterface/sorters/external/kilosort3.py b/src/spikeinterface/sorters/external/kilosort3.py
index 95cd145718..be405ae5fc 100644
--- a/src/spikeinterface/sorters/external/kilosort3.py
+++ b/src/spikeinterface/sorters/external/kilosort3.py
@@ -226,9 +226,9 @@ def _get_specific_options(cls, ops, params) -> dict:
         ops["skip_kilosort_preprocessing"] = params["skip_kilosort_preprocessing"]
         if params["skip_kilosort_preprocessing"]:
             ops["fproc"] = ops["fbinary"]
-            assert (
-                params["scaleproc"] is not None
-            ), "When skip_kilosort_preprocessing=True scaleproc must explicitly given"
+            assert params["scaleproc"] is not None, (
+                "When skip_kilosort_preprocessing=True scaleproc must explicitly given"
+            )
 
         # int16 scaling of whitened data, when None then scaleproc is set to 200.
         scaleproc = params["scaleproc"]
diff --git a/src/spikeinterface/sorters/external/kilosortbase.py b/src/spikeinterface/sorters/external/kilosortbase.py
index 15cbf4d3d0..68af4fa61e 100644
--- a/src/spikeinterface/sorters/external/kilosortbase.py
+++ b/src/spikeinterface/sorters/external/kilosortbase.py
@@ -226,9 +226,9 @@ def _run_from_folder(cls, sorter_output_folder, params, verbose):
             else:
                 tmp_files_to_remove = ()
         else:
-            assert isinstance(
-                params["delete_tmp_files"], (tuple, list)
-            ), "`delete_tmp_files` must be a `Bool`, `Tuple` or `List`."
+            assert isinstance(params["delete_tmp_files"], (tuple, list)), (
+                "`delete_tmp_files` must be a `Bool`, `Tuple` or `List`."
+            )
 
             for name in params["delete_tmp_files"]:
                 assert name in all_tmp_files, f"{name} is not a valid option, must be one of: {all_tmp_files}"
diff --git a/src/spikeinterface/sorters/external/mountainsort4.py b/src/spikeinterface/sorters/external/mountainsort4.py
index f2a0e585c2..95d8fc2f04 100644
--- a/src/spikeinterface/sorters/external/mountainsort4.py
+++ b/src/spikeinterface/sorters/external/mountainsort4.py
@@ -30,7 +30,7 @@ class Mountainsort4Sorter(BaseSorter):
     }
 
     _params_description = {
-        "detect_sign": "Use -1 (negative) or 1 (positive) depending " "on the sign of the spikes in the recording",
+        "detect_sign": "Use -1 (negative) or 1 (positive) depending on the sign of the spikes in the recording",
         # Use -1, 0, or 1, depending on the sign of the spikes in the recording
         "adjacency_radius": "Radius in um to build channel neighborhood "
         "(Use -1 to include all channels in every neighborhood)",
@@ -126,7 +126,7 @@ def _run_from_folder(cls, sorter_output_folder, params, verbose):
             if p["tempdir"] is not None:
                 p["tempdir"] = str(p["tempdir"])
             if verbose:
-                print(f'Using temporary directory {p["tempdir"]}')
+                print(f"Using temporary directory {p['tempdir']}")
             ms4_params.update(tempdir=p["tempdir"])
 
         # Check location no more needed done in basesorter
diff --git a/src/spikeinterface/sorters/external/tridesclous.py b/src/spikeinterface/sorters/external/tridesclous.py
index 95a9f2ef43..47c5d90878 100644
--- a/src/spikeinterface/sorters/external/tridesclous.py
+++ b/src/spikeinterface/sorters/external/tridesclous.py
@@ -31,7 +31,7 @@ class TridesclousSorter(BaseSorter):
         "freq_min": "High-pass filter cutoff frequency",
         "freq_max": "Low-pass filter cutoff frequency",
         "detect_threshold": "Threshold for spike detection",
-        "detect_sign": "Use -1 (negative) or 1 (positive) depending " "on the sign of the spikes in the recording",
+        "detect_sign": "Use -1 (negative) or 1 (positive) depending on the sign of the spikes in the recording",
         "common_ref_removal": "remove common reference with median",
     }
 
diff --git a/src/spikeinterface/sorters/launcher.py b/src/spikeinterface/sorters/launcher.py
index e1b5921746..8dc295e1fc 100644
--- a/src/spikeinterface/sorters/launcher.py
+++ b/src/spikeinterface/sorters/launcher.py
@@ -290,7 +290,7 @@ def run_sorter_by_property(
     working_folder = Path(folder).absolute()
 
     assert grouping_property in recording.get_property_keys(), (
-        f"The 'grouping_property' {grouping_property} is not " f"a recording property!"
+        f"The 'grouping_property' {grouping_property} is not a recording property!"
     )
     recording_dict = recording.split_by(grouping_property)
 
diff --git a/src/spikeinterface/sorters/tests/test_launcher.py b/src/spikeinterface/sorters/tests/test_launcher.py
index 6619431866..3e13fa0e24 100644
--- a/src/spikeinterface/sorters/tests/test_launcher.py
+++ b/src/spikeinterface/sorters/tests/test_launcher.py
@@ -16,7 +16,6 @@
 def create_recordings(folder, NUM_RECORDINGS=2, base_seed=42):
     recordings = []
     for i in range(NUM_RECORDINGS):
-
         recording, _ = generate_ground_truth_recording(num_channels=8, durations=[10.0], seed=base_seed + i)
         recording = recording.save(folder=folder / f"rec_for_generate_recording_{i}", format="binary", overwrite=True)
 
diff --git a/src/spikeinterface/sortingcomponents/clustering/graph_tools.py b/src/spikeinterface/sortingcomponents/clustering/graph_tools.py
index a76adec994..df38fdca10 100644
--- a/src/spikeinterface/sortingcomponents/clustering/graph_tools.py
+++ b/src/spikeinterface/sortingcomponents/clustering/graph_tools.py
@@ -58,7 +58,6 @@ def create_graph_from_peak_features(
     channel_locations = recording.get_channel_locations()
 
     if bin_mode == "channels":
-
         dims = ["xyz".index(i) for i in direction]
         channel_locs = channel_locations[:, dims]
         channel_distances = np.linalg.norm(channel_locs[:, np.newaxis] - channel_locs[np.newaxis, :], axis=2)
@@ -71,7 +70,6 @@ def create_graph_from_peak_features(
             loop.append((local_chans, neighbors_indices, target_local_inds))
 
     elif bin_mode == "vertical_bins":
-
         assert len(direction) == 1
         dim = "xyz".index(direction)
         channel_depth = channel_locations[:, dim]
@@ -92,7 +90,6 @@ def create_graph_from_peak_features(
 
         loop = []
         for b in range(bins.size - 1):
-
             # limits for peaks
             l0, l1 = bins[b], bins[b + 1]
             # mask = (peak_depths> l0) & (peak_depths<= l1)
diff --git a/src/spikeinterface/sortingcomponents/clustering/isosplit_isocut.py b/src/spikeinterface/sortingcomponents/clustering/isosplit_isocut.py
index c5dd6654ab..a6be2db181 100644
--- a/src/spikeinterface/sortingcomponents/clustering/isosplit_isocut.py
+++ b/src/spikeinterface/sortingcomponents/clustering/isosplit_isocut.py
@@ -42,7 +42,6 @@
 
 
 if HAVE_NUMBA:
-
     ##########################
     # isocut zone
 
@@ -284,7 +283,6 @@ def isosplit(
     """
 
     if initial_labels is None:
-
         if n_init >= X.shape[0]:
             # protect against too high n_init compared to sample size
             warnings.warn(f"isosplit : n_init {n_init} is too big compared to sample size {X.shape[0]}")
@@ -367,7 +365,6 @@ def isosplit(
                 break
 
             if active_labels.size > 1:
-
                 # Find the pairs to compare on this iteration
                 # These will be closest pairs of active clusters that have not yet
                 # been compared in this pass
diff --git a/src/spikeinterface/sortingcomponents/clustering/iterative_isosplit.py b/src/spikeinterface/sortingcomponents/clustering/iterative_isosplit.py
index 002de2feeb..4ca8c3616a 100644
--- a/src/spikeinterface/sortingcomponents/clustering/iterative_isosplit.py
+++ b/src/spikeinterface/sortingcomponents/clustering/iterative_isosplit.py
@@ -271,7 +271,6 @@ def main_function(cls, recording, peaks, params, job_kwargs=dict()):
         # templates_array = dense_templates.templates_array
 
         if params["merge_from_features"] is not None:
-
             merge_from_features_kwargs = params["merge_from_features"].copy()
             merge_radius_um = merge_from_features_kwargs.pop("merge_radius_um")
 
diff --git a/src/spikeinterface/sortingcomponents/matching/base.py b/src/spikeinterface/sortingcomponents/matching/base.py
index 3288417173..e4efa41948 100644
--- a/src/spikeinterface/sortingcomponents/matching/base.py
+++ b/src/spikeinterface/sortingcomponents/matching/base.py
@@ -16,9 +16,9 @@ def __init__(self, recording, templates, return_output=True):
         # TODO make a sharedmem of template here
         # TODO maybe check that channel_id are the same with recording
 
-        assert isinstance(
-            templates, Templates
-        ), f"The templates supplied is of type {type(templates)} and must be a Templates"
+        assert isinstance(templates, Templates), (
+            f"The templates supplied is of type {type(templates)} and must be a Templates"
+        )
         self.templates = templates
         self.recording = recording
         PeakDetector.__init__(self, recording, return_output=return_output, parents=None)
diff --git a/src/spikeinterface/sortingcomponents/matching/wobble.py b/src/spikeinterface/sortingcomponents/matching/wobble.py
index e9ee961c3e..9a42f3d9b3 100644
--- a/src/spikeinterface/sortingcomponents/matching/wobble.py
+++ b/src/spikeinterface/sortingcomponents/matching/wobble.py
@@ -171,9 +171,9 @@ def from_parameters_and_templates(cls, params, templates):
         if params.template_indices2unit_indices is None:  # Trivial grouping of templates = units
             template_indices2unit_indices = np.arange(num_templates)
         else:
-            assert params.template_indices2unit_indices.shape == (
-                templates.shape[0],
-            ), "template_indices2unit_indices must have shape (num_templates,)"
+            assert params.template_indices2unit_indices.shape == (templates.shape[0],), (
+                "template_indices2unit_indices must have shape (num_templates,)"
+            )
             template_indices2unit_indices = params.template_indices2unit_indices
         unit_indices = np.unique(template_indices2unit_indices)
         num_units = len(unit_indices)
diff --git a/src/spikeinterface/sortingcomponents/motion/dredge.py b/src/spikeinterface/sortingcomponents/motion/dredge.py
index 6d9cc1afdf..b6a0529776 100644
--- a/src/spikeinterface/sortingcomponents/motion/dredge.py
+++ b/src/spikeinterface/sortingcomponents/motion/dredge.py
@@ -296,7 +296,6 @@ def dredge_ap(
     threshold_kw = dict(bin_s=bin_s)
 
     if batching_mode == "full":
-
         displacement, extra = compute_displacement_full(
             raster,
             windows,
@@ -313,7 +312,6 @@ def dredge_ap(
         )
 
     elif batching_mode == "online":
-
         # T_total is number of bin_s in recording
         T_total = raster.shape[1]
         T_chunk = max(1, int(np.ceil(chunk_len_s / bin_s)))
diff --git a/src/spikeinterface/sortingcomponents/motion/motion_interpolation.py b/src/spikeinterface/sortingcomponents/motion/motion_interpolation.py
index 0eb63b8b6b..dc2b9ae2a2 100644
--- a/src/spikeinterface/sortingcomponents/motion/motion_interpolation.py
+++ b/src/spikeinterface/sortingcomponents/motion/motion_interpolation.py
@@ -359,8 +359,7 @@ def __init__(
 
         channel_locations = recording.get_channel_locations()
         assert channel_locations.ndim >= motion.dim, (
-            f"'direction' {motion.direction} not available. "
-            f"Channel locations have {channel_locations.ndim} dimensions."
+            f"'direction' {motion.direction} not available. Channel locations have {channel_locations.ndim} dimensions."
         )
         spatial_interpolation_kwargs = dict(
             sigma_um=sigma_um, p=p, num_closest=num_closest, **spatial_interpolation_kwargs
diff --git a/src/spikeinterface/sortingcomponents/peak_localization/base.py b/src/spikeinterface/sortingcomponents/peak_localization/base.py
index 5e6a16fe4c..04d4307ffc 100644
--- a/src/spikeinterface/sortingcomponents/peak_localization/base.py
+++ b/src/spikeinterface/sortingcomponents/peak_localization/base.py
@@ -6,7 +6,6 @@
 
 
 class LocalizeBase(PipelineNode):
-
     def __init__(self, recording, parents, return_output=True, radius_um=75.0):
         PipelineNode.__init__(self, recording, parents=parents, return_output=return_output)
         self.recording = recording
diff --git a/src/spikeinterface/sortingcomponents/peak_selection.py b/src/spikeinterface/sortingcomponents/peak_selection.py
index 018e627217..b260e7ef5e 100644
--- a/src/spikeinterface/sortingcomponents/peak_selection.py
+++ b/src/spikeinterface/sortingcomponents/peak_selection.py
@@ -288,7 +288,7 @@ def select_peak_indices(peaks, method, seed, **method_kwargs):
 
     else:
         raise NotImplementedError(
-            f"The 'method' {method} does not exist for peaks selection." f" possible methods are {_possible_methods}"
+            f"The 'method' {method} does not exist for peaks selection. possible methods are {_possible_methods}"
         )
 
     selected_indices = np.concatenate(selected_indices)
diff --git a/src/spikeinterface/sortingcomponents/waveforms/waveform_thresholder.py b/src/spikeinterface/sortingcomponents/waveforms/waveform_thresholder.py
index ec223d0047..b6fb38350b 100644
--- a/src/spikeinterface/sortingcomponents/waveforms/waveform_thresholder.py
+++ b/src/spikeinterface/sortingcomponents/waveforms/waveform_thresholder.py
@@ -59,7 +59,7 @@ def __init__(
             parents=parents,
         )
         assert feature in ["ptp", "mean", "energy", "peak_voltage"], (
-            f"{feature} is not a valid feature" " must be one of 'ptp', 'mean', 'energy'," " or 'peak_voltage'"
+            f"{feature} is not a valid feature must be one of 'ptp', 'mean', 'energy', or 'peak_voltage'"
         )
 
         self.threshold = threshold
diff --git a/src/spikeinterface/widgets/motion.py b/src/spikeinterface/widgets/motion.py
index a08c4b789a..4ac8c9b030 100644
--- a/src/spikeinterface/widgets/motion.py
+++ b/src/spikeinterface/widgets/motion.py
@@ -180,9 +180,9 @@ def __init__(
                 recording = None
                 sampling_frequency = sorting_analyzer.sampling_frequency
             peaks = sorting_analyzer.sorting.to_spike_vector()
-            assert sorting_analyzer.has_extension(
-                "spike_locations"
-            ), "The sorting analyzer must have the 'spike_locations' extension to use this function"
+            assert sorting_analyzer.has_extension("spike_locations"), (
+                "The sorting analyzer must have the 'spike_locations' extension to use this function"
+            )
             peak_locations = sorting_analyzer.get_extension("spike_locations").get_data()
             if color_amplitude:
                 assert sorting_analyzer.has_extension("spike_amplitudes"), (
@@ -348,9 +348,9 @@ def __init__(
                 raise ValueError(
                     "plot drift map : the Motion object is multi-segment you must provide segment_index=XX"
                 )
-        assert recording.get_num_segments() == len(
-            motion.displacement
-        ), "The number of segments in the recording must be the same as the number of segments in the motion object"
+        assert recording.get_num_segments() == len(motion.displacement), (
+            "The number of segments in the recording must be the same as the number of segments in the motion object"
+        )
 
         plot_data = dict(
             sampling_frequency=motion_info["parameters"]["sampling_frequency"],

From f23e7d2052d1c73556f0c3c26a896190137b7013 Mon Sep 17 00:00:00 2001
From: Alessio Buccino <alejoe9187@gmail.com>
Date: Mon, 9 Nov 2026 15:24:04 +0100
Subject: [PATCH 18/30] fix: installation tips

---
 installation_tips/check_your_install.py | 4 ++--
 pyproject.toml                          | 2 +-
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/installation_tips/check_your_install.py b/installation_tips/check_your_install.py
index 1778f6bdac..cf9ffe65fd 100644
--- a/installation_tips/check_your_install.py
+++ b/installation_tips/check_your_install.py
@@ -11,11 +11,11 @@
 
 
 def check_import_si():
-    pass
+    import spikeinterface as si
 
 
 def check_import_si_full():
-    pass
+    import spikeinterface.full as si
 
 
 def _create_recording(short=False):
diff --git a/pyproject.toml b/pyproject.toml
index 6224c5411c..bcef87b34e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -55,7 +55,7 @@ exclude = ["spikeinterface.*.tests"]
 line-length = 120
 [tool.ruff.lint]
 select = ['E4', 'E7', 'E9', 'F']
-exclude = ["**/tests/**", "**/test_*.py", "**/conftest.py", "examples/**", "doc/conf.py"]
+exclude = ["**/tests/**", "**/test_*.py", "**/conftest.py", "examples/**", "doc/conf.py", "installation_tips/**"]
 ignore = ['E741', 'E731', 'F821']
 [tool.ruff.lint.per-file-ignores]
 "**/__init__.py" = ['F401', 'F403']

From 88ae0b8eb539026bf9157d4753c0156ac1ed716f Mon Sep 17 00:00:00 2001
From: Alessio Buccino <alejoe9187@gmail.com>
Date: Mon, 9 Nov 2026 15:34:06 +0100
Subject: [PATCH 19/30] fix: extractor_classes

---
 pyproject.toml                                     | 1 +
 src/spikeinterface/extractors/extractor_classes.py | 7 +++++++
 src/spikeinterface/postprocessing/__init__.py      | 2 --
 src/spikeinterface/postprocessing/noise_level.py   | 2 --
 4 files changed, 8 insertions(+), 4 deletions(-)
 delete mode 100644 src/spikeinterface/postprocessing/noise_level.py

diff --git a/pyproject.toml b/pyproject.toml
index bcef87b34e..a914983b09 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -61,6 +61,7 @@ ignore = ['E741', 'E731', 'F821']
 "**/__init__.py" = ['F401', 'F403']
 "src/spikeinterface/full.py" = ['F403']
 "src/spikeinterface/core/testing_tools.py" = ['E402', 'F403']
+"src/spikeinterface/extractors/extractor_classes.py" = ['F401', 'F403']
 
 [project.urls]
 homepage = "https://github.com/SpikeInterface/spikeinterface"
diff --git a/src/spikeinterface/extractors/extractor_classes.py b/src/spikeinterface/extractors/extractor_classes.py
index e46ebbf0a2..b28bfb7fa0 100644
--- a/src/spikeinterface/extractors/extractor_classes.py
+++ b/src/spikeinterface/extractors/extractor_classes.py
@@ -5,16 +5,22 @@
     NumpyRecording,
     NpzSortingExtractor,
     NumpySorting,
+    read_binary,
+    read_zarr,
     read_npz_sorting,
 )
 
 from spikeinterface.core.zarrextractors import (
     ZarrRecordingExtractor,
     ZarrSortingExtractor,
+    read_zarr_array,
 )
 
 # sorting/recording/event from neo
+from .neoextractors import *
 from .neoextractors import neo_recording_extractors_dict, neo_sorting_extractors_dict, neo_event_extractors_dict
+from .neoextractors import read_neuroscope
+from .neoextractors.intan import read_split_intan_files, IntanSplitFilesRecordingExtractor
 
 # non-NEO objects implemented in neo folder
 # keep for reference Currently pulling from neoextractor __init__
@@ -25,6 +31,7 @@
     NwbRecordingExtractor,
     NwbSortingExtractor,
     NwbTimeSeriesExtractor,
+    read_nwb,
     read_nwb_recording,
     read_nwb_sorting,
     read_nwb_timeseries,
diff --git a/src/spikeinterface/postprocessing/__init__.py b/src/spikeinterface/postprocessing/__init__.py
index 2495536d03..fc5c878fe0 100644
--- a/src/spikeinterface/postprocessing/__init__.py
+++ b/src/spikeinterface/postprocessing/__init__.py
@@ -41,8 +41,6 @@
 
 from .alignsorting import align_sorting, AlignSortingExtractor
 
-from .noise_level import compute_noise_levels, ComputeNoiseLevels
-
 from .valid_unit_periods import (
     ComputeValidUnitPeriods,
     compute_valid_unit_periods,
diff --git a/src/spikeinterface/postprocessing/noise_level.py b/src/spikeinterface/postprocessing/noise_level.py
deleted file mode 100644
index 84c6a3ae7e..0000000000
--- a/src/spikeinterface/postprocessing/noise_level.py
+++ /dev/null
@@ -1,2 +0,0 @@
-# "noise_levels" extensions is now in core
-# this is kept name space compatibility but should be removed soon

From 54f5fef3e062a6c10735f0b478f354edf59e87bc Mon Sep 17 00:00:00 2001
From: Alessio Buccino <alejoe9187@gmail.com>
Date: Mon, 9 Nov 2026 16:32:10 +0100
Subject: [PATCH 20/30] fix: add from spikeinterface.core.basesorting import
 LEXSORT_UNIT_COMPACT back

---
 src/spikeinterface/core/tests/test_basesorting.py  | 1 +
 src/spikeinterface/extractors/extractor_classes.py | 1 -
 2 files changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/spikeinterface/core/tests/test_basesorting.py b/src/spikeinterface/core/tests/test_basesorting.py
index b153619b78..3a1986e353 100644
--- a/src/spikeinterface/core/tests/test_basesorting.py
+++ b/src/spikeinterface/core/tests/test_basesorting.py
@@ -22,6 +22,7 @@
     load,
 )
 from spikeinterface.core.base import BaseExtractor, minimum_spike_dtype, unit_period_dtype
+from spikeinterface.core.basesorting import LEXSORT_UNIT_COMPACT
 from spikeinterface.core.testing import check_sorted_arrays_equal, check_sortings_equal
 
 
diff --git a/src/spikeinterface/extractors/extractor_classes.py b/src/spikeinterface/extractors/extractor_classes.py
index b28bfb7fa0..e398300f8e 100644
--- a/src/spikeinterface/extractors/extractor_classes.py
+++ b/src/spikeinterface/extractors/extractor_classes.py
@@ -19,7 +19,6 @@
 # sorting/recording/event from neo
 from .neoextractors import *
 from .neoextractors import neo_recording_extractors_dict, neo_sorting_extractors_dict, neo_event_extractors_dict
-from .neoextractors import read_neuroscope
 from .neoextractors.intan import read_split_intan_files, IntanSplitFilesRecordingExtractor
 
 # non-NEO objects implemented in neo folder

From ac3eed592024834f1b7a9b3a12f1ca4af56b50a6 Mon Sep 17 00:00:00 2001
From: Alessio Buccino <alejoe9187@gmail.com>
Date: Mon, 9 Nov 2026 16:44:31 +0100
Subject: [PATCH 21/30] fix a couple of F821 errors

---
 pyproject.toml                                |   1 +
 .../sortingcomponents/matching/circus.py      | 222 +-----------------
 .../sortingcomponents/matching/main.py        |   6 +-
 3 files changed, 5 insertions(+), 224 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index a914983b09..ba1ba84525 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -53,6 +53,7 @@ exclude = ["spikeinterface.*.tests"]
 
 [tool.ruff]
 line-length = 120
+force-exclude = true
 [tool.ruff.lint]
 select = ['E4', 'E7', 'E9', 'F']
 exclude = ["**/tests/**", "**/test_*.py", "**/conftest.py", "examples/**", "doc/conf.py", "installation_tips/**"]
diff --git a/src/spikeinterface/sortingcomponents/matching/circus.py b/src/spikeinterface/sortingcomponents/matching/circus.py
index 9e537ca33c..72706dd5f3 100644
--- a/src/spikeinterface/sortingcomponents/matching/circus.py
+++ b/src/spikeinterface/sortingcomponents/matching/circus.py
@@ -386,6 +386,7 @@ def compute_matching(self, traces, start_frame, end_frame, segment_index):
         all_selections = np.empty((2, scalar_products.size), dtype=np.int32)
         final_amplitudes = np.zeros(scalar_products.shape, dtype=np.float32)
         num_selection = 0
+        selection = all_selections[:, :0]  # empty until the first peak is picked
 
         full_sps = scalar_products.copy()
 
@@ -571,224 +572,3 @@ def __del__(self):
             self.overlaps = None
             self.shm.close()
             self.shm = None
-
-
-class CircusPeeler(BaseTemplateMatching):
-    """
-    Greedy Template-matching ported from the Spyking Circus sorter
-
-    https://elifesciences.org/articles/34518
-
-    This is a Greedy Template Matching algorithm. The idea is to detect
-    all the peaks (negative, positive or both) above a certain threshold
-    Then, at every peak (plus or minus some jitter) we look if the signal
-    can be explained with a scaled template.
-    The amplitudes allowed, for every templates, are automatically adjusted
-    in an optimal manner, to enhance the Matthew Correlation Coefficient
-    between all spikes/templates in the waveformextractor. For speed and
-    memory optimization, templates are automatically sparsified if the
-    density of the matrix falls below a given threshold
-
-    Parameters
-    ----------
-    peak_sign : str
-        Sign of the peak (neg, pos, or both)
-    exclude_sweep_ms : float
-        The number of samples before/after to classify a peak (should be low)
-    jitter : int
-        The number of samples considered before/after every peak to search for
-        matches
-    detect_threshold : int
-        The detection threshold
-    max_amplitude : float
-        Maximal amplitude allowed for every template
-    min_amplitude : float
-        Minimal amplitude allowed for every template
-    use_sparse_matrix_threshold : float
-        If density of the templates is below a given threshold, sparse matrix
-        are used (memory efficient)
-    sparse_kwargs : dict
-        Parameters to extract a sparsity mask from the waveform_extractor, if not
-        already sparse.
-    -----
-
-
-    """
-
-    def __init__(
-        self,
-        recording,
-        return_output=True,
-        templates=None,
-        peak_sign="neg",
-        exclude_sweep_ms=0.8,
-        jitter_ms=0.1,
-        detect_threshold=5,
-        noise_levels=None,
-        max_amplitude=1.5,
-        min_amplitude=0.5,
-        use_sparse_matrix_threshold=0.25,
-    ):
-
-        BaseTemplateMatching.__init__(self, recording, templates, return_output=return_output)
-        sklearn_spec = importlib.util.find_spec("sklearn") is not None
-        if sklearn_spec is not None:
-            HAVE_SKLEARN = True
-        else:
-            HAVE_SKLEARN = False
-
-        assert HAVE_SKLEARN, "CircusPeeler needs sklearn to work"
-
-        assert (use_sparse_matrix_threshold >= 0) and (use_sparse_matrix_threshold <= 1), (
-            "use_sparse_matrix_threshold should be in [0, 1]"
-        )
-
-        self.num_channels = recording.get_num_channels()
-        self.num_samples = templates.num_samples
-        self.num_templates = len(templates.unit_ids)
-
-        self.abs_threholds = noise_levels * detect_threshold
-
-        self.use_sparse_matrix_threshold = use_sparse_matrix_threshold
-        self._prepare_templates()
-        self.overlaps = compute_overlaps(
-            self.normed_templates,
-            self.num_samples,
-            self.num_channels,
-            self.sparsities,
-        )
-
-        self.exclude_sweep_size = int(exclude_sweep_ms * recording.get_sampling_frequency() / 1000.0)
-
-        self.nbefore = templates.nbefore
-        self.nafter = templates.nafter
-        self.patch_sizes = (templates.num_samples, self.num_channels)
-        self.sym_patch = self.nbefore == self.nafter
-        self.jitter = int(jitter_ms * recording.get_sampling_frequency() / 1000.0)
-
-        self.amplitudes = np.zeros((self.num_templates, 2), dtype=np.float32)
-        self.amplitudes[:, 0] = min_amplitude
-        self.amplitudes[:, 1] = max_amplitude
-
-        self.margin = max(self.nbefore, self.nafter) * 2
-        self.peak_sign = peak_sign
-
-    def _prepare_templates(self):
-
-        from scipy.sparse import csr_matrix
-
-        self.norms = np.zeros(self.num_templates, dtype=np.float32)
-
-        all_units = self.templates.unit_ids
-
-        sparsity = self.templates.sparsity.mask
-
-        templates_array = self.templates.get_dense_templates()
-        self.sparsities = {}
-        self.normed_templates = {}
-
-        for count, unit_id in enumerate(all_units):
-            self.sparsities[count] = np.flatnonzero(sparsity[count])
-            self.norms[count] = np.linalg.norm(templates_array[count])
-            templates_array[count] /= self.norms[count]
-            self.normed_templates[count] = templates_array[count][:, sparsity[count]]
-
-        templates_array = templates_array.reshape(self.num_templates, -1)
-
-        nnz = np.sum(templates_array != 0) / (self.num_templates * self.num_samples * self.num_channels)
-        if nnz <= self.use_sparse_matrix_threshold:
-            templates_array = csr_matrix(templates_array)
-            print(f"Templates are automatically sparsified (sparsity level is {nnz})")
-            self.is_dense = False
-        else:
-            self.is_dense = True
-
-        self.circus_templates = templates_array
-
-    def get_margin(self):
-        return self.margin
-
-    def compute_matching(self, traces, start_frame, end_frame, segment_index):
-
-        neighbor_window = self.num_samples - 1
-
-        peak_traces = traces[self.margin // 2 : -self.margin // 2, :]
-        peak_sample_index, peak_chan_ind = DetectPeakByChannel.detect_peaks(
-            peak_traces, self.peak_sign, self.abs_threholds, self.exclude_sweep_size
-        )
-        from sklearn.feature_extraction.image import extract_patches_2d
-
-        if self.jitter > 0:
-            jittered_peaks = peak_sample_index[:, np.newaxis] + np.arange(-self.jitter, self.jitter)
-            jittered_channels = peak_chan_ind[:, np.newaxis] + np.zeros(2 * self.jitter)
-            mask = (jittered_peaks > 0) & (jittered_peaks < len(peak_traces))
-            jittered_peaks = jittered_peaks[mask]
-            jittered_channels = jittered_channels[mask]
-            peak_sample_index, unique_idx = np.unique(jittered_peaks, return_index=True)
-            peak_chan_ind = jittered_channels[unique_idx]
-        else:
-            peak_sample_index, unique_idx = np.unique(peak_sample_index, return_index=True)
-            peak_chan_ind = peak_chan_ind[unique_idx]
-
-        num_peaks = len(peak_sample_index)
-
-        if self.sym_patch:
-            snippets = extract_patches_2d(traces, self.patch_sizes)[peak_sample_index]
-            peak_sample_index += self.margin // 2
-        else:
-            peak_sample_index += self.margin // 2
-            snippet_window = np.arange(-self.nbefore, self.nafter)
-            snippets = traces[peak_sample_index[:, np.newaxis] + snippet_window]
-
-        if num_peaks > 0:
-            snippets = snippets.reshape(num_peaks, -1)
-            scalar_products = self.circus_templates.dot(snippets.T)
-        else:
-            scalar_products = np.zeros((self.num_templates, 0), dtype=np.float32)
-
-        num_spikes = 0
-        spikes = np.empty(scalar_products.size, dtype=spike_dtype)
-        idx_lookup = np.arange(scalar_products.size).reshape(self.num_templates, -1)
-
-        min_sps = (self.amplitudes[:, 0] * self.norms)[:, np.newaxis]
-        max_sps = (self.amplitudes[:, 1] * self.norms)[:, np.newaxis]
-
-        is_valid = (scalar_products > min_sps) & (scalar_products < max_sps)
-
-        cached_overlaps = {}
-
-        while np.any(is_valid):
-            best_amplitude_ind = scalar_products[is_valid].argmax()
-            best_cluster_ind, peak_index = np.unravel_index(idx_lookup[is_valid][best_amplitude_ind], idx_lookup.shape)
-
-            best_amplitude = scalar_products[best_cluster_ind, peak_index]
-            best_peak_sample_index = peak_sample_index[peak_index]
-            best_peak_chan_ind = peak_chan_ind[peak_index]
-
-            peak_data = peak_sample_index - peak_sample_index[peak_index]
-            is_valid_nn = np.searchsorted(peak_data, [-neighbor_window, neighbor_window + 1])
-            idx_neighbor = peak_data[is_valid_nn[0] : is_valid_nn[1]] + neighbor_window
-
-            if best_cluster_ind not in cached_overlaps.keys():
-                cached_overlaps[best_cluster_ind] = self.overlaps[best_cluster_ind].toarray()
-
-            to_add = -best_amplitude * cached_overlaps[best_cluster_ind][:, idx_neighbor]
-
-            scalar_products[:, is_valid_nn[0] : is_valid_nn[1]] += to_add
-            scalar_products[best_cluster_ind, is_valid_nn[0] : is_valid_nn[1]] = -np.inf
-
-            spikes["sample_index"][num_spikes] = best_peak_sample_index
-            spikes["channel_index"][num_spikes] = best_peak_chan_ind
-            spikes["cluster_index"][num_spikes] = best_cluster_ind
-            spikes["amplitude"][num_spikes] = best_amplitude
-            num_spikes += 1
-
-            is_valid = (scalar_products > min_sps) & (scalar_products < max_sps)
-
-        spikes["amplitude"][:num_spikes] /= self.norms[spikes["cluster_index"][:num_spikes]]
-
-        spikes = spikes[:num_spikes]
-        order = np.argsort(spikes["sample_index"])
-        spikes = spikes[order]
-
-        return spikes
diff --git a/src/spikeinterface/sortingcomponents/matching/main.py b/src/spikeinterface/sortingcomponents/matching/main.py
index 46dae15ad7..ec54f91bc7 100644
--- a/src/spikeinterface/sortingcomponents/matching/main.py
+++ b/src/spikeinterface/sortingcomponents/matching/main.py
@@ -64,9 +64,6 @@ def find_spikes_from_templates(
     # if method_class.full_convolution:
     #   Maybe we need to automatically adjust the temporal chunks given templates and n_processes
 
-    if len(templates.unit_ids) == 0:
-        return np.zeros(0, dtype=node0.get_dtype())
-
     if method_class.need_noise_levels:
         if "noise_levels" not in method_kwargs:
             raise ValueError(f"find_spikes_from_templates() method {method} need noise_levels")
@@ -74,6 +71,9 @@ def find_spikes_from_templates(
     node0 = method_class(recording, templates=templates, **method_kwargs)
     nodes = [node0]
 
+    if len(templates.unit_ids) == 0:
+        return np.zeros(0, dtype=node0.get_dtype())
+
     if pipeline_kwargs is None:
         pipeline_kwargs = dict()
 

From 7061477e6cb1433791138b8617f7074d32e4f950 Mon Sep 17 00:00:00 2001
From: Alessio Buccino <alejoe9187@gmail.com>
Date: Mon, 9 Nov 2026 17:12:06 +0100
Subject: [PATCH 22/30] fix: MDA read test

---
 src/spikeinterface/extractors/mdaextractors.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/src/spikeinterface/extractors/mdaextractors.py b/src/spikeinterface/extractors/mdaextractors.py
index b5b744e568..639c77597f 100644
--- a/src/spikeinterface/extractors/mdaextractors.py
+++ b/src/spikeinterface/extractors/mdaextractors.py
@@ -489,6 +489,7 @@ def _read_header(path):
     f = open(path, "rb")
     try:
         dt_code = _read_int32(f)
+        _read_int32(f)  # num_bytes_per_entry: unused, but must be read to advance the file pointer
         num_dims = _read_int32(f)
         uses64bitdims = False
         if num_dims < 0:
@@ -815,6 +816,7 @@ def _write_int64(f, val):
 def _header_from_file(f):
     try:
         dt_code = _read_int32(f)
+        _read_int32(f)  # num_bytes_per_entry: unused, but must be read to advance the file pointer
         num_dims = _read_int32(f)
         uses64bitdims = False
         if num_dims < 0:

From 13fbcbe9ab5a2f5bf481d719cf78290360153f55 Mon Sep 17 00:00:00 2001
From: Alessio Buccino <alejoe9187@gmail.com>
Date: Mon, 9 Nov 2026 17:27:21 +0100
Subject: [PATCH 23/30] fix: curation imputer

---
 src/spikeinterface/curation/train_manual_curation.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/src/spikeinterface/curation/train_manual_curation.py b/src/spikeinterface/curation/train_manual_curation.py
index d9b7dcc4eb..f6dd01e161 100644
--- a/src/spikeinterface/curation/train_manual_curation.py
+++ b/src/spikeinterface/curation/train_manual_curation.py
@@ -386,6 +386,7 @@ def process_test_data_for_classification(self):
 
     def apply_scaling_imputation(self, imputation_strategy, scaling_technique, X_train, X_test, y_train, y_test):
         """Impute and scale the data using the specified techniques."""
+        from sklearn.experimental import enable_iterative_imputer  # noqa: F401  (side-effect import, required by IterativeImputer)
         from sklearn.impute import SimpleImputer, KNNImputer, IterativeImputer
         from sklearn.ensemble import HistGradientBoostingRegressor
         from sklearn.preprocessing import StandardScaler, MinMaxScaler, RobustScaler

From ac0e62f910770a4219f4e7aa2d1b7f3580e3c4a5 Mon Sep 17 00:00:00 2001
From: Alessio Buccino <alejoe9187@gmail.com>
Date: Mon, 9 Nov 2026 17:49:57 +0100
Subject: [PATCH 24/30] fix: restore spython and docker imports in tests

---
 .../sorters/tests/test_runsorter_dependency_checks.py         | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/spikeinterface/sorters/tests/test_runsorter_dependency_checks.py b/src/spikeinterface/sorters/tests/test_runsorter_dependency_checks.py
index cae63fbe50..af164b3f2a 100644
--- a/src/spikeinterface/sorters/tests/test_runsorter_dependency_checks.py
+++ b/src/spikeinterface/sorters/tests/test_runsorter_dependency_checks.py
@@ -71,9 +71,9 @@ def uninstall_python_dependency(self, request):
 
         try:
             if dep_name == "spython":
-                pass
+                import spython  # noqa: F401
             else:
-                pass
+                import docker  # noqa: F401
             dependency_installed = True
         except Exception:
             dependency_installed = False

From 68dc02f3e9029eef6522d32c4790d8f8a986baee Mon Sep 17 00:00:00 2001
From: Alessio Buccino <alejoe9187@gmail.com>
Date: Tue, 10 Nov 2026 09:51:18 +0100
Subject: [PATCH 25/30] fix: move curation fixtures to conftest.py

---
 src/spikeinterface/curation/tests/conftest.py | 65 +++++++++++++++++++
 1 file changed, 65 insertions(+)
 create mode 100644 src/spikeinterface/curation/tests/conftest.py

diff --git a/src/spikeinterface/curation/tests/conftest.py b/src/spikeinterface/curation/tests/conftest.py
new file mode 100644
index 0000000000..a299219bb3
--- /dev/null
+++ b/src/spikeinterface/curation/tests/conftest.py
@@ -0,0 +1,65 @@
+import pytest
+from pathlib import Path
+
+from spikeinterface.core import generate_ground_truth_recording, create_sorting_analyzer, aggregate_units
+from spikeinterface.curation import train_model
+from spikeinterface.curation.tests.common import make_sorting_analyzer, make_sorting_analyzer_with_splits
+
+
+@pytest.fixture(scope="module")
+def sorting_analyzer_for_curation():
+    return make_sorting_analyzer(sparse=True)
+
+
+@pytest.fixture(scope="module")
+def sorting_analyzer_for_unitrefine_curation():
+    """Makes an analyzer whose first 10 units are good normal units, and 10 which are noise. We make them
+    noise by using a spike trains which are uncorrelated with the recording for `sorting2`."""
+
+    recording, sorting_1 = generate_ground_truth_recording(num_channels=4, seed=1, num_units=6)
+    _, sorting_2 = generate_ground_truth_recording(num_channels=4, seed=2, num_units=6)
+    both_sortings = aggregate_units([sorting_1, sorting_2])
+    analyzer = create_sorting_analyzer(sorting=both_sortings, recording=recording)
+    analyzer.compute(["random_spikes", "noise_levels", "templates"])
+    return analyzer
+
+
+@pytest.fixture(scope="module")
+def sorting_analyzer_multi_segment_for_curation():
+    return make_sorting_analyzer(sparse=True, durations=[50.0, 30.0])
+
+
+@pytest.fixture(scope="module")
+def sorting_analyzer_with_splits():
+    sorting_analyzer = make_sorting_analyzer(sparse=True, durations=[50.0])
+    return make_sorting_analyzer_with_splits(sorting_analyzer)
+
+
+@pytest.fixture(scope="module")
+def trained_pipeline_path(sorting_analyzer_for_unitrefine_curation):
+    """
+    Makes a model saved at "./trained_pipeline" which will be used by other tests in the module.
+    If the model already exists, this function does nothing.
+    """
+    trained_model_folder = Path(__file__).parent / Path("trained_pipeline")
+    if trained_model_folder.is_dir():
+        yield trained_model_folder
+    else:
+        analyzer = sorting_analyzer_for_unitrefine_curation
+        analyzer.compute(
+            {
+                "quality_metrics": {"metric_names": ["snr"]},
+                "template_metrics": {"metric_names": ["half_width", "peak_to_trough_duration", "number_of_peaks"]},
+            }
+        )
+        train_model(
+            analyzers=[analyzer] * 5,
+            folder=trained_model_folder,
+            labels=[[1] * 6 + [0] * 6] * 5,
+            imputation_strategies=["median"],
+            scaling_techniques=["standard_scaler"],
+            classifiers=["RandomForestClassifier"],
+            overwrite=True,
+            search_kwargs={"cv": 3, "scoring": "balanced_accuracy", "n_iter": 2},
+        )
+        yield trained_model_folder

From 451530537724262f0a231d372f3c7d087cc9c1ab Mon Sep 17 00:00:00 2001
From: Alessio Buccino <alejoe9187@gmail.com>
Date: Tue, 10 Nov 2026 10:07:12 +0100
Subject: [PATCH 26/30] fix: curation and exporters tests

---
 pyproject.toml                                |   2 +
 src/spikeinterface/curation/tests/common.py   | 124 ------------------
 src/spikeinterface/curation/tests/conftest.py |  57 +++++++-
 .../curation/tests/test_auto_merge.py         |   5 -
 .../curation/tests/test_remove_redundant.py   |   7 -
 .../tests/test_train_manual_curation.py       |   2 +-
 src/spikeinterface/exporters/tests/common.py  |  77 -----------
 .../exporters/tests/conftest.py               |  72 ++++++++++
 .../exporters/tests/test_export_to_ibl.py     |   9 +-
 .../exporters/tests/test_export_to_phy.py     |  14 --
 .../exporters/tests/test_report.py            |   8 --
 11 files changed, 132 insertions(+), 245 deletions(-)
 create mode 100644 src/spikeinterface/exporters/tests/conftest.py

diff --git a/pyproject.toml b/pyproject.toml
index ba1ba84525..e81fba5912 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -58,6 +58,8 @@ force-exclude = true
 select = ['E4', 'E7', 'E9', 'F']
 exclude = ["**/tests/**", "**/test_*.py", "**/conftest.py", "examples/**", "doc/conf.py", "installation_tips/**"]
 ignore = ['E741', 'E731', 'F821']
+# report but never auto-remove unused imports/variables: they may be side-effect imports, re-exports, or calls that advance state
+unfixable = ['F401', 'F841']
 [tool.ruff.lint.per-file-ignores]
 "**/__init__.py" = ['F401', 'F403']
 "src/spikeinterface/full.py" = ['F403']
diff --git a/src/spikeinterface/curation/tests/common.py b/src/spikeinterface/curation/tests/common.py
index 20dbd2f1f2..e69de29bb2 100644
--- a/src/spikeinterface/curation/tests/common.py
+++ b/src/spikeinterface/curation/tests/common.py
@@ -1,124 +0,0 @@
-import pytest
-
-from spikeinterface.core import generate_ground_truth_recording, create_sorting_analyzer, aggregate_units
-from spikeinterface.core.generate import inject_some_split_units
-from spikeinterface.curation import train_model
-from pathlib import Path
-
-extensions = [
-    "noise_levels",
-    "random_spikes",
-    "waveforms",
-    "templates",
-    "unit_locations",
-    "spike_amplitudes",
-    "spike_locations",
-    "correlograms",
-    "template_similarity",
-]
-
-
-def make_sorting_analyzer(sparse=True, num_units=5, durations=[300.0]):
-    recording, sorting = generate_ground_truth_recording(
-        durations=durations,
-        sampling_frequency=30000.0,
-        num_channels=4,
-        num_units=num_units,
-        generate_sorting_kwargs=dict(firing_rates=20.0, refractory_period_ms=4.0),
-        noise_kwargs=dict(noise_levels=5.0, strategy="on_the_fly"),
-        seed=2205,
-    )
-
-    sorting_analyzer = create_sorting_analyzer(
-        sorting=sorting,
-        recording=recording,
-        format="memory",
-        sparse=sparse,
-    )
-    sorting_analyzer.compute(extensions)
-
-    return sorting_analyzer
-
-
-def make_sorting_analyzer_with_splits(sorting_analyzer, num_unit_splitted=1, num_split=2):
-    sorting = sorting_analyzer.sorting
-
-    split_ids = sorting.unit_ids[:num_unit_splitted]
-    sorting_with_split, other_ids = inject_some_split_units(
-        sorting,
-        split_ids=split_ids,
-        num_split=num_split,
-        output_ids=True,
-        seed=42,
-    )
-
-    sorting_analyzer_with_splits = create_sorting_analyzer(
-        sorting=sorting_with_split, recording=sorting_analyzer.recording, format="memory", sparse=True
-    )
-    sorting_analyzer_with_splits.compute(extensions)
-
-    return sorting_analyzer_with_splits, num_unit_splitted, other_ids
-
-
-@pytest.fixture(scope="module")
-def sorting_analyzer_for_curation():
-    return make_sorting_analyzer(sparse=True)
-
-
-@pytest.fixture(scope="module")
-def sorting_analyzer_for_unitrefine_curation():
-    """Makes an analyzer whose first 10 units are good normal units, and 10 which are noise. We make them
-    noise by using a spike trains which are uncorrelated with the recording for `sorting2`."""
-
-    recording, sorting_1 = generate_ground_truth_recording(num_channels=4, seed=1, num_units=6)
-    _, sorting_2 = generate_ground_truth_recording(num_channels=4, seed=2, num_units=6)
-    both_sortings = aggregate_units([sorting_1, sorting_2])
-    analyzer = create_sorting_analyzer(sorting=both_sortings, recording=recording)
-    analyzer.compute(["random_spikes", "noise_levels", "templates"])
-    return analyzer
-
-
-@pytest.fixture(scope="module")
-def sorting_analyzer_multi_segment_for_curation():
-    return make_sorting_analyzer(sparse=True, durations=[50.0, 30.0])
-
-
-@pytest.fixture(scope="module")
-def sorting_analyzer_with_splits():
-    sorting_analyzer = make_sorting_analyzer(sparse=True, durations=[50.0])
-    return make_sorting_analyzer_with_splits(sorting_analyzer)
-
-
-@pytest.fixture(scope="module")
-def trained_pipeline_path(sorting_analyzer_for_unitrefine_curation):
-    """
-    Makes a model saved at "./trained_pipeline" which will be used by other tests in the module.
-    If the model already exists, this function does nothing.
-    """
-    trained_model_folder = Path(__file__).parent / Path("trained_pipeline")
-    if trained_model_folder.is_dir():
-        yield trained_model_folder
-    else:
-        analyzer = sorting_analyzer_for_unitrefine_curation
-        analyzer.compute(
-            {
-                "quality_metrics": {"metric_names": ["snr"]},
-                "template_metrics": {"metric_names": ["half_width", "peak_to_trough_duration", "number_of_peaks"]},
-            }
-        )
-        train_model(
-            analyzers=[analyzer] * 5,
-            folder=trained_model_folder,
-            labels=[[1] * 6 + [0] * 6] * 5,
-            imputation_strategies=["median"],
-            scaling_techniques=["standard_scaler"],
-            classifiers=["RandomForestClassifier"],
-            overwrite=True,
-            search_kwargs={"cv": 3, "scoring": "balanced_accuracy", "n_iter": 2},
-        )
-        yield trained_model_folder
-
-
-if __name__ == "__main__":
-    sorting_analyzer = make_sorting_analyzer(sparse=False)
-    print(sorting_analyzer)
diff --git a/src/spikeinterface/curation/tests/conftest.py b/src/spikeinterface/curation/tests/conftest.py
index a299219bb3..ad8c42a884 100644
--- a/src/spikeinterface/curation/tests/conftest.py
+++ b/src/spikeinterface/curation/tests/conftest.py
@@ -3,7 +3,62 @@
 
 from spikeinterface.core import generate_ground_truth_recording, create_sorting_analyzer, aggregate_units
 from spikeinterface.curation import train_model
-from spikeinterface.curation.tests.common import make_sorting_analyzer, make_sorting_analyzer_with_splits
+from spikeinterface.core.generate import inject_some_split_units
+
+
+extensions = [
+    "noise_levels",
+    "random_spikes",
+    "waveforms",
+    "templates",
+    "unit_locations",
+    "spike_amplitudes",
+    "spike_locations",
+    "correlograms",
+    "template_similarity",
+]
+
+
+def make_sorting_analyzer(sparse=True, num_units=5, durations=[300.0]):
+    recording, sorting = generate_ground_truth_recording(
+        durations=durations,
+        sampling_frequency=30000.0,
+        num_channels=4,
+        num_units=num_units,
+        generate_sorting_kwargs=dict(firing_rates=20.0, refractory_period_ms=4.0),
+        noise_kwargs=dict(noise_levels=5.0, strategy="on_the_fly"),
+        seed=2205,
+    )
+
+    sorting_analyzer = create_sorting_analyzer(
+        sorting=sorting,
+        recording=recording,
+        format="memory",
+        sparse=sparse,
+    )
+    sorting_analyzer.compute(extensions)
+
+    return sorting_analyzer
+
+
+def make_sorting_analyzer_with_splits(sorting_analyzer, num_unit_splitted=1, num_split=2):
+    sorting = sorting_analyzer.sorting
+
+    split_ids = sorting.unit_ids[:num_unit_splitted]
+    sorting_with_split, other_ids = inject_some_split_units(
+        sorting,
+        split_ids=split_ids,
+        num_split=num_split,
+        output_ids=True,
+        seed=42,
+    )
+
+    sorting_analyzer_with_splits = create_sorting_analyzer(
+        sorting=sorting_with_split, recording=sorting_analyzer.recording, format="memory", sparse=True
+    )
+    sorting_analyzer_with_splits.compute(extensions)
+
+    return sorting_analyzer_with_splits, num_unit_splitted, other_ids
 
 
 @pytest.fixture(scope="module")
diff --git a/src/spikeinterface/curation/tests/test_auto_merge.py b/src/spikeinterface/curation/tests/test_auto_merge.py
index 1e611dba07..03545c318b 100644
--- a/src/spikeinterface/curation/tests/test_auto_merge.py
+++ b/src/spikeinterface/curation/tests/test_auto_merge.py
@@ -6,11 +6,6 @@
 from spikeinterface.generation import split_sorting_by_times
 
 
-from spikeinterface.curation.tests.common import (
-    make_sorting_analyzer,
-)
-
-
 @pytest.mark.parametrize(
     "preset", ["x_contaminations", "feature_neighbors", "temporal_splits", "similarity_correlograms", "slay", None]
 )
diff --git a/src/spikeinterface/curation/tests/test_remove_redundant.py b/src/spikeinterface/curation/tests/test_remove_redundant.py
index 6449b582fe..4e74a738a5 100644
--- a/src/spikeinterface/curation/tests/test_remove_redundant.py
+++ b/src/spikeinterface/curation/tests/test_remove_redundant.py
@@ -2,8 +2,6 @@
 
 from spikeinterface import create_sorting_analyzer
 from spikeinterface.core.generate import inject_some_duplicate_units
-from spikeinterface.curation.tests.common import make_sorting_analyzer
-
 from spikeinterface.curation import remove_redundant_units
 
 
@@ -22,8 +20,3 @@ def test_remove_redundant_units(sorting_analyzer_for_curation):
     for remove_strategy in ("max_spikes", "minimum_shift", "highest_amplitude"):
         sorting_clean = remove_redundant_units(sorting_analyzer, remove_strategy=remove_strategy)
         assert np.all(sorting_clean.unit_ids == sorting.unit_ids)
-
-
-if __name__ == "__main__":
-    sorting_analyzer = make_sorting_analyzer(sparse=True)
-    test_remove_redundant_units(sorting_analyzer)
diff --git a/src/spikeinterface/curation/tests/test_train_manual_curation.py b/src/spikeinterface/curation/tests/test_train_manual_curation.py
index 249605046c..65c0be3947 100644
--- a/src/spikeinterface/curation/tests/test_train_manual_curation.py
+++ b/src/spikeinterface/curation/tests/test_train_manual_curation.py
@@ -4,7 +4,7 @@
 import csv
 from pathlib import Path
 
-from spikeinterface.curation.tests.common import make_sorting_analyzer
+from spikeinterface.curation.tests.conftest import make_sorting_analyzer
 from spikeinterface.curation.train_manual_curation import CurationTrainer, train_model
 
 
diff --git a/src/spikeinterface/exporters/tests/common.py b/src/spikeinterface/exporters/tests/common.py
index d42c1b7253..e69de29bb2 100644
--- a/src/spikeinterface/exporters/tests/common.py
+++ b/src/spikeinterface/exporters/tests/common.py
@@ -1,77 +0,0 @@
-import pytest
-
-from spikeinterface.core import generate_ground_truth_recording, create_sorting_analyzer, compute_sparsity
-
-
-def make_sorting_analyzer(sparse=True, with_group=False):
-    recording, sorting = generate_ground_truth_recording(
-        durations=[30.0],
-        sampling_frequency=28000.0,
-        num_channels=8,
-        num_units=4,
-        generate_probe_kwargs=dict(
-            num_columns=2,
-            xpitch=20,
-            ypitch=20,
-            contact_shapes="circle",
-            contact_shape_params={"radius": 6},
-        ),
-        generate_sorting_kwargs=dict(firing_rates=10.0, refractory_period_ms=4.0),
-        noise_kwargs=dict(noise_levels=5.0, strategy="on_the_fly"),
-        seed=2205,
-    )
-
-    if with_group:
-        # this is a bit painful. We need to figure out which units belong to which group
-        initial_sorting_analyzer = create_sorting_analyzer(
-            sorting=sorting, recording=recording, format="memory", sparse=True
-        )
-        main_channels = initial_sorting_analyzer.main_channel_indices
-        sorting_groups = [0 if main_channel < 4 else 1 for main_channel in main_channels]
-        recording.set_channel_groups([0, 0, 0, 0, 1, 1, 1, 1])
-        sorting.set_property("group", sorting_groups)
-
-        # Now we know that, we can make an analyzer with a working sparsity_group
-        sorting_analyzer_unused = create_sorting_analyzer(
-            sorting=sorting, recording=recording, format="memory", sparse=False, sparsity=None
-        )
-        sparsity_group = compute_sparsity(sorting_analyzer_unused, method="by_property", by_property="group")
-        sorting_analyzer = create_sorting_analyzer(
-            sorting=sorting, recording=recording, format="memory", sparse=False, sparsity=sparsity_group
-        )
-    else:
-        sorting_analyzer = create_sorting_analyzer(sorting=sorting, recording=recording, format="memory", sparse=sparse)
-
-    sorting_analyzer.compute("random_spikes")
-    sorting_analyzer.compute("waveforms")
-    sorting_analyzer.compute("templates")
-    sorting_analyzer.compute("noise_levels")
-    sorting_analyzer.compute("principal_components")
-    sorting_analyzer.compute("template_similarity")
-    sorting_analyzer.compute("spike_amplitudes")
-    sorting_analyzer.compute(
-        "quality_metrics", metric_names=["snr", "amplitude_median", "isi_violation", "amplitude_cutoff"]
-    )
-    sorting_analyzer.compute(["spike_amplitudes", "spike_locations"])
-
-    return sorting_analyzer
-
-
-@pytest.fixture(scope="module")
-def sorting_analyzer_dense_for_export():
-    return make_sorting_analyzer(sparse=False)
-
-
-@pytest.fixture(scope="module")
-def sorting_analyzer_with_group_for_export():
-    return make_sorting_analyzer(sparse=False, with_group=True)
-
-
-@pytest.fixture(scope="module")
-def sorting_analyzer_sparse_for_export():
-    return make_sorting_analyzer(sparse=True)
-
-
-if __name__ == "__main__":
-    sorting_analyzer = make_sorting_analyzer(sparse=False)
-    print(sorting_analyzer)
diff --git a/src/spikeinterface/exporters/tests/conftest.py b/src/spikeinterface/exporters/tests/conftest.py
new file mode 100644
index 0000000000..a524c3b965
--- /dev/null
+++ b/src/spikeinterface/exporters/tests/conftest.py
@@ -0,0 +1,72 @@
+import pytest
+
+from spikeinterface.core import generate_ground_truth_recording, create_sorting_analyzer, compute_sparsity
+
+
+def make_sorting_analyzer(sparse=True, with_group=False):
+    recording, sorting = generate_ground_truth_recording(
+        durations=[30.0],
+        sampling_frequency=28000.0,
+        num_channels=8,
+        num_units=4,
+        generate_probe_kwargs=dict(
+            num_columns=2,
+            xpitch=20,
+            ypitch=20,
+            contact_shapes="circle",
+            contact_shape_params={"radius": 6},
+        ),
+        generate_sorting_kwargs=dict(firing_rates=10.0, refractory_period_ms=4.0),
+        noise_kwargs=dict(noise_levels=5.0, strategy="on_the_fly"),
+        seed=2205,
+    )
+
+    if with_group:
+        # this is a bit painful. We need to figure out which units belong to which group
+        initial_sorting_analyzer = create_sorting_analyzer(
+            sorting=sorting, recording=recording, format="memory", sparse=True
+        )
+        main_channels = initial_sorting_analyzer.main_channel_indices
+        sorting_groups = [0 if main_channel < 4 else 1 for main_channel in main_channels]
+        recording.set_channel_groups([0, 0, 0, 0, 1, 1, 1, 1])
+        sorting.set_property("group", sorting_groups)
+
+        # Now we know that, we can make an analyzer with a working sparsity_group
+        sorting_analyzer_unused = create_sorting_analyzer(
+            sorting=sorting, recording=recording, format="memory", sparse=False, sparsity=None
+        )
+        sparsity_group = compute_sparsity(sorting_analyzer_unused, method="by_property", by_property="group")
+        sorting_analyzer = create_sorting_analyzer(
+            sorting=sorting, recording=recording, format="memory", sparse=False, sparsity=sparsity_group
+        )
+    else:
+        sorting_analyzer = create_sorting_analyzer(sorting=sorting, recording=recording, format="memory", sparse=sparse)
+
+    sorting_analyzer.compute("random_spikes")
+    sorting_analyzer.compute("waveforms")
+    sorting_analyzer.compute("templates")
+    sorting_analyzer.compute("noise_levels")
+    sorting_analyzer.compute("principal_components")
+    sorting_analyzer.compute("template_similarity")
+    sorting_analyzer.compute("spike_amplitudes")
+    sorting_analyzer.compute(
+        "quality_metrics", metric_names=["snr", "amplitude_median", "isi_violation", "amplitude_cutoff"]
+    )
+    sorting_analyzer.compute(["spike_amplitudes", "spike_locations"])
+
+    return sorting_analyzer
+
+
+@pytest.fixture(scope="module")
+def sorting_analyzer_dense_for_export():
+    return make_sorting_analyzer(sparse=False)
+
+
+@pytest.fixture(scope="module")
+def sorting_analyzer_with_group_for_export():
+    return make_sorting_analyzer(sparse=False, with_group=True)
+
+
+@pytest.fixture(scope="module")
+def sorting_analyzer_sparse_for_export():
+    return make_sorting_analyzer(sparse=True)
diff --git a/src/spikeinterface/exporters/tests/test_export_to_ibl.py b/src/spikeinterface/exporters/tests/test_export_to_ibl.py
index 9f1d24300a..ee11d40695 100644
--- a/src/spikeinterface/exporters/tests/test_export_to_ibl.py
+++ b/src/spikeinterface/exporters/tests/test_export_to_ibl.py
@@ -2,9 +2,7 @@
 
 from spikeinterface.preprocessing import bandpass_filter, decimate
 from spikeinterface.exporters import export_to_ibl_gui
-from spikeinterface.exporters.tests.common import (
-    make_sorting_analyzer,
-)
+
 
 required_output_files = [
     "spikes.times.npy",
@@ -106,8 +104,3 @@ def test_missing_info(sorting_analyzer_sparse_for_export, create_cache_folder):
 
     with pytest.raises(ValueError, match="Missing required extension"):
         export_to_ibl_gui(sorting_analyzer, output_folder, n_jobs=-1)
-
-
-if __name__ == "__main__":
-    sorting_analyzer = make_sorting_analyzer(sparse=True)
-    test_export_ap_to_ibl(sorting_analyzer)
diff --git a/src/spikeinterface/exporters/tests/test_export_to_phy.py b/src/spikeinterface/exporters/tests/test_export_to_phy.py
index 301c534fd0..08c91fa0f2 100644
--- a/src/spikeinterface/exporters/tests/test_export_to_phy.py
+++ b/src/spikeinterface/exporters/tests/test_export_to_phy.py
@@ -6,10 +6,6 @@
 from spikeinterface.core import generate_ground_truth_recording, create_sorting_analyzer
 from spikeinterface.exporters import export_to_phy
 
-from spikeinterface.exporters.tests.common import (
-    make_sorting_analyzer,
-)
-
 
 def test_export_to_phy_dense(sorting_analyzer_dense_for_export, create_cache_folder):
     cache_folder = create_cache_folder
@@ -283,13 +279,3 @@ def test_export_to_phy_add_waveforms_missing_extension(create_cache_folder):
     assert not (output_folder / "_phy_spikes_subset.spikes.npy").is_file()
     assert not (output_folder / "_phy_spikes_subset.channels.npy").is_file()
     assert not (output_folder / "_phy_spikes_subset.waveforms.npy").is_file()
-
-
-if __name__ == "__main__":
-    sorting_analyzer_sparse = make_sorting_analyzer(sparse=True)
-    sorting_analyzer_group = make_sorting_analyzer(sparse=False, with_group=True)
-    sorting_analyzer_dense = make_sorting_analyzer(sparse=False)
-
-    test_export_to_phy_dense(sorting_analyzer_dense)
-    test_export_to_phy_sparse(sorting_analyzer_sparse)
-    test_export_to_phy_by_property(sorting_analyzer_group)
diff --git a/src/spikeinterface/exporters/tests/test_report.py b/src/spikeinterface/exporters/tests/test_report.py
index 9646ab6d9c..7f9e7636d6 100644
--- a/src/spikeinterface/exporters/tests/test_report.py
+++ b/src/spikeinterface/exporters/tests/test_report.py
@@ -1,9 +1,6 @@
 import shutil
 
 from spikeinterface.exporters import export_report
-from spikeinterface.exporters.tests.common import (
-    make_sorting_analyzer,
-)
 
 
 def test_export_report(sorting_analyzer_sparse_for_export, create_cache_folder):
@@ -16,8 +13,3 @@ def test_export_report(sorting_analyzer_sparse_for_export, create_cache_folder):
 
     job_kwargs = dict(n_jobs=1, chunk_size=30000, progress_bar=True)
     export_report(sorting_analyzer, report_folder, force_computation=True, **job_kwargs)
-
-
-if __name__ == "__main__":
-    sorting_analyzer = make_sorting_analyzer(sparse=True)
-    test_export_report(sorting_analyzer)

From 433ef5586129daf8ef57d5faf433fb216c9b61f8 Mon Sep 17 00:00:00 2001
From: Alessio Buccino <alejoe9187@gmail.com>
Date: Tue, 10 Nov 2026 10:16:17 +0100
Subject: [PATCH 27/30] doc: add instructions (plus some test fixes)

---
 .pre-commit-config.yaml                       |  7 +++
 doc/development/development.rst               | 60 ++++++++++++-------
 .../core/tests/test_generate.py               | 10 ----
 .../curation/tests/test_curationsorting.py    |  5 +-
 .../postprocessing/tests/test_correlograms.py | 52 +++++-----------
 .../tests/test_detect_bad_channels.py         |  5 +-
 .../motion/tests/test_medicine.py             |  7 ++-
 7 files changed, 67 insertions(+), 79 deletions(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 315c4cff72..157acbefda 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -11,5 +11,12 @@ repos:
     -   id: ruff-check
         args: [--fix]
         files: ^src/
+    # occasional full lint including tests: pre-commit run ruff-check-tests --hook-stage manual --all-files
+    -   id: ruff-check
+        alias: ruff-check-tests
+        name: ruff check (including tests)
+        args: [--fix, --config, "lint.exclude = []"]
+        files: ^src/
+        stages: [manual]
     -   id: ruff-format
         files: ^src/
diff --git a/doc/development/development.rst b/doc/development/development.rst
index 82b17e7a35..dba523b3c4 100644
--- a/doc/development/development.rst
+++ b/doc/development/development.rst
@@ -111,49 +111,65 @@ maintainability of the code, making it easier for contributors to collaborate. T
 for the developer we use the following tools and conventions:
 
 
-Install Black and pre-commit
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+Install ruff and pre-commit
+^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-We use the Python formatter Black, with defaults set in the :code:`pyproject.toml`. This allows for
-easy local formatting of code.
+We use `ruff <https://docs.astral.sh/ruff/>`_ both to format code and to lint it (catch errors such as
+undefined names or unused variables). Its settings live in the :code:`[tool.ruff]` section of :code:`pyproject.toml`.
+We use pre-commit to run ruff, and a few other checks, automatically before every commit.
 
-To install Black, you can use pip, the Python package installer. Run the following command in your terminal:
+You can install both with pip:
 
 .. code-block:: bash
 
-    pip install black
+    pip install ruff pre-commit
 
-This will install Black into your current Python environment.
+Then set up the pre-commit hooks for your local repository by running, from the repository root:
 
-In addition to Black, we use pre-commit to manage a suite of code formatting.
-Pre-commit helps to automate the process of running these tools (including Black) before every commit,
-ensuring that all code is checked for style.
+.. code-block:: bash
+
+    pre-commit install
 
-You can install pre-commit using pip as well:
+Now, each time you make a commit, pre-commit will run :code:`ruff format` and :code:`ruff check --fix` on the changed files
+under :code:`src/`. If the hooks make changes or find issues, the commit is stopped so you can review the changes, add them and commit again.
+
+You can also run ruff yourself at any time:
 
 .. code-block:: bash
 
-    pip install pre-commit
+    ruff format src          # format the code
+    ruff check src           # report lint errors
+    ruff check src --fix     # report lint errors and apply the safe automatic fixes
+
+A few things to know about the lint configuration:
 
+* Test files (:code:`tests/` folders, :code:`test_*.py` and :code:`conftest.py`) are excluded from linting.
+* Unused imports (:code:`F401`) and unused variables (:code:`F841`) are reported but never removed automatically,
+  because they are sometimes needed: side-effect imports, re-exports, or function calls that read from a file.
+  Fix them by hand, or keep them and mark the line with :code:`# noqa: F401`.
+* Pytest fixtures shared by several test modules belong in a :code:`conftest.py`, so pytest finds them without an import
+  (an import that ruff would see as unused).
 
-Once pre-commit is installed, you can set up the pre-commit hooks for your local repository.
-These hooks are scripts that pre-commit will run prior to each commit. To install the pre-commit hooks,
-navigate to your local repository in your terminal and run the following command:
+Since tests are not linted on every commit, it is worth checking them every now and then. A manual pre-commit hook lints
+everything under :code:`src/`, tests included:
 
 .. code-block:: bash
 
-    pre-commit install
+    pre-commit run ruff-check-tests --hook-stage manual --all-files
+
+or, equivalently, with ruff directly:
+
+.. code-block:: bash
 
-Now, each time you make a commit, pre-commit will automatically run Black and any other configured hooks.
-If the hooks make changes or if there are any issues, the commit will be stopped, and you'll be able to review and add the changes.
+    ruff check src --config 'lint.exclude = []'
 
-If you want Black to omit a line from formatting, you can add the following comment to the end of the line:
+If you want ruff to leave a line unformatted, add the following comment to the end of the line:
 
 .. code-block:: python
 
     # fmt: skip
 
-To ignore a block of code you must flank the code with two comments:
+To leave a block of code unformatted, put these two comments around it:
 
 .. code-block:: python
 
@@ -161,7 +177,7 @@ To ignore a block of code you must flank the code with two comments:
     code here
     # fmt: on
 
-As described in the `black documentation <https://black.readthedocs.io/en/stable/the_black_code_style/current_style.html#code-style>`_.
+To silence a single lint error on one line, add :code:`# noqa: <code>` (for example :code:`# noqa: F401`) to the end of that line.
 
 
 Docstring Conventions
@@ -202,7 +218,7 @@ This allows users to quickly understand the type of data that should be input in
 
 There should be a space between each parameter and the colon following it. This is neccessary for using the `numpydoc validator <https://numpydoc.readthedocs.io/en/latest/validation.html>`_.
 In the above example we demonstrate two other docstring conventions followed by SpikeInterface. First, that all string arguments should be presented
-with double quotes. This is the same stylistic convention followed by Black and enforced by the pre-commit for the repo. Second, when a parameter is a
+with double quotes. This is the same stylistic convention enforced by ruff format in the pre-commit for the repo. Second, when a parameter is a
 string with a limited number of values (e.g. :code:`mean` and :code:`median`), rather than give the type a value of :code:`str`, please list the possible strings
 so that the user knows what the options are.
 
diff --git a/src/spikeinterface/core/tests/test_generate.py b/src/spikeinterface/core/tests/test_generate.py
index d8945699a3..69fe3ff913 100644
--- a/src/spikeinterface/core/tests/test_generate.py
+++ b/src/spikeinterface/core/tests/test_generate.py
@@ -33,16 +33,6 @@
 strategy_list = ["tile_pregenerated", "on_the_fly"]
 
 
-def test_generate_recording():
-    # TODO even this is extensively tested in all other functions
-    pass
-
-
-def test_generate_sorting():
-    # TODO even this is extensively tested in all other functions
-    pass
-
-
 def test_generate_sorting_with_spikes_on_borders():
     num_spikes_on_borders = 10
     border_size_samples = 10
diff --git a/src/spikeinterface/curation/tests/test_curationsorting.py b/src/spikeinterface/curation/tests/test_curationsorting.py
index 95a87fc1d1..fb263bec8e 100644
--- a/src/spikeinterface/curation/tests/test_curationsorting.py
+++ b/src/spikeinterface/curation/tests/test_curationsorting.py
@@ -52,9 +52,8 @@ def test_split_merge():
 
     merged = MergeUnitsSorting(splitted, units_to_merge=[[8, 10]], new_unit_ids=[4], properties_policy="keep")
     for i in range(len(spikestimes)):
-        assert (
-            all(parent_sort.get_unit_spike_train(4, segment_index=i) == merged.get_unit_spike_train(4, segment_index=i))
-            == True
+        assert all(
+            parent_sort.get_unit_spike_train(4, segment_index=i) == merged.get_unit_spike_train(4, segment_index=i)
         ), "splir or merge error"
     assert parent_sort.get_unit_property(4, "someprop") == merged.get_unit_property(4, "someprop"), (
         "property wasn't kept"
diff --git a/src/spikeinterface/postprocessing/tests/test_correlograms.py b/src/spikeinterface/postprocessing/tests/test_correlograms.py
index 96503d7840..e93f97d5c1 100644
--- a/src/spikeinterface/postprocessing/tests/test_correlograms.py
+++ b/src/spikeinterface/postprocessing/tests/test_correlograms.py
@@ -1,21 +1,7 @@
-import numpy as np
-import importlib.util
-
-numba_spec = importlib.util.find_spec("numba")
-if numba_spec is not None:
-    HAVE_NUMBA = True
-else:
-    HAVE_NUMBA = False
-
-npyx_spec = importlib.util.find_spec("npyx")
-if npyx_spec is not None:
-    HAVE_NPYX = True
-else:
-    HAVE_NPYX = False
-
-
 import pytest
 from pytest import param
+import numpy as np
+import importlib.util
 
 from spikeinterface import NumpySorting, generate_sorting
 from spikeinterface.postprocessing import ComputeACG3D, ComputeCorrelograms, ComputeAutoCorrelograms
@@ -32,6 +18,19 @@
 )
 from spikeinterface.postprocessing.tests.common_extension_tests import AnalyzerExtensionCommonTestSuite
 
+
+numba_spec = importlib.util.find_spec("numba")
+if numba_spec is not None:
+    HAVE_NUMBA = True
+else:
+    HAVE_NUMBA = False
+
+npyx_spec = importlib.util.find_spec("npyx")
+if npyx_spec is not None:
+    HAVE_NPYX = True
+else:
+    HAVE_NPYX = False
+
 SKIP_NUMBA = pytest.mark.skipif(not HAVE_NUMBA, reason="Numba not available")
 
 
@@ -254,27 +253,6 @@ def test_equal_results_auto_correlograms(window_and_bin_ms):
     assert np.array_equal(result_numpy, result_numba)
 
 
-@pytest.mark.skipif(not HAVE_NUMBA, reason="Numba not available")
-@pytest.mark.parametrize("window_and_bin_ms", [(60.0, 2.0), (3.57, 1.6421)])
-def test_equal_results_auto_correlograms(window_and_bin_ms):
-    """
-    Test that the 2 methods have same results with some varied time bins
-    that are not tested in other tests.
-    """
-
-    window_ms, bin_ms = window_and_bin_ms
-    sorting = generate_sorting(num_units=5, sampling_frequency=30000.0, durations=[10.325, 3.5], seed=0)
-
-    result_numpy, bins_numpy = _compute_auto_correlograms_on_sorting(
-        sorting, window_ms=window_ms, bin_ms=bin_ms, method="numpy"
-    )
-    result_numba, bins_numba = _compute_auto_correlograms_on_sorting(
-        sorting, window_ms=window_ms, bin_ms=bin_ms, method="numba"
-    )
-
-    assert np.array_equal(result_numpy, result_numba)
-
-
 @pytest.mark.parametrize("method", ["numpy", param("numba", marks=SKIP_NUMBA)])
 def test_flat_cross_correlogram(method):
     """
diff --git a/src/spikeinterface/preprocessing/tests/test_detect_bad_channels.py b/src/spikeinterface/preprocessing/tests/test_detect_bad_channels.py
index 0de46b7c4f..4a0df49156 100644
--- a/src/spikeinterface/preprocessing/tests/test_detect_bad_channels.py
+++ b/src/spikeinterface/preprocessing/tests/test_detect_bad_channels.py
@@ -3,12 +3,9 @@
 import importlib.util
 
 
-from spikeinterface import NumpyRecording, get_random_data_chunks
 from probeinterface import generate_linear_probe
 
-from spikeinterface.generation import generate_recording
-
-from spikeinterface.core import generate_recording
+from spikeinterface.core import generate_recording, get_random_data_chunks, NumpyRecording
 from spikeinterface.core.base import BaseExtractor
 from spikeinterface.core.testing import check_recordings_equal
 from spikeinterface.preprocessing import detect_bad_channels, highpass_filter, detect_and_remove_bad_channels
diff --git a/src/spikeinterface/sortingcomponents/motion/tests/test_medicine.py b/src/spikeinterface/sortingcomponents/motion/tests/test_medicine.py
index 4db1d8bfd7..cdbafa504b 100644
--- a/src/spikeinterface/sortingcomponents/motion/tests/test_medicine.py
+++ b/src/spikeinterface/sortingcomponents/motion/tests/test_medicine.py
@@ -1,9 +1,6 @@
 import numpy as np
 import pytest
 
-torch = pytest.importorskip("torch")
-medicine = pytest.importorskip("medicine")
-
 from spikeinterface import get_noise_levels
 from spikeinterface.core.node_pipeline import ExtractDenseWaveforms, run_node_pipeline
 from spikeinterface.sortingcomponents.motion import estimate_motion
@@ -11,6 +8,10 @@
 from spikeinterface.sortingcomponents.peak_localization.method_list import LocalizeCenterOfMass
 from spikeinterface.sortingcomponents.tests.common import make_dataset
 
+
+torch = pytest.importorskip("torch")
+medicine = pytest.importorskip("medicine")
+
 # Kept tiny so the model trains in a fraction of a second. Not representative of settings
 # one would use for real motion estimation.
 _FAST_TRAINING_KWARGS = dict(batch_size=32, training_steps=15, motion_noise_steps=5)

From 4b2b6338f9c2f7abc89c36db28ed8acd272c04ce Mon Sep 17 00:00:00 2001
From: Alessio Buccino <alejoe9187@gmail.com>
Date: Tue, 10 Nov 2026 11:17:04 +0100
Subject: [PATCH 28/30] fix: test linting with manual pre-commit

---
 .../tests/test_benchmark_peak_selection.py    |  2 +-
 .../benchmark/tests/test_benchmark_sorter.py  |  9 +++--
 .../tests/test_benchmark_sorter_without_gt.py |  2 +-
 .../tests/test_groundtruthcomparison.py       |  1 +
 .../tests/test_analyzer_extension_core.py     | 12 ++++---
 .../core/tests/test_basesorting.py            |  7 +++-
 .../core/tests/test_channelslicerecording.py  |  2 +-
 .../core/tests/test_generate.py               | 14 +++-----
 .../core/tests/test_node_pipeline.py          |  3 +-
 .../tests/test_noise_levels_propagation.py    |  4 +--
 .../core/tests/test_npzsortingextractor.py    |  8 ++---
 .../core/tests/test_numpy_extractors.py       |  2 --
 .../core/tests/test_recording_tools.py        | 13 +++----
 .../core/tests/test_sorting_tools.py          |  1 -
 .../core/tests/test_sortinganalyzer.py        |  2 ++
 .../core/tests/test_sparsity.py               | 34 ++++++++-----------
 .../core/tests/test_template_class.py         |  2 +-
 .../core/tests/test_unitsselectionsorting.py  |  2 +-
 ...forms_extractor_backwards_compatibility.py |  8 ++---
 .../curation/tests/test_auto_merge.py         |  2 +-
 .../curation/tests/test_curation_format.py    |  1 -
 .../curation/tests/test_curationsorting.py    |  2 +-
 .../tests/test_model_based_curation.py        |  6 ++--
 .../tests/test_sortingview_curation.py        |  3 +-
 .../tests/test_unitrefine_curation.py         | 10 +++---
 .../extractors/tests/common_tests.py          |  2 +-
 .../extractors/tests/test_bidsextractors.py   |  6 ++--
 .../tests/test_datalad_downloading.py         |  1 +
 .../tests/test_herdingspikesextractors.py     |  2 --
 .../extractors/tests/test_mdaextractors.py    |  2 +-
 .../extractors/tests/test_nwbextractors.py    |  4 +--
 .../tests/test_nwbextractors_streaming.py     |  6 ----
 .../tests/test_shybridextractors.py           |  1 +
 .../extractors/tests/test_toy_example.py      |  1 +
 .../tests/test_drifing_generator.py           | 10 ++----
 .../generation/tests/test_noise_tools.py      |  4 +--
 .../quality/tests/test_metrics_functions.py   |  3 +-
 .../tests/test_quality_metric_calculator.py   |  4 +--
 .../tests/test_multi_extensions.py            |  2 +-
 .../tests/test_deepinterpolation.py           |  9 ++---
 .../tests/test_common_reference.py            |  2 +-
 .../preprocessing/tests/test_filter.py        | 25 ++++++--------
 .../tests/test_filter_gaussian.py             |  1 -
 .../tests/test_highpass_spatial_filter.py     |  3 +-
 .../preprocessing/tests/test_motion.py        |  4 ++-
 .../tests/test_normalize_scale.py             |  2 +-
 .../preprocessing/tests/test_phase_shift.py   |  1 -
 .../tests/test_silence_periods.py             | 10 ++----
 .../preprocessing/tests/test_zero_padding.py  |  1 -
 .../internal/tests/test_spykingcircus2.py     |  2 +-
 .../internal/tests/test_tridesclous2.py       |  2 +-
 .../sorters/tests/test_container_tools.py     | 14 ++++----
 .../clustering/tests/test_clustering.py       |  2 +-
 .../clustering/tests/test_isosplit_isocut.py  |  4 +--
 .../matching/tests/test_template_matching.py  | 30 ++++++++--------
 55 files changed, 136 insertions(+), 176 deletions(-)

diff --git a/src/spikeinterface/benchmark/tests/test_benchmark_peak_selection.py b/src/spikeinterface/benchmark/tests/test_benchmark_peak_selection.py
index a6eb090a9d..d56529269b 100644
--- a/src/spikeinterface/benchmark/tests/test_benchmark_peak_selection.py
+++ b/src/spikeinterface/benchmark/tests/test_benchmark_peak_selection.py
@@ -5,7 +5,7 @@
 
 @pytest.mark.skip()
 def test_benchmark_peak_selection(create_cache_folder):
-    cache_folder = create_cache_folder
+    pass
 
 
 if __name__ == "__main__":
diff --git a/src/spikeinterface/benchmark/tests/test_benchmark_sorter.py b/src/spikeinterface/benchmark/tests/test_benchmark_sorter.py
index f95edbaaf9..71e670f79b 100644
--- a/src/spikeinterface/benchmark/tests/test_benchmark_sorter.py
+++ b/src/spikeinterface/benchmark/tests/test_benchmark_sorter.py
@@ -65,7 +65,7 @@ def _create_simple_study(study_folder, cache_folder):
         },
     }
 
-    study = SorterStudy.create(
+    _ = SorterStudy.create(
         study_folder, datasets=datasets, cases=cases, levels=["sorter_name", "processing", "probe_type"]
     )
     # print(study)
@@ -100,7 +100,7 @@ def _create_very_simple_study(study_folder, cache_folder):
         },
     }
 
-    study = SorterStudy.create(
+    _ = SorterStudy.create(
         study_folder, datasets=datasets, cases=cases, levels=["sorter_name", "processing", "probe_type"]
     )
     # print(study)
@@ -245,7 +245,7 @@ def _create_complex_study(study_folder, cache_folder):
         },
     }
 
-    study = SorterStudy.create(
+    _ = SorterStudy.create(
         study_folder, datasets=datasets, cases=cases, levels=["sorter_name", "processing", "probe_type"]
     )
 
@@ -266,13 +266,16 @@ def test_SorterStudy(create_simple_study):
 
     # this is from the base class
     rt = study.get_run_times()
+    assert rt is not None
     # rt = study.plot_run_times()
     # import matplotlib.pyplot as plt
     # plt.show()
 
     perf_by_unit = study.get_performance_by_unit()
+    assert perf_by_unit is not None
     # print(perf_by_unit)
     count_units = study.get_count_units()
+    assert count_units is not None
     # print(count_units)
 
 
diff --git a/src/spikeinterface/benchmark/tests/test_benchmark_sorter_without_gt.py b/src/spikeinterface/benchmark/tests/test_benchmark_sorter_without_gt.py
index 15131e0f28..4055342a46 100644
--- a/src/spikeinterface/benchmark/tests/test_benchmark_sorter_without_gt.py
+++ b/src/spikeinterface/benchmark/tests/test_benchmark_sorter_without_gt.py
@@ -41,7 +41,7 @@ def _create_simple_study_no_gt(study_folder):
         },
     }
 
-    study = SorterStudyWithoutGroundTruth.create(study_folder, datasets=datasets, cases=cases)
+    _ = SorterStudyWithoutGroundTruth.create(study_folder, datasets=datasets, cases=cases)
     # print(study)
 
 
diff --git a/src/spikeinterface/comparison/tests/test_groundtruthcomparison.py b/src/spikeinterface/comparison/tests/test_groundtruthcomparison.py
index 48b91c6877..34fe86c1f8 100644
--- a/src/spikeinterface/comparison/tests/test_groundtruthcomparison.py
+++ b/src/spikeinterface/comparison/tests/test_groundtruthcomparison.py
@@ -110,6 +110,7 @@ def test_compare_sorter_to_ground_truth():
     bad_ids = sc.get_bad_units()
     assert_array_equal(bad_ids, [6, 11])
     num_bad = sc.count_bad_units()
+    assert num_bad == 2
 
     # bad units is union of false_positive_units + redundant_units
     fpu_ids = sc.get_false_positive_units()
diff --git a/src/spikeinterface/core/tests/test_analyzer_extension_core.py b/src/spikeinterface/core/tests/test_analyzer_extension_core.py
index a903c15cb0..030f4f50b3 100644
--- a/src/spikeinterface/core/tests/test_analyzer_extension_core.py
+++ b/src/spikeinterface/core/tests/test_analyzer_extension_core.py
@@ -66,12 +66,13 @@ def _check_result_extension(sorting_analyzer, extension_name, cache_folder):
             folder = None
 
         # check unit slice
+        original_data = sorting_analyzer.get_extension(extension_name).data
         keep_unit_ids = sorting_analyzer.sorting.unit_ids[::2]
         sorting_analyzer2 = sorting_analyzer.select_units(unit_ids=keep_unit_ids, format=format, folder=folder)
 
         data = sorting_analyzer2.get_extension(extension_name).data
-        # for k, arr in data.items():
-        #     print(k, arr.shape)
+        for k in original_data:
+            assert k in data
 
 
 @pytest.mark.parametrize("format", ["memory", "binary_folder", "zarr"])
@@ -112,8 +113,7 @@ def test_ComputeWaveforms(format, sparse, create_cache_folder):
 
     job_kwargs = dict(n_jobs=2, chunk_duration="1s", progress_bar=True)
     sorting_analyzer.compute("random_spikes", max_spikes_per_unit=50, seed=2205)
-    ext = sorting_analyzer.compute("waveforms", **job_kwargs)
-    wfs = ext.data["waveforms"]
+    _ = sorting_analyzer.compute("waveforms", **job_kwargs)
     _check_result_extension(sorting_analyzer, "waveforms", cache_folder)
 
 
@@ -212,8 +212,10 @@ def test_ComputeTemplates(format, sparse, create_cache_folder):
 
     # ask for more operator later
     temp_ext = sorting_analyzer.get_extension("templates")
-    templated_median = temp_ext.get_templates(operator="median")
+    template_median = temp_ext.get_templates(operator="median")
+    assert template_median is not None
     templated_per_5 = temp_ext.get_templates(operator="percentile", percentile=5.0)
+    assert templated_per_5 is not None
 
     # they all should be in data
     data = sorting_analyzer.get_extension("templates").data
diff --git a/src/spikeinterface/core/tests/test_basesorting.py b/src/spikeinterface/core/tests/test_basesorting.py
index 3a1986e353..2b7421b855 100644
--- a/src/spikeinterface/core/tests/test_basesorting.py
+++ b/src/spikeinterface/core/tests/test_basesorting.py
@@ -131,9 +131,14 @@ def test_BaseSorting(create_cache_folder):
     )
     assert np.array_equal(spikes[order], ordered_spikes)
 
-    num_spikes_per_unit = sorting.count_num_spikes_per_unit(outputs="dict")
+    num_spikes_per_unit_dict = sorting.count_num_spikes_per_unit(outputs="dict")
+    assert isinstance(num_spikes_per_unit_dict, dict)
+    assert all(unit in num_spikes_per_unit_dict for unit in sorting.unit_ids)
     num_spikes_per_unit = sorting.count_num_spikes_per_unit(outputs="array")
+    assert isinstance(num_spikes_per_unit, np.ndarray)
+    assert num_spikes_per_unit.size == sorting.unit_ids.size
     total_spikes = sorting.count_total_num_spikes()
+    assert total_spikes == num_spikes_per_unit.sum()
 
     # select units
     keep_units = [0, 1]
diff --git a/src/spikeinterface/core/tests/test_channelslicerecording.py b/src/spikeinterface/core/tests/test_channelslicerecording.py
index 0f8247e85e..1756c022a6 100644
--- a/src/spikeinterface/core/tests/test_channelslicerecording.py
+++ b/src/spikeinterface/core/tests/test_channelslicerecording.py
@@ -75,7 +75,7 @@ def test_failure_with_non_unique_channel_ids():
     seed = 10
     rec = generate_recording(num_channels=4, durations=durations, set_probe=False, seed=seed)
     with pytest.raises(AssertionError):
-        rec_sliced = ChannelSliceRecording(rec, channel_ids=["0", "1"], renamed_channel_ids=[0, 0])
+        _ = ChannelSliceRecording(rec, channel_ids=["0", "1"], renamed_channel_ids=[0, 0])
 
 
 def test_remove_channels():
diff --git a/src/spikeinterface/core/tests/test_generate.py b/src/spikeinterface/core/tests/test_generate.py
index 69fe3ff913..d1360473dc 100644
--- a/src/spikeinterface/core/tests/test_generate.py
+++ b/src/spikeinterface/core/tests/test_generate.py
@@ -98,7 +98,7 @@ def test_memory_sorting_generator():
     seed = 0
 
     before_instanciation_MiB = measure_memory_allocation() / bytes_to_MiB_factor
-    sorting = SortingGenerator(
+    _ = SortingGenerator(
         num_units=num_units,
         sampling_frequency=sampling_frequency,
         durations=durations,
@@ -165,11 +165,10 @@ def test_noise_generator_memory():
     dtype = np.dtype("float32")
     num_channels = 384
     seed = 0
-    num_samples = int(durations[0] * sampling_frequency)
 
     # case 1 preallocation of noise use one noise block 88M for 60000 sample of 384
     before_instanciation_MiB = measure_memory_allocation() / bytes_to_MiB_factor
-    rec1 = MockRecording(
+    _ = MockRecording(
         num_channels=num_channels,
         sampling_frequency=sampling_frequency,
         durations=durations,
@@ -188,7 +187,7 @@ def test_noise_generator_memory():
 
     # case 2: no preallocation very few memory (under 2 MiB)
     before_instanciation_MiB = measure_memory_allocation() / bytes_to_MiB_factor
-    rec2 = MockRecording(
+    _ = MockRecording(
         num_channels=num_channels,
         sampling_frequency=sampling_frequency,
         durations=durations,
@@ -360,17 +359,12 @@ def test_noise_generator_consistency_after_dump(strategy, seed):
     assert np.allclose(traces0, traces1)
 
 
-def test_generate_recording():
-    # check the high level function
-    rec = generate_recording()
-
-
 def test_generate_single_fake_waveform():
     sampling_frequency = 30000.0
     ms_before = 1.0
     ms_after = 3.0
     wf = generate_single_fake_waveform(ms_before=ms_before, ms_after=ms_after, sampling_frequency=sampling_frequency)
-
+    assert wf.shape == (int((ms_before + ms_after) / 1000 * sampling_frequency),)
     # import matplotlib.pyplot as plt
     # times = np.arange(wf.size) / sampling_frequency * 1000 - ms_before
     # fig, ax = plt.subplots()
diff --git a/src/spikeinterface/core/tests/test_node_pipeline.py b/src/spikeinterface/core/tests/test_node_pipeline.py
index 3ea66063ed..7ff3fae682 100644
--- a/src/spikeinterface/core/tests/test_node_pipeline.py
+++ b/src/spikeinterface/core/tests/test_node_pipeline.py
@@ -74,8 +74,6 @@ def test_run_node_pipeline(cache_folder_creation):
     # job_kwargs = dict(chunk_duration="0.5s", n_jobs=2, progress_bar=False)
     job_kwargs = dict(chunk_duration="0.5s", n_jobs=1, progress_bar=False)
 
-    spikes = sorting.to_spike_vector()
-
     # create peaks from spikes
     sorting_analyzer = create_sorting_analyzer(sorting, recording, format="memory")
     sorting_analyzer.compute(["random_spikes", "templates"], **job_kwargs)
@@ -268,6 +266,7 @@ def test_run_node_pipeline(cache_folder_creation):
 
             pickled_node = pickle.dumps(node)
             unpickled_node = pickle.loads(pickled_node)
+            assert isinstance(unpickled_node, type(node))
 
 
 def test_gather_to_zarr_chunking(tmp_path):
diff --git a/src/spikeinterface/core/tests/test_noise_levels_propagation.py b/src/spikeinterface/core/tests/test_noise_levels_propagation.py
index 6c97284efd..d553348d51 100644
--- a/src/spikeinterface/core/tests/test_noise_levels_propagation.py
+++ b/src/spikeinterface/core/tests/test_noise_levels_propagation.py
@@ -8,7 +8,7 @@ def test_skip_noise_levels_propagation(create_cache_folder):
     rec = generate_recording(durations=[5.0], num_channels=4)
     rec.set_property("test", ["1", "2", "3", "4"])
     rec = rec.save(folder=create_cache_folder / "rec_saved_noise")
-    noise_level_raw = get_noise_levels(rec, return_in_uV=False, method="mad")
+    _ = get_noise_levels(rec, return_in_uV=False, method="mad")
     assert "noise_level_mad_raw" in rec.get_property_keys()
 
     rec_frame_slice = rec.frame_slice(start_frame=0, end_frame=1000)
@@ -18,7 +18,7 @@ def test_skip_noise_levels_propagation(create_cache_folder):
     # make scaled
     rec.set_channel_gains([100] * 4)
     rec.set_channel_offsets([0] * 4)
-    noise_level_scaled = get_noise_levels(rec, return_in_uV=True, method="std")
+    _ = get_noise_levels(rec, return_in_uV=True, method="std")
     assert "noise_level_std_scaled" in rec.get_property_keys()
 
     rec_frame_slice = rec.frame_slice(start_frame=0, end_frame=1000)
diff --git a/src/spikeinterface/core/tests/test_npzsortingextractor.py b/src/spikeinterface/core/tests/test_npzsortingextractor.py
index 1e4cf470d1..90a8061bb8 100644
--- a/src/spikeinterface/core/tests/test_npzsortingextractor.py
+++ b/src/spikeinterface/core/tests/test_npzsortingextractor.py
@@ -1,5 +1,6 @@
 from spikeinterface.core import NpzSortingExtractor
 from spikeinterface.core import create_sorting_npz
+from spikeinterface.core.testing import check_sortings_equal
 
 
 def test_NpzSortingExtractor(create_cache_folder):
@@ -13,12 +14,9 @@ def test_NpzSortingExtractor(create_cache_folder):
 
     for segment_index in range(num_seg):
         for unit_id in (0, 1, 2):
-            st = sorting.get_unit_spike_train(unit_id, segment_index=segment_index)
+            _ = sorting.get_unit_spike_train(unit_id, segment_index=segment_index)
 
     file_path_copy = cache_folder / "test_NpzSortingExtractor_copy.npz"
     NpzSortingExtractor.write_sorting(sorting, file_path_copy)
     sorting_copy = NpzSortingExtractor(file_path_copy)
-
-
-if __name__ == "__main__":
-    test_NpzSortingExtractor()
+    check_sortings_equal(sorting, sorting_copy)
diff --git a/src/spikeinterface/core/tests/test_numpy_extractors.py b/src/spikeinterface/core/tests/test_numpy_extractors.py
index 26b6aaf62b..67aab07366 100644
--- a/src/spikeinterface/core/tests/test_numpy_extractors.py
+++ b/src/spikeinterface/core/tests/test_numpy_extractors.py
@@ -27,8 +27,6 @@ def setup_NumpyRecording(tmp_path_factory):
 
     rec = NumpyRecording(timeseries_list, sampling_frequency)
     # print(rec)
-
-    times1 = rec.get_times(1)
     cache_folder = tmp_path_factory.mktemp("cache_folder")
     rec.save(folder=cache_folder / "test_NumpyRecording")
     return cache_folder
diff --git a/src/spikeinterface/core/tests/test_recording_tools.py b/src/spikeinterface/core/tests/test_recording_tools.py
index abeafe8e0c..0166c3bfdd 100644
--- a/src/spikeinterface/core/tests/test_recording_tools.py
+++ b/src/spikeinterface/core/tests/test_recording_tools.py
@@ -11,7 +11,6 @@
     get_random_data_chunks,
     get_chunk_with_margin,
     get_closest_channels,
-    get_channel_distances,
     get_noise_levels,
     order_channels_by_depth,
     do_recording_attributes_match,
@@ -174,8 +173,6 @@ def test_get_closest_channels():
     closest_channels_inds, distances = get_closest_channels(rec)
     closest_channels_inds, distances = get_closest_channels(rec, num_channels=4)
 
-    dist = get_channel_distances(rec)
-
 
 def test_get_noise_levels():
     job_kwargs = dict(n_jobs=1, progress_bar=True)
@@ -186,9 +183,8 @@ def test_get_noise_levels():
 
     rec.set_channel_gains(0.1)
     rec.set_channel_offsets(0)
-    noise_levels = get_noise_levels(rec, return_in_uV=True, force_recompute=True, **job_kwargs)
-
-    noise_levels = get_noise_levels(rec, return_in_uV=True, method="std", **job_kwargs)
+    _ = get_noise_levels(rec, return_in_uV=True, force_recompute=True, **job_kwargs)
+    _ = get_noise_levels(rec, return_in_uV=True, method="std", **job_kwargs)
 
     # Generate a recording following a gaussian distribution to check the result of get_noise.
     std = 6.0
@@ -300,10 +296,9 @@ def test_order_channels_by_depth():
     locations_copy = locations_copy[::-1]
     rec.set_channel_locations(locations_copy)
 
-    order_1d, order_r1d = order_channels_by_depth(rec, dimensions="y")
+    order_1d, _ = order_channels_by_depth(rec, dimensions="y")
     order_2d, order_r2d = order_channels_by_depth(rec, dimensions=("x", "y"))
-    locations_rev = locations_copy[order_1d][order_r1d]
-    order_2d_fliped, order_r2d_fliped = order_channels_by_depth(rec, dimensions=("x", "y"), flip=True)
+    order_2d_fliped, _ = order_channels_by_depth(rec, dimensions=("x", "y"), flip=True)
 
     assert np.array_equal(locations[:, 1], locations_copy[order_1d][:, 1])
     assert np.array_equal(locations_copy[order_1d][:, 1], locations_copy[order_2d][:, 1])
diff --git a/src/spikeinterface/core/tests/test_sorting_tools.py b/src/spikeinterface/core/tests/test_sorting_tools.py
index fe624cb0b6..1cb413c915 100644
--- a/src/spikeinterface/core/tests/test_sorting_tools.py
+++ b/src/spikeinterface/core/tests/test_sorting_tools.py
@@ -191,7 +191,6 @@ def test_random_spikes_selection():
     random_spikes_indices = random_spikes_selection(
         sorting, num_samples, method="uniform", max_spikes_per_unit=max_spikes_per_unit, margin_size=None, seed=2205
     )
-    random_spikes_indices1 = random_spikes_indices
     spikes = sorting.to_spike_vector()
     some_spikes = spikes[random_spikes_indices]
     for unit_index, unit_id in enumerate(sorting.unit_ids):
diff --git a/src/spikeinterface/core/tests/test_sortinganalyzer.py b/src/spikeinterface/core/tests/test_sortinganalyzer.py
index f21499b151..ab01eca320 100644
--- a/src/spikeinterface/core/tests/test_sortinganalyzer.py
+++ b/src/spikeinterface/core/tests/test_sortinganalyzer.py
@@ -641,10 +641,12 @@ def test_extension_params():
         assert ext in computable_extension
         if mod == "spikeinterface.core":
             default_params = get_default_analyzer_extension_params(ext)
+            assert default_params is not None
             # print(ext, default_params)
         else:
             try:
                 default_params = get_default_analyzer_extension_params(ext)
+                assert default_params is not None
                 # print(ext, default_params)
             except Exception:
                 print(f"Failed to import {ext}")
diff --git a/src/spikeinterface/core/tests/test_sparsity.py b/src/spikeinterface/core/tests/test_sparsity.py
index cc9da07387..99457d4686 100644
--- a/src/spikeinterface/core/tests/test_sparsity.py
+++ b/src/spikeinterface/core/tests/test_sparsity.py
@@ -299,10 +299,10 @@ def test_compute_sparsity():
     # Check that we can still pass sparsity kwargs using the old signature (e.g. passing radius_um)
     with pytest.warns(FutureWarning):
         # radius_um is a sparsity kwarg
-        sorting_analyzer_old_kwargs = create_sorting_analyzer(sorting=sorting, recording=recording, radius_um=50)
+        _ = create_sorting_analyzer(sorting=sorting, recording=recording, radius_um=50)
     with pytest.warns(FutureWarning):
         # n_jobs is a job kwarg
-        sorting_analyzer_old_kwargs = create_sorting_analyzer(sorting=sorting, recording=recording, n_jobs=2)
+        _ = create_sorting_analyzer(sorting=sorting, recording=recording, n_jobs=2)
 
     sorting_analyzer.compute("random_spikes")
     sorting_analyzer.compute(
@@ -313,30 +313,24 @@ def test_compute_sparsity():
     # this is needed for method="energy"
 
     # using object SortingAnalyzer
-    sparsity = compute_sparsity(sorting_analyzer, method="best_channels", num_channels=2)
-    sparsity = compute_sparsity(sorting_analyzer, method="radius", radius_um=50.0)
-    sparsity = compute_sparsity(sorting_analyzer, method="closest_channels", num_channels=2)
-    sparsity = compute_sparsity(sorting_analyzer, method="snr", threshold=5)
-    sparsity = compute_sparsity(sorting_analyzer, method="amplitude", threshold=5)
-    sparsity = compute_sparsity(sorting_analyzer, method="energy", threshold=5)
-    sparsity = compute_sparsity(sorting_analyzer, method="by_property", by_property="group")
+    _ = compute_sparsity(sorting_analyzer, method="best_channels", num_channels=2)
+    _ = compute_sparsity(sorting_analyzer, method="radius", radius_um=50.0)
+    _ = compute_sparsity(sorting_analyzer, method="closest_channels", num_channels=2)
+    _ = compute_sparsity(sorting_analyzer, method="snr", threshold=5)
+    _ = compute_sparsity(sorting_analyzer, method="amplitude", threshold=5)
+    _ = compute_sparsity(sorting_analyzer, method="energy", threshold=5)
+    _ = compute_sparsity(sorting_analyzer, method="by_property", by_property="group")
 
     # using object Templates
     templates = sorting_analyzer.get_extension("templates").get_data(outputs="Templates")
     noise_levels = sorting_analyzer.get_extension("noise_levels").get_data()
-    sparsity = compute_sparsity(
-        templates, method="best_channels", num_channels=2, peak_sign="neg", amplitude_mode="extremum"
-    )
-    sparsity = compute_sparsity(
-        templates, method="radius", radius_um=50.0, peak_sign="both", amplitude_mode="peak_to_peak"
-    )
-    sparsity = compute_sparsity(
+    _ = compute_sparsity(templates, method="best_channels", num_channels=2, peak_sign="neg", amplitude_mode="extremum")
+    _ = compute_sparsity(templates, method="radius", radius_um=50.0, peak_sign="both", amplitude_mode="peak_to_peak")
+    _ = compute_sparsity(
         templates, method="snr", noise_levels=noise_levels, threshold=5, peak_sign="neg", amplitude_mode="extremum"
     )
-    sparsity = compute_sparsity(
-        templates, method="amplitude", threshold=5, peak_sign="neg", amplitude_mode="peak_to_peak"
-    )
-    sparsity = compute_sparsity(
+    _ = compute_sparsity(templates, method="amplitude", threshold=5, peak_sign="neg", amplitude_mode="peak_to_peak")
+    _ = compute_sparsity(
         templates, method="closest_channels", num_channels=2, peak_sign="neg", amplitude_mode="extremum"
     )
 
diff --git a/src/spikeinterface/core/tests/test_template_class.py b/src/spikeinterface/core/tests/test_template_class.py
index 953527c8d5..b9b77bc6c7 100644
--- a/src/spikeinterface/core/tests/test_template_class.py
+++ b/src/spikeinterface/core/tests/test_template_class.py
@@ -112,7 +112,7 @@ def test_get_dense_templates(template_type, is_in_uV):
 
 def test_initialization_fail_with_dense_templates():
     with pytest.raises(ValueError, match="Sparsity mask passed but the templates are not sparse"):
-        template = generate_test_template(template_type="sparse_with_dense_templates")
+        _ = generate_test_template(template_type="sparse_with_dense_templates")
 
 
 @pytest.mark.parametrize("is_in_uV", [True, False])
diff --git a/src/spikeinterface/core/tests/test_unitsselectionsorting.py b/src/spikeinterface/core/tests/test_unitsselectionsorting.py
index 890bc0a93e..d01f5d302b 100644
--- a/src/spikeinterface/core/tests/test_unitsselectionsorting.py
+++ b/src/spikeinterface/core/tests/test_unitsselectionsorting.py
@@ -42,7 +42,7 @@ def test_failure_with_non_unique_unit_ids():
     seed = 10
     sorting = generate_sorting(num_units=3, durations=[0.100], sampling_frequency=30000.0, seed=seed)
     with pytest.raises(AssertionError):
-        sorting2 = UnitsSelectionSorting(sorting, unit_ids=["0", "2"], renamed_unit_ids=["a", "a"])
+        _ = UnitsSelectionSorting(sorting, unit_ids=["0", "2"], renamed_unit_ids=["a", "a"])
 
 
 def test_compute_and_cache_spike_vector():
diff --git a/src/spikeinterface/core/tests/test_waveforms_extractor_backwards_compatibility.py b/src/spikeinterface/core/tests/test_waveforms_extractor_backwards_compatibility.py
index dbb64090e1..629778bfd1 100644
--- a/src/spikeinterface/core/tests/test_waveforms_extractor_backwards_compatibility.py
+++ b/src/spikeinterface/core/tests/test_waveforms_extractor_backwards_compatibility.py
@@ -61,16 +61,16 @@ def test_extract_waveforms(create_cache_folder):
     print(we_mock)
 
     for we in (we_old, we_mock):
-        selected_spikes = we.get_sampled_indices(unit_id=sorting.unit_ids[0])
+        _ = we.get_sampled_indices(unit_id=sorting.unit_ids[0])
         # print(selected_spikes.size, selected_spikes.dtype)
 
-        wfs = we.get_waveforms(sorting.unit_ids[0])
+        _ = we.get_waveforms(sorting.unit_ids[0])
         # print(wfs.shape)
 
-        wfs = we.get_waveforms(sorting.unit_ids[0], force_dense=True)
+        _ = we.get_waveforms(sorting.unit_ids[0], force_dense=True)
         # print(wfs.shape)
 
-        templates = we.get_all_templates()
+        _ = we.get_all_templates()
         # print(templates.shape)
 
     # test reading old WaveformsExtractor folder
diff --git a/src/spikeinterface/curation/tests/test_auto_merge.py b/src/spikeinterface/curation/tests/test_auto_merge.py
index 03545c318b..05d5a22994 100644
--- a/src/spikeinterface/curation/tests/test_auto_merge.py
+++ b/src/spikeinterface/curation/tests/test_auto_merge.py
@@ -54,7 +54,7 @@ def test_compute_merge_unit_groups_multi_segment(sorting_analyzer_multi_segment_
     sorting_analyzer = sorting_analyzer_multi_segment_for_curation
     print(sorting_analyzer)
 
-    merge_unit_groups = compute_merge_unit_groups(
+    _ = compute_merge_unit_groups(
         sorting_analyzer,
         preset=preset,
     )
diff --git a/src/spikeinterface/curation/tests/test_curation_format.py b/src/spikeinterface/curation/tests/test_curation_format.py
index a837e510bd..e3d6dcb262 100644
--- a/src/spikeinterface/curation/tests/test_curation_format.py
+++ b/src/spikeinterface/curation/tests/test_curation_format.py
@@ -330,7 +330,6 @@ def test_apply_curation_with_split():
 def test_apply_curation_with_split_multi_segment():
     recording, sorting = generate_ground_truth_recording(durations=[10.0, 10.0], num_units=9, seed=2205)
     sorting = sorting.rename_units(np.array([1, 2, 3, 6, 10, 14, 20, 31, 42]))
-    analyzer = create_sorting_analyzer(sorting, recording, sparse=False)
     num_segments = sorting.get_num_segments()
 
     curation_with_splits_multi_segment = curation_with_splits.copy()
diff --git a/src/spikeinterface/curation/tests/test_curationsorting.py b/src/spikeinterface/curation/tests/test_curationsorting.py
index fb263bec8e..b1a063eac5 100644
--- a/src/spikeinterface/curation/tests/test_curationsorting.py
+++ b/src/spikeinterface/curation/tests/test_curationsorting.py
@@ -138,7 +138,7 @@ def test_curation():
         )
 
     # Test with empty sorting
-    empty_sorting = CurationSorting(NumpySorting.from_unit_dict({}, parent_sort.sampling_frequency))
+    _ = CurationSorting(NumpySorting.from_unit_dict({}, parent_sort.sampling_frequency))
 
 
 if __name__ == "__main__":
diff --git a/src/spikeinterface/curation/tests/test_model_based_curation.py b/src/spikeinterface/curation/tests/test_model_based_curation.py
index 6cfb86fe9d..8563c8130e 100644
--- a/src/spikeinterface/curation/tests/test_model_based_curation.py
+++ b/src/spikeinterface/curation/tests/test_model_based_curation.py
@@ -96,9 +96,7 @@ def test_model_based_classification_get_metrics_for_classification(
 
     all_metric_names, all_metric_columns, qm_names, tm_names = required_metrics
 
-    model_based_classification = ModelBasedClassification(
-        sorting_analyzer=sorting_analyzer_for_unitrefine_curation, pipeline=model[0]
-    )
+    _ = ModelBasedClassification(sorting_analyzer=sorting_analyzer_for_unitrefine_curation, pipeline=model[0])
 
     # Compute some (but not all) of the required metrics in sorting_analyzer, should still error
     sorting_analyzer_for_unitrefine_curation.compute("quality_metrics", metric_names=[all_metric_names[0]])
@@ -157,7 +155,7 @@ def test_predict_labels_with_phy_export(sorting_analyzer_for_unitrefine_curation
     model_based_classification = ModelBasedClassification(
         sorting_analyzer=sorting_analyzer_for_unitrefine_curation, pipeline=model[0]
     )
-    classified_units = model_based_classification.predict_labels(export_to_phy=True, phy_folder=phy_folder)
+    _ = model_based_classification.predict_labels(export_to_phy=True, phy_folder=phy_folder)
 
     # Check that the cluster_prediction.tsv file was created in the specified phy_folder
     assert (phy_folder / "cluster_prediction.tsv").exists()
diff --git a/src/spikeinterface/curation/tests/test_sortingview_curation.py b/src/spikeinterface/curation/tests/test_sortingview_curation.py
index 9e4d579f62..22ce09f7b8 100644
--- a/src/spikeinterface/curation/tests/test_sortingview_curation.py
+++ b/src/spikeinterface/curation/tests/test_sortingview_curation.py
@@ -95,7 +95,6 @@ def test_sha1_curation():
     assert "accept" in sorting_curated_sha1.get_property_keys()
     assert "mua" in sorting_curated_sha1.get_property_keys()
     assert "artifact" in sorting_curated_sha1.get_property_keys()
-    unit_ids = sorting_curated_sha1.unit_ids
     sorting_curated_sha1_accepted = apply_sortingview_curation(sorting, uri_or_json=sha1_uri, include_labels=["accept"])
     sorting_curated_sha1_mua = apply_sortingview_curation(sorting, uri_or_json=sha1_uri, exclude_labels=["mua"])
     sorting_curated_sha1_art_mua = apply_sortingview_curation(
@@ -255,7 +254,7 @@ def test_json_no_merge_curation():
     sorting = sorting.rename_units(new_unit_ids=unit_ids_as_int)
 
     json_file = parent_folder / "sv-sorting-curation-no-merge.json"
-    sorting_curated = apply_sortingview_curation(sorting, uri_or_json=json_file)
+    _ = apply_sortingview_curation(sorting, uri_or_json=json_file)
 
 
 if __name__ == "__main__":
diff --git a/src/spikeinterface/curation/tests/test_unitrefine_curation.py b/src/spikeinterface/curation/tests/test_unitrefine_curation.py
index 99764fffd7..7c8fb29705 100644
--- a/src/spikeinterface/curation/tests/test_unitrefine_curation.py
+++ b/src/spikeinterface/curation/tests/test_unitrefine_curation.py
@@ -48,7 +48,7 @@ def test_unitrefine_label_units_hf(sorting_analyzer_for_unitrefine_curation):
 
     # test passing none
     with pytest.raises(ValueError):
-        labels = unitrefine_label_units(
+        _ = unitrefine_label_units(
             sorting_analyzer_for_unitrefine_curation,
             noise_neural_classifier=None,
             sua_mua_classifier=None,
@@ -56,14 +56,14 @@ def test_unitrefine_label_units_hf(sorting_analyzer_for_unitrefine_curation):
 
     # test warnings when unexpected labels are returned
     with pytest.warns(UserWarning):
-        labels = unitrefine_label_units(
+        _ = unitrefine_label_units(
             sorting_analyzer_for_unitrefine_curation,
             noise_neural_classifier="SpikeInterface/UnitRefine_sua_mua_classifier_lightweight",
             sua_mua_classifier=None,
         )
 
     with pytest.warns(UserWarning):
-        labels = unitrefine_label_units(
+        _ = unitrefine_label_units(
             sorting_analyzer_for_unitrefine_curation,
             noise_neural_classifier=None,
             sua_mua_classifier="SpikeInterface/UnitRefine_noise_neural_classifier_lightweight",
@@ -78,13 +78,13 @@ def test_unitrefine_label_units_with_local_models(sorting_analyzer_for_unitrefin
     sorting_analyzer_for_unitrefine_curation.compute("quality_metrics")
 
     # test passing model folder
-    labels = unitrefine_label_units(
+    _ = unitrefine_label_units(
         sorting_analyzer_for_unitrefine_curation,
         noise_neural_classifier=trained_pipeline_path,
     )
 
     # test passing model folder
-    labels = unitrefine_label_units(
+    _ = unitrefine_label_units(
         sorting_analyzer_for_unitrefine_curation,
         noise_neural_classifier=trained_pipeline_path / "best_model.skops",
     )
diff --git a/src/spikeinterface/extractors/tests/common_tests.py b/src/spikeinterface/extractors/tests/common_tests.py
index ea733a368b..0741785d9f 100644
--- a/src/spikeinterface/extractors/tests/common_tests.py
+++ b/src/spikeinterface/extractors/tests/common_tests.py
@@ -102,7 +102,7 @@ def test_neo_annotations(self):
                 path = entity
                 kwargs = {}
             if hasattr(self.ExtractorClass, "NeoRawIOClass"):
-                rec = self.ExtractorClass(self.get_full_path(path), all_annotations=True, **kwargs)
+                _ = self.ExtractorClass(self.get_full_path(path), all_annotations=True, **kwargs)
 
     def test_pickling(self):
         for entity in self.entities:
diff --git a/src/spikeinterface/extractors/tests/test_bidsextractors.py b/src/spikeinterface/extractors/tests/test_bidsextractors.py
index 2c78c844ce..075c8e7166 100644
--- a/src/spikeinterface/extractors/tests/test_bidsextractors.py
+++ b/src/spikeinterface/extractors/tests/test_bidsextractors.py
@@ -5,6 +5,7 @@
 
 @pytest.mark.skip("BIDS is tested locally only at the moment")
 def test_read_bids_folder():
+    import spikeinterface.full as si
     # gin get NeuralEnsemble/BEP032-examples
     # cd BEP032-examples
     # gin get NeuralEnsemble/BEP032-examples
@@ -16,12 +17,10 @@ def test_read_bids_folder():
     recordings = read_bids(folder_path)
     # ~ print(recordings)
 
-    rec0 = recordings[0]
+    _ = recordings[0]
     rec1 = recordings[1]
     rec2 = recordings[2]
 
-    import spikeinterface.full as si
-
     sorting = si.run_sorter("herdingspikes", rec1)
     print(sorting)
     exit()
@@ -32,7 +31,6 @@ def test_read_bids_folder():
     import matplotlib.pyplot as plt
     from probeinterface.plotting import plot_probe_group
 
-    fig, ax = plt.subplots()
     probegroup = rec2.get_probegroup()
     print(probegroup)
     plot_probe_group(
diff --git a/src/spikeinterface/extractors/tests/test_datalad_downloading.py b/src/spikeinterface/extractors/tests/test_datalad_downloading.py
index 8abccc6707..082fe52da3 100644
--- a/src/spikeinterface/extractors/tests/test_datalad_downloading.py
+++ b/src/spikeinterface/extractors/tests/test_datalad_downloading.py
@@ -13,6 +13,7 @@ def test_download_dataset():
 
     # local_folder automatic
     local_path = download_dataset(repo=repo, remote_path=remote_path, local_folder=None)
+    assert local_path is not None
 
 
 if __name__ == "__main__":
diff --git a/src/spikeinterface/extractors/tests/test_herdingspikesextractors.py b/src/spikeinterface/extractors/tests/test_herdingspikesextractors.py
index 2286e229c0..15828c4c70 100644
--- a/src/spikeinterface/extractors/tests/test_herdingspikesextractors.py
+++ b/src/spikeinterface/extractors/tests/test_herdingspikesextractors.py
@@ -1,7 +1,5 @@
 import pytest
 
-from spikeinterface.extractors import *
-
 
 @pytest.mark.skip("HerdingSpikes can be tested after running run_herdingspikes()")
 def test_herdingspikesextractors():
diff --git a/src/spikeinterface/extractors/tests/test_mdaextractors.py b/src/spikeinterface/extractors/tests/test_mdaextractors.py
index 88daddeab4..e0db494eb2 100644
--- a/src/spikeinterface/extractors/tests/test_mdaextractors.py
+++ b/src/spikeinterface/extractors/tests/test_mdaextractors.py
@@ -17,7 +17,7 @@ def test_mda_extractors(create_cache_folder):
 
     MdaRecordingExtractor.write_recording(rec, cache_folder / "mdatest")
     rec_mda = MdaRecordingExtractor(cache_folder / "mdatest")
-    probe = rec_mda.get_probe()
+    assert rec_mda.has_probe()
 
     check_recordings_equal(rec, rec_mda, return_in_uV=False)
 
diff --git a/src/spikeinterface/extractors/tests/test_nwbextractors.py b/src/spikeinterface/extractors/tests/test_nwbextractors.py
index b61eb1f4b8..ba724b4731 100644
--- a/src/spikeinterface/extractors/tests/test_nwbextractors.py
+++ b/src/spikeinterface/extractors/tests/test_nwbextractors.py
@@ -447,7 +447,7 @@ def test_failure_with_wrong_electrical_series_path(generate_nwbfile, use_pynwb):
     """Test that the extractor raises an error if the electrical series name is not found."""
     path_to_nwbfile, _ = generate_nwbfile
     with pytest.raises(ValueError):
-        recording_extractor = NwbRecordingExtractor(
+        _ = NwbRecordingExtractor(
             path_to_nwbfile,
             electrical_series_path="acquisition/ElectricalSeries3",
             use_pynwb=use_pynwb,
@@ -1097,7 +1097,7 @@ def test_multiple_unit_tables(tmp_path, use_pynwb):
 
     # passing a non existing unit table name should raise an error
     with pytest.raises(ValueError):
-        sorting_extractor = NwbSortingExtractor(
+        _ = NwbSortingExtractor(
             file_path=file_path, sampling_frequency=10.0, t_start=0, use_pynwb=use_pynwb, unit_table_path="units2"
         )
 
diff --git a/src/spikeinterface/extractors/tests/test_nwbextractors_streaming.py b/src/spikeinterface/extractors/tests/test_nwbextractors_streaming.py
index bc5ff1c823..691f0c978b 100644
--- a/src/spikeinterface/extractors/tests/test_nwbextractors_streaming.py
+++ b/src/spikeinterface/extractors/tests/test_nwbextractors_streaming.py
@@ -42,8 +42,6 @@ def test_recording_s3_nwb_fsspec(tmp_path, cache):
     dtype = rec.get_dtype()
 
     for segment_index in range(num_seg):
-        num_samples = rec.get_num_samples(segment_index=segment_index)
-
         full_traces = rec.get_traces(segment_index=segment_index, start_frame=start_frame, end_frame=end_frame)
         assert full_traces.shape == (num_frames, num_chans)
         assert full_traces.dtype == dtype
@@ -78,8 +76,6 @@ def test_recording_s3_nwb_remfile():
     dtype = rec.get_dtype()
 
     for segment_index in range(num_seg):
-        num_samples = rec.get_num_samples(segment_index=segment_index)
-
         full_traces = rec.get_traces(segment_index=segment_index, start_frame=start_frame, end_frame=end_frame)
         assert full_traces.shape == (num_frames, num_chans)
         assert full_traces.dtype == dtype
@@ -108,8 +104,6 @@ def test_recording_s3_nwb_remfile_file_like(tmp_path):
     dtype = rec.get_dtype()
 
     for segment_index in range(num_seg):
-        num_samples = rec.get_num_samples(segment_index=segment_index)
-
         full_traces = rec.get_traces(segment_index=segment_index, start_frame=start_frame, end_frame=end_frame)
         assert full_traces.shape == (num_frames, num_chans)
         assert full_traces.dtype == dtype
diff --git a/src/spikeinterface/extractors/tests/test_shybridextractors.py b/src/spikeinterface/extractors/tests/test_shybridextractors.py
index e4458f0b36..b69e37cdbd 100644
--- a/src/spikeinterface/extractors/tests/test_shybridextractors.py
+++ b/src/spikeinterface/extractors/tests/test_shybridextractors.py
@@ -22,6 +22,7 @@ def test_shybrid_extractors(create_cache_folder):
     )
     rec_shybrid = SHYBRIDRecordingExtractor(cache_folder / "shybridtest" / "recording.yml")
     probe = rec_shybrid.get_probe()
+    assert probe is not None
 
     check_recordings_equal(rec, rec_shybrid, return_in_uV=False)
 
diff --git a/src/spikeinterface/extractors/tests/test_toy_example.py b/src/spikeinterface/extractors/tests/test_toy_example.py
index fccb977c85..f863d89cdb 100644
--- a/src/spikeinterface/extractors/tests/test_toy_example.py
+++ b/src/spikeinterface/extractors/tests/test_toy_example.py
@@ -12,6 +12,7 @@ def test_toy_example():
     assert sorting.get_num_segments() == 1
 
     probe = rec.get_probe()
+    assert probe is not None
 
 
 if __name__ == "__main__":
diff --git a/src/spikeinterface/generation/tests/test_drifing_generator.py b/src/spikeinterface/generation/tests/test_drifing_generator.py
index 5eb49a04c6..99210abb6b 100644
--- a/src/spikeinterface/generation/tests/test_drifing_generator.py
+++ b/src/spikeinterface/generation/tests/test_drifing_generator.py
@@ -9,17 +9,13 @@
 
 def test_make_one_displacement_vector():
 
-    displacement_vector = make_one_displacement_vector(
-        drift_mode="zigzag", duration=700.0, period_s=300, t_start_drift=100.0
-    )
+    _ = make_one_displacement_vector(drift_mode="zigzag", duration=700.0, period_s=300, t_start_drift=100.0)
 
-    displacement_vector = make_one_displacement_vector(
+    _ = make_one_displacement_vector(
         drift_mode="bump", duration=700.0, period_s=300, bump_interval_s=(30, 90.0), t_start_drift=100.0, seed=2205
     )
 
-    displacement_vector = make_one_displacement_vector(
-        drift_mode="random_walk", duration=700.0, t_start_drift=100.0, seed=2205
-    )
+    _ = make_one_displacement_vector(drift_mode="random_walk", duration=700.0, t_start_drift=100.0, seed=2205)
 
     # import matplotlib.pyplot as plt
     # fig, ax = plt.subplots()
diff --git a/src/spikeinterface/generation/tests/test_noise_tools.py b/src/spikeinterface/generation/tests/test_noise_tools.py
index f633ed1de4..d09ea86fde 100644
--- a/src/spikeinterface/generation/tests/test_noise_tools.py
+++ b/src/spikeinterface/generation/tests/test_noise_tools.py
@@ -8,7 +8,7 @@
 def test_generate_noise():
     probe = probeinterface.generate_multi_columns_probe()
 
-    noise = generate_noise(
+    _ = generate_noise(
         probe,
         sampling_frequency=25000.0,
         durations=[10.0],
@@ -18,7 +18,7 @@ def test_generate_noise():
         seed=2205,
     )
 
-    noise = generate_noise(
+    _ = generate_noise(
         probe,
         sampling_frequency=25000.0,
         durations=[10.0],
diff --git a/src/spikeinterface/metrics/quality/tests/test_metrics_functions.py b/src/spikeinterface/metrics/quality/tests/test_metrics_functions.py
index 5a2742ad26..316a01ef17 100644
--- a/src/spikeinterface/metrics/quality/tests/test_metrics_functions.py
+++ b/src/spikeinterface/metrics/quality/tests/test_metrics_functions.py
@@ -309,7 +309,7 @@ def test_calculate_firing_range(sorting_analyzer_simple):
     firing_ranges_empty = compute_firing_ranges(sorting_analyzer, periods=empty_periods)
     assert np.all(np.isnan(np.array(list(firing_ranges_empty.values()))))
 
-    with pytest.warns(UserWarning) as w:
+    with pytest.warns(UserWarning):
         firing_ranges_nan = compute_firing_ranges(
             sorting_analyzer, bin_size_s=sorting_analyzer.get_total_duration() + 1
         )
@@ -394,6 +394,7 @@ def test_calculate_amplitude_cv_metrics(sorting_analyzer_simple, periods_simple)
 def test_calculate_snrs(sorting_analyzer_simple, periods_simple):
     sorting_analyzer = sorting_analyzer_simple
     snrs = compute_snrs(sorting_analyzer)
+    assert isinstance(snrs, dict)
     # SNR doesn't support periods
 
     # testing method accuracy with magic number is not a good pratcice, I remove this.
diff --git a/src/spikeinterface/metrics/quality/tests/test_quality_metric_calculator.py b/src/spikeinterface/metrics/quality/tests/test_quality_metric_calculator.py
index 34b94f625b..2f45a45449 100644
--- a/src/spikeinterface/metrics/quality/tests/test_quality_metric_calculator.py
+++ b/src/spikeinterface/metrics/quality/tests/test_quality_metric_calculator.py
@@ -217,7 +217,7 @@ def test_quality_metrics_with_periods():
             periods[idx]["end_sample_index"] = period_end
             periods[idx]["segment_index"] = segment_index
 
-    metrics_ext_periods = compute_quality_metrics(
+    _ = compute_quality_metrics(
         sorting_analyzer,
         metric_names=None,
         skip_pc_metrics=True,
@@ -239,7 +239,7 @@ def test_quality_metrics_with_periods():
 
     # should not fail if external periods are the same as valid unit periods
     valid_periods = sorting_analyzer.get_extension("valid_unit_periods").get_data(outputs="numpy")
-    metrics_ext_periods = compute_quality_metrics(
+    _ = compute_quality_metrics(
         sorting_analyzer,
         metric_names=None,
         skip_pc_metrics=True,
diff --git a/src/spikeinterface/postprocessing/tests/test_multi_extensions.py b/src/spikeinterface/postprocessing/tests/test_multi_extensions.py
index b863037cdc..d8180b6e1d 100644
--- a/src/spikeinterface/postprocessing/tests/test_multi_extensions.py
+++ b/src/spikeinterface/postprocessing/tests/test_multi_extensions.py
@@ -139,7 +139,7 @@ def test_SortingAnalyzer_merge_all_extensions(dataset_to_merge, lazy, sparse, fo
 
     set_global_job_kwargs(n_jobs=1)
 
-    rng = np.random.default_rng(seed=2308)
+    _ = np.random.default_rng(seed=2308)
 
     recording, sorting, other_ids = dataset_to_merge
 
diff --git a/src/spikeinterface/preprocessing/deepinterpolation/tests/test_deepinterpolation.py b/src/spikeinterface/preprocessing/deepinterpolation/tests/test_deepinterpolation.py
index 1d99788525..d61aca4239 100644
--- a/src/spikeinterface/preprocessing/deepinterpolation/tests/test_deepinterpolation.py
+++ b/src/spikeinterface/preprocessing/deepinterpolation/tests/test_deepinterpolation.py
@@ -97,12 +97,8 @@ def deepinterpolation_model(recording_and_shape_fixture, create_cache_folder):
 
 
 @pytest.mark.skipif(not HAVE_DEEPINTERPOLATION, reason="requires deepinterpolation")
-def test_deepinterpolation_transfer(
-    recording_and_shape_fixture, tmp_path, create_cache_folder, deepinterpolation_model
-):
+def test_deepinterpolation_transfer(recording_and_shape_fixture, tmp_path, deepinterpolation_model):
     recording, desired_shape = recording_and_shape_fixture
-    cache_folder = create_cache_folder
-
     existing_model_path = deepinterpolation_model
     model_folder = Path(tmp_path) / "transfer"
 
@@ -127,10 +123,9 @@ def test_deepinterpolation_transfer(
 
 
 @pytest.mark.skipif(not HAVE_DEEPINTERPOLATION, reason="requires deepinterpolation")
-def test_deepinterpolation_inference(recording_and_shape_fixture, create_cache_folder, deepinterpolation_model):
+def test_deepinterpolation_inference(recording_and_shape_fixture, deepinterpolation_model):
     recording, _ = recording_and_shape_fixture
     pre_frame = post_frame = 20
-    cache_folder = create_cache_folder
     existing_model_path = deepinterpolation_model
     recording_di = deepinterpolate(
         recording, model_path=existing_model_path, pre_frame=pre_frame, post_frame=post_frame, pre_post_omission=1
diff --git a/src/spikeinterface/preprocessing/tests/test_common_reference.py b/src/spikeinterface/preprocessing/tests/test_common_reference.py
index 9a5b81d9c8..d3559d862b 100644
--- a/src/spikeinterface/preprocessing/tests/test_common_reference.py
+++ b/src/spikeinterface/preprocessing/tests/test_common_reference.py
@@ -242,7 +242,7 @@ def test_min_local_radius():
     # remove closest channel to first channel
     recording = recording.remove_channels(recording.channel_ids[1:5])
     with pytest.warns(UserWarning):
-        recording_local_car = common_reference(
+        _ = common_reference(
             recording, reference="local", local_radius=(60, 150), operator="average", min_local_neighbors=5
         )
 
diff --git a/src/spikeinterface/preprocessing/tests/test_filter.py b/src/spikeinterface/preprocessing/tests/test_filter.py
index 42d6619671..13a5a42c03 100644
--- a/src/spikeinterface/preprocessing/tests/test_filter.py
+++ b/src/spikeinterface/preprocessing/tests/test_filter.py
@@ -109,8 +109,8 @@ def test_causal_kwarg_error_raised(self, recording_and_data):
         """
         recording, raw_data = recording_and_data
 
-        with pytest.raises(BaseException) as e:
-            filt_data = causal_filter(recording, direction="forward-backward")
+        with pytest.raises(BaseException):
+            _ = causal_filter(recording, direction="forward-backward")
 
     def _run_iirfilter(self, options, recording):
         """
@@ -140,34 +140,31 @@ def _get_filter_options(self):
 
 
 def test_filter(create_cache_folder):
+    from scipy.signal import iirfilter
+
     rec = generate_recording()
     rec = rec.save(folder=create_cache_folder / "test_filter_recording")
 
     rec2 = bandpass_filter(rec, freq_min=300.0, freq_max=6000.0)
 
     # compute by chunk
-    rec2_cached0 = rec2.save(
-        folder=create_cache_folder / "rec2_cached0", chunk_size=100000, verbose=False, progress_bar=True
-    )
+    _ = rec2.save(folder=create_cache_folder / "rec2_cached0", chunk_size=100000, verbose=False, progress_bar=True)
 
-    # compute by chunkf with joblib
+    # compute by chunk in parallel
     rec2_cached1 = rec2.save(folder=create_cache_folder / "rec2_cached1", total_memory="10k", n_jobs=4, verbose=True)
 
     # compute once
-    rec2_cached2 = rec2.save(folder=create_cache_folder / "rec2_cached2", verbose=False)
+    _ = rec2.save(folder=create_cache_folder / "rec2_cached2", verbose=False)
 
     trace0 = rec2.get_traces(segment_index=0)
     trace1 = rec2_cached1.get_traces(segment_index=0)
 
     # other filtering types
-    rec3 = filter(rec, band=500.0, btype="highpass", filter_mode="ba", filter_order=2, margin_ms=5.0)
-    rec4 = notch_filter(rec, freq=3000, q=30, margin_ms=5.0)
+    _ = filter(rec, band=500.0, btype="highpass", filter_mode="ba", filter_order=2, margin_ms=5.0)
+    _ = notch_filter(rec, freq=3000, q=30, margin_ms=5.0)
     rec5 = causal_filter(rec, direction="forward")
     rec6 = causal_filter(rec, direction="backward")
 
-    # filter from coefficients
-    from scipy.signal import iirfilter
-
     coeff = iirfilter(8, [0.02, 0.4], rs=30, btype="band", analog=False, ftype="cheby2", output="sos")
     rec5 = filter(rec, coeff=coeff, filter_mode="sos", margin_ms=5.0)
 
@@ -178,7 +175,7 @@ def test_filter(create_cache_folder):
 
     trace50 = rec5.get_traces(segment_index=0)
     trace51 = rec5_cached0.get_traces(segment_index=0)
-
+    assert np.allclose(trace50, trace51)
     assert np.allclose(rec.get_times(0), rec2.get_times(0))
 
     # reflect padding test
@@ -214,7 +211,7 @@ def test_filter_opencl():
     rec_filtered = rec_filtered.save(chunk_size=1000, progress_bar=True, n_jobs=30)
 
     rec2 = filter(rec, engine="opencl")
-    rec2_cached0 = rec2.save(chunk_size=1000, verbose=False, progress_bar=True, n_jobs=1)
+    _ = rec2.save(chunk_size=1000, verbose=False, progress_bar=True, n_jobs=1)
     # rec2_cached0 = rec2.save(chunk_size=1000,verbose=False, progress_bar=True, n_jobs=4)
 
     # import matplotlib.pyplot as plt
diff --git a/src/spikeinterface/preprocessing/tests/test_filter_gaussian.py b/src/spikeinterface/preprocessing/tests/test_filter_gaussian.py
index f3da50671d..4cb822cf07 100644
--- a/src/spikeinterface/preprocessing/tests/test_filter_gaussian.py
+++ b/src/spikeinterface/preprocessing/tests/test_filter_gaussian.py
@@ -56,7 +56,6 @@ def test_bandpower(freq_min, freq_max, debug=False):
 
     fs = 1000
     T = 300
-    t = np.arange(0, T, 1 / fs)
 
     rng = np.random.default_rng()
     x = rng.standard_normal(T * fs)
diff --git a/src/spikeinterface/preprocessing/tests/test_highpass_spatial_filter.py b/src/spikeinterface/preprocessing/tests/test_highpass_spatial_filter.py
index 89e8e36cf8..b4579451a1 100644
--- a/src/spikeinterface/preprocessing/tests/test_highpass_spatial_filter.py
+++ b/src/spikeinterface/preprocessing/tests/test_highpass_spatial_filter.py
@@ -88,8 +88,7 @@ def test_highpass_spatial_filter_synthetic_data(num_channels, ntr_pad, ntr_tap,
     options = dict(lagc=lagc, ntr_pad=ntr_pad, ntr_tap=ntr_tap, butter_kwargs=butter_kwargs)
 
     durations = [2, 2]
-    rng = np.random.default_rng(seed=100)
-    si_recording = generate_recording(num_channels=num_channels, durations=durations)
+    si_recording = generate_recording(num_channels=num_channels, durations=durations, seed=100)
 
     _, si_highpass_spatial_filter = run_si_highpass_filter(si_recording, get_traces=False, **options)
     frames = [(0, 500), (30000, 33000), (57000, 60000)]
diff --git a/src/spikeinterface/preprocessing/tests/test_motion.py b/src/spikeinterface/preprocessing/tests/test_motion.py
index 07dd810890..01dce124ac 100644
--- a/src/spikeinterface/preprocessing/tests/test_motion.py
+++ b/src/spikeinterface/preprocessing/tests/test_motion.py
@@ -10,6 +10,7 @@
     compute_motion,
 )
 from spikeinterface.preprocessing.motion import _get_default_motion_params
+from spikeinterface.sortingcomponents.motion import InterpolateMotionRecording
 
 
 def test_estimate_and_correct_motion(create_cache_folder):
@@ -21,6 +22,7 @@ def test_estimate_and_correct_motion(create_cache_folder):
         shutil.rmtree(folder)
 
     rec_corrected = correct_motion(rec, folder=folder, estimate_motion_kwargs={"win_step_um": 50, "win_scale_um": 100})
+    assert isinstance(rec_corrected, InterpolateMotionRecording)
 
     # test reloading motion info
     motion_info = load_motion_info(folder)
@@ -43,7 +45,7 @@ def test_get_motion_parameters_preset():
     from pprint import pprint
 
     p = _get_default_motion_params()
-    # pprint(p)
+    assert isinstance(p, dict)
 
     params = get_motion_parameters_preset("nonrigid_accurate")
     params = get_motion_parameters_preset("dredge")
diff --git a/src/spikeinterface/preprocessing/tests/test_normalize_scale.py b/src/spikeinterface/preprocessing/tests/test_normalize_scale.py
index a304a18f18..58d6432ae5 100644
--- a/src/spikeinterface/preprocessing/tests/test_normalize_scale.py
+++ b/src/spikeinterface/preprocessing/tests/test_normalize_scale.py
@@ -93,8 +93,8 @@ def test_zscore_int():
     zscore_recording = zscore(rec_int, dtype="int16", int_scale=256, mode="mean+std", seed=seed)
     traces = zscore_recording.get_traces(segment_index=0)
     trace_mean = np.mean(traces, axis=0)
-    trace_std = np.std(traces, axis=0)
     assert np.all(np.abs(trace_mean) < 1)
+    # trace_std = np.std(traces, axis=0)
     # assert np.all(np.abs(trace_std - 256) < 1)
 
 
diff --git a/src/spikeinterface/preprocessing/tests/test_phase_shift.py b/src/spikeinterface/preprocessing/tests/test_phase_shift.py
index bd8a5b209c..12d4efdecf 100644
--- a/src/spikeinterface/preprocessing/tests/test_phase_shift.py
+++ b/src/spikeinterface/preprocessing/tests/test_phase_shift.py
@@ -20,7 +20,6 @@ def create_shifted_channel():
 
     ratio = 10
     sr = sr_h / ratio
-    times = times_h[0::ratio]
     delay_sample = 4
     sig0 = sig_h[0::ratio]
     sig1 = sig_h[delay_sample::ratio]
diff --git a/src/spikeinterface/preprocessing/tests/test_silence_periods.py b/src/spikeinterface/preprocessing/tests/test_silence_periods.py
index 5b8598aee7..fcc25a8b28 100644
--- a/src/spikeinterface/preprocessing/tests/test_silence_periods.py
+++ b/src/spikeinterface/preprocessing/tests/test_silence_periods.py
@@ -9,10 +9,7 @@
 from pathlib import Path
 
 
-def test_silence(create_cache_folder):
-
-    cache_folder = create_cache_folder
-
+def test_silence():
     rec = generate_recording()
 
     periods = np.array([(0, 0, 1000), (0, 5000, 6000)], dtype=base_period_dtype)
@@ -46,10 +43,7 @@ def test_silence(create_cache_folder):
     assert not np.all(traces_mix[:-200] == 0)
 
 
-def test_silence_with_apodization(create_cache_folder):
-
-    cache_folder = create_cache_folder
-
+def test_silence_with_apodization():
     rec = generate_recording()
 
     periods = np.array([(0, 0, 1000), (0, 5000, 6000)], dtype=base_period_dtype)
diff --git a/src/spikeinterface/preprocessing/tests/test_zero_padding.py b/src/spikeinterface/preprocessing/tests/test_zero_padding.py
index b6fcb00f03..724dc255f9 100644
--- a/src/spikeinterface/preprocessing/tests/test_zero_padding.py
+++ b/src/spikeinterface/preprocessing/tests/test_zero_padding.py
@@ -251,7 +251,6 @@ def test_trace_padded_recording_retrieve_traces_with_partial_padding(recording,
 
 @pytest.mark.parametrize("padding_start, padding_end", [(5, 5), (0, 5), (5, 0), (0, 0)])
 def test_trace_padded_recording_retrieve_only_start_padding(recording, padding_start, padding_end):
-    num_samples = recording.get_num_samples()
     num_channels = recording.get_num_channels()
 
     padded_recording = TracePaddedRecording(
diff --git a/src/spikeinterface/sorters/internal/tests/test_spykingcircus2.py b/src/spikeinterface/sorters/internal/tests/test_spykingcircus2.py
index 5188dd8329..7350809414 100644
--- a/src/spikeinterface/sorters/internal/tests/test_spykingcircus2.py
+++ b/src/spikeinterface/sorters/internal/tests/test_spykingcircus2.py
@@ -18,7 +18,7 @@ def test_with_numpy_gather(self):
 
         sorter_params["matching"]["gather_mode"] = "npy"
 
-        sorting = run_sorter(
+        _ = run_sorter(
             sorter_name,
             recording,
             folder=output_folder,
diff --git a/src/spikeinterface/sorters/internal/tests/test_tridesclous2.py b/src/spikeinterface/sorters/internal/tests/test_tridesclous2.py
index 18d58e55ab..73d8e34a42 100644
--- a/src/spikeinterface/sorters/internal/tests/test_tridesclous2.py
+++ b/src/spikeinterface/sorters/internal/tests/test_tridesclous2.py
@@ -25,7 +25,7 @@ def test_with_numpy_gather(self):
 
         sorter_params["gather_mode"] = "npy"
 
-        sorting = run_sorter(
+        _ = run_sorter(
             sorter_name,
             recording,
             folder=output_folder,
diff --git a/src/spikeinterface/sorters/tests/test_container_tools.py b/src/spikeinterface/sorters/tests/test_container_tools.py
index 2f3b176cc5..9fa2a69974 100644
--- a/src/spikeinterface/sorters/tests/test_container_tools.py
+++ b/src/spikeinterface/sorters/tests/test_container_tools.py
@@ -101,24 +101,24 @@ def test_install_package_in_container():
     container_client = ContainerClient(mode, container_image, volumes, py_user_base, extra_kwargs)
     container_client.start()
 
-    txt = container_client.run_command("pip install --user --upgrade pip")
+    _ = container_client.run_command("pip install --user --upgrade pip")
 
     # # pypi installation
-    txt = install_package_in_container(container_client, "neo", installation_mode="pypi", version="0.11.0")
+    _ = install_package_in_container(container_client, "neo", installation_mode="pypi", version="0.11.0")
     # print(txt)
-    txt = container_client.run_command("pip list")
+    _ = container_client.run_command("pip list")
     # print(txt)
 
     # # github installation
-    txt = install_package_in_container(
+    _ = install_package_in_container(
         container_client, "spikeinterface", extra="[full]", installation_mode="github", version="0.99.0"
     )
     # print(txt)
-    txt = container_client.run_command("pip list")
+    _ = container_client.run_command("pip list")
     # print(txt)
 
     # folder installation
-    txt = install_package_in_container(
+    _ = install_package_in_container(
         container_client,
         "spikeinterface",
         extra="[full]",
@@ -127,7 +127,7 @@ def test_install_package_in_container():
     )
     # print(txt)
 
-    txt = container_client.run_command("pip list")
+    _ = container_client.run_command("pip list")
     # print(txt)
 
     container_client.stop()
diff --git a/src/spikeinterface/sortingcomponents/clustering/tests/test_clustering.py b/src/spikeinterface/sortingcomponents/clustering/tests/test_clustering.py
index 35984f3732..081c6c02d3 100644
--- a/src/spikeinterface/sortingcomponents/clustering/tests/test_clustering.py
+++ b/src/spikeinterface/sortingcomponents/clustering/tests/test_clustering.py
@@ -107,7 +107,7 @@ def test_templates_from_svd(recording, peaks, job_kwargs):
     peaks_svd, sparse_mask, svd_model = extract_peaks_svd(
         recording, peaks, n_components=1, ms_before=1, ms_after=1, job_kwargs=job_kwargs
     )
-    templates = get_templates_from_peaks_and_svd(
+    _ = get_templates_from_peaks_and_svd(
         recording,
         peaks,
         peaks["channel_index"],
diff --git a/src/spikeinterface/sortingcomponents/clustering/tests/test_isosplit_isocut.py b/src/spikeinterface/sortingcomponents/clustering/tests/test_isosplit_isocut.py
index 1b1deffc8a..7635b158b6 100644
--- a/src/spikeinterface/sortingcomponents/clustering/tests/test_isosplit_isocut.py
+++ b/src/spikeinterface/sortingcomponents/clustering/tests/test_isosplit_isocut.py
@@ -147,10 +147,10 @@ def test_isosplit():
 
     # check that numba handle the 2 dtypes
     data = data.astype("float64")
-    labels = isosplit(data, isocut_threshold=2.0, n_init=40, seed=2205)
+    _ = isosplit(data, isocut_threshold=2.0, n_init=40, seed=2205)
 
     data = data.astype("float32")
-    labels = isosplit(data, isocut_threshold=2.0, n_init=40, seed=2205)
+    _ = isosplit(data, isocut_threshold=2.0, n_init=40, seed=2205)
 
     # the beauty is that it discovers the number of clusters automatically, at least for this this seed :)
     # assert np.unique(labels).size == 3
diff --git a/src/spikeinterface/sortingcomponents/matching/tests/test_template_matching.py b/src/spikeinterface/sortingcomponents/matching/tests/test_template_matching.py
index 90767007d7..3fbf404907 100644
--- a/src/spikeinterface/sortingcomponents/matching/tests/test_template_matching.py
+++ b/src/spikeinterface/sortingcomponents/matching/tests/test_template_matching.py
@@ -1,7 +1,7 @@
 import pytest
 import numpy as np
 
-from spikeinterface import NumpySorting, create_sorting_analyzer, compute_sparsity, get_noise_levels
+from spikeinterface import create_sorting_analyzer, compute_sparsity, get_noise_levels
 
 from spikeinterface.sortingcomponents.matching import find_spikes_from_templates
 from spikeinterface.sortingcomponents.matching.method_list import matching_methods
@@ -89,25 +89,25 @@ def test_find_spikes_from_templates(method, sorting_analyzer):
     # print(info)
 
     # DEBUG = True
-    DEBUG = False
+    # DEBUG = False
 
-    if DEBUG:
-        sorting_analyzer.compute("waveforms")
-        sorting_analyzer.compute("templates")
+    # if DEBUG:
+    #     sorting_analyzer.compute("waveforms")
+    #     sorting_analyzer.compute("templates")
 
-        gt_sorting = sorting_analyzer.sorting
+    #     gt_sorting = sorting_analyzer.sorting
 
-        sorting = NumpySorting.from_samples_and_labels(
-            spikes["sample_index"], spikes["cluster_index"], recording.sampling_frequency
-        )
+    #     sorting = NumpySorting.from_samples_and_labels(
+    #         spikes["sample_index"], spikes["cluster_index"], recording.sampling_frequency
+    #     )
 
-        ##metrics = si.compute_quality_metrics(sorting_analyzer, metric_names=["snr"])
+    #     #metrics = si.compute_quality_metrics(sorting_analyzer, metric_names=["snr"])
 
-        # fig, ax = plt.subplots()
-        # comp = si.compare_sorter_to_ground_truth(gt_sorting, sorting)
-        # si.plot_agreement_matrix(comp, ax=ax)
-        # ax.set_title(method)
-        # plt.show()
+    #     fig, ax = plt.subplots()
+    #     comp = si.compare_sorter_to_ground_truth(gt_sorting, sorting)
+    #     si.plot_agreement_matrix(comp, ax=ax)
+    #     ax.set_title(method)
+    #     plt.show()
 
 
 if __name__ == "__main__":

From bebdeecc4a20b32cf6533fc4cc89058845f904c9 Mon Sep 17 00:00:00 2001
From: Alessio Buccino <alejoe9187@gmail.com>
Date: Tue, 10 Nov 2026 11:45:27 +0100
Subject: [PATCH 29/30] fix(test): increase margin_ms in tesT_filter

---
 src/spikeinterface/preprocessing/tests/test_filter.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/spikeinterface/preprocessing/tests/test_filter.py b/src/spikeinterface/preprocessing/tests/test_filter.py
index 13a5a42c03..79d3a7b3ce 100644
--- a/src/spikeinterface/preprocessing/tests/test_filter.py
+++ b/src/spikeinterface/preprocessing/tests/test_filter.py
@@ -166,7 +166,7 @@ def test_filter(create_cache_folder):
     rec6 = causal_filter(rec, direction="backward")
 
     coeff = iirfilter(8, [0.02, 0.4], rs=30, btype="band", analog=False, ftype="cheby2", output="sos")
-    rec5 = filter(rec, coeff=coeff, filter_mode="sos", margin_ms=5.0)
+    rec5 = filter(rec, coeff=coeff, filter_mode="sos", margin_ms=50.0)
 
     # compute by chunk
     rec5_cached0 = rec5.save(
@@ -175,7 +175,7 @@ def test_filter(create_cache_folder):
 
     trace50 = rec5.get_traces(segment_index=0)
     trace51 = rec5_cached0.get_traces(segment_index=0)
-    assert np.allclose(trace50, trace51)
+    np.testing.assert_array_almost_equal(trace50, trace51, decimal=4)
     assert np.allclose(rec.get_times(0), rec2.get_times(0))
 
     # reflect padding test

From 0a0f285f0d066b29972509686499ba830b36920a Mon Sep 17 00:00:00 2001
From: Alessio Buccino <alejoe9187@gmail.com>
Date: Tue, 10 Nov 2026 17:17:21 +0100
Subject: [PATCH 30/30] fix: remove stray import numba

---
 .../sortingcomponents/clustering/itersplit_tools.py         | 6 ------
 1 file changed, 6 deletions(-)

diff --git a/src/spikeinterface/sortingcomponents/clustering/itersplit_tools.py b/src/spikeinterface/sortingcomponents/clustering/itersplit_tools.py
index c2c56cf214..5864ae9e68 100644
--- a/src/spikeinterface/sortingcomponents/clustering/itersplit_tools.py
+++ b/src/spikeinterface/sortingcomponents/clustering/itersplit_tools.py
@@ -1,5 +1,4 @@
 import warnings
-import importlib.util
 from multiprocessing import get_context
 from threadpoolctl import threadpool_limits
 from tqdm.auto import tqdm
@@ -10,11 +9,6 @@
 
 from .tools import aggregate_sparse_features, FeaturesLoader
 
-if importlib.util.find_spec("numba") is not None:
-    pass
-else:
-    pass
-# isocut requires numba
 
 # important all DEBUG and matplotlib are left in the code intentionally