From 8293febb4b7ec46afdfa6b8deedff57042b5b8a9 Mon Sep 17 00:00:00 2001
From: Gene Dan <genedan@gmail.com>
Date: Sat, 2 May 2026 17:23:54 -0500
Subject: [PATCH 1/8] ENH: Continue work on type hinting, add pyright to check
 type coverage.

---
 chainladder/core/common.py             | 46 ++++++++++++--
 chainladder/core/triangle.py           | 43 +++++++++----
 chainladder/development/base.py        | 45 +++++++++++--
 chainladder/development/development.py | 88 ++++++++++++++++++--------
 chainladder/py.typed                   |  0
 pyproject.toml                         | 12 +++-
 pyrightconfig.json                     |  9 +++
 uv.lock                                | 25 ++++++++
 8 files changed, 215 insertions(+), 53 deletions(-)
 create mode 100644 chainladder/py.typed
 create mode 100644 pyrightconfig.json

diff --git a/chainladder/core/common.py b/chainladder/core/common.py
index d600f06d..62d4c46a 100644
--- a/chainladder/core/common.py
+++ b/chainladder/core/common.py
@@ -1,13 +1,27 @@
 # This Source Code Form is subject to the terms of the Mozilla Public
 # License, v. 2.0. If a copy of the MPL was not distributed with this
 # file, You can obtain one at https://mozilla.org/MPL/2.0/.
+from __future__ import annotations
+
+import numpy as np
 import pandas as pd
+
+from chainladder import options
 from chainladder.utils.cupy import cp
-from chainladder.utils.sparse import sp
 from chainladder.utils.dask import dp
-import numpy as np
+from chainladder.utils.sparse import sp
 from chainladder.utils.utility_functions import concat
-from chainladder import options
+
+from typing import (
+    Callable,
+    Literal,
+    TYPE_CHECKING
+)
+
+if TYPE_CHECKING:
+    from numpy.typing import ArrayLike
+    from chainladder.core.typing import TriangleLike
+
 
 
 def _get_full_expectation(cdf_, ultimate_, is_cumulative=True):
@@ -201,15 +215,33 @@ def set_backend(
             obj = self.copy()
             return obj.set_backend(backend=backend, inplace=True, deep=deep, **kwargs)
 
-    def _validate_assumption(self, triangle, value, axis):
+    @staticmethod
+    def _validate_assumption(
+            triangle: TriangleLike,
+            value: str | int | float | list | tuple | set | np.ndarray | dict | Callable,
+            axis: Literal[1, 2, 3, 4]
+    ) -> np.ndarray:
+        """
+
+        Parameters
+        ----------
+
+        """
         if type(value) in (int, float, str):
             arr = np.repeat(value, triangle.shape[axis])
-        if type(value) in (list, tuple, set, np.ndarray):
+        elif type(value) in (list, tuple, set, np.ndarray):
             arr = np.array(value)
-        if type(value) is dict:
+        elif type(value) is dict:
             arr = np.array([value[a] for a in triangle._get_axis_value(axis)])
-        if callable(value):
+        elif callable(value):
             arr = np.array([value(a) for a in triangle._get_axis_value(axis)])
+        else:
+            raise TypeError(
+                """
+                Invalid type provided to value parameter. 
+                Accepted types are str, int, float, list, tuple, set, ndarray, dict, or Callable.
+                """
+            )
         if axis == 3:
             arr = arr[None, None, None]
         if axis == 2:
diff --git a/chainladder/core/triangle.py b/chainladder/core/triangle.py
index 826bb959..a7caf1c9 100644
--- a/chainladder/core/triangle.py
+++ b/chainladder/core/triangle.py
@@ -919,8 +919,18 @@ def link_ratio(self) -> Triangle:
 
         Examples
         --------
-        >>> tr = cl.load_sample('ukmotor')
-        >>> tr.link_ratio
+
+        .. testsetup::
+
+            import chainladder as cl
+
+        .. testcode::
+
+            tr = cl.load_sample('ukmotor')
+            print(tr.link_ratio)
+
+        .. testoutput::
+
                  12-24     24-36     36-48     48-60     60-72    72-84
         2007  1.915694  1.336902  1.190391  1.098935  1.049902  1.02753
         2008  1.925269  1.295729  1.118225  1.085655  1.051911      NaN
@@ -1254,16 +1264,25 @@ def val_to_dev(self, inplace=False):
         development triangle through valuation form and back returns the
         original layout.
 
-        >>> tr = cl.load_sample('ukmotor')
-        >>> tr.dev_to_val().val_to_dev()
-                  12      24       36       48       60       72       84
-        2007  3511.0  6726.0   8992.0  10704.0  11763.0  12350.0  12690.0
-        2008  4001.0  7703.0   9981.0  11161.0  12117.0  12746.0      NaN
-        2009  4355.0  8287.0  10233.0  11755.0  12993.0      NaN      NaN
-        2010  4295.0  7750.0   9773.0  11093.0      NaN      NaN      NaN
-        2011  4150.0  7897.0  10217.0      NaN      NaN      NaN      NaN
-        2012  5102.0  9650.0      NaN      NaN      NaN      NaN      NaN
-        2013  6283.0     NaN      NaN      NaN      NaN      NaN      NaN
+        .. testsetup::
+
+            import chainladder as cl
+
+        .. testcode::
+
+            tr = cl.load_sample('ukmotor')
+            tr.dev_to_val().val_to_dev()
+
+        .. testoutput::
+
+                      12      24       36       48       60       72       84
+            2007  3511.0  6726.0   8992.0  10704.0  11763.0  12350.0  12690.0
+            2008  4001.0  7703.0   9981.0  11161.0  12117.0  12746.0      NaN
+            2009  4355.0  8287.0  10233.0  11755.0  12993.0      NaN      NaN
+            2010  4295.0  7750.0   9773.0  11093.0      NaN      NaN      NaN
+            2011  4150.0  7897.0  10217.0      NaN      NaN      NaN      NaN
+            2012  5102.0  9650.0      NaN      NaN      NaN      NaN      NaN
+            2013  6283.0     NaN      NaN      NaN      NaN      NaN      NaN
         """
         if not self.is_val_tri:
             if inplace:
diff --git a/chainladder/development/base.py b/chainladder/development/base.py
index 6a8b7198..0488f80c 100644
--- a/chainladder/development/base.py
+++ b/chainladder/development/base.py
@@ -1,17 +1,34 @@
 # This Source Code Form is subject to the terms of the Mozilla Public
 # License, v. 2.0. If a copy of the MPL was not distributed with this
 # file, You can obtain one at https://mozilla.org/MPL/2.0/.
+from __future__ import annotations
+
 import numpy as np
 import pandas as pd
 import warnings
-from sklearn.base import BaseEstimator, TransformerMixin
+
+from sklearn.base import (
+    BaseEstimator,
+    TransformerMixin
+)
+
 from chainladder.utils import WeightedRegression
 from chainladder.utils.utility_functions import num_to_nan
 from chainladder.core.io import EstimatorIO
 from chainladder.core.common import Common
 
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from chainladder.core.typing import TriangleLike
 
-class DevelopmentBase(BaseEstimator, TransformerMixin, EstimatorIO, Common):
+
+class DevelopmentBase(
+    BaseEstimator,
+    TransformerMixin,
+    EstimatorIO,
+    Common
+):
     def fit(self, X, y=None, sample_weight=None):
         average_ = self._validate_assumption(y, self.average, axis=3)
         self.average_ = average_.flatten()
@@ -25,8 +42,22 @@ def fit(self, X, y=None, sample_weight=None):
         )
         return self
 
-    def _set_fit_groups(self, X):
-        """Used for assigning group_index in fit"""
+    def _set_fit_groups(
+            self,
+            X: TriangleLike
+    ) -> TriangleLike:
+        """
+        Used for assigning group_index in fit.
+
+        Parameters
+        ----------
+        X: TriangleLike
+
+        Returns
+        -------
+        TriangleLike, after performing the groupby on it.
+
+        """
         backend = "numpy" if X.array_backend in ["sparse", "numpy"] else "cupy"
         if self.groupby is None:
             return X.set_backend(backend)
@@ -354,7 +385,11 @@ def _param_array_helper(self, size, param, default_value):
             param_array = param_array.astype(type(default_value))
         return param_array.to_numpy()
 
-    def _set_weight_func(self, factor, secondary_rank=None):
+    def _set_weight_func(
+            self,
+            factor: TriangleLike,
+            secondary_rank: TriangleLike = None
+    ):
         w = (~np.isnan(factor.values)).astype(float)
         w = w * self._assign_n_periods_weight_func(factor)
         if self.drop is not None:
diff --git a/chainladder/development/development.py b/chainladder/development/development.py
index 975bad33..6ab5dd16 100644
--- a/chainladder/development/development.py
+++ b/chainladder/development/development.py
@@ -1,15 +1,34 @@
 # This Source Code Form is subject to the terms of the Mozilla Public
 # License, v. 2.0. If a copy of the MPL was not distributed with this
 # file, You can obtain one at https://mozilla.org/MPL/2.0/.
+from __future__ import annotations
+
 import numpy as np
 import pandas as pd
 import warnings
-from chainladder.utils import WeightedRegression
+
 from chainladder.development.base import DevelopmentBase
+from chainladder.utils import WeightedRegression
+from chainladder.utils.utility_functions import num_to_nan
+
+from typing import (
+    Callable,
+    Literal,
+    Optional,
+    Self,
+    TYPE_CHECKING
+)
+
+if TYPE_CHECKING:
+    from chainladder.core.typing import TriangleLike
+    from numpy.typing import ArrayLike
+    from pandas import Series
+    from types import ModuleType
 
 
 class Development(DevelopmentBase):
-    """A Transformer that allows for basic loss development pattern selection.
+    """
+    A Transformer that allows for basic loss development pattern selection.
 
     Parameters
     ----------
@@ -49,7 +68,7 @@ class Development(DevelopmentBase):
         excluded from the ``ldf_`` calculation.  For the specific case of 'volume'
         averaging in a deterministic method, this may be reasonable.  For all other
         averages and stochastic methods, this assumption should be avoided.
-    groupby:
+    groupby: Callable, list, str, Series (default = None)
         An option to group levels of the triangle index together for the purposes
         of estimating patterns.  If omitted, each level of the triangle
         index will receive its own patterns.
@@ -73,18 +92,18 @@ class Development(DevelopmentBase):
 
     def __init__(
         self,
-        n_periods=-1,
-        average="volume",
-        sigma_interpolation="log-linear",
-        drop=None,
-        drop_high=None,
-        drop_low=None,
-        preserve=1,
-        drop_valuation=None,
-        drop_above=np.inf,
-        drop_below=0.00,
-        fillna=None,
-        groupby=None,
+        n_periods: int = -1,
+        average: str = "volume",
+        sigma_interpolation: Literal['log-linear', 'mack'] = "log-linear",
+        drop: tuple | list[tuple] | None = None,
+        drop_high: bool | int | list[bool] | list[int] | None = None,
+        drop_low: bool | int | list[bool] | list[int] | None = None,
+        preserve: int = 1,
+        drop_valuation: str | list[str] = None,
+        drop_above: float = np.inf,
+        drop_below: float = 0.00,
+        fillna: float | None = None,
+        groupby: Callable | list | str | Series = None,
     ):
         self.n_periods = n_periods
         self.average = average
@@ -99,12 +118,19 @@ def __init__(
         self.fillna = fillna
         self.groupby = groupby
 
-    def fit(self, X, y=None, sample_weight=None):
+        # Undeclared until fitted attributes - scikit-learn convention.
+        self.average_: np.ndarray
+
+    def fit(
+            self, X: TriangleLike,
+            y: None = None,
+            sample_weight: None = None
+    ) -> Self:
         """Fit the model with X.
 
         Parameters
         ----------
-        X : Triangle-like
+        X : TriangleLike
             Set of LDFs to which the munich adjustment will be applied.
         y : None
             Ignored
@@ -116,30 +142,34 @@ def fit(self, X, y=None, sample_weight=None):
         self : object
             Returns the instance itself.
         """
-        from chainladder.utils.utility_functions import num_to_nan
 
-        # Triangle must be cumulative and in "development" mode
-        obj = self._set_fit_groups(X).incr_to_cum().val_to_dev().copy()
-        xp = obj.get_array_module()
+        # Triangle must be cumulative and in "development" mode.
+        obj: TriangleLike = self._set_fit_groups(X).incr_to_cum().val_to_dev().copy()
+        xp: ModuleType = obj.get_array_module()
 
         if self.fillna:
-            tri_array = num_to_nan((obj + self.fillna).values)
+            tri_array: ArrayLike = num_to_nan((obj + self.fillna).values)
         else:
-            tri_array = num_to_nan(obj.values.copy())
+            tri_array: ArrayLike = num_to_nan(obj.values.copy())
 
-        average_ = self._validate_assumption(X, self.average, axis=3)[
+        average_: np.ndarray = self._validate_assumption(X, self.average, axis=3)[
             ..., : X.shape[3] - 1
         ]
-        self.average_ = average_.flatten()
-        n_periods_ = self._validate_assumption(X, self.n_periods, axis=3)[
+
+        # noinspection PyAttributeOutsideInit
+        self.average_: np.ndarray = average_.flatten()
+        n_periods_: np.ndarray = self._validate_assumption(X, self.n_periods, axis=3)[
             ..., : X.shape[3] - 1
         ]
+
+        x: ArrayLike
+        y: ArrayLike
         x, y = tri_array[..., :-1], tri_array[..., 1:]
-        exponent = xp.array(
+        exponent: ArrayLike = xp.array(
             [{"regression": 0, "volume": 1, "simple": 2}[x] for x in average_[0, 0, 0]]
         )
         exponent = xp.nan_to_num(exponent * (y * 0 + 1))
-        link_ratio = y / x
+        link_ratio: ArrayLike = y / x
 
         if hasattr(X, "w_v2_"):
             self.w_v2_ = self._set_weight_func(
@@ -188,6 +218,8 @@ def fit(self, X, y=None, sample_weight=None):
 
         return self
 
+
+
     def transform(self, X):
         """If X and self are of different shapes, align self to X, else
         return self.
diff --git a/chainladder/py.typed b/chainladder/py.typed
new file mode 100644
index 00000000..e69de29b
diff --git a/pyproject.toml b/pyproject.toml
index 36f050c9..4d060dce 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -55,6 +55,7 @@ dev = [
     "jinja2",
     "ipython",
     "ipykernel",
+    "pyright",
 ]
 docs = [
     "sphinx",
@@ -86,6 +87,12 @@ all = [
     "chainladder[dev,docs,test]",
 ]
 
+# Exclude if TYPE_CHECKING block at the beginning of modules.
+[tool.coverage.report]
+exclude_also = [
+    "if TYPE_CHECKING:"
+]
+
 [tool.pytest.ini_options]
 testpaths = ["chainladder/*", "docs/_ext"]
 pythonpath = ["docs/_ext"]
@@ -97,4 +104,7 @@ include-package-data = true
 include = ["chainladder", "chainladder.*"]
 
 [tool.setuptools.package-data]
-chainladder = ["utils/data/*"]
+chainladder = ["utils/data/*", "py.typed"]
+
+[tool.uv]
+config-settings = {editable_mode="compat"}
\ No newline at end of file
diff --git a/pyrightconfig.json b/pyrightconfig.json
new file mode 100644
index 00000000..74bff3fc
--- /dev/null
+++ b/pyrightconfig.json
@@ -0,0 +1,9 @@
+{
+    "include": ["chainladder"],
+    "exclude": [".venv"],
+    "venvPath": ".",
+    "extraPaths": ["."],
+    "venv": ".venv",
+    "pythonVersion": "3.14",
+    "typeCheckingMode": "basic"
+}
\ No newline at end of file
diff --git a/uv.lock b/uv.lock
index e4612f6c..f25210e9 100644
--- a/uv.lock
+++ b/uv.lock
@@ -214,6 +214,7 @@ all = [
     { name = "numpydoc" },
     { name = "parso" },
     { name = "polars" },
+    { name = "pyright" },
     { name = "pytest" },
     { name = "pytest-cov" },
     { name = "pytest-xdist" },
@@ -228,6 +229,7 @@ dev = [
     { name = "ipython", version = "9.6.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11'" },
     { name = "jinja2" },
     { name = "lxml" },
+    { name = "pyright" },
     { name = "pytest" },
     { name = "pytest-cov" },
     { name = "pytest-xdist" },
@@ -286,6 +288,7 @@ requires-dist = [
     { name = "parso", marker = "extra == 'docs'", specifier = ">=0.8" },
     { name = "patsy" },
     { name = "polars", marker = "extra == 'docs'" },
+    { name = "pyright", marker = "extra == 'dev'" },
     { name = "pytest", marker = "extra == 'dev'" },
     { name = "pytest", marker = "extra == 'test'" },
     { name = "pytest-cov", marker = "extra == 'dev'" },
@@ -1876,6 +1879,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl", hash = "sha256:87af6efd6b5e897c81050477ef65c62e2b2f35d51703cae01aff2905b1852e1c", size = 5195, upload-time = "2024-01-21T14:25:17.223Z" },
 ]
 
+[[package]]
+name = "nodeenv"
+version = "1.10.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/24/bf/d1bda4f6168e0b2e9e5958945e01910052158313224ada5ce1fb2e1113b8/nodeenv-1.10.0.tar.gz", hash = "sha256:996c191ad80897d076bdfba80a41994c2b47c68e224c542b48feba42ba00f8bb", size = 55611, upload-time = "2025-12-20T14:08:54.006Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/88/b2/d0896bdcdc8d28a7fc5717c305f1a861c26e18c05047949fb371034d98bd/nodeenv-1.10.0-py2.py3-none-any.whl", hash = "sha256:5bb13e3eed2923615535339b3c620e76779af4cb4c6a90deccc9e36b274d3827", size = 23438, upload-time = "2025-12-20T14:08:52.782Z" },
+]
+
 [[package]]
 name = "numba"
 version = "0.63.1"
@@ -2459,6 +2471,19 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/10/5e/1aa9a93198c6b64513c9d7752de7422c06402de6600a8767da1524f9570b/pyparsing-3.2.5-py3-none-any.whl", hash = "sha256:e38a4f02064cf41fe6593d328d0512495ad1f3d8a91c4f73fc401b3079a59a5e", size = 113890, upload-time = "2025-09-21T04:11:04.117Z" },
 ]
 
+[[package]]
+name = "pyright"
+version = "1.1.409"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "nodeenv" },
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/51/4e/3aa27f74211522dba7e9cbc3e74de779c6d4b654c54e50a4840623be8014/pyright-1.1.409.tar.gz", hash = "sha256:986ee05beca9e077c165758ad123667c679e050059a2546aa02473930394bc93", size = 4430434, upload-time = "2026-04-23T11:02:03.799Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/16/6b/330d8ebae582b30c2959a1ef4c3bc344ebde48c2ff0c3f113c4710735e11/pyright-1.1.409-py3-none-any.whl", hash = "sha256:aa3ea228cab90c845c7a60d28db7a844c04315356392aa09fafcee98c8c22fb3", size = 6438161, upload-time = "2026-04-23T11:02:01.309Z" },
+]
+
 [[package]]
 name = "pytest"
 version = "9.0.3"

From f667a5ad8d8fa5cae6bdf770a0c28a07bbc4458a Mon Sep 17 00:00:00 2001
From: Gene Dan <genedan@gmail.com>
Date: Sat, 2 May 2026 20:50:57 -0500
Subject: [PATCH 2/8] FIX: Fix glob capturing py.typed.

---
 chainladder/development/development.py | 5 ++---
 pyproject.toml                         | 2 +-
 2 files changed, 3 insertions(+), 4 deletions(-)

diff --git a/chainladder/development/development.py b/chainladder/development/development.py
index 6ab5dd16..5d2a962d 100644
--- a/chainladder/development/development.py
+++ b/chainladder/development/development.py
@@ -14,8 +14,7 @@
 from typing import (
     Callable,
     Literal,
-    Optional,
-    Self,
+    # Self,  # Make use of this once Python 3.10 is deprecated.
     TYPE_CHECKING
 )
 
@@ -125,7 +124,7 @@ def fit(
             self, X: TriangleLike,
             y: None = None,
             sample_weight: None = None
-    ) -> Self:
+    ):
         """Fit the model with X.
 
         Parameters
diff --git a/pyproject.toml b/pyproject.toml
index 4d060dce..c644d32b 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -94,7 +94,7 @@ exclude_also = [
 ]
 
 [tool.pytest.ini_options]
-testpaths = ["chainladder/*", "docs/_ext"]
+testpaths = ["chainladder", "docs/_ext"]
 pythonpath = ["docs/_ext"]
 
 [tool.setuptools]

From c5305b8c37056ed6b48b8e7e9a244f8c1d8d7d84 Mon Sep 17 00:00:00 2001
From: Gene Dan <genedan@gmail.com>
Date: Sat, 2 May 2026 21:27:07 -0500
Subject: [PATCH 3/8] FIX: Fix incorrect literal. Fix exclusion of `if
 TYPE_CHECKING:` block.

---
 .coveragerc                | 2 ++
 chainladder/core/common.py | 2 +-
 2 files changed, 3 insertions(+), 1 deletion(-)

diff --git a/.coveragerc b/.coveragerc
index 79f03f1f..f786e10c 100644
--- a/.coveragerc
+++ b/.coveragerc
@@ -5,6 +5,8 @@ omit = *tests*
 
 [report]
 show_missing = True
+exclude_also =
+   if TYPE_CHECKING:
 
 # Regexes for lines to exclude from consideration
 exclude_lines =
diff --git a/chainladder/core/common.py b/chainladder/core/common.py
index 62d4c46a..7ad6e1f5 100644
--- a/chainladder/core/common.py
+++ b/chainladder/core/common.py
@@ -219,7 +219,7 @@ def set_backend(
     def _validate_assumption(
             triangle: TriangleLike,
             value: str | int | float | list | tuple | set | np.ndarray | dict | Callable,
-            axis: Literal[1, 2, 3, 4]
+            axis: Literal[0, 1, 2, 3]
     ) -> np.ndarray:
         """
 

From 1012136121561904673581e82c86857c35f414e0 Mon Sep 17 00:00:00 2001
From: Gene Dan <genedan@gmail.com>
Date: Sat, 2 May 2026 21:43:01 -0500
Subject: [PATCH 4/8] FIX: Apply bugbot fixes.

---
 pyproject.toml     | 6 ------
 pyrightconfig.json | 1 -
 2 files changed, 7 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index c644d32b..a81b7460 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -87,12 +87,6 @@ all = [
     "chainladder[dev,docs,test]",
 ]
 
-# Exclude if TYPE_CHECKING block at the beginning of modules.
-[tool.coverage.report]
-exclude_also = [
-    "if TYPE_CHECKING:"
-]
-
 [tool.pytest.ini_options]
 testpaths = ["chainladder", "docs/_ext"]
 pythonpath = ["docs/_ext"]
diff --git a/pyrightconfig.json b/pyrightconfig.json
index 74bff3fc..2efc03ab 100644
--- a/pyrightconfig.json
+++ b/pyrightconfig.json
@@ -4,6 +4,5 @@
     "venvPath": ".",
     "extraPaths": ["."],
     "venv": ".venv",
-    "pythonVersion": "3.14",
     "typeCheckingMode": "basic"
 }
\ No newline at end of file

From af2b680cb7479b6b0fbecf6c8f1c0e1f8267c79f Mon Sep 17 00:00:00 2001
From: Gene Dan <genedan@gmail.com>
Date: Sat, 2 May 2026 21:55:37 -0500
Subject: [PATCH 5/8] TEST: Add unit test for incorrect type provided to
 Common._validate_assumption.

---
 chainladder/core/tests/test_triangle.py | 29 ++++++++++++++++++++-----
 1 file changed, 24 insertions(+), 5 deletions(-)

diff --git a/chainladder/core/tests/test_triangle.py b/chainladder/core/tests/test_triangle.py
index f9acf21c..dc1a7c4c 100644
--- a/chainladder/core/tests/test_triangle.py
+++ b/chainladder/core/tests/test_triangle.py
@@ -1,13 +1,19 @@
+from __future__ import annotations
+
 import chainladder as cl
-import pandas as pd
+import io
 import numpy as np
+import pandas as pd
 import pytest
-import io
-from datetime import datetime
+
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from chainladder import Triangle
 
 try:
     from IPython.core.display import HTML
-except:
+except ImportError:
     HTML = None
 
 
@@ -1004,4 +1010,17 @@ def test_triangle_init_from_dict() -> None:
         cumulative=True
     )
 
-    assert tri_from_df == tri_from_dict
\ No newline at end of file
+    assert tri_from_df == tri_from_dict
+
+
+def test_validate_assumption(raa: Triangle) -> None:
+    """
+    Tests Common._validate_assumption.
+    """
+
+    # Check incorrect type provided to value argument.
+    with pytest.raises(TypeError):
+        raa._validate_assumption(
+            triangle=raa,
+            value=raa, axis=3  # noqa - incorrect type provided on purpose.
+        )

From 5b4221684e9b50e0f7ea1fd6364b34028e0d3d2e Mon Sep 17 00:00:00 2001
From: Gene Dan <genedan@gmail.com>
Date: Sun, 3 May 2026 08:18:35 -0500
Subject: [PATCH 6/8] FIX: Missing print function.

---
 chainladder/core/triangle.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/chainladder/core/triangle.py b/chainladder/core/triangle.py
index a7caf1c9..e7c04038 100644
--- a/chainladder/core/triangle.py
+++ b/chainladder/core/triangle.py
@@ -1271,7 +1271,7 @@ def val_to_dev(self, inplace=False):
         .. testcode::
 
             tr = cl.load_sample('ukmotor')
-            tr.dev_to_val().val_to_dev()
+            print(tr.dev_to_val().val_to_dev())
 
         .. testoutput::
 

From 08176c1ae58bfaec8113a0fcc337a1bef34922e7 Mon Sep 17 00:00:00 2001
From: Gene Dan <genedan@gmail.com>
Date: Sun, 3 May 2026 09:04:27 -0500
Subject: [PATCH 7/8] FIX: Reformat docstring tests.

---
 chainladder/core/triangle.py | 765 +++++++++++++++++++++++------------
 1 file changed, 512 insertions(+), 253 deletions(-)

diff --git a/chainladder/core/triangle.py b/chainladder/core/triangle.py
index e7c04038..dd80c21e 100644
--- a/chainladder/core/triangle.py
+++ b/chainladder/core/triangle.py
@@ -643,14 +643,28 @@ def origin(self):
         --------
         Annual-origin Triangle.
 
-        >>> tr = cl.load_sample('ukmotor')
-        >>> tr.origin.year.tolist()
-        [2007, 2008, 2009, 2010, 2011, 2012, 2013]
+        .. testsetup::
+
+            import chainladder as cl
+
+        .. testcode::
+
+            tr = cl.load_sample('ukmotor')
+            print(tr.origin.year.tolist())
+
+        .. testoutput::
+
+            [2007, 2008, 2009, 2010, 2011, 2012, 2013]
 
         The number of origin periods matches ``Triangle.shape[-2]``.
 
-        >>> len(tr.origin) == tr.shape[-2]
-        True
+        .. testcode::
+
+            print(len(tr.origin) == tr.shape[-2])
+
+        .. testoutput::
+
+            True
         """
         if self.is_pattern and len(self.odims) == 1:
             return pd.Series(["(All)"])
@@ -699,19 +713,38 @@ def development(self):
         --------
         Annual-grain development on a loss Triangle is reported as month lags.
 
-        >>> tr = cl.load_sample('ukmotor')
-        >>> tr.development.tolist()
-        [12, 24, 36, 48, 60, 72, 84]
+        .. testsetup:
+
+            import chainladder as cl
+
+        .. testcode::
+
+            tr = cl.load_sample('ukmotor')
+            print(tr.development.tolist())
+
+        .. testoutput::
+
+            [12, 24, 36, 48, 60, 72, 84]
 
         On a valuation Triangle the labels become calendar periods.
 
-        >>> tr.dev_to_val().development.tolist()
-        ['2007', '2008', '2009', '2010', '2011', '2012', '2013']
+        .. testcode::
+
+            print(tr.dev_to_val().development.tolist())
+
+        .. testoutput::
+
+            ['2007', '2008', '2009', '2010', '2011', '2012', '2013']
 
         On a link-ratio (pattern) Triangle the labels span the from/to lags.
 
-        >>> tr.link_ratio.development.tolist()
-        ['12-24', '24-36', '36-48', '48-60', '60-72', '72-84']
+        .. testcode::
+
+            print(tr.link_ratio.development.tolist())
+
+        .. testoutput::
+
+            ['12-24', '24-36', '36-48', '48-60', '60-72', '72-84']
         """
         ddims = self.ddims.copy()
         if self.is_val_tri:
@@ -763,15 +796,29 @@ def is_val_tri(self):
         --------
         A development-lag Triangle has integer lags on the development axis.
 
-        >>> tr = cl.load_sample('ukmotor')
-        >>> tr.is_val_tri
-        False
+        .. testsetup::
+
+            import chainladder as cl
+
+        .. testcode::
+
+            tr = cl.load_sample('ukmotor')
+            print(tr.is_val_tri)
+
+        .. testoutput::
+
+            False
 
         Calling ``dev_to_val`` reshapes the development axis into calendar
         valuation periods.
 
-        >>> tr.dev_to_val().is_val_tri
-        True
+        .. testcode::
+
+            print(tr.dev_to_val().is_val_tri)
+
+        .. testoutput::
+
+            True
         """
         return type(self.ddims) == pd.DatetimeIndex
 
@@ -790,16 +837,30 @@ def is_full(self) -> bool:
         A loaded sample loss Triangle is upper-triangular: future cells below
         the latest diagonal are NaN, so ``is_full`` is ``False``.
 
-        >>> tr = cl.load_sample('ukmotor')
-        >>> bool(tr.is_full)
-        False
+        .. testsetup::
+
+            import chainladder as cl
+
+        .. testcode::
+
+            tr = cl.load_sample('ukmotor')
+            print(bool(tr.is_full))
+
+        .. testoutput::
+
+            False
 
         A ``cdf_`` Triangle from a fitted development model has every cell
         populated, so it is full.
 
-        >>> cdf = cl.Development().fit(tr).cdf_
-        >>> bool(cdf.is_full)
-        True
+        .. testcode::
+
+            cdf = cl.Development().fit(tr).cdf_
+            print(bool(cdf.is_full))
+
+        .. testoutput::
+
+            True
         """
 
         return self.nan_triangle.sum().sum() == np.prod(self.shape[-2:])
@@ -826,15 +887,28 @@ def is_pattern(self) -> bool:
         --------
         A loss Triangle is not a pattern.
 
-        >>> tr = cl.load_sample('ukmotor')
-        >>> tr.is_pattern
-        False
+        .. testsetup::
+            import chainladder as cl
+
+        .. testcode::
+
+            tr = cl.load_sample('ukmotor')
+            print(tr.is_pattern)
+
+        .. testoutput:
+
+            False
 
         Calling ``link_ratio`` returns a Triangle of age-to-age factors, which
         is flagged as a pattern.
 
-        >>> tr.link_ratio.is_pattern
-        True
+        .. testcode::
+
+            print(tr.link_ratio.is_pattern)
+
+        .. testoutput::
+
+            True
         """
         return self._pattern
 
@@ -861,16 +935,30 @@ def is_ultimate(self) ->  np.bool:
         --------
         A loaded sample triangle has no ultimate column.
 
-        >>> tr = cl.load_sample('ukmotor')
-        >>> bool(tr.is_ultimate)
-        False
+        .. testsetup::
+
+            import chainladder as cl
+
+        .. testcode::
+
+            tr = cl.load_sample('ukmotor')
+            print(bool(tr.is_ultimate))
+
+        .. testoutput::
+
+            False
 
         Fitting a chainladder model produces an ``ultimate_`` Triangle whose
         single development column is the ultimate valuation.
 
-        >>> ult = cl.Chainladder().fit(tr).ultimate_
-        >>> bool(ult.is_ultimate)
-        True
+        .. testcode::
+
+            ult = cl.Chainladder().fit(tr).ultimate_
+            print(bool(ult.is_ultimate))
+
+        .. testoutput::
+
+            True
         """
         return sum(self.valuation >= options.ULT_VAL[:4]) > 0
 
@@ -892,16 +980,26 @@ def latest_diagonal(self) -> Triangle:
 
         Examples
         --------
-        >>> tr = cl.load_sample('ukmotor')
-        >>> tr.latest_diagonal
-                 2013
-        2007  12690.0
-        2008  12746.0
-        2009  12993.0
-        2010  11093.0
-        2011  10217.0
-        2012   9650.0
-        2013   6283.0
+
+        .. testsetup::
+
+            import chainladder as cl
+
+        .. testcode::
+
+            tr = cl.load_sample('ukmotor')
+            print(tr.latest_diagonal)
+
+        .. testoutput::
+
+                     2013
+            2007  12690.0
+            2008  12746.0
+            2009  12993.0
+            2010  11093.0
+            2011  10217.0
+            2012   9650.0
+            2013   6283.0
         """
         return self[self.valuation == self.valuation_date].sum(axis="development")
 
@@ -973,15 +1071,25 @@ def age_to_age(self):
 
         Examples
         --------
-        >>> tr = cl.load_sample('ukmotor')
-        >>> tr.age_to_age
-                 12-24     24-36     36-48     48-60     60-72    72-84
-        2007  1.915694  1.336902  1.190391  1.098935  1.049902  1.02753
-        2008  1.925269  1.295729  1.118225  1.085655  1.051911      NaN
-        2009  1.902870  1.234826  1.148734  1.105317       NaN      NaN
-        2010  1.804424  1.261032  1.135066       NaN       NaN      NaN
-        2011  1.902892  1.293782       NaN       NaN       NaN      NaN
-        2012  1.891415       NaN       NaN       NaN       NaN      NaN
+
+        .. testsetup::
+
+            import chainladder cl
+
+        .. testcode::
+
+            tr = cl.load_sample('ukmotor')
+            print(tr.age_to_age)
+
+        .. testoutput::
+
+                     12-24     24-36     36-48     48-60     60-72    72-84
+            2007  1.915694  1.336902  1.190391  1.098935  1.049902  1.02753
+            2008  1.925269  1.295729  1.118225  1.085655  1.051911      NaN
+            2009  1.902870  1.234826  1.148734  1.105317       NaN      NaN
+            2010  1.804424  1.261032  1.135066       NaN       NaN      NaN
+            2011  1.902892  1.293782       NaN       NaN       NaN      NaN
+            2012  1.891415       NaN       NaN       NaN       NaN      NaN
         """
         return self.link_ratio
 
@@ -1001,42 +1109,67 @@ def incr_to_cum(self, inplace=False):
         --------
         Construct an incremental triangle and accumulate it along the development axis.
 
-        >>> df = pd.DataFrame(
-        ...     data={
-        ...         'origin': [1981, 1981, 1981, 1981, 1982, 1982, 1982, 1983, 1983, 1984],
-        ...         'development': [1981, 1982, 1983, 1984, 1982, 1983, 1984, 1983, 1984, 1984],
-        ...         'reported': [5012, 3257, 2638, 898, 106, 4179, 1111, 3410, 5582, 5655],
-        ...     }
-        ... )
-        >>> tr = cl.Triangle(
-        ...     data=df,
-        ...     origin='origin',
-        ...     development='development',
-        ...     columns=['reported'],
-        ...     cumulative=False,
-        ... )
-        >>> tr
-                  12      24      36     48
-        1981  5012.0  3257.0  2638.0  898.0
-        1982   106.0  4179.0  1111.0    NaN
-        1983  3410.0  5582.0     NaN    NaN
-        1984  5655.0     NaN     NaN    NaN
+        .. testsetup::
 
-        >>> tr.incr_to_cum()
-                  12      24       36       48
-        1981  5012.0  8269.0  10907.0  11805.0
-        1982   106.0  4285.0   5396.0      NaN
-        1983  3410.0  8992.0      NaN      NaN
-        1984  5655.0     NaN      NaN      NaN
+            import chainladder as cl
+
+        .. testcode::
+
+            df = pd.DataFrame(
+                data={
+                    'origin': [1981, 1981, 1981, 1981, 1982, 1982, 1982, 1983, 1983, 1984],
+                    'development': [1981, 1982, 1983, 1984, 1982, 1983, 1984, 1983, 1984, 1984],
+                    'reported': [5012, 3257, 2638, 898, 106, 4179, 1111, 3410, 5582, 5655],
+                }
+            )
+            tr = cl.Triangle(
+                data=df,
+                origin='origin',
+                development='development',
+                columns=['reported'],
+                cumulative=False,
+            )
+            print(tr)
+
+        .. testoutput::
+
+                      12      24      36     48
+            1981  5012.0  3257.0  2638.0  898.0
+            1982   106.0  4179.0  1111.0    NaN
+            1983  3410.0  5582.0     NaN    NaN
+            1984  5655.0     NaN     NaN    NaN
+
+        .. testcode::
+
+            print(tr.incr_to_cum())
+
+        .. testoutput::
+
+                      12      24       36       48
+            1981  5012.0  8269.0  10907.0  11805.0
+            1982   106.0  4285.0   5396.0      NaN
+            1983  3410.0  8992.0      NaN      NaN
+            1984  5655.0     NaN      NaN      NaN
 
         By default ``incr_to_cum`` returns a new Triangle. Pass ``inplace=True`` to
         mutate the calling Triangle instead.
 
-        >>> tr.is_cumulative
-        False
-        >>> _ = tr.incr_to_cum(inplace=True)
-        >>> tr.is_cumulative
-        True
+        .. testcode::
+
+            print(tr.is_cumulative)
+
+        .. testoutput::
+
+            False
+
+        .. testcode::
+
+            tr.incr_to_cum(inplace=True)
+            print(tr.is_cumulative)
+
+        .. testoutput::
+
+            True
         """
         if inplace:
             xp = self.get_array_module()
@@ -1099,16 +1232,25 @@ def cum_to_incr(self, inplace=False):
         differences each cell against the prior development period, returning
         per-period increments.
 
-        >>> tr = cl.load_sample('ukmotor')
-        >>> tr.cum_to_incr()
-                  12      24      36      48      60     72     84
-        2007  3511.0  3215.0  2266.0  1712.0  1059.0  587.0  340.0
-        2008  4001.0  3702.0  2278.0  1180.0   956.0  629.0    NaN
-        2009  4355.0  3932.0  1946.0  1522.0  1238.0    NaN    NaN
-        2010  4295.0  3455.0  2023.0  1320.0     NaN    NaN    NaN
-        2011  4150.0  3747.0  2320.0     NaN     NaN    NaN    NaN
-        2012  5102.0  4548.0     NaN     NaN     NaN    NaN    NaN
-        2013  6283.0     NaN     NaN     NaN     NaN    NaN    NaN
+        .. testsetup::
+
+            import chainladder as cl
+
+        .. testcode::
+
+            tr = cl.load_sample('ukmotor')
+            print(tr.cum_to_incr())
+
+        .. testoutput::
+
+                      12      24      36      48      60     72     84
+            2007  3511.0  3215.0  2266.0  1712.0  1059.0  587.0  340.0
+            2008  4001.0  3702.0  2278.0  1180.0   956.0  629.0    NaN
+            2009  4355.0  3932.0  1946.0  1522.0  1238.0    NaN    NaN
+            2010  4295.0  3455.0  2023.0  1320.0     NaN    NaN    NaN
+            2011  4150.0  3747.0  2320.0     NaN     NaN    NaN    NaN
+            2012  5102.0  4548.0     NaN     NaN     NaN    NaN    NaN
+            2013  6283.0     NaN     NaN     NaN     NaN    NaN    NaN
         """
         if inplace:
             v = self.valuation_date
@@ -1193,29 +1335,43 @@ def dev_to_val(self, inplace=False):
         ``cl.load_sample('ukmotor')`` is a 7x7 cumulative Triangle in development
         form. Each column represents months of development from the origin year.
 
-        >>> tr = cl.load_sample('ukmotor')
-        >>> tr
-                  12      24       36       48       60       72       84
-        2007  3511.0  6726.0   8992.0  10704.0  11763.0  12350.0  12690.0
-        2008  4001.0  7703.0   9981.0  11161.0  12117.0  12746.0      NaN
-        2009  4355.0  8287.0  10233.0  11755.0  12993.0      NaN      NaN
-        2010  4295.0  7750.0   9773.0  11093.0      NaN      NaN      NaN
-        2011  4150.0  7897.0  10217.0      NaN      NaN      NaN      NaN
-        2012  5102.0  9650.0      NaN      NaN      NaN      NaN      NaN
-        2013  6283.0     NaN      NaN      NaN      NaN      NaN      NaN
+        .. testsetup::
+
+            import chainladder as cl
+
+        .. testcode::
+
+            tr = cl.load_sample('ukmotor')
+            print(tr)
+
+        .. testoutput::
+
+                      12      24       36       48       60       72       84
+            2007  3511.0  6726.0   8992.0  10704.0  11763.0  12350.0  12690.0
+            2008  4001.0  7703.0   9981.0  11161.0  12117.0  12746.0      NaN
+            2009  4355.0  8287.0  10233.0  11755.0  12993.0      NaN      NaN
+            2010  4295.0  7750.0   9773.0  11093.0      NaN      NaN      NaN
+            2011  4150.0  7897.0  10217.0      NaN      NaN      NaN      NaN
+            2012  5102.0  9650.0      NaN      NaN      NaN      NaN      NaN
+            2013  6283.0     NaN      NaN      NaN      NaN      NaN      NaN
 
         Calling ``dev_to_val`` reshapes the columns from development lags to
         valuation periods, so each column corresponds to a calendar year.
 
-        >>> tr.dev_to_val()
-                2007    2008    2009     2010     2011     2012     2013
-        2007  3511.0  6726.0  8992.0  10704.0  11763.0  12350.0  12690.0
-        2008     NaN  4001.0  7703.0   9981.0  11161.0  12117.0  12746.0
-        2009     NaN     NaN  4355.0   8287.0  10233.0  11755.0  12993.0
-        2010     NaN     NaN     NaN   4295.0   7750.0   9773.0  11093.0
-        2011     NaN     NaN     NaN      NaN   4150.0   7897.0  10217.0
-        2012     NaN     NaN     NaN      NaN      NaN   5102.0   9650.0
-        2013     NaN     NaN     NaN      NaN      NaN      NaN   6283.0
+        .. testcode::
+
+            print(tr.dev_to_val())
+
+        .. testoutput::
+
+                    2007    2008    2009     2010     2011     2012     2013
+            2007  3511.0  6726.0  8992.0  10704.0  11763.0  12350.0  12690.0
+            2008     NaN  4001.0  7703.0   9981.0  11161.0  12117.0  12746.0
+            2009     NaN     NaN  4355.0   8287.0  10233.0  11755.0  12993.0
+            2010     NaN     NaN     NaN   4295.0   7750.0   9773.0  11093.0
+            2011     NaN     NaN     NaN      NaN   4150.0   7897.0  10217.0
+            2012     NaN     NaN     NaN      NaN      NaN   5102.0   9650.0
+            2013     NaN     NaN     NaN      NaN      NaN      NaN   6283.0
         """
         if self.is_val_tri:
             if inplace:
@@ -1334,72 +1490,93 @@ def grain(self, grain="", trailing=False, inplace=False):
         --------
         Build a quarterly origin / quarterly development Triangle (OQDQ).
 
-        >>> df = pd.DataFrame(
-        ...     data={
-        ...         'origin': [
-        ...             '2022Q1', '2022Q1', '2022Q1', '2022Q1', '2022Q1', '2022Q1', '2022Q1', '2022Q1',
-        ...             '2022Q2', '2022Q2', '2022Q2', '2022Q2', '2022Q2', '2022Q2', '2022Q2',
-        ...             '2022Q3', '2022Q3', '2022Q3', '2022Q3', '2022Q3', '2022Q3',
-        ...             '2022Q4', '2022Q4', '2022Q4', '2022Q4', '2022Q4',
-        ...             '2023Q1', '2023Q1', '2023Q1', '2023Q1',
-        ...             '2023Q2', '2023Q2', '2023Q2',
-        ...             '2023Q3', '2023Q3',
-        ...             '2023Q4',
-        ...         ],
-        ...         'development': [
-        ...             '2022Q1', '2022Q2', '2022Q3', '2022Q4', '2023Q1', '2023Q2', '2023Q3', '2023Q4',
-        ...             '2022Q2', '2022Q3', '2022Q4', '2023Q1', '2023Q2', '2023Q3', '2023Q4',
-        ...             '2022Q3', '2022Q4', '2023Q1', '2023Q2', '2023Q3', '2023Q4',
-        ...             '2022Q4', '2023Q1', '2023Q2', '2023Q3', '2023Q4',
-        ...             '2023Q1', '2023Q2', '2023Q3', '2023Q4',
-        ...             '2023Q2', '2023Q3', '2023Q4',
-        ...             '2023Q3', '2023Q4',
-        ...             '2023Q4',
-        ...         ],
-        ...         'reported': [
-        ...             100, 200, 300, 400, 480, 540, 580, 600,
-        ...             110, 220, 320, 420, 500, 560, 600,
-        ...             120, 240, 350, 450, 520, 580,
-        ...             130, 250, 370, 470, 540,
-        ...             140, 260, 380, 480,
-        ...             150, 270, 390,
-        ...             160, 280,
-        ...             170,
-        ...         ],
-        ...     }
-        ... )
-        >>> tr = cl.Triangle(
-        ...     data=df,
-        ...     origin='origin',
-        ...     development='development',
-        ...     columns=['reported'],
-        ...     cumulative=True,
-        ... )
-        >>> tr
-                   3      6      9      12     15     18     21     24
-        2022Q1  100.0  200.0  300.0  400.0  480.0  540.0  580.0  600.0
-        2022Q2  110.0  220.0  320.0  420.0  500.0  560.0  600.0    NaN
-        2022Q3  120.0  240.0  350.0  450.0  520.0  580.0    NaN    NaN
-        2022Q4  130.0  250.0  370.0  470.0  540.0    NaN    NaN    NaN
-        2023Q1  140.0  260.0  380.0  480.0    NaN    NaN    NaN    NaN
-        2023Q2  150.0  270.0  390.0    NaN    NaN    NaN    NaN    NaN
-        2023Q3  160.0  280.0    NaN    NaN    NaN    NaN    NaN    NaN
-        2023Q4  170.0    NaN    NaN    NaN    NaN    NaN    NaN    NaN
+        .. testsetup::
+
+            import chainladder as cl
+
+        .. testcode::
+
+            import pandas as pd
+
+            df = pd.DataFrame(
+                data={
+                    'origin': [
+                        '2022Q1', '2022Q1', '2022Q1', '2022Q1', '2022Q1', '2022Q1', '2022Q1', '2022Q1',
+                        '2022Q2', '2022Q2', '2022Q2', '2022Q2', '2022Q2', '2022Q2', '2022Q2',
+                        '2022Q3', '2022Q3', '2022Q3', '2022Q3', '2022Q3', '2022Q3',
+                        '2022Q4', '2022Q4', '2022Q4', '2022Q4', '2022Q4',
+                        '2023Q1', '2023Q1', '2023Q1', '2023Q1',
+                        '2023Q2', '2023Q2', '2023Q2',
+                        '2023Q3', '2023Q3',
+                        '2023Q4',
+                    ],
+                    'development': [
+                        '2022Q1', '2022Q2', '2022Q3', '2022Q4', '2023Q1', '2023Q2', '2023Q3', '2023Q4',
+                        '2022Q2', '2022Q3', '2022Q4', '2023Q1', '2023Q2', '2023Q3', '2023Q4',
+                        '2022Q3', '2022Q4', '2023Q1', '2023Q2', '2023Q3', '2023Q4',
+                        '2022Q4', '2023Q1', '2023Q2', '2023Q3', '2023Q4',
+                        '2023Q1', '2023Q2', '2023Q3', '2023Q4',
+                        '2023Q2', '2023Q3', '2023Q4',
+                        '2023Q3', '2023Q4',
+                        '2023Q4',
+                    ],
+                    'reported': [
+                        100, 200, 300, 400, 480, 540, 580, 600,
+                        110, 220, 320, 420, 500, 560, 600,
+                        120, 240, 350, 450, 520, 580,
+                        130, 250, 370, 470, 540,
+                        140, 260, 380, 480,
+                        150, 270, 390,
+                        160, 280,
+                        170,
+                    ],
+                }
+            )
+            tr = cl.Triangle(
+                data=df,
+                origin='origin',
+                development='development',
+                columns=['reported'],
+                cumulative=True,
+            )
+            print(tr)
+
+        .. testoutput::
+
+                       3      6      9      12     15     18     21     24
+            2022Q1  100.0  200.0  300.0  400.0  480.0  540.0  580.0  600.0
+            2022Q2  110.0  220.0  320.0  420.0  500.0  560.0  600.0    NaN
+            2022Q3  120.0  240.0  350.0  450.0  520.0  580.0    NaN    NaN
+            2022Q4  130.0  250.0  370.0  470.0  540.0    NaN    NaN    NaN
+            2023Q1  140.0  260.0  380.0  480.0    NaN    NaN    NaN    NaN
+            2023Q2  150.0  270.0  390.0    NaN    NaN    NaN    NaN    NaN
+            2023Q3  160.0  280.0    NaN    NaN    NaN    NaN    NaN    NaN
+            2023Q4  170.0    NaN    NaN    NaN    NaN    NaN    NaN    NaN
 
         Convert to annual origin / annual development. Origins are summed within
         each calendar year and development periods are aggregated to year-end.
 
-        >>> tr.grain('OYDY')
-                  12      24
-        2022  1090.0  2320.0
-        2023  1320.0     NaN
+        .. testcode::
+
+            print(tr.grain('OYDY'))
+
+        .. testoutput::
+
+                      12      24
+            2022  1090.0  2320.0
+            2023  1320.0     NaN
 
         Convert origin to annual but keep development quarterly (``OYDQ``).
 
-        >>> tr.grain('OYDQ')
-                 3      6      9       12      15      18      21      24
-        2022  100.0  310.0  640.0  1090.0  1500.0  1860.0  2130.0  2320.0
-        2023  140.0  410.0  810.0  1320.0     NaN     NaN     NaN     NaN
+        .. testcode::
+
+            print(tr.grain('OYDQ'))
+
+        .. testoutput::
+
+                     3      6      9       12      15      18      21      24
+            2022  100.0  310.0  640.0  1090.0  1500.0  1860.0  2130.0  2320.0
+            2023  140.0  410.0  810.0  1320.0     NaN     NaN     NaN     NaN
         """
         ograin_old, ograin_new = self.origin_grain, grain[1:2]
         dgrain_old, dgrain_new = self.development_grain, grain[-1]
@@ -1536,39 +1713,66 @@ def trend(
 
         Examples
         --------
-        >>> df = pd.DataFrame(
-        ...     data={
-        ...         'origin': [2020, 2020, 2020, 2021, 2021, 2022],
-        ...         'development': [2020, 2021, 2022, 2021, 2022, 2022],
-        ...         'reported': [100, 200, 300, 110, 220, 120],
-        ...     }
-        ... )
-        >>> tr = cl.Triangle(
-        ...     data=df,
-        ...     origin='origin',
-        ...     development='development',
-        ...     columns=['reported'],
-        ...     cumulative=True,
-        ... )
+
+        .. testsetup::
+
+            import chainladder as cl
+
+        .. testcode::
+
+            import pandas as pd
+
+            df = pd.DataFrame(
+                data={
+                    'origin': [2020, 2020, 2020, 2021, 2021, 2022],
+                    'development': [2020, 2021, 2022, 2021, 2022, 2022],
+                    'reported': [100, 200, 300, 110, 220, 120],
+                }
+            )
+            tr = cl.Triangle(
+                data=df,
+                origin='origin',
+                development='development',
+                columns=['reported'],
+                cumulative=True,
+            )
+            print(tr)
+
+        .. testoutput::
+
+                     12     24     36
+            2020  100.0  200.0  300.0
+            2021  110.0  220.0    NaN
+            2022  120.0    NaN    NaN
 
         Apply a 10% annual trend along the origin axis. The latest origin year
         (2022) is unchanged; older origins are scaled up by ``1.10`` per year
         of distance from the latest origin.
 
-        >>> tr.trend(0.10, axis='origin')
-                 12     24     36
-        2020  121.0  242.0  363.0
-        2021  121.0  242.0    NaN
-        2022  120.0    NaN    NaN
+        .. testcode::
+
+            print(tr.trend(0.10, axis='origin'))
+
+        .. testoutput::
+
+                     12     24     36
+            2020  121.0  242.0  363.0
+            2021  121.0  242.0    NaN
+            2022  120.0    NaN    NaN
 
         Apply a 10% annual trend along the valuation axis instead. The latest
         diagonal is unchanged and earlier diagonals are scaled up.
 
-        >>> tr.trend(0.10, axis='valuation')
-                 12     24     36
-        2020  121.0  220.0  300.0
-        2021  121.0  220.0    NaN
-        2022  120.0    NaN    NaN
+        .. testcode::
+
+            print(tr.trend(0.10, axis='valuation'))
+
+        .. testoutput::
+
+                     12     24     36
+            2020  121.0  220.0  300.0
+            2021  121.0  220.0    NaN
+            2022  120.0    NaN    NaN
         """
         if axis not in ["origin", "valuation", 2, -2]:
             raise ValueError(
@@ -1638,10 +1842,20 @@ def development_correlation(self, p_critical=0.5):
 
         Examples
         --------
-        >>> tr = cl.load_sample('raa')
-        >>> dc = tr.development_correlation()
-        >>> bool(dc.t_critical.iloc[0, 0])
-        False
+
+        .. testsetup::
+
+            import chainladder as cl
+
+        .. testcode::
+
+            tr = cl.load_sample('raa')
+            dc = tr.development_correlation()
+            print(bool(dc.t_critical.iloc[0, 0]))
+
+        .. testoutput::
+
+            False
 
         ``t_critical`` reports whether the calculated rank correlation falls
         outside the no-correlation confidence interval. ``False`` indicates the
@@ -1671,11 +1885,21 @@ def valuation_correlation(self, p_critical=0.1, total=False):
 
         Examples
         --------
-        >>> tr = cl.load_sample('raa')
-        >>> vc = tr.valuation_correlation()
-        >>> vc.z_critical
-               1982   1983   1984   1985   1986   1987   1988   1989   1990
-        1981  False  False  False  False  False  False  False  False  False
+
+        .. testsetup::
+
+            import chainladder as cl
+
+        .. testcode::
+
+            tr = cl.load_sample('raa')
+            vc = tr.valuation_correlation()
+            print(vc.z_critical)
+
+        .. testoutput::
+
+                   1982   1983   1984   1985   1986   1987   1988   1989   1990
+            1981  False  False  False  False  False  False  False  False  False
 
         Each cell of ``z_critical`` flags whether the calendar-period z-statistic
         for that valuation falls outside the no-effect confidence interval.
@@ -1704,43 +1928,64 @@ def shift(self, periods=-1, axis=3):
 
         Examples
         --------
-        >>> df = pd.DataFrame(
-        ...     data={
-        ...         'origin': [2020, 2020, 2020, 2021, 2021, 2022],
-        ...         'development': [2020, 2021, 2022, 2021, 2022, 2022],
-        ...         'reported': [100, 200, 300, 110, 220, 120],
-        ...     }
-        ... )
-        >>> tr = cl.Triangle(
-        ...     data=df,
-        ...     origin='origin',
-        ...     development='development',
-        ...     columns=['reported'],
-        ...     cumulative=True,
-        ... )
-        >>> tr
-                 12     24     36
-        2020  100.0  200.0  300.0
-        2021  110.0  220.0    NaN
-        2022  120.0    NaN    NaN
+
+        .. testsetup::
+
+            import chainladder as cl
+
+        .. testcode::
+
+            import pandas as pd
+            df = pd.DataFrame(
+                data={
+                    'origin': [2020, 2020, 2020, 2021, 2021, 2022],
+                    'development': [2020, 2021, 2022, 2021, 2022, 2022],
+                    'reported': [100, 200, 300, 110, 220, 120],
+                }
+            )
+            tr = cl.Triangle(
+                data=df,
+                origin='origin',
+                development='development',
+                columns=['reported'],
+                cumulative=True,
+            )
+            print(tr)
+
+        .. testoutput::
+
+                     12     24     36
+            2020  100.0  200.0  300.0
+            2021  110.0  220.0    NaN
+            2022  120.0    NaN    NaN
 
         Shift one period along the development axis (the default). Values move
         right by one column and the leading column is filled with zeros.
 
-        >>> tr.shift()
-               12     24     36
-        2020  0.0  100.0  200.0
-        2021  0.0  110.0  220.0
-        2022  0.0  120.0    NaN
+        .. testcode::
+
+            print(tr.shift())
+
+        .. testoutput::
+
+                   12     24     36
+            2020  0.0  100.0  200.0
+            2021  0.0  110.0  220.0
+            2022  0.0  120.0    NaN
 
         Shift one period along the origin axis. Each origin row's data moves
         down by one and the first origin row is zeroed out.
 
-        >>> tr.shift(periods=-1, axis='origin')
-                 12     24     36
-        2020    0.0    0.0    0.0
-        2021  100.0  200.0  300.0
-        2022  110.0  220.0    NaN
+        .. testcode::
+
+            print(tr.shift(periods=-1, axis='origin'))
+
+        .. testoutput::
+
+                     12     24     36
+            2020    0.0    0.0    0.0
+            2021  100.0  200.0  300.0
+            2022  110.0  220.0    NaN
         """
         axis = self._get_axis(axis)
         if axis < 2:
@@ -1807,29 +2052,43 @@ def sort_axis(self, axis):
         --------
         Build a Triangle with two columns supplied in non-alphabetical order.
 
-        >>> df = pd.DataFrame(
-        ...     data={
-        ...         'origin': [2020, 2020, 2021, 2021],
-        ...         'development': [2020, 2021, 2021, 2021],
-        ...         'reported': [100, 200, 110, 110],
-        ...         'paid': [50, 100, 60, 60],
-        ...     }
-        ... )
-        >>> tr = cl.Triangle(
-        ...     data=df,
-        ...     origin='origin',
-        ...     development='development',
-        ...     columns=['reported', 'paid'],
-        ...     cumulative=True,
-        ... )
-        >>> list(tr.columns)
-        ['reported', 'paid']
+        .. testsetup::
+
+            import chainladder as cl
+
+        .. testcode::
+
+            df = pd.DataFrame(
+                data={
+                    'origin': [2020, 2020, 2021, 2021],
+                    'development': [2020, 2021, 2021, 2021],
+                    'reported': [100, 200, 110, 110],
+                    'paid': [50, 100, 60, 60],
+                }
+            )
+            tr = cl.Triangle(
+                data=df,
+                origin='origin',
+                development='development',
+                columns=['reported', 'paid'],
+                cumulative=True,
+            )
+            print(list(tr.columns))
+
+        .. testoutput::
+
+            ['reported', 'paid']
 
         Sorting on the columns axis returns a new Triangle with columns in
         alphabetical order.
 
-        >>> list(tr.sort_axis('columns').columns)
-        ['paid', 'reported']
+        .. testcode::
+
+            print(list(tr.sort_axis('columns').columns))
+
+        .. testoutput::
+
+            ['paid', 'reported']
         """
 
         axis = self._get_axis(axis)

From 9358eddb7295faf8a726500755ef0d17e4694b41 Mon Sep 17 00:00:00 2001
From: Gene Dan <genedan@gmail.com>
Date: Tue, 5 May 2026 06:11:37 -0500
Subject: [PATCH 8/8] FIX: Correct typing for average: to Literal.

---
 chainladder/development/development.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/chainladder/development/development.py b/chainladder/development/development.py
index 5d2a962d..07fc86c7 100644
--- a/chainladder/development/development.py
+++ b/chainladder/development/development.py
@@ -92,7 +92,7 @@ class Development(DevelopmentBase):
     def __init__(
         self,
         n_periods: int = -1,
-        average: str = "volume",
+        average: Literal['volume', 'simple', 'regression'] = "volume",
         sigma_interpolation: Literal['log-linear', 'mack'] = "log-linear",
         drop: tuple | list[tuple] | None = None,
         drop_high: bool | int | list[bool] | list[int] | None = None,
@@ -130,7 +130,7 @@ def fit(
         Parameters
         ----------
         X : TriangleLike
-            Set of LDFs to which the munich adjustment will be applied.
+            Set of LDFs to which the Munich adjustment will be applied.
         y : None
             Ignored
         sample_weight : None