From 25fbc287371225ccec7cb2f5912d8a3fe999b475 Mon Sep 17 00:00:00 2001
From: Heather Patrick <htx7@cdc.gov>
Date: Fri, 14 Aug 2026 12:07:02 -0400
Subject: [PATCH 1/7] Added a Troubleshooting Guide

Troubleshooting Guide added to enhance usability by providing fixes to common issues users may encounter using cfa-dataops.
---
 docs/Troubleshooting Guide | 291 +++++++++++++++++++++++++++++++++++++
 1 file changed, 291 insertions(+)
 create mode 100644 docs/Troubleshooting Guide

diff --git a/docs/Troubleshooting Guide b/docs/Troubleshooting Guide
new file mode 100644
index 0000000..8527f07
--- /dev/null
+++ b/docs/Troubleshooting Guide	
@@ -0,0 +1,291 @@
+# CFA DataOps — Troubleshooting Guide
+
+## Purpose
+
+This guide is intended to improve the user experience with cfa-dataops client capabilities.  It provides guidance on troubleshooting common issues that CFA users may encounter when using **CFA dataops** toolkit, catalogs, and reporting utilities.
+ 
+
+## How to Use This Guide
+
+1. **Start with a quick health check** (environment, access).
+2. **Find your issue** in the sections below.
+3. **Implement a solution**, then re‑run the minimal example(s).
+4. If the issue persists, collect logs and **open a GitHub issue** in the [Repo](https://github.com/CDCgov/cfa-dataops)
+
+
+## Quick Health Check
+
+- **Python environment**
+  
+  - Confirm Python 3.10+ is active and dependencies installed (pandas, polars, duckdb, papermill, etc.).  
+
+- **Import the core namespaces**
+  
+  ```Python```
+
+  `from cfa.dataops import datacat, reportcat`
+
+  `print("Datasets:", datacat.__namespace_list__)`
+
+  `print("Reports:", reportcat.__namespace_list__)`
+
+  If imports fail, see **Environment & Installation** below.
+
+- **Azure Cloud access**
+
+    If your workflow requires blob access, ensure you’re logged in, using the appropriate authorization for your context.
+
+        `az login --identity`
+
+## Common Issues & Solutions
+
+### 1. Environment & Installation
+   
+  **Issue**
+
+  `ModuleNotFoundError` for cfa.dataops, polars, duckdb, or pandera
+
+**Common causes**
+
+  - Virtual environment not activated.
+  - Installed with incompatible Python version.
+
+**Solution**
+
+  - Verify Python listed in pyproject.toml and install/upgrade accordingly.
+  - Re‑install the project using your team’s standard (e.g., uv, pip, or poetry) and re‑activate the venv.
+  - Re‑try minimal imports (see Quick Health Check). 
+
+
+### 2. Accessing Data — get_dataframe() Errors
+
+  **Issue**
+
+  Errors when loading dataframes (e.g., “no matching version”, “cannot resolve selection”).
+
+**Common causes**
+
+  - No dataset versions meet your version-spec.
+  - Using default selection where multiple matches exist.
+  - Attempting to load large outputs into pandas that exceed memory.
+
+**Solution**
+
+  - Preview the version that would be used before loading:
+  
+      `from cfa.dataops import datacat`
+      
+      `resolved = datacat.private.scenarios.covid19vax_trends.load.resolve_version(    version_spec=">=2025-05-01,<2025-06-01",    selection="newest",)`
+      
+      `print(resolved.version)`
+      
+      `print(resolved.blob_url)`
+      
+      Then pass the same arguments to:
+
+      `get_dataframe()` 
+
+
+  - List available versions to confirm your constraints
+
+    `datacat.private.scenarios.covid19vax_trends.load.get_versions()`
+    
+    If empty or unexpected, re‑run ETL or relax version-spec. 
+
+  - Choose appropriate output for size/performance
+  
+    \# pandas DataFrame
+    
+      `df = datacat.private.scenarios.covid19vax_trends.load.get_dataframe(output="pandas")`
+      
+      \# polars DataFrame
+      
+        `df_pl = datacat.private.scenarios.covid19vax_trends.load.get_dataframe(output="polars")`
+      
+      \# lazy polars (defer materialization)
+      
+        `df_lazy = datacat.private.scenarios.covid19vax_trends.load.get_dataframe(output="pl_lazy")`
+        
+    Use polars/pl_lazy for large datasets to mitigate memory pressure. 
+
+
+  - Advanced version filters
+    
+    - If you rely on range or pattern filters (e.g., >=..., <..., latest), confirm your string syntax matches the project’s conventions noted in release notes.
+
+
+### 3. Authentication / Azure Blob Access
+
+**Issue**
+
+  Read/write fails to blob storage; “permission denied” or timeouts.
+
+**Common causes**
+
+  - Not authenticated in the current shell/session.
+  - Missing role or wrong subscription/tenant.
+  - Network constraints.
+
+**Solution**
+
+  - Log in using your approved method (e.g., az login --identity) and verify subscription.
+  - If you use helper utilities from the companion cfa-cloudops library for authentication/workflows, ensure it’s correctly configured and you’re on a supported Python version. 
+  - Re‑run a small read_blobs/get_versions check to validate access via the catalog (see **Data User Guide**).
+
+
+### 4. Catalog Creation & Management
+
+  **Issue**
+    
+  New datasets or catalogs don’t appear under datacat.__namespace_list__.
+
+**Common causes**
+
+  - Catalog not installed/registered in the environment.
+  - Misconfigured dataset definition (TOML).
+  - Namespace conflicts.
+
+**Solution**
+
+  - Use the catalog initialization CLI to create a standards‑compliant structure:
+  
+    `dataops_catalog_init --help`
+    
+    
+    Then follow the catalog creation and managing guides in docs/.
+
+  - Validate dataset configuration (paths, names, and extract/load endpoints) and re‑install the catalog if needed. (See Managing Catalogs and Catalog Creation pages).
+  - Restart your Python session to refresh namespace discovery and re‑check:
+  
+    `from cfa.dataops import datacat`
+    
+    `print(datacat.__namespace_list__)`
+    
+    
+### 5. Schema Validation Failures
+
+  **Issue**
+  
+  Errors citing required columns, types, or value ranges.
+
+  **Common causes**
+
+  - Source feed changed upstream.
+  - Transform altered types unexpectedly.
+  - Misaligned schema definitions.
+
+  **Solution**
+
+  - Review the dataset’s schema expectations and correct the ETL or input source. (See Data Validation in the Data User Guide).
+  
+  - If recent changes impacted schemas, consult **Release Notes** for updates and migrate accordingly.
+
+
+### 6. Reporting / Notebook Conversion (Reportcat)
+
+  **Issue**
+  
+  Notebook→HTML export fails; missing assets or runtime errors.
+
+  **Common causes**
+
+  - Missing notebook dependencies (e.g., papermill, ipykernel, ipywidgets).
+  - Incorrect report namespace or path.
+
+**Solution**
+
+  - Verify report namespaces
+  
+    `from cfa.dataops import reportcat`
+    
+    `print("Reports:", reportcat.__namespace_list__)`
+
+
+  - Try a minimal conversion
+  
+    `html = reportcat.private.examples.basics_ipynb.nb_to_html_str()`
+    
+    If this works, the issue is likely report‑specific.
+
+  - Confirm report dependencies are installed; pyproject.toml lists required packages (e.g., papermill, ipykernel, ipywidgets). 
+
+  - Check the **Report Generation** docs for patterns & publishing steps.
+
+
+### 7. Performance & Memory
+
+  **Issue**
+  
+  Slow dataframe operations; process killed due to memory.
+
+  **Common causes**
+
+  - Loading large datasets into pandas.
+  - Inefficient transformations and eager evaluation.
+
+  **Solution**
+
+  - Use Polars or DuckDB for large joins/aggregations
+  - Use lazy operations via output="pl_lazy" and materialize only the final result. 
+  - Filter and project early (column & row pruning) before joins; verify results on a small sample.
+
+
+### 8. Versioning & Reproducibility
+
+  **Issue**
+  
+  Analyses aren’t reproducible; different runs return different data.
+
+  **Common causes**
+
+  - Implicit latest version selection.
+  - Ambiguous version-spec ranges.
+
+  **Solution**
+
+  - Pin exact versions using timestamp equality:
+  
+  `df = datacat.private.scenarios.covid19vax_trends.load.get_dataframe(version_spec="==2025-06-03T17-59-16")`
+  
+  - Document your version-spec and selection and store them with the analysis for auditability.
+
+
+## Minimal Working Examples (MWE)
+
+  - List datasets & load one
+
+    `from cfa.dataops import datacat`
+
+    `print(datacat.__namespace_list__)`
+
+    `df = datacat.private.scenarios.covid19vax_trends.load.get_dataframe()`
+    
+  - Preview version before load
+
+    `from cfa.dataops import datacatresolved = datacat.private.scenarios.covid19vax_trends.load.resolve_version(version_spec=">=2025-05-01,<2025-06-01", selection="newest",)`
+
+    `print(resolved.version, resolved.blob_url)`
+    
+  - Notebook → HTML (quick check)
+
+    `from cfa.dataops import reportcat`
+    
+    `html = reportcat.private.examples.basics_ipynb.nb_to_html_str()`
+
+
+## When to Open a GitHub Issue
+
+Open an issue when:
+
+  - You can reproduce a failure using an MWE above.
+  - Behavior contradicts documented APIs or release notes.
+  - A dataset’s schema or versioning appears inconsistent with docs.
+
+Provide:
+
+  - Python version, package versions (pip list/uv pip list), OS.
+  - Exact code snippet and traceback.
+  - Dataset/catalog names and version-spec.
+  - Whether Azure auth was active (az login), if relevant.
+
+Use the repo’s [issue tracker](CDCgov/cfa-dataops)

From 1f512da802c36a98c71d0238abc51eb97fbc6355 Mon Sep 17 00:00:00 2001
From: Heather Patrick <htx7@cdc.gov>
Date: Thu, 20 Aug 2026 08:23:19 -0400
Subject: [PATCH 2/7] Removed reportcat import from troubleshooting guide

---
 docs/Troubleshooting Guide | 47 ++++----------------------------------
 1 file changed, 5 insertions(+), 42 deletions(-)

diff --git a/docs/Troubleshooting Guide b/docs/Troubleshooting Guide
index 8527f07..d141c54 100644
--- a/docs/Troubleshooting Guide	
+++ b/docs/Troubleshooting Guide	
@@ -23,12 +23,10 @@ This guide is intended to improve the user experience with cfa-dataops client ca
   
   ```Python```
 
-  `from cfa.dataops import datacat, reportcat`
+  `from cfa.dataops import datacat`
 
   `print("Datasets:", datacat.__namespace_list__)`
 
-  `print("Reports:", reportcat.__namespace_list__)`
-
   If imports fail, see **Environment & Installation** below.
 
 - **Azure Cloud access**
@@ -181,37 +179,6 @@ This guide is intended to improve the user experience with cfa-dataops client ca
   - If recent changes impacted schemas, consult **Release Notes** for updates and migrate accordingly.
 
 
-### 6. Reporting / Notebook Conversion (Reportcat)
-
-  **Issue**
-  
-  Notebook→HTML export fails; missing assets or runtime errors.
-
-  **Common causes**
-
-  - Missing notebook dependencies (e.g., papermill, ipykernel, ipywidgets).
-  - Incorrect report namespace or path.
-
-**Solution**
-
-  - Verify report namespaces
-  
-    `from cfa.dataops import reportcat`
-    
-    `print("Reports:", reportcat.__namespace_list__)`
-
-
-  - Try a minimal conversion
-  
-    `html = reportcat.private.examples.basics_ipynb.nb_to_html_str()`
-    
-    If this works, the issue is likely report‑specific.
-
-  - Confirm report dependencies are installed; pyproject.toml lists required packages (e.g., papermill, ipykernel, ipywidgets). 
-
-  - Check the **Report Generation** docs for patterns & publishing steps.
-
-
 ### 7. Performance & Memory
 
   **Issue**
@@ -262,17 +229,13 @@ This guide is intended to improve the user experience with cfa-dataops client ca
     
   - Preview version before load
 
-    `from cfa.dataops import datacatresolved = datacat.private.scenarios.covid19vax_trends.load.resolve_version(version_spec=">=2025-05-01,<2025-06-01", selection="newest",)`
+    `from cfa.dataops import datacat`
 
-    `print(resolved.version, resolved.blob_url)`
-    
-  - Notebook → HTML (quick check)
+    `resolved = datacat.private.scenarios.covid19vax_trends.load.resolve_version(version_spec=">=2025-05-01,<2025-06-01", selection="newest",)`
 
-    `from cfa.dataops import reportcat`
+    `print(resolved.version, resolved.blob_url)`
     
-    `html = reportcat.private.examples.basics_ipynb.nb_to_html_str()`
-
-
+  
 ## When to Open a GitHub Issue
 
 Open an issue when:

From 2100cf81cccb0f46ff5c71886e165eaa43d6cdaf Mon Sep 17 00:00:00 2001
From: Heather Patrick <htx7@AZ1CFA1VSWL-58.ext.cdc.gov>
Date: Tue, 25 Aug 2026 22:38:53 +0000
Subject: [PATCH 3/7] removed references to reportcat

---
 docs/{Troubleshooting Guide => troubleshooting-guide.md} | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)
 rename docs/{Troubleshooting Guide => troubleshooting-guide.md} (99%)

diff --git a/docs/Troubleshooting Guide b/docs/troubleshooting-guide.md
similarity index 99%
rename from docs/Troubleshooting Guide
rename to docs/troubleshooting-guide.md
index d141c54..7ba8d39 100644
--- a/docs/Troubleshooting Guide	
+++ b/docs/troubleshooting-guide.md
@@ -10,7 +10,7 @@ This guide is intended to improve the user experience with cfa-dataops client ca
 1. **Start with a quick health check** (environment, access).
 2. **Find your issue** in the sections below.
 3. **Implement a solution**, then re‑run the minimal example(s).
-4. If the issue persists, collect logs and **open a GitHub issue** in the [Repo](https://github.com/CDCgov/cfa-dataops)
+4. If the issue persists, collect logs and **open a GitHub issue** in the [Repo](https://github.com/CDCgov/cfa-dataops).
 
 
 ## Quick Health Check

From 0ad9b99d63f793a2469de23830922108e9684d5a Mon Sep 17 00:00:00 2001
From: Heather Patrick <htx7@AZ1CFA1VSWL-58.ext.cdc.gov>
Date: Tue, 25 Aug 2026 23:27:07 +0000
Subject: [PATCH 4/7] re-checking pre-commit status

---
 docs/troubleshooting-guide.md | 84 +++++++++++++++++------------------
 1 file changed, 42 insertions(+), 42 deletions(-)

diff --git a/docs/troubleshooting-guide.md b/docs/troubleshooting-guide.md
index 7ba8d39..8113781 100644
--- a/docs/troubleshooting-guide.md
+++ b/docs/troubleshooting-guide.md
@@ -3,7 +3,7 @@
 ## Purpose
 
 This guide is intended to improve the user experience with cfa-dataops client capabilities.  It provides guidance on troubleshooting common issues that CFA users may encounter when using **CFA dataops** toolkit, catalogs, and reporting utilities.
- 
+
 
 ## How to Use This Guide
 
@@ -16,11 +16,11 @@ This guide is intended to improve the user experience with cfa-dataops client ca
 ## Quick Health Check
 
 - **Python environment**
-  
-  - Confirm Python 3.10+ is active and dependencies installed (pandas, polars, duckdb, papermill, etc.).  
+
+  - Confirm Python 3.10+ is active and dependencies installed (pandas, polars, duckdb, papermill, etc.).
 
 - **Import the core namespaces**
-  
+
   ```Python```
 
   `from cfa.dataops import datacat`
@@ -38,7 +38,7 @@ This guide is intended to improve the user experience with cfa-dataops client ca
 ## Common Issues & Solutions
 
 ### 1. Environment & Installation
-   
+
   **Issue**
 
   `ModuleNotFoundError` for cfa.dataops, polars, duckdb, or pandera
@@ -52,7 +52,7 @@ This guide is intended to improve the user experience with cfa-dataops client ca
 
   - Verify Python listed in pyproject.toml and install/upgrade accordingly.
   - Re‑install the project using your team’s standard (e.g., uv, pip, or poetry) and re‑activate the venv.
-  - Re‑try minimal imports (see Quick Health Check). 
+  - Re‑try minimal imports (see Quick Health Check).
 
 
 ### 2. Accessing Data — get_dataframe() Errors
@@ -70,45 +70,45 @@ This guide is intended to improve the user experience with cfa-dataops client ca
 **Solution**
 
   - Preview the version that would be used before loading:
-  
+
       `from cfa.dataops import datacat`
-      
+
       `resolved = datacat.private.scenarios.covid19vax_trends.load.resolve_version(    version_spec=">=2025-05-01,<2025-06-01",    selection="newest",)`
-      
+
       `print(resolved.version)`
-      
+
       `print(resolved.blob_url)`
-      
+
       Then pass the same arguments to:
 
-      `get_dataframe()` 
+      `get_dataframe()`
 
 
   - List available versions to confirm your constraints
 
     `datacat.private.scenarios.covid19vax_trends.load.get_versions()`
-    
-    If empty or unexpected, re‑run ETL or relax version-spec. 
+
+    If empty or unexpected, re‑run ETL or relax version-spec.
 
   - Choose appropriate output for size/performance
-  
+
     \# pandas DataFrame
-    
+
       `df = datacat.private.scenarios.covid19vax_trends.load.get_dataframe(output="pandas")`
-      
+
       \# polars DataFrame
-      
+
         `df_pl = datacat.private.scenarios.covid19vax_trends.load.get_dataframe(output="polars")`
-      
+
       \# lazy polars (defer materialization)
-      
+
         `df_lazy = datacat.private.scenarios.covid19vax_trends.load.get_dataframe(output="pl_lazy")`
-        
-    Use polars/pl_lazy for large datasets to mitigate memory pressure. 
+
+    Use polars/pl_lazy for large datasets to mitigate memory pressure.
 
 
   - Advanced version filters
-    
+
     - If you rely on range or pattern filters (e.g., >=..., <..., latest), confirm your string syntax matches the project’s conventions noted in release notes.
 
 
@@ -127,14 +127,14 @@ This guide is intended to improve the user experience with cfa-dataops client ca
 **Solution**
 
   - Log in using your approved method (e.g., az login --identity) and verify subscription.
-  - If you use helper utilities from the companion cfa-cloudops library for authentication/workflows, ensure it’s correctly configured and you’re on a supported Python version. 
+  - If you use helper utilities from the companion cfa-cloudops library for authentication/workflows, ensure it’s correctly configured and you’re on a supported Python version.
   - Re‑run a small read_blobs/get_versions check to validate access via the catalog (see **Data User Guide**).
 
 
 ### 4. Catalog Creation & Management
 
   **Issue**
-    
+
   New datasets or catalogs don’t appear under datacat.__namespace_list__.
 
 **Common causes**
@@ -146,24 +146,24 @@ This guide is intended to improve the user experience with cfa-dataops client ca
 **Solution**
 
   - Use the catalog initialization CLI to create a standards‑compliant structure:
-  
+
     `dataops_catalog_init --help`
-    
-    
+
+
     Then follow the catalog creation and managing guides in docs/.
 
   - Validate dataset configuration (paths, names, and extract/load endpoints) and re‑install the catalog if needed. (See Managing Catalogs and Catalog Creation pages).
   - Restart your Python session to refresh namespace discovery and re‑check:
-  
+
     `from cfa.dataops import datacat`
-    
+
     `print(datacat.__namespace_list__)`
-    
-    
+
+
 ### 5. Schema Validation Failures
 
   **Issue**
-  
+
   Errors citing required columns, types, or value ranges.
 
   **Common causes**
@@ -175,14 +175,14 @@ This guide is intended to improve the user experience with cfa-dataops client ca
   **Solution**
 
   - Review the dataset’s schema expectations and correct the ETL or input source. (See Data Validation in the Data User Guide).
-  
+
   - If recent changes impacted schemas, consult **Release Notes** for updates and migrate accordingly.
 
 
 ### 7. Performance & Memory
 
   **Issue**
-  
+
   Slow dataframe operations; process killed due to memory.
 
   **Common causes**
@@ -193,14 +193,14 @@ This guide is intended to improve the user experience with cfa-dataops client ca
   **Solution**
 
   - Use Polars or DuckDB for large joins/aggregations
-  - Use lazy operations via output="pl_lazy" and materialize only the final result. 
+  - Use lazy operations via output="pl_lazy" and materialize only the final result.
   - Filter and project early (column & row pruning) before joins; verify results on a small sample.
 
 
 ### 8. Versioning & Reproducibility
 
   **Issue**
-  
+
   Analyses aren’t reproducible; different runs return different data.
 
   **Common causes**
@@ -211,9 +211,9 @@ This guide is intended to improve the user experience with cfa-dataops client ca
   **Solution**
 
   - Pin exact versions using timestamp equality:
-  
+
   `df = datacat.private.scenarios.covid19vax_trends.load.get_dataframe(version_spec="==2025-06-03T17-59-16")`
-  
+
   - Document your version-spec and selection and store them with the analysis for auditability.
 
 
@@ -226,7 +226,7 @@ This guide is intended to improve the user experience with cfa-dataops client ca
     `print(datacat.__namespace_list__)`
 
     `df = datacat.private.scenarios.covid19vax_trends.load.get_dataframe()`
-    
+
   - Preview version before load
 
     `from cfa.dataops import datacat`
@@ -234,8 +234,8 @@ This guide is intended to improve the user experience with cfa-dataops client ca
     `resolved = datacat.private.scenarios.covid19vax_trends.load.resolve_version(version_spec=">=2025-05-01,<2025-06-01", selection="newest",)`
 
     `print(resolved.version, resolved.blob_url)`
-    
-  
+
+
 ## When to Open a GitHub Issue
 
 Open an issue when:

From 41bd722bb43ea6ad3a70eb0b4816b59665f553ad Mon Sep 17 00:00:00 2001
From: Heather Patrick <htx7@AZ1CFA1VSWL-58.ext.cdc.gov>
Date: Wed, 26 Aug 2026 21:08:27 +0000
Subject: [PATCH 5/7] new README file for dataops/tests directory added

---
 tests/dataops-tests.md | 94 ++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 94 insertions(+)
 create mode 100644 tests/dataops-tests.md

diff --git a/tests/dataops-tests.md b/tests/dataops-tests.md
new file mode 100644
index 0000000..4904469
--- /dev/null
+++ b/tests/dataops-tests.md
@@ -0,0 +1,94 @@
+# CFA DataOps Tests
+
+## Overview
+The cfa-dataops/tests directory contains automated checks to help ensure the reliability of **cfa-dataops** library and its supporting utilities.  The suite is designed to run locally and in CI, emphasizing fast unit tests while allowing (optional) integration tests that touch cloud resources used by CFA DataOps (e.g. Azure Blob Storage)
+
+
+## Quick Start Checklist
+1. Python: install Python 3.10 or newer.
+
+2. Clone the repo
+
+    `git clone https://github.com/CDCgov/cfa-dataops.git`
+
+    `cd cfa-dataops`
+
+3.	Set up the environment (recommended: uv)
+
+    \# Install project dependencies using uv
+
+    `uv sync`
+
+4.	Authenticate to Azure (Optional)
+
+    if you will run integration tests that touch cloud resources:
+
+    `az login –identity`
+
+5.	Run the tests
+
+    \# All tests (recommended)
+
+    `uv run pytest`
+
+
+## Getting Started
+1.  Install & Setup
+
+    #### With uv (recommended)
+
+    \# from the repository root
+
+    `uv sync`
+
+    `uv run pytest`
+
+    #### With pip (alternative)
+
+    `python -m venv .venv`
+
+    `source .venv/bin/activate'
+
+    \# Windows:
+
+    `.venv\Scripts\activate`
+
+    `python -m pip install --upgrade pip`
+
+    `pip install -e .`
+
+    `pytest`
+
+2. Running Specific Tests
+
+    #### Single file or node ID (pytest standard)
+
+    `uv run pytest tests/path/to/testmodule.py::TestClass::testmethod`
+
+
+    Selecting tests via node IDs is a standard pytest feature.
+    - Show detailed output
+
+        `uv run pytest -vv`
+
+3. Coverage (optional)
+
+    If you’d like coverage reports:
+
+    `uv run pytest --cov=cfa.dataops --cov-report=term-missing`
+
+4. Cloud-Dependent Tests (optional)
+
+    Some tests may rely on access to CDC cloud resources.
+
+    \# Authenticate (if applicable)
+
+    `az login –identity`
+
+
+## Docs for developers
+    Project documentation explains how data catalogs and ETL/reporting components work:
+    - Project documentation
+    - Data User Guide
+    - Data Developer Guide
+    - CLI Tools Reference

From dfb3be8ff36a4c5a715029e1f9750bf9a084df1e Mon Sep 17 00:00:00 2001
From: Heather Patrick <htx7@AZ1CFA1VSWL-58.ext.cdc.gov>
Date: Thu, 27 Aug 2026 13:16:13 +0000
Subject: [PATCH 6/7] added a key features section

---
 tests/dataops-tests.md | 10 ++++++++--
 1 file changed, 8 insertions(+), 2 deletions(-)

diff --git a/tests/dataops-tests.md b/tests/dataops-tests.md
index 4904469..60a2c28 100644
--- a/tests/dataops-tests.md
+++ b/tests/dataops-tests.md
@@ -1,8 +1,14 @@
 # CFA DataOps Tests
 
 ## Overview
-The cfa-dataops/tests directory contains automated checks to help ensure the reliability of **cfa-dataops** library and its supporting utilities.  The suite is designed to run locally and in CI, emphasizing fast unit tests while allowing (optional) integration tests that touch cloud resources used by CFA DataOps (e.g. Azure Blob Storage)
-
+The cfa-dataops/tests directory contains automated checks to help ensure the reliability of **cfa-dataops** library and its supporting utilities.  The suite is designed to run locally and in CI, emphasizing fast unit tests while allowing (optional) integration tests that touch cloud resources used by CFA DataOps (e.g. Azure Blob Storage).
+
+## Key Features of Tests Directory
+**Pytest-based suite:** Leverages pytest for discovery and execution.  
+**Mocking support:** Uses pytest-mock to isolate external dependencies during unit testing.  
+**Property-based tests:** Optionally uses hypothesis to validate invariants across randomized inputs.  
+**Coverage instrumentation:** Configurable via .coveragerc and pytest-cov.  
+**Works with uv:** The ecosystem commonly runs commands through uv (e.g., uv run pytest) for consistent environments.
 
 ## Quick Start Checklist
 1. Python: install Python 3.10 or newer.

From d82dacdd5e7ba84106283c5c3ebd5c1b091a6a20 Mon Sep 17 00:00:00 2001
From: Heather Patrick <htx7@AZ1CFA1VSWL-58.ext.cdc.gov>
Date: Thu, 27 Aug 2026 13:19:08 +0000
Subject: [PATCH 7/7] added a key features section

---
 tests/dataops-tests.md | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/tests/dataops-tests.md b/tests/dataops-tests.md
index 60a2c28..84b369e 100644
--- a/tests/dataops-tests.md
+++ b/tests/dataops-tests.md
@@ -4,10 +4,10 @@
 The cfa-dataops/tests directory contains automated checks to help ensure the reliability of **cfa-dataops** library and its supporting utilities.  The suite is designed to run locally and in CI, emphasizing fast unit tests while allowing (optional) integration tests that touch cloud resources used by CFA DataOps (e.g. Azure Blob Storage).
 
 ## Key Features of Tests Directory
-**Pytest-based suite:** Leverages pytest for discovery and execution.  
-**Mocking support:** Uses pytest-mock to isolate external dependencies during unit testing.  
-**Property-based tests:** Optionally uses hypothesis to validate invariants across randomized inputs.  
-**Coverage instrumentation:** Configurable via .coveragerc and pytest-cov.  
+**Pytest-based suite:** Leverages pytest for discovery and execution.
+**Mocking support:** Uses pytest-mock to isolate external dependencies during unit testing.
+**Property-based tests:** Optionally uses hypothesis to validate invariants across randomized inputs.
+**Coverage instrumentation:** Configurable via .coveragerc and pytest-cov.
 **Works with uv:** The ecosystem commonly runs commands through uv (e.g., uv run pytest) for consistent environments.
 
 ## Quick Start Checklist