A Python package for generating PDF codebooks from tabular data. Quickly create project descriptions, data dictionaries, and variable summaries with customizable formatting. Ideal for data science, reproducible research, and sharing dataset documentation.

0 stars 0 forks 0 watchers Python BSD 3-Clause "New" or "Revised" License
2 Open Issues Need Help Last updated: Sep 24, 2025

Open Issues Need Help

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AI Summary: This issue tasks developers with reviewing all functions in the codebase to enhance their clarity and documentation. The goal is to ensure each function has a well-defined signature, including type hints for parameters and return values, and a comprehensive docstring. Docstrings should detail the function's purpose, input/output types, side effects, and any exceptions to improve code readability and maintainability.

Complexity: 4/5
documentation good first issue refactor

A Python package for generating PDF codebooks from tabular data. Quickly create project descriptions, data dictionaries, and variable summaries with customizable formatting. Ideal for data science, reproducible research, and sharing dataset documentation.

Python

AI Summary: This GitHub issue provides a beginner's guide on how to run `pytest` locally before creating a pull request. It explains the purpose of `pytest` and virtual environments, then offers step-by-step instructions starting with creating a virtual environment in the project folder.

Complexity: 1/5
documentation good first issue testing beginner-friendly

A Python package for generating PDF codebooks from tabular data. Quickly create project descriptions, data dictionaries, and variable summaries with customizable formatting. Ideal for data science, reproducible research, and sharing dataset documentation.

Python