Streamlines the creation and management of BayesFlow extension packages using standardized project structures and Python packaging best practices.
This skill automates the setup and maintenance of BayesFlow extension packages, ensuring they adhere to the src/ layout convention and maintain a clean public API. It provides comprehensive templates for pyproject.toml, handles the meticulous management of __all__ exports for IDE compatibility, implements robust version detection, and configures standardized CI/CD pipelines via GitHub Actions. It is an essential tool for developers building modular components within the BayesFlow ecosystem who need to ensure their contributions are consistent, installable, and professional.
主要功能
01Consistent __all__ and public API export management
02Pre-configured CI/CD matrix for Python 3.11+
03Standardized pyproject.toml and optional dependency templates
04Robust package version detection with fallback support
050 GitHub stars
06Automated src-layout project scaffolding
使用场景
01Managing optional extras and dependency groups like calibration or notebooks
02Setting up GitHub Actions for automated testing, linting, and type checking
03Creating a new BayesFlow extension module with standardized folder structures