What is the BayesFlow Packaging skill?

It is a specialized capability for Claude to automate the project structure, dependency management, and API exports specifically for BayesFlow-related Python packages.

Why does this skill enforce the src-layout convention?

The src-layout is a Python packaging best practice that prevents accidental imports of development code and ensures that tests run against the actual installed version of the package.

What CI/CD tools are included?

It provides standardized GitHub Actions configurations that include multi-version Python testing, Ruff linting, and Mypy type checking tailored for the BayesFlow ecosystem.

How does it handle public API management?

The skill manages the __all__ variable in __init__.py files, ensuring all public symbols are correctly exported for user access and IDE auto-completion.

BayesFlow Packaging Standards

Name: BayesFlow Packaging Standards
Author: matthiaskloft

bymatthiaskloft

0•

Despliegue y DevOps

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.

Características Principales

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

Casos de Uso

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

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add matthiaskloft/claude-skills bayesflow-packaging

For use in Claude.ai and ChatGPT

Características Principales

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

Casos de Uso

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

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add matthiaskloft/claude-skills bayesflow-packaging

For use in Claude.ai and ChatGPT