Does it support specific Python package managers?

Yes, it specifically emphasizes the use of 'uv run' for consistent, fast, and reliable execution of Python checks within the CI environment.

How does this skill handle existing CI configurations?

It is designed to detect and extend existing CI workflows rather than replace them, ensuring minimal disruption to your current setup.

Will this slow down my development process with long build times?

No, the skill follows a guardrail to keep runtime short by splitting heavy jobs into optional workflows, ensuring the default CI remains fast.

Can I run these CI checks locally?

Absolutely. One of the core workflow steps is to document and provide the exact commands needed to run the same checks on your local machine.

Python CI Automation

Name: Python CI Automation
Author: Silviase

bySilviase

Deployment & DevOps

Automates essential linting, testing, and type-checking pipelines for Python projects to maintain code health.

About

The Python CI Automation skill streamlines the implementation of minimal Continuous Integration workflows specifically tailored for Python research and development environments. It guides Claude to integrate automated checks—including linting, unit testing, and type-checking—while leveraging the 'uv' package manager for speed and consistency. By focusing on minimal, high-impact automation, it ensures code health remains high without introducing unnecessary complexity or slow build times.

Key Features

Standardized documentation for running checks locally
Integration with 'uv run' for efficient environment management
Optimized pipeline runtime through smart job splitting
Seamless extension of existing CI workflows without replacement
Automated linting and type-checking configuration
0 GitHub stars

Use Cases

Setting up a GitHub Actions pipeline for a new Python research project
Standardizing CI checks across multiple Python development environments
Adding automated type-checking and linting to an existing repository

About

Key Features

Standardized documentation for running checks locally
Integration with 'uv run' for efficient environment management
Optimized pipeline runtime through smart job splitting
Seamless extension of existing CI workflows without replacement
Automated linting and type-checking configuration
0 GitHub stars

Use Cases

Setting up a GitHub Actions pipeline for a new Python research project
Standardizing CI checks across multiple Python development environments
Adding automated type-checking and linting to an existing repository