Standardize Python project setup with uv, pip, or poetry and pytest.
npx skills add https://github.com/ilude/claude-code-config --skill python-workflow
Please help me install this Agent Skill. Skill: python-workflow Source: https://github.com/ilude/claude-code-config/tree/main/skills/python-workflow Command: npx skills add https://github.com/ilude/claude-code-config --skill python-workflow
This Skill standardizes Python project setup and execution, eliminating virtual environment headaches, ensuring consistent package management, and promoting best practices for code style and testing. It saves you time on environment configuration and ensures project consistency.
uv run python for seamless virtual environment activation, preventing cross-platform issues and manual path references.uv, pip, poetry, or pipenv, respecting project-specific configurations (pyproject.toml, requirements.txt) without mixing tools.pytest for high-quality code.uv sync, and ensure all subsequent Python commands are run correctly within the virtual environment, saving you setup time and potential dependency conflicts.Set up the Python project in the current directory. Install all dependencies using the project's package manager. Then, run the main script app.py.
High-intent search queries and answers about installing and using this skill.
Python project setup uses uv to manage dependencies and virtual environments consistently across Windows, macOS, and Linux. Run `uv sync` to install dependencies from your project configuration, then execute code with `uv run python` to activate the environment automatically, eliminating manual .venv references and cross-platform path issues.
A standardized Python workflow respects your project's existing package manager—uv, pip, poetry, or pipenv—by detecting and using the configuration in pyproject.toml, requirements.txt, or setup.cfg. Mixing tools in one project causes dependency conflicts; this workflow enforces consistent tooling throughout.
Code quality enforcement integrates Black for formatting, isort for import sorting, Ruff for linting, and type hints to catch errors early. A standardized workflow automates these tools during development, ensuring PEP 8 compliance and type safety without manual intervention across your codebase.
A standardized Python workflow integrates pytest for testing and Pydantic for data validation, working within your virtual environment via `uv run pytest`. This ensures tests execute in the correct isolated environment and configurations in pyproject.toml or setup.cfg are honored automatically.
No. Using `uv run python` activates your virtual environment automatically without manual `.venv` activation, eliminating setup steps and shell-specific commands. This approach works identically on Windows, macOS, and Linux within the standardized workflow.
Run `uv sync` to detect your project's existing package manager configuration and install dependencies into a uv-managed virtual environment. Subsequent commands use `uv run python` instead of manual activation, preserving your pyproject.toml, requirements.txt, or poetry.lock while adopting the standardized workflow.
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