Set up Python projects and manage dependencies with uv.
npx skills add https://github.com/pproenca/dot-claude --skill python-project-pproenca
Please help me install this Agent Skill. Skill: python-project Source: https://github.com/pproenca/dot-claude/tree/main/domain_plugins/dev-python/skills/python-project Command: npx skills add https://github.com/pproenca/dot-claude --skill python-project-pproenca
This Skill helps bootstrap Python projects and manage dependencies using uv, configure pyproject.toml, create a solid project structure, and publish packages with modern tooling.
Create a new project with uv init my-project, pin Python 3.12, add core dependencies (fastapi, pydantic), and run uv sync.
High-intent search queries and answers about installing and using this skill.
Use uv init to create a new project with standard structure, configure pyproject.toml for metadata and dependencies, pin your Python version in .python-version, and run uv sync to install dependencies. This establishes a reproducible, src/-layout project ready for development and publishing.
Yes. uv works with existing projects by reading and updating pyproject.toml, pinning dependencies via uv lock, and syncing your environment. Migrate gradually by adding uv commands alongside your current workflow.
Store your target Python version in a .python-version file at the project root. uv reads this file automatically, ensuring all team members and CI/CD pipelines use the same Python version without manual configuration.
Use uv add package-name to add a dependency to pyproject.toml and generate a locked version file. Run uv sync to install exact versions, and commit the lock file to version control for reproducible builds across environments.
Yes. Configure package metadata in pyproject.toml (name, version, author, description) and use uv to manage dependencies and build artifacts. Then use standard publishing tools to upload to PyPI or private registries.
uv scaffolds projects with a src/ layout, separating source code from tests and config files. This structure improves packaging, isolates dependencies, and follows Python packaging best practices for distributable projects.
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jacexhCreate distributable Python packages with pyproject.toml and CI publishing workflows.
CuriousLearnerCreate and manage Python virtual environments and dependencies with venv, virtualenv, poetry, and pyenv.
