releasing-to-pypi

To automate a PyPI release, you follow an atomic checklist that lints code, bumps versions across multiple files, creates a git tag, and pushes to GitHub. This ensures the tagged commit is production-ready and prevents release failures.

For a consistent PyPI release version, you must update version numbers across all relevant configuration files including pyproject.toml, __init__.py, tests, and CHANGELOG.md. This prevents distribution errors and maintains code integrity.

Your CI/CD pipeline may fail because immutable PyPI filename conflicts occur if a tagged commit is not production-ready. Enforcing pre-commit checks and post-push verification prevents these release failures by ensuring all steps are completed correctly.

Yes, you can use an atomic release process checklist to prevent failed PyPI releases. It enforces strict pre-commit linting, version consistency, and documentation updates in a single verifiable commit before pushing code.

The best way to prepare code for a reproducible PyPI distribution is to run linters, update version numbers across all project files, verify the changelog, and create the Git tag and GitHub release in one unified process.

You should not use an automated release process if your project lacks CI/CD configuration or if version numbers are managed manually across files without synchronization, as the atomic checklist enforces strict version consistency and pre-commit validation.