Improve Documentation on PyPI Release Process
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- Dominant language
- Ruby
- Stars
- 3
- Forks
- 9
- PR merge metrics
- No merged PRs in 30d
Description
The example of releasing a Poetry-built package to PyPI is using manual CLI commands, which should not be the recommended approach IMO. Releases should be managed through some kind of CI workflow (Jenkins, GitHub Actions, Travis, GitLab CI, or others). Using manual uploads from a developer laptop is error prone and should be discouraged as you can end up with "dirty" (uncommitted code) releases on PyPI, which are immutable once published. Automated pipelines can perform validation checks prior to publishing to ensure tags, versions, and package metadata is in sync. They can also streamline releasing to GitHub, PyPI, and Conda all at once, which is critical for consistent release management between ecosystems.
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by locating the documentation example for releasing a Poetry-built package to PyPI. Review how the current manual CLI process is described and determine the scope of an automated CI-based replacement; done means the documentation clearly recommends and explains an agreed release workflow with validation before publishing.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- documentation, release
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 30/100