Скачать или смотреть How to Change Your Python Package Version from Development to Stable Release on PyPi

Learn the steps to change your Python package version from development to a stable release on PyPi, ensuring proper versioning and compatibility.
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When it comes to releasing your Python package on PyPi, transitioning from a development version to a stable release is crucial. Here's a step-by-step guide to help you make this transition seamlessly.

Step-by-Step Guide to Update Your Package Version

Understand Semantic Versioning: Before making any changes, it's critical to understand semantic versioning (SemVer), which typically follows the pattern of MAJOR.MINOR.PATCH.

MAJOR version when you make incompatible API changes.

MINOR version when you add functionality in a backwards-compatible manner.

PATCH version when you make backwards-compatible bug fixes.

Modify the setup.py File: Open your package’s setup.py file. You need to update the version parameter in this file to reflect your new stable version.

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Commit Your Changes: Commit the changes you made to the setup.py file to your version control system (e.g., Git).

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Update Your Package on PyPi:

Build the Distribution: Generate the distribution archives for your package.

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Upload to PyPi: Upload the recently created distribution archives to PyPi using Twine.

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Tag Your Release: Create a new git tag corresponding to this stable release version.

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Remove Old Development Versions: Optionally, you can clean up any old development versions from your distribution directory.

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Compatibility Considerations

When you transition to a stable release, especially if you are moving from an older version of Python (like Python 2.7), ensure that:

All dependencies used in your package are compatible with your current Python version.

Your code has been tested thoroughly across different environments.

Conclusion

Following these steps ensures that your Python package transitions smoothly from a development version to a stable release on PyPi. Proper versioning is not only a good practice but also crucial for maintaining compatibility and user trust.

Remember, consistency in packaging and versioning plays a significant role in the user experience and stability of the packages you distribute on PyPi.