Distributing Packages#



  • How can I get my project out there?


  • Discuss community strategies

This lesson is under development

This lesson is in a preliminary stage and is not as polished as the rest of the lessons. We expect to add more content to and update this lesson in the future!

This lesson will discuss how to distribute packages through the Python Package Index (PyPI) and conda.


Register a test account on test.pypi.org.

Create an access token, and don’t lose it! (I keep a copy of the text for my token in my password manager.)

The access token will be a string that begins with pypi- followed by a sequence of base64 encoded bytes that we will refer to as “YOURTOKEN” below.

Create $HOME/.pypirc. It should look something like the following, substituting your access token in the password field.

  username = __token__
  password = YOURTOKEN

You will also eventually need to get an account on the main pypi.org, but you can do that later.

Install some additional packages to help build and upload your distribution.

pip install build twine

Preparing a release#

Release notes#

Make sure your README file and documentation are up to date. Check the project description in your project’s metadata, too.

Consider whether there is some announcement text that you would want to include in a text file or in a blurb in your GitHub Releases tab. This can be a good place to publish release notes.

Tagging the release#

git status

Make sure that your changes are checked in and that you don’t have extra files sitting around.

Tag the latest commit with a version identifier. Let’s get ready to publish molecool 1.0.0a1, the first alpha release of our package.

git tag 1.0.0a1

Build the distribution archive(s) for the packaging system you are using (see below): PyPI or Conda.

Synchonizing Tags

Tags created in your local repository are not automatically shared when you git push a branch. You can push tags the same way you push branches, or you can create the tag directly on GitHub. With the GitHub interface, you can associate tags with Releases to provide a place to publish release notes and automatically generate links to archive files of your repository at the tagged commits.

Tags created through the GitHub interface (or pushed from a different location) will be available locally the next time you git fetch.

Keep in mind that the GitHub repository page is one of the main entry points for new users of your package. Your project looks healthier and better maintained with a nice, well-documented history of releases.

Tags and GitHub releases do not automatically make your package easier to find or install, but they can help prepare the source of version information or the source archive as you prepare the distribution of your package.

Packages and distributions#

A “distribution” is a collection of files including one (or more) Python packages that have been made portable and ready to share.

The cookiecutter template provided several additional files and metadata to help you get your package ready for distribution, such as the LICENSE file, MANIFEST.in, setup.cfg, and pyproject.toml.

Some of these files are essential details to make your distribution portable or discoverable. Others are specific to the build system (e.g. setuptools or conda).

The build system is responsible for assembling your files into a distribution archive that can be easily placed into anyone’s site-packages directory. It also makes sure that various package metadata is assembled so that a package installer like pip can evaluate software dependencies so that your package looks good when it is shared, such as on pypi.org.

Distributing packages for pip install#

Building the distribution#

We previously mentioned that pip install . invokes setuptools to build the distribution archive for our package before installing the package in our environment. What does this mean? More importantly, what does it have to do with letting other people do pip install molecool and get my package automatically downloaded from “the cloud”?

Setuptools is not the only package for configuring and building Python distribution archives, but it is what we will tell pip to use for this project. When pip install is run on package sources, it notices the pyproject.toml file (which marks a folder as containing buildable packages), launches the configured build system, and then installs the resulting “wheel” (distribution archive). Note that, if we only want to prepare a distribution for sharing, we can just use the build module.

pip install build
python -m build .

Note the version string embedded in the distribution archive name. versioningit (configured in pyproject.toml) also participated in the build process. versioningit generated a _version.py file with a version string derived from your most recent git tag. We will not add this file to our git revision control, but it will be packaged in our distribution. versioningit will regenerate this file as necessary and appropriate.

Note that the untagged post-release version strings (using our formatting rules in pyproject.toml) do not satisfy PEP 440 and will be rejected if we try to upload to pypi. This is probably a good thing; it will help keep us from accidentally publishing releases before they are ready, or messing up our versioning scheme by forgetting a semantic versioning tag.

Goodbye to setup.py?

Historically packages built with setuptools used a setup.py script as the entry point to the setuptools build system. setup.py is specific to setuptools and the distutils package it is built on. Many tools for helping to build and test packages came to rely on setup.py, which made them incompatible with non-setuptools build systems.

In an ongoing effort at generalization, the Python community is now encouraging package authors to use a pyproject.toml file to direct the build system. distutils is scheduled for retirement with Python 3.12. In preparation, setuptools no longer requires distutils or setup.py, and can be configured entirely with pyproject.toml.

Building and uploading to PyPI#

Read through https://packaging.python.org/en/latest/tutorials/packaging-projects/ for a build-system-agnostic tutorial on

  • packaging Python projects for distribution

  • publishing packages to pypi.org for automatic download with pip install

By the end of the tutorial, you will understand how to get an account on pypi.org, build a distribution archive with python -m build, and use twine to upload your package.

The tutorial should go quickly because, as you will note, most of the configuration it describes has already been pre-configured by the CookieCutter. Caution: strongly consider creating an account on test.pypi.org and uploading an initial “alpha” or “beta” release of your package to see how it looks and to do test installations.

Note that pypi.org enforces the universal uniqueness of packages and versions. Once you have uploaded molecool version 1.0.0, you cannot replace it; you can only upload additional versions. (You can “yank” a release, but this only marks the package as “yanked”, indicating it should not be used. It is still out there.)

  • Be tidy with your official releases.

  • Be conservative with alpha and beta pre-releases.

  • Test the publication of new releases on test.pypi.org before pypi.org to avoid cluttering your versioning scheme and your release history on pypi.

For more in-depth documentation on packaging for PyPI specifically with setuptools, see https://packaging.python.org/en/latest/guides/distributing-packages-using-setuptools/

Distributing packages for conda install#

conda has a completely different approach to building and distributing packages, and is not yet PEP-517 compliant. (It does not use pyproject.toml.) For fundamental information about using conda build (such as preparing your build details and metadata with meta.yml), see conda-build docs. For documentation on publishing packages through the conda-forge channel, refer to the channel’s contribution docs.

Preparing for future releases#

Consider adding or updating a CHANGELOG.

Version specifiers#

Python has a strict syntax for version strings.

  • Refer to PEP 440 for constraints on Python version specifiers.

  • Know how to mark versions for pre-release (or post-release) and consider tagging “alpha” and “beta” releases.

Versioning semantics#

Refer to Semantic Versioning for guidelines on how to use versions meaningfully.

Once your package has outside users, consider how your changes affect your users. Avoid surprising your users by effectively supporting the package manager heuristics (e.g. use prerelease version semantics to make a version only available when pip install --pre is used). Make sure your version increments reflect the compatibility changes in the distributions you release.

Making these considerations may lead you to moderate the changes you make. For instance, instead of completely changing an interface, consider introducing a new function or module with a different name. Or provide backwards-compatible support for the old interfaces.

Exercises - Versioning semantics#

Answer the following questions about how you should change your package version in the following scenarios.

Case 1

This is a completely incompatible change to the interface of the package.

Case 2

A backwards compatible update, or a new feature that does not conflict with existing features.

Case 3

An internal change or bug fix that you don’t expect users to notice (but who knows? There could be a bug…)?

Case 4

Is this a change to documentation or something that does not affect the code at all, with no implications for compatibility, but you just need some sort of version bump so that people get your edit the next time the package is downloaded?

Key Points

  • Add package metadata and build a distribution to share a package through community platforms.

  • Adopt common conventions and establish clear expectations for compatibility versus breaking changes so that prospective users of your package have confidence in its stability and maturity.

  • Multiple packaging systems exist and require separate preparation.