Awesome Python

Posted : admin On 1/23/2022

If you are like me, every once in a while you write a useful python utility and want to share it with your colleagues. The best way to do this is to make a package: it easy to install and saves from copy-pasting.

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If you are like me, you might be thinking that creating packages is a real headache. Well, that’s not the case anymore. And I am going to prove it with this step-by-step guide. Just three main steps (and a bunch of optional ones) accompanied by few GitHub links. See for yourself:

1. Stub

We will create podsearch - a utility that searches for podcasts in iTunes. Let’s create a directory and a virtual environment:

Define a minimal package structure:

2. Test package

Creating a package in Python used to be a troublesome task. Fortunately, nowadays there is a great little flit utility which simplifies everything. Let’s install it:

And create package description:


Flit has created pyproject.toml - the project metadata file. It already has everything you need to publish the package to the public repository - PyPI.

Sign up for TestPyPi (test repository) and PyPI (the main one). They are completely independent, so you will need two accounts.

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Setup access to repositories in the ~/.pypirc:

And publish the package to the test repository:

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Done! The package is available on TestPyPi.

3. Public package

Let’s improve the code so that it actually searches for podcasts:

And publish to the main repository - PyPI. Perform this step only after your package has working code that does something useful. Do not publish non-working packages and stubs.

Done! Time to share it with colleagues.

To make the package a pleasure to use, I recommend that you follow a few more steps.

A. Readme and changelog

No one likes to write documentation. But without docs, it is unlikely that people will want to install your package, so let’s add and

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Add readme to the pyproject.toml, so that PyPI shows it on the package page:

Also specify the minimal supported Python version:

Update the version in and publish the package via flit publish:

Mmm, nice.

B. Linters and tests

Let’s take care of formatting (black), test coverage (coverage), code quality (flake8, pylint, mccabe), and static analysis (mypy). We will run everything through tox.

Create tox configuration in tox.ini:

And run all the checks:

Lovely! The linters are happy, the tests passed, the coverage is 100%.

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C. Cloud build

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Every solid open-source project runs cloud tests after each commit, so we will too. A nice side effect is having beautiful badges in the readme ツ

Let’s build the project with GitHub Actions, check test coverage with Codecov and code quality with Code Climate.

You will have to sign up for Codecov and Code Climate (both support GitHub login) and enable package repository in the settings.

After that, add the GitHub Actions build config to .github/workflows/build.yml:

GitHub runs tests via tox - just as we did. tox-gh-actions package and USING_COVERAGE settings ensure that tox uses the same Python version as GitHub Actions themself, as required by strategy.matrix (I learned this clever trick from Hynek Schlawak).

The last step sends test coverage to Codecov. Code Climate does not need a separate step - it spots repository changes automatically.

Now commit, push, and enjoy the result in a minute. And let everyone enjoy as well - add badges to

Aren’t they cute?

D. Task automation

tox is fine, but not very handy for development. It’s faster to run individual commands like pylint, coverage etc. But they are quite verbose, so we’ll automate the boring stuff.

Let’s create short aliases for frequent actions with Makefile:

Here are our tasks:

To make the code more DRY, replace raw build.yml steps with make calls:

E. Cloud publish

GitHub is quite capable of running flit publish for us. Let’s create a separate workflow:

PYPI_USERNAME and PYPI_PASSWORD are set in repository settings (Settings > Secrets > New repository secret). Use your PyPi username and password, or even better - an API token.

Now GitHub will automatically publish the package as soon as you create a new release. Sweet!

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Your perfect package is ready! It has everything one could dream of: clean code, clear documentation, tests, and cloud builds. Time to tell your colleagues and friends.

These settings will make your package awesome:

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Thanks for reading! Follow @ohmypy on Twitter to keep up with new posts 🚀