Documentation - 7/9

Heya fellows,

This is part 7 of the multi-part series “The Evolution of a Script”. The code of this post can be found on Github (see here).


  1. A Simple Script
  2. Sys Module
  3. Argparse Module
  4. Distribution via Installation Script
  5. Distribution via Setup File
  6. Testing and Continuous Integration
  7. Documentation
  8. Publishing at PyPI
  9. Publishing at Anaconda

In this post I wanna talk about a few dimensions of how to document a project in the python world. This makes it easier for the user or fellow developers to understand the project as a whole or separate parts of it. We will start at the lowest level and move toward higher abstraction levels.

Clean, Self-Descriptive Code

The lowest level of documentation is the code itself. The goal is to create readable and reusable software. This can be achieved by adhering to a few principles:

  • Meaningful, pronounceable and consistent naming of variables/functions/classes.
  • Single-responsibility principle: Each function fulfills only 1 purpose, same applies for classes/modules on a higher abstraction level.
  • Use static typing for bigger projects, enforce type checking with mypy. Dynamic languages like Python make object identification difficult.
  • Avoid reinventing the wheel and make good use of Python’s standard library. A good developer uses existing code strategically to his advantage.
  • Stick to a consistent style, I like Googles styleguide for Python.
  • Is the code elegant and pleasing? Listen to your intuition, your subconscious will point to the right things.

Docstrings, Comments and Git Commit Messages

>>> import math
>>> math.__doc__
'This module is always available.  It provides access to the'
'mathematical functions defined by the C standard.'

Docstrings are string literals which occur as first statement in a function, class, method or module definition. The docstrings become the __doc__ special attribute of that object. They’re used to explain the general purpose of an object whereas comments explain smaller parts of the code. Comments are used to explain non-obvious portions of the code. Docstrings are surrounded by """triple quotes""" and divided into one-line or multi-line docstrings whereas comments starts with # at the beginning.

def my_function():
    """This is a docstring"""
    return None

# docstring of the function

# displays documentation of the function

There are many docstring formats available. Most commonly used are NumPy, PyDoc and Googles docstring style. It’s a good idea to stick with a format which supports the Python documentation generator Sphinx. This generates a part of your documentation automatically from your docstrings. The last section of this post will show how to generate and host documentation with Sphinx and readthedocs.

A convenient VSCode extension is the Python Docstring Generator to facilitate the creation of docstrings.

def multiply(x: int, y: int) -> int:

        x (int): [description]
        y (int): [description]

        int: [description]
    return x * y

It detects parameters automatically and you just have to fill out the marked fields. It uses the Google style by default.

Another source of documentation is available if the project has a Git history. A good git history gives you information about the reason for each code change. You can supercharge the git capabilities of VSCode by GitLens and you will see each commit message next to the code it was committed to.

Furthermore, I like to use gitmoji to make the reading of my commit messages visually more appealing and force myself to commit only code changes which fall into one category of the gitmojis.


A nicely written README is the first document the visitor of a project will see. Here’s a screenshot of THELOUNGE, an IRC client for self-hosting:

What a beautiful README! What does it make so good?

  • It has a visually appealing and memorable logo which is compatible with Github’s light and dark theme by using a transparent .png picture.
  • A concise self-description.
  • Badges from which visualize the quality of the project.
  • Links to documentation.
  • An example, here screenshot of the application when running.
  • A list of contained features.

Often README files also contain instructions for the installation or a tutorial on how to use it. The READMEs file format is .md (markdown) or .rst (reStructuredText). Sometimes it’s also a good idea to provide examples to the user for certain, common use cases. Projects with a data scientific background tend to use jupyter notebooks (.ipynb) to demonstrate the capabilities of the project. Other projects use plain python files for demonstration purposes.

Sphinx Documentation

For smaller projects the can be sufficient whereas projects like libraries benefit from a more extensive hosted technical documentation. I will show you here how simple it is to create your own freely hosted documentation with Sphinx, readthedocs and Github Pages!

OK, let’s create some documentation! Sphinx is the tool that will help us to simplify this process.

$ pip install sphinx

$ mkdir docs
$ cd docs

Sphinx will ask us a couple of questions:

$ sphinx-quickstart

> Separate source and build directories (y/n) [n]: y
> Project name: tinyHTTPie
> Author name(s): Niklas Tiede
> Project release []: 0.1.0
> Project language [en]: enter

To create the documentation we have to use the make html command within the docs directory. This creates the HTML of our documentation.

$ cd ..
$ make html

If we open the index.html file with the browser via live server we can see how it will look like. But its appearance is pretty puristic yet. Therefore we use the popular RTD theme to give it a professional look. We install the theme…

$ pip install sphinx_rtd_theme

…and customize the file. We add the following lines:

import sphinx_rtd_theme

extensions = ["sphinx_rtd_theme",]
pygments_style = "sphinx"
version = '0.1.0'
html_theme = 'sphinx_rtd_theme'

And render again.

$ make html

Now it looks way better! Ok, next we wanna write some more content. The documentation should be written in the reStructuredText (.rst) syntax. Here’s a nice cheat sheet. A .rst previewer in your IDE will speed up things. I’ve added some documentation about tinyHTTPie, see index.rst, install.rst and tutorial.rst. The last step is to publish our documentation. We have to register at and let it hook our repository.

Voilà! A nice documentation was created! I hope you see how easy it is to setup such a good-looking documentation and that documentation has so many interesting aspects we’re typically not aware of! 😃