Beginning Open Source Programming

This guide is primarily focused on beginning contributions to Python open source projects because that is where I have experience.


Github is one of the most common places to find open source repositories and one of the easiest ways to contribute. As such this is the first step to learn towards open source programming contributions. Below is a series of two videos, the first describes how to use git the tool and the second describes how to interact with Github the site.

  1. Github YouTube Tutorial
  2. Github YouTube Tutorial 2

Obtain Git

If your machine does not yet have git, it is easy to acquire. On windows follow this guide. On mac or linux, if you try to use a git command before git is installed, your system will suggest a command that you can use to acquire git.

Git SSH Keys

In order to be able to push and pull to your repositories without having to enter your password every time you need to set up ssh keys with github. Github has a useful guide for setting up ssh keys. Once you have ssh set up make sure you use the ssh link for your git clone statement.

Find a project to which you'd like to contribute

Choose a topic you like or something that is meaningful to you. You'll be more likely to stick with it and you'll learn more. Once you find a project clone it to your local machine and use the python develop. By using the develop option instead of install your python instance will use the git repo version of the code rather than copying it internally. This means as you work in the git repository you do not have to reinstall the code to see the changes take effect.

Note: If develop is not working it may be that is using distutils instead of setuptools. You can try just changing them in the import statement to get it to work.

First Contributions

When you find your project the first steps will be to read through the documentation to familiarize yourself with their contribution process, any standards they use and generally how the code works. I would recommend writing down any and all spelling and gramatical errors you find while reading. When you finish reading you can go in and create a pull request to fix all of the errors you have found. This is a great way to make a first contribution, meet your fellow contributors and get your feet wet with the contribution process.

Common Open Source Tools


Python Enhancement Proposal 8 (PEP8) is a common style guide across open source projects as it is the one endorsed by Python Software Foundation itself. If the project you've found does not use a style guide it would be a good idea to bring this one to their attention. Otherwise use the exact same style guide that the project uses.


TravisCI is a tool that runs a project's tests with every commit in a PR. This allows members to know that the new code will not break functionality without having to go through the process of acquiring the new code and running the tests manually.


Sphinx is a documentation tool commonly used by Python projects. A big reason for this is that is can pull documentation directly from the code itself. This allows projects to only have to maintain the code in the docstrings of the classes/functions and still have good documentation.

The standard formatting for sphinx can lead to docstrings that are not very readable unrendered and so some extensions have been developed to allow readable docstrings. The two common extensions are numpydoc and Napoleon. Napoleon is included with sphinx and numpydoc needs to be installed separately. To get sphinx to use them you need to add "numpydoc" or "sphinx.ext.napoleon" to the extensions list in your file.


ReadTheDocs is a site that will host open source projects documentation for free. Also important is that ReadTheDocs will integrate with sphinx and automatically update the documentation every time a pull request is merged.

Test Code (Python)

This test code guide goes over many different tools that can be used in python to facilitate test code writing.

Airspeed Velocity

Airspeed Velocity is a tool that is used to write benchmark tests. If a project is dealing with optimization of their code this is a useful tool to turn to.