Your event cheat sheet#
Welcome to this PyMC & Data Umbrella Open Source Working Session to help you get started contributing to PyMC.
PyMC is already a mature package with multiple dedicated teams within its core contributor base. PyMC welcomes many types of contributions and we wanted to host an event where this “functional” diversity was one of the pillars.
We also wanted to allow people from many different backgrounds to be able to participate in the event, so we eventually decided not to do a session. Instead, we hosted a whole series of webinars and multiple Open Source Working Sessions!
This is very ambitious (though hopefully not too much) and can be confusing so we have written this document to help you navigate this series, and attend the content that will help you reach your goal.
This page is structured as a decision tree. We have written questions and provide advise based on your answers.
Already comfortable with Bayesian statistics but not interested in Python nor PyMC?
Jump straight to the last webinar about contributing to documentation. We have extensive statistical documentation to which you can contribute to! For example examples with detailed explanation along the code, a glossary of statistical terms, or descriptions of distributions and their parametrizations.
The bulk of our documentation is written in markdown and Jupyter notebooks, so most of the skills you’ll use: git/github, stats, technical writing and markdown transfer to any other stats related open source project I understand, jump
Do you know what Bayesian statistics is? What about PPLs? And PyMC?#
If you know about this (no need to be an expert) move to the next question, otherwise we recommend you open the dropdown and watch the embedded video.
About Bayesian statistics and PyMC
This talk by PyMC core contributor Oriol Abril Pla covers the basics of the Bayesian paradigm, probabilistic programming and PyMC.
It is divided in two parts. The first half is explanatory of the concepts above. The second half goes over some PyMC examples from the community which you can skip. They use version 3 of PyMC but the event is focused on PyMC version 4. One of the webinars of the series is about using PyMC which goes in much more detail.
Are you comfortable working with Python and NumPy arrays?#
In case you aren’t yet, we recommend the first webinar of the series: Introduction to Array Operations in Python.
Are you familiar with PyMC?#
In case you aren’t yet, we recommend the second webinar of the series: Introduction to Probabilistic Programming with PyMC.
STOP: Any questions about PyMC so far? We encourage you to ask them on PyMC Discourse the whole PyMC community (core contributors included) will do their best to help you out.
Interested in contributing to code, to documentation or a bit of both?#
Before anything, thanks
Now you should have all the context necessary to start contributing. Let’s go watch the webinars preparing you to contribute.
From here on, there will be steps common to everyone and steps specific to docs or code contributions. Specific steps are separated in two columns, left for docs specific, right for code specific.
Have you already contributed to PyMC?#
If you haven’t, we recommend reading this tutorial: Your first contribution to PyMC. It covers all the steps from zero to submitting a pull request improving a docstring. We believe this will help you become familiar with Git, GitHub, and the whole contributing process quickly so you can then focus on the content of your contributions, not struggle with the tooling.