ArviZ and Open Source (contributing & more)

Data Umbrella has two upcoming (online) webinars in November 2022 that will be of interest to PyMC users:
Time: 17:00 UTC

  1. Nov 15, 2022: Intro to Rust Programming
  2. Nov 29, 2022: Contributing to ArviZ and Open Source: Social and Technical Sides (Speaker is @OriolAbril, a PyMC and ArviZ maintainer)

If you are unable to attend, the webinars are recorded, you can subscribe to the DU YT to receive notifications of when the videos will be posted: Data Umbrella YouTube


video is up: Contributing to ArviZ and Open Source: Social and Technical Sides (Oriol Abril Pla)

ArviZ is a Python package for exploratory analysis of Bayesian models. It serves as a backend-agnostic tool for diagnosing and visualizing Bayesian inference.

In this webinar we go over both social and technical aspects we face when we contribute to ArviZ and to open source in general. We cover: finding an issue to work on, understanding how to work on it, to submitting the pull request and addressing the feedback received, and challenges faced. The talk will be focused on ArviZ, but it should also be useful to anyone interested in contributing to open source.

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Happy to share that timestamps have been added for the video Contributing to ArviZ and Open Source: Social and Technical Sides (presentation by @OriolAbril)


00:00 Data Umbrella introduction
05:07 Introduce the speaker, Oriol
06:20 Oriol begins talk
09:45 Why / Where / What / How … to contribute to open source?
11:45 Why contribute?
13:15 Where to contribute: documentation, event planning, triaging issues, Q&A forums, code)
16:02 What to contribute (specific to ArviZ): Issue browsing, finding/creation, direction
22:50 How to contribute to ArviZ
24:21 Example #1: of submitting a pull request (PR) to ArviZ
25:40 Example of a documentation fix
27:00 Set up: pull request step-by-step (git clone, install requirements)
36:50 A maintainer reviews the pull request
38:00 Update the changelog
43:00 Example #2: review a pull request to documentation submitted by a contributor
47:15 Q: Are there any plans to have a contributing session or open source sprint for ArviZ?
48:35 Q: How can people learn of ArviZ events?
49:03 Q: Do you need to be an ArviZ expert to contribute to the project?
49:38 Q: Do you have regular project meetings and are they open to the public?
50:42 Q: How many GitHub projects depend on ArviZ? (PyMC, Bambi, etc): Community — ArviZ 0.16.1 documentation
52:11 Q: How long does it take to get a pull request reviewed in ArviZ?
53:42 Q: Do you have any thoughts on imposter syndrome? Any helpful tips?
56:40 Q: What are good resources and tutorials to learn ArviZ? How did you learn ArviZ?
58:10 Q: What is the future of Arviz?