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- Transcript: https://github.com/data-umbrella/event-transcripts/blob/main/2022/70-oriol-arviz.md
- Meetup Event: https://www.meetup.com/data-umbrella/events/289308615/
- Video: https://youtu.be/457ZTes4xOI
- GitHub repo:
- Transcriber: ? [needs a transcriber]
- Slides: https://oriolabril.github.io/contributing_to_arviz/
- Example pull request: arviz-devs/arviz#2176
- ArviZ docs: https://arviz-devs.github.io/arviz/#
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.
Oriol is an ArviZ and PyMC team member who dedicates a large part of his work on "non-technical" work such as community building or mentoring new contributors. He started contributing to open source a bit over 3 years ago and is currently working as a freelancer around open source and bayesian statistics.
- Website: https://oriolabrilpla.cat/en/
- Twitter: https://twitter.com/OriolAbril/
- LinkedIn: https://www.linkedin.com/in/oriol-abril-pla-1b9123180/
## Timestamps
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): https://python.arviz.org/en/stable/community.html#the-bayesian-python-ecosystem
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?
#bayesian #stan #opensource #pymc #stan #dataviz