Key Challenges In the PyData Ecosystem and How we Can All Make a Difference
summary
PyData claims 25–40 million users and traces deep technical debt: core libraries still rely on Fortran 77, the NumPy-based stack remains largely single-threaded, and packaging plus supply-chain security keep breaking installs. Funding is fragmented — GitHub Sponsors and one-off donations arrive but rarely cover sustained maintainer time — and community work (mentorship, triage, docs) is invisible unless credited. Expect concrete proposals for measurable funding, leadership pipelines, and artifact-level attribution.
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chapters (31)
- 0:00Introduction
- 0:43Our core mission
- 1:35Three main topics
- 2:45Building our shared vocabulary
- 3:14Open Source Definition
- 3:54What does Open Source mean to you
- 6:39What does PyData mean to you
- 7:07What does Open Source and PyData mean to you
- 7:58What does Ecosystem mean
- 10:11Its the number one tool set for scientific computing
- 11:50There are many
- 17:37We have to rethink
- 21:36Associate Technical System
- 23:43Building for the Upstream
- 26:18Community Safety
- 29:32Diversity
- 30:31Leadership
- 36:01What do we owe each other
- 36:47Longevity to open source
- 38:37Count thought is universal
- 40:14Make all labor visible
- 41:06Props
- 42:51Processes
- 43:19Infrastructure
- 44:09Open Source
- 46:38How can you contribute
- 48:38SciFi
- 49:05Acumenopolis
- 50:26Android Dream of Electrics
- 51:40Conclusion
- 52:35Thank you
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