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What bottlenecks were preventing NumPy from scaling on free-threaded Python? Christopher Trudeau is back on the show this week with another batch of PyCoder's Weekly articles and projects.
👉 Links from the show:
Christopher shares a recent article on the work done in NumPy to make multi-threaded workloads scale on the free-threaded build of CPython. It covers how removing the Global Interpreter Lock (GIL) is not enough on its own and how profiling revealed hidden bottlenecks in NumPy and CPython.
We also share other articles and projects from the Python community, including recent releases, a pair of announcements from PyPI, a tool for crawling your Django project, SIMD in pure Python, managing wildcard imports, a publication-quality Python Data Visualization library, and a tool to review your Django schema.
Topics:
- 00:00:00 -- Introduction
- 00:02:26 -- Python 3.15.0 candidate 1 is here!
- 00:02:47 -- Python 3.14.7 and 3.13.15 are now available!
- 00:03:00 -- Django 6.1 released
- 00:03:39 -- Planned Updates to the PyPI User Interface
- 00:04:13 -- PyPI Releases Now Reject New Files After 14 Days
- 00:05:07 -- PEP 837 – Extensible JSON serialization
- 00:06:20 -- PEP 842: Module Exports
- 00:07:51 -- Introducing `django-crawl`
- 00:12:02 -- SIMD in Pure Python
- 00:18:29 -- Managing Imports With Python's `__all__`
- 00:29:34 -- Spotlight: Modern Object-Oriented Python Book
- 00:30:53 -- Scaling NumPy on Free-Threaded Python
- 00:37:53 -- cnsplots: Python Data Visuali
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2026/08/14
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