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tar-codec: a fast and secure tar parser for the Rust ecosystem
Astral's William Woodruff explains tar-codec, the new Rust tar parser uv uses for source distributions from 0.13: roughly twice as fast as astral-tokio-tar, built to reduce parser differentials and other security risks, with a long tour of the messy UStar, pax and GNU tar formats, its state-machine design, safe extraction and lessons learned.
26 min · 5,898 words
Aikido's Dania Durnas tracks how the Brotli decompression flaw CVE-2026-111497, first disclosed for Node.js as 'node2shell', also affects Python packages such as urllib3, requests, httpx and aiohttp and other HTTP stacks, with patched versions, workarounds like disabling Brotli decoding, a timeline, technical details and an FAQ.
11 min · 2,503 words
Miguel Grinberg runs his informal Fibonacci and bubble-sort benchmark on Python 3.15.0rc3 against 3.10 through 3.14, JIT and free-threaded builds, PyPy and other languages. His take: 3.15 is at best a minor speed improvement over 3.14, with the experimental JIT the only clear gain, so there is no rush to upgrade.
10 min · 2,289 words
Making np.searchsorted up to 25× Faster in NumPy 2.5
Alejandro Candioti explains how NumPy 2.5 makes np.searchsorted up to 25 times faster by batching many binary searches so their independent memory accesses overlap, starting from a vectorized Python prototype that beat NumPy 2.4's native code, and discusses cache-friendly layouts like Eytzinger as a future direction.
12 min · 2,861 words
From Any to Certainty: A Typechecking Journey
Aniket’s napari Island Dispatch post on an open-source typing journey: why the team migrated from mypy to Pyrefly, what improved, and how to choose a type checker for a large Python project.
9 min · 2,100 words
Eddie argues that Pandas forces data practitioners to adopt distributed compute infrastructure long before their data sizes justify it, and that DuckDB and Polars can fill the gap for workloads up to around 100 GB on a single machine. Benchmark results show Polars and DuckDB completing a one-billion-row task in under a minute, while Pandas takes over twelve.
1 min · 268 wordsagent-written