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Bump the setup-deps group in /setup with 4 updates - #41

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Aug 19, 2026
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Bump the setup-deps group in /setup with 4 updates#41
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Updates the requirements on numpy, httpx2, bitsandbytes and pyarrow to permit the latest version.
Updates numpy to 2.4.6

Release notes

Sourced from numpy's releases.

v2.4.6 (May 18, 2026)

NumPy 2.4.6 Release Notes

NumPy 2.4.6 is a quick release that fixes a regression discovered in the 2.4.5 release.

This release supports Python versions 3.11-3.14

Contributors

A total of 4 people contributed to this release. People with a "+" by their names contributed a patch for the first time.

  • !EarlMilktea
  • Charles Harris
  • Sebastian Berg
  • Warren Weckesser

Pull requests merged

A total of 4 pull requests were merged for this release.

  • #31444: MAINT: Prepare 2.4.x for further development
  • #31453: BUG: Fix regression in arr.conj()
  • #31459: BUG: np.linalg.svd(..., hermitian=True) returns non-unitary...
  • #31460: BUG: Don't call INCREF/DECREF on descr in NpyStringAcquireAllocator...
Changelog

Sourced from numpy's changelog.

This is a walkthrough of the NumPy 2.4.0 release on Linux, which will be the first feature release using the numpy/numpy-release <https://github.com/numpy/numpy-release>__ repository.

The commands can be copied into the command line, but be sure to replace 2.4.0 with the correct version. This should be read together with the :ref:general release guide <prepare_release>.

Facility preparation

Before beginning to make a release, use the requirements/*_requirements.txt files to ensure that you have the needed software. Most software can be installed with pip, but some will require apt-get, dnf, or whatever your system uses for software. You will also need a GitHub personal access token (PAT) to push the documentation. There are a few ways to streamline things:

  • Git can be set up to use a keyring to store your GitHub personal access token. Search online for the details.

Prior to release

Add/drop Python versions

When adding or dropping Python versions, multiple config and CI files need to be edited in addition to changing the minimum version in pyproject.toml. Make these changes in an ordinary PR against main and backport if necessary. We currently release wheels for new Python versions after the first Python RC once manylinux and cibuildwheel support that new Python version.

Backport pull requests

Changes that have been marked for this release must be backported to the maintenance/2.4.x branch.

Update 2.4.0 milestones

Look at the issues/prs with 2.4.0 milestones and either push them off to a later version, or maybe remove the milestone. You may need to add a milestone.

Check the numpy-release repo

... (truncated)

Commits
  • b832a09 Merge pull request #31462 from charris/prepare-2.4.6
  • 57cc147 REL: Prepare for the NumPy 2.4.6 release
  • 0c72b0b Merge pull request #31459 from charris/backport-31347
  • 9778d26 BUG: core: Don't call INCREF/DECREF on descr in NpyStringAcquireAllocator. (#...
  • e0e3876 BUG: core: Don't call INCREF/DECREF on descr in NpyStringAcquireAllocator. (#...
  • d1bffeb BUG: np.linalg.svd(..., hermitian=True) returns non-unitary vh (#31347)
  • 8d8d7e5 Merge pull request #31453 from seberg/issue-31452
  • bddaab7 BUG: Fix regression in arr.conj()
  • 37a1ecc Merge pull request #31444 from charris/begin-2.4.6
  • 3c0e043 MAINT: Prepare 2.4.x for further development
  • Additional commits viewable in compare view

Updates httpx2 to 2.10.0

Release notes

Sourced from httpx2's releases.

v2.10.0

Highlights

🚀 Performance and memory improvements

  • Sending large HTTP/2 request bodies no longer copies the body quadratically - sending a 256 MiB body went from ~36s to under 0.1s (pydantic/httpx2#1127).
  • SSE parsing is up to 35x faster on highly fragmented streams (pydantic/httpx2#1117).
  • Cookie extraction is now skipped for responses without a Set-Cookie header, making typical requests roughly 8% faster (pydantic/httpx2#1107).

🕸️ WebAssembly / Emscripten support

httpx2 now runs on Pyodide / Emscripten, using a JavaScript fetch-based transport defined in httpx2-jsfetch (pydantic/httpx2#1119, pydantic/httpx2#1114). Thanks @​hoodmane!

httpx2

Added

Changed

Fixed

httpcore2

Added

Changed

Fixed

🙏 New Contributors

... (truncated)

Changelog

Sourced from httpx2's changelog.

2.10.0 (August 9th, 2026)

Added

  • Add support for running on WebAssembly / Emscripten via Pyodide, using a JavaScript fetch-based transport defined in httpx2-jsfetch. (#1119)
  • Add max_event_size to cap SSE event buffering. (#1071)
  • Add RFC 9110 status code constants. (#1069)
  • Add support for Python 3.15. (#1090)

Changed

  • Improve SSE chunk buffering performance. (#1117)
  • Skip cookie extraction for responses without Set-Cookie headers. (#1107)
  • Return str | None instead of Any from Headers.get. (#1121)

Fixed

  • Enforce the WebSocket max message size across fragmented messages. (#1085)
  • Ignore unsolicited and duplicate WebSocket Pong frames. (#1122)

2.9.1 (July 24th, 2026)

Fixed

  • Alias httpcore imports to httpcore2 in alias_httpx(). (#1082)

2.9.0 (July 23rd, 2026)

Added

  • Add alias_httpx(), letting applications make import httpx resolve to httpx2 process-wide. (#1077)

2.8.0 (July 23rd, 2026)

No changes since 2.7.0. Version bumped to stay in lockstep with httpcore2.

2.7.0 (July 14th, 2026)

Changed

  • Update the vendored httpx-ws to upstream v0.9.0. (#1067)

2.6.0 (July 14th, 2026)

Added

  • Add native WebSocket support by vendoring httpx-ws, installable with httpx2[ws]. (#1042)
  • Add support for the QUERY HTTP method via httpx2.query() and client.query(). (#1055)

... (truncated)

Commits
  • a966320 Version 2.10.0 (#1129)
  • dee1d1a Return str | None instead of Any from Headers.get (#1121)
  • dec24ad Use httpx2-jsfetch on Emscripten (#1119)
  • 454b8b2 Ignore unsolicited and duplicate Pong frames (#1122)
  • cbfc0e0 Improve SSE chunk buffering performance (#1117)
  • ad141d8 Refactor SSE parser coordination (#1118)
  • e0b0124 Make _client depend on the _transports package instead of its submodules ...
  • e52f963 Skip dependencies not needed on Emscripten (#1114)
  • 5d9eedc Add max_event_size to cap SSE event buffering (#1071)
  • 55fad71 Bump the python-packages group across 1 directory with 15 updates (#1112)
  • Additional commits viewable in compare view

Updates bitsandbytes to 0.50.1

Release notes

Sourced from bitsandbytes's releases.

0.50.1: RTX Spark Support

This release adds support for additional hardware platforms and improves performance on RTX Spark / DGX Spark.

Highlights

  • Support added for NVIDIA RTX Spark products running Windows on ARM64 (#2038, #2037, #2032)
  • Improved 4bit GEMM dispatch heuristics for NVIDIA GB10 (#2030)
  • Support for AMD CDNA5 hardware (e.g. MI455X)

What's Changed

New Contributors

Full Changelog: bitsandbytes-foundation/bitsandbytes@0.50.0...0.50.1

Changelog

Sourced from bitsandbytes's changelog.

v0.45.1

Improvements:

  • Compatibility for triton>=3.2.0
  • Moved package configuration to pyproject.toml
  • Build system: initial support for NVIDIA Blackwell B100 GPUs, RTX 50 Blackwell series GPUs and Jetson Thor Blackwell.
    • Note: Binaries built for these platforms are not included in this release. They will be included in future releases upon the availability of the upcoming CUDA Toolkit 12.7 and 12.8.

Bug Fixes:

  • Packaging: wheels will no longer include unit tests. (#1478)

Dependencies:

  • Sets the minimum PyTorch version to 2.0.0.

0.45.0

This is a significant release, bringing support for LLM.int8() to NVIDIA Hopper GPUs such as the H100.

As part of the compatibility enhancements, we've rebuilt much of the LLM.int8() code in order to simplify for future compatibility and maintenance. We no longer use the col32 or architecture-specific tensor layout formats while maintaining backwards compatibility. We additionally bring performance improvements targeted for inference scenarios.

Performance Improvements

This release includes broad performance improvements for a wide variety of inference scenarios. See this X thread for a detailed explanation.

Breaking Changes

🤗PEFT users wishing to merge adapters with 8-bit weights will need to upgrade to peft>=0.14.0.

Packaging Improvements

  • The size of our wheel has been reduced by ~43.5% from 122.4 MB to 69.1 MB! This results in an on-disk size decrease from ~396MB to ~224MB.
  • Binaries built with CUDA Toolkit 12.6.2 are now included in the PyPI distribution.
  • The CUDA 12.5.0 build has been updated to CUDA Toolkit 12.5.1.

Deprecations

  • A number of public API functions have been marked for deprecation and will emit FutureWarning when used. These functions will become unavailable in future releases. This should have minimal impact on most end-users.
  • The k-bit quantization features are deprecated in favor of blockwise quantization. For all optimizers, using block_wise=False is not recommended and support will be removed in a future release.
  • As part of the refactoring process, we've implemented many new 8bit operations. These operations no longer use specialized data layouts.

Full Changelog

0.44.1

Bug fixes:

... (truncated)

Commits
  • 37d2a93 Release 0.50.1
  • 0b3a226 Add sm121 (GB10) tier to the 4-bit GEMM dispatch heuristic
  • 557bfc2 build: Add Windows ARM64 build with CUDA 13.4 for RTX Spark (#2038)
  • 930274c Merge pull request #2032 from mfuntowicz/fix/cuda_121_win
  • 0330f40 Merge branch 'main' into fix/cuda_121_win
  • d799cfd Gate /Zc:preprocessor to cl.exe only
  • 915aa03 Merge pull request #2037 from mfuntowicz/docs/rtx-spark-install-guidelines
  • cf86065 docs: add installation instructions for NVIDIA Spark (ARM64) devices
  • b459659 fix: missing compilation flag on recent msvc version
  • a2b90e6 Fix truncated FP4 constant in Triton dequantize_fp4_tree (#2026)
  • Additional commits viewable in compare view

Updates pyarrow to 25.0.1

Release notes

Sourced from pyarrow's releases.

Apache Arrow 25.0.1

Release Notes URL: https://arrow.apache.org/release/25.0.1.html

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@dependabot
Bump the setup-deps group in /setup with 4 updates
416f705 
Updates the requirements on [numpy](https://github.com/numpy/numpy), [httpx2](https://github.com/pydantic/httpx2), [bitsandbytes](https://github.com/bitsandbytes-foundation/bitsandbytes) and [pyarrow](https://github.com/apache/arrow) to permit the latest version.

Updates `numpy` to 2.4.6
- [Release notes](https://github.com/numpy/numpy/releases)
- [Changelog](https://github.com/numpy/numpy/blob/main/doc/RELEASE_WALKTHROUGH.rst)
- [Commits](numpy/numpy@v1.26.4...v2.4.6)

Updates `httpx2` to 2.10.0
- [Release notes](https://github.com/pydantic/httpx2/releases)
- [Changelog](https://github.com/pydantic/httpx2/blob/main/src/httpx2/CHANGELOG.md)
- [Commits](pydantic/httpx2@v2.9.1...v2.10.0)

Updates `bitsandbytes` to 0.50.1
- [Release notes](https://github.com/bitsandbytes-foundation/bitsandbytes/releases)
- [Changelog](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/main/CHANGELOG.md)
- [Commits](bitsandbytes-foundation/bitsandbytes@0.50.0...0.50.1)

Updates `pyarrow` to 25.0.1
- [Release notes](https://github.com/apache/arrow/releases)
- [Commits](apache/arrow@apache-arrow-25.0.0...apache-arrow-25.0.1)

---
updated-dependencies:
- dependency-name: numpy
  dependency-version: 2.4.6
  dependency-type: direct:production
  dependency-group: setup-deps
- dependency-name: httpx2
  dependency-version: 2.10.0
  dependency-type: direct:production
  dependency-group: setup-deps
- dependency-name: bitsandbytes
  dependency-version: 0.50.1
  dependency-type: direct:production
  dependency-group: setup-deps
- dependency-name: pyarrow
  dependency-version: 25.0.1
  dependency-type: direct:production
  dependency-group: setup-deps
...

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot Bot added dependencies Pull requests that update a dependency file python Pull requests that update python code labels Aug 19, 2026
@K4TEL
K4TEL merged commit c884bee into test Aug 19, 2026
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@dependabot
dependabot Bot deleted the dependabot/pip/setup/test/setup-deps-ec2b910909 branch August 19, 2026 09:39
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