build(deps): bump the pip group across 3 directories with 19 updates

[dependabot]

Updates the requirements on datasets, setuptools, setuptools-scm, pandas, huggingface-hub, transformers, trl, data-designer-engine, pytest, pytest-rerunfailures, scikit-learn, torchao, chardet, faker, fsspec, python-json-logger, sqlfluff, data-designer and data-designer-config to permit the latest version.
Updates datasets to 4.5.0

Release notes

Sourced from datasets's releases.

4.5.0

Dataset Features

• Add lance format support by @​eddyxu in huggingface/datasets#7913

  • Support for both Lance dataset (including metadata / manifests) and standalone .lance files
  • e.g. with lance-format/fineweb-edu

  from datasets import load_dataset
  ds = load_dataset("lance-format/fineweb-edu", streaming=True)
  for example in ds["train"]:
  ...

What's Changed

• Raise early for invalid revision in load_dataset by @​Scott-Simmons in huggingface/datasets#7929
• fix low but large example indexerror by @​CloseChoice in huggingface/datasets#7912
• Fix method to retrieve attributes from file object by @​lhoestq in huggingface/datasets#7938
• add _OverridableIOWrapper by @​lhoestq in huggingface/datasets#7942
• Add _generate_shards by @​lhoestq in huggingface/datasets#7943

New Contributors

• @​eddyxu made their first contribution in huggingface/datasets#7913
• @​Scott-Simmons made their first contribution in huggingface/datasets#7929

Full Changelog: huggingface/datasets@4.4.2...4.5.0

Commits

• 69d773a Release: 4.5.0 (#7944)
• dc98f97 Add _generate_shards (#7943)
• 38d28bf add _OverridableIOWrapper (#7942)
• 7431153 Fix method to retrieve attributes from file object (#7938)
• 6a1bc35 fix low but large example indexerror (#7912)
• 7bdf840 Raise early for invalid revision in load_dataset (#7929)
• 06b6e02 Add lance format support (#7913)
• 0feb65d set dev version (#7908)
• 37d9615 release: 4.4.2 (#7907)
• 58dda42 Don't save original_shard_lengths by default for backward compat (#7906)
• Additional commits viewable in compare view

Updates setuptools from 80.9.0 to 82.0.1

Changelog

Sourced from setuptools's changelog.

v82.0.1

Bugfixes

• Fix the loading of launcher manifest.xml file. (#5047)
• Replaced deprecated json.__version__ with fixture in tests. (#5186)

Improved Documentation

• Add advice about how to improve predictability when installing sdists. (#5168)

Misc

• #4941, #5157, #5169, #5175

v82.0.0

Deprecations and Removals

• pkg_resources has been removed from Setuptools. Most common uses of pkg_resources have been superseded by the importlib.resources <https://docs.python.org/3/library/importlib.resources.html>_ and importlib.metadata <https://docs.python.org/3/library/importlib.metadata.html>_ projects. Projects and environments relying on pkg_resources for namespace packages or other behavior should depend on older versions of setuptools. (#3085)

v81.0.0

Deprecations and Removals

• Removed support for the --dry-run parameter to setup.py. This one feature by its nature threads through lots of core and ancillary functionality, adding complexity and friction. Removal of this parameter will help decouple the compiler functionality from distutils and thus the eventual full integration of distutils. These changes do affect some class and function signatures, so any derivative functionality may require some compatibility shims to support their expected interface. Please report any issues to the Setuptools project for investigation. (#4872)

v80.10.2

Bugfixes

• Update vendored dependencies. (#5159)

Misc

... (truncated)

Commits

• 5a13876 Bump version: 82.0.0 → 82.0.1
• 51ab8f1 Avoid using (deprecated) 'json.version' in tests (#5194)
• f9c37b2 Docs/CI: Fix intersphinx references (#5195)
• 8173db2 Docs: Fix intersphinx references
• 09bafbc Fix past tense on newsfragment
• 461ea56 Add news fragment
• c4ffe53 Avoid using (deprecated) 'json.version' in tests
• 749258b Cleanup pkg_resources dependencies and configuration (#5175)
• 2019c16 Parse ext-module.define-macros from pyproject.toml as list of tuples (#5169)
• b809c86 Sync setuptools schema with validate-pyproject (#5157)
• Additional commits viewable in compare view

Updates setuptools-scm from 9.2.0 to 9.2.2

Changelog

Sourced from setuptools-scm's changelog.

v9.2.2

Fixed

• fix #1231: don't warn about tool.setuptools.dynamic.version when only using file finder. The warning about combining version guessing with setuptools dynamic versions should only be issued when setuptools-scm is performing version inference, not when it's only being used for its file finder functionality.

v9.2.1

Fixed

• fix #1216: accept and create a warning for usages of version = attr: in setuptools config. unfortunately dozens of projects cargo-culted that antipattern

Commits

• e56b78f Merge pull request #1232 from RonnyPfannschmidt/fix-1231-dont-warn-when-no-guess
• 4f55e95 docs: update changelog for v9.2.2 patch release
• 95a0c47 fix: don't warn about tool.setuptools.dynamic.version when only using file fi...
• 338f562 Merge pull request #1226 from RonnyPfannschmidt/prepare-release
• a893634 Prepare release v9.2.1
• ad83282 Merge pull request #1225 from pypa/pre-commit-ci-update-config
• 20a4464 [pre-commit.ci] pre-commit autoupdate
• 70f6942 Merge pull request #1219 from RonnyPfannschmidt/fix-1216-explicitly-deprecate...
• 14d85c0 Install Mercurial on Windows runners via Chocolatey
• 8c5cec9 Fix API stability check workflow to install griffe and improve reporting
• Additional commits viewable in compare view

Updates setuptools from 80.9.0 to 82.0.1

Changelog

Sourced from setuptools's changelog.

v82.0.1

Bugfixes

• Fix the loading of launcher manifest.xml file. (#5047)
• Replaced deprecated json.__version__ with fixture in tests. (#5186)

Improved Documentation

• Add advice about how to improve predictability when installing sdists. (#5168)

Misc

• #4941, #5157, #5169, #5175

v82.0.0

Deprecations and Removals

• pkg_resources has been removed from Setuptools. Most common uses of pkg_resources have been superseded by the importlib.resources <https://docs.python.org/3/library/importlib.resources.html>_ and importlib.metadata <https://docs.python.org/3/library/importlib.metadata.html>_ projects. Projects and environments relying on pkg_resources for namespace packages or other behavior should depend on older versions of setuptools. (#3085)

v81.0.0

Deprecations and Removals

• Removed support for the --dry-run parameter to setup.py. This one feature by its nature threads through lots of core and ancillary functionality, adding complexity and friction. Removal of this parameter will help decouple the compiler functionality from distutils and thus the eventual full integration of distutils. These changes do affect some class and function signatures, so any derivative functionality may require some compatibility shims to support their expected interface. Please report any issues to the Setuptools project for investigation. (#4872)

v80.10.2

Bugfixes

• Update vendored dependencies. (#5159)

Misc

... (truncated)

Commits

• 5a13876 Bump version: 82.0.0 → 82.0.1
• 51ab8f1 Avoid using (deprecated) 'json.version' in tests (#5194)
• f9c37b2 Docs/CI: Fix intersphinx references (#5195)
• 8173db2 Docs: Fix intersphinx references
• 09bafbc Fix past tense on newsfragment
• 461ea56 Add news fragment
• c4ffe53 Avoid using (deprecated) 'json.version' in tests
• 749258b Cleanup pkg_resources dependencies and configuration (#5175)
• 2019c16 Parse ext-module.define-macros from pyproject.toml as list of tuples (#5169)
• b809c86 Sync setuptools schema with validate-pyproject (#5157)
• Additional commits viewable in compare view

Updates pandas to 3.0.2

Release notes

Sourced from pandas's releases.

pandas 3.0.2

We are pleased to announce the release of pandas 3.0.2. This is a patch release in the 3.0.x series and includes some regression fixes and bug fixes. We recommend that all users of the 3.0.x series upgrade to this version.

See the full whatsnew for a list of all the changes.

Pandas 3.0 supports Python 3.11 and higher. The release can be installed from PyPI:

python -m pip install --upgrade pandas==3.0.*

Or from conda-forge

conda install -c conda-forge pandas=3.0

Please report any issues with the release on the pandas issue tracker.

Thanks to all the contributors who made this release possible.

Commits

• ab90747 RLS: 3.0.2 (#64934)
• 6f27013 Backport PR #64931 on branch 3.0.x (DOC/BLD: temporary disable upload of docs...
• 48ddc60 Backport PR #64664 on branch 3.0.x (BUG: DataFrame.sum() crashes on empty Dat...
• 8774488 [backport 3.0.x] PERF: fix slow python loop in validation for ArrowStringArra...
• 33af6cc Backport PR #64133 on branch 3.0.x (BUG: str.find returns byte offset instead...
• 4ef49d8 [backport 3.0.x] BUG: fix convert_dtypes dropping values from sliced mixed-dt...
• 0668f34 [backport 3.0.x] BUG: Fix HDFStore.put with StringDtype columns and compressi...
• 23f2f44 [backport 3.0.x] BUG: Suppress unnecessary RuntimeWarning in to_datetime with...
• 83ba804 Backport PR #64886: BUG: Compute Variance of Complex Numbers Correctly (#64892)
• bb5ca1a Backport PR #64386 on branch 3.0.x (BUG: fix sort_index AssertionError with R...
• Additional commits viewable in compare view

Updates datasets from 4.3.0 to 4.8.4

Release notes

Sourced from datasets's releases.

4.5.0

Dataset Features

• Add lance format support by @​eddyxu in huggingface/datasets#7913

  • Support for both Lance dataset (including metadata / manifests) and standalone .lance files
  • e.g. with lance-format/fineweb-edu

  from datasets import load_dataset
  ds = load_dataset("lance-format/fineweb-edu", streaming=True)
  for example in ds["train"]:
  ...

What's Changed

• Raise early for invalid revision in load_dataset by @​Scott-Simmons in huggingface/datasets#7929
• fix low but large example indexerror by @​CloseChoice in huggingface/datasets#7912
• Fix method to retrieve attributes from file object by @​lhoestq in huggingface/datasets#7938
• add _OverridableIOWrapper by @​lhoestq in huggingface/datasets#7942
• Add _generate_shards by @​lhoestq in huggingface/datasets#7943

New Contributors

• @​eddyxu made their first contribution in huggingface/datasets#7913
• @​Scott-Simmons made their first contribution in huggingface/datasets#7929

Full Changelog: huggingface/datasets@4.4.2...4.5.0

Commits

• 69d773a Release: 4.5.0 (#7944)
• dc98f97 Add _generate_shards (#7943)
• 38d28bf add _OverridableIOWrapper (#7942)
• 7431153 Fix method to retrieve attributes from file object (#7938)
• 6a1bc35 fix low but large example indexerror (#7912)
• 7bdf840 Raise early for invalid revision in load_dataset (#7929)
• 06b6e02 Add lance format support (#7913)
• 0feb65d set dev version (#7908)
• 37d9615 release: 4.4.2 (#7907)
• 58dda42 Don't save original_shard_lengths by default for backward compat (#7906)
• Additional commits viewable in compare view

Updates huggingface-hub from 0.36.2 to 1.8.0

Release notes

Sourced from huggingface-hub's releases.

[v1.8.0] Mounted volumes on Jobs, complete papers CLI, and more

🚀 Jobs can now mount volumes

Jobs can now access Hugging Face repositories (models, datasets, Spaces) and Storage Buckets directly as mounted volumes in their containers. This enables powerful workflows like running queries directly against datasets, loading models without explicit downloads, and persisting training checkpoints to buckets.

from huggingface_hub import run_job, Volume
job = run_job(
image="duckdb/duckdb",
command=["duckdb", "-c", "SELECT * FROM '/data/**/*.parquet' LIMIT 5"],
volumes=[
Volume(type="dataset", source="HuggingFaceFW/fineweb", mount_path="/data"),
],
)

hf jobs run -v hf://datasets/HuggingFaceFW/fineweb:/data duckdb/duckdb duckdb -c "SELECT * FROM '/data/**/*.parquet' LIMIT 5"

• Add volume mounting support for buckets and repos by @​XciD in #3936

📖 Papers CLI is now complete

The hf papers command now has full functionality: search papers by keyword, get structured JSON metadata, and read the full paper content as markdown. The ls command is also enhanced with new filters for week, month, and submitter.

# Search papers
hf papers search "vision language"
Get metadata
hf papers info 2601.15621
Read as markdown
hf papers read 2601.15621

• Complete hf papers with search, info, read + ls filters by @​mishig25 in #3952

🖥️ CLI repo ID shorthand

You can now use repo ID prefixes like spaces/user/repo, datasets/user/repo, and models/user/repo as a shorthand for user/repo --type space. This works automatically for all CLI commands that accept a --type flag.

# Before
hf download user/my-space --type space
hf discussions list user/my-dataset --type dataset
After
</tr></table>

... (truncated)

Commits

• 8b7c45c Release: v1.8.0
• 5e62f96 Release: v1.8.0.rc0
• 701fb0b feat(jobs): add volume mounting support for buckets and repos (#3936)
• 98e9a94 Use huggingface-hub-bot for post-release PR creation (#3967)
• 9e7fbad [CLI] Accept spaces/user/repo as repo ID prefix shorthand (#3929)
• da46c21 More robust stream to stdout in hf cp command (#3968)
• e41dce2 Add visibility parameter to HfApi repo create/update/duplicate methods (#...
• 274fabf [CLI] Mention hf-mount in CLI skill (#3966)
• 778d306 [CLI] Add space-specific options to hf repos create and `hf repos duplicate...
• 5596477 Update hardware flavors with HF Hub (#3965)
• Additional commits viewable in compare view

Updates transformers from 4.57.6 to 5.5.0

Release notes

Sourced from transformers's releases.

Release v5.5.0

New Model additions

Gemma4

Gemma 4 is a multimodal model with pretrained and instruction-tuned variants, available in 1B, 13B, and 27B parameters. The architecture is mostly the same as the previous Gemma versions. The key differences are a vision processor that can output images of fixed token budget and a spatial 2D RoPE to encode vision-specific information across height and width axis.

You can find all the original Gemma 4 checkpoints under the Gemma 4 release.

The key difference from previous Gemma releases is the new design to process images of different sizes using a fixed-budget number of tokens. Unlike many models that squash every image into a fixed square (like 224×224), Gemma 4 keeps the image's natural aspect ratio while making it the right size. There a a couple constraints to follow:

• The total number of pixels must fit within a patch budget
• Both height and width must be divisible by 48 (= patch size 16 × pooling kernel 3)

[!IMPORTANT] Gemma 4 does not apply the standard ImageNet mean/std normalization that many other vision models use. The model's own patch embedding layer handles the final scaling internally (shifting values to the [-1, 1] range).

The number of "soft tokens" (aka vision tokens) an image processor can produce is configurable. The supported options are outlined below and the default is 280 soft tokens per image.

Soft Tokens	Patches (before pooling)	Approx. Image Area
70	630	~161K pixels
140	1,260	~323K pixels
280	2,520	~645K pixels
560	5,040	~1.3M pixels
1,120	10,080	~2.6M pixels

To encode positional information for each patch in the image, Gemma 4 uses a learned 2D position embedding table. The position table stores up to 10,240 positions per axis, which allows the model to handle very large images. Each position is a learned vector of the same dimensions as the patch embedding. The 2D RoPE which Gemma 4 uses independently rotate half the attention head dimensions for the x-axis and the other half for the y-axis. This allows the model to understand spatial relationships like "above," "below," "left of," and "right of."

NomicBERT

NomicBERT is a BERT-inspired encoder model that applies Rotary Position Embeddings (RoPE) to create reproducible long context text embeddings. It is the first fully reproducible, open-source text embedding model with 8192 context length that outperforms both OpenAI Ada-002 and OpenAI text-embedding-3-small on short-context MTEB and long context LoCo benchmarks. The model generates dense vector embeddings for various tasks including search, clustering, and classification using specific instruction prefixes.

Links: Documentation | Paper

• Internalise the NomicBERT model (#43067) by @​ed22699 in #43067

MusicFlamingo

Music Flamingo is a fully open large audio–language model designed for robust understanding and reasoning over music. It builds upon the Audio Flamingo 3 architecture by including Rotary Time Embeddings (RoTE), which injects temporal position information to enable the model to handle audio sequences up to 20 minutes. The model features a unified audio encoder across speech, sound, and music with special sound boundary tokens for improved audio sequence modeling.

Links: Documentation | Paper

• Add Music Flamingo (#43538) by @​lashahub in #43538

... (truncated)

Commits

• c1c3424 update
• 20bff68 update release workflow
• 8956441 v5.5.0
• 5135e5e casually dropping the most capable open weights on the planet (#45192)
• a594e09 Internalise the NomicBERT model (#43067)
• 4932e97 Fix resized LM head weights being overwritten by post_init (#45079)
• 57e8413 [Qwen3.5 MoE] Add _tp_plan to ForConditionalGeneration (#45124)
• b10552e Fix TypeError: 'NoneType' object is not iterable in GenerationMixin.generate ...
• 423f2a3 fix(models): Fix dtype mismatch in SwitchTransformers and TimmWrapperModel (#...
• ade7a05 Generalize gemma vision mask to videos (#45185)
• Additional commits viewable in compare view

Updates trl from 0.23.1 to 1.0.0

Release notes

Sourced from trl's releases.

v1.0.0

Read our blog post for an overview of TRL v1.

Features

Asynchronous GRPO

Asynchronous GRPO decouples generation from the gradient update loop by offloading rollouts to an external vLLM server. Generation runs in parallel while training continues, eliminating idle GPU time and improving hardware utilization.

from trl.experimental.async_grpo import AsyncGRPOTrainer
from trl.rewards import accuracy_reward
from datasets import load_dataset
dataset = load_dataset("trl-lib/DeepMath-103K", split="train")
trainer = AsyncGRPOTrainer(
model="Qwen/Qwen2.5-0.5B-Instruct",
reward_funcs=accuracy_reward,
train_dataset=dataset,
)
trainer.train()

by @​qgallouedec in huggingface/trl#5293

Variational Sequence-Level Soft Policy Optimization (VESPO)

VESPO addresses training instability in off-policy RL caused by policy staleness, asynchronous updates, and train-inference mismatches. Rather than relying on heuristic token-level clipping (GRPO) or sequence-length normalization (GSPO), VESPO derives a principled reshaping kernel from a variational framework. In practice, this yields a smooth, asymmetric Gamma weighting function that gracefully suppresses extreme sequence-level importance weights without introducing length bias. It can be enabled via the loss_type parameter of GRPOConfig:

from trl import GRPOConfig, GRPOTrainer
trainer = GRPOTrainer(
model="Qwen/Qwen3-0.6B",
args=GRPOConfig(loss_type="vespo"),
...
)

by @​casinca in huggingface/trl#5199

Divergence Proximal Policy Optimization (DPPO)

... (truncated)

Commits

• f3e9ac1 Release: v1.0 (#5409)
• e8d5dfc Add second version of Qwen 3.5 chat template to chat_template_utils (#5405)
• 71ff6a2 Add HF_TOKEN environment variable to workflow files (#5397)
• 1ee3975 Add vLLM inference to the Base Self-Distillation Trainer (#5388)
• 79e6e79 Move disable_config=True from generate to GenerationConfig (#5384)
• 83d68dd chore: update pr_template_check.yml (#5393)
• 4cb7ab1 Enhance PR template check to exclude reopened PRs from first-time contributor...
• 32a40bf Enforce PR template for first-time contributors and document AI usage policy ...
• 8e69b68 Mark test_rloo[fsdp2] as xfail for transformers 5.4.0 (#5387)
• c264266 Remove deprecated TRACKIO_SPACE_ID env var from all scripts (#5365)
• Additional commits viewable in compare view

Updates data-designer-engine from 0.5.4 to 0.5.5

Updates pandas from 2.3.3 to 3.0.2

Release notes

Sourced from pandas's releases.

pandas 3.0.2

We are pleased to announce the release of pandas 3.0.2. This is a patch release in the 3.0.x series and includes some regression fixes and bug fixes. We recommend that all users of the 3.0.x series upgrade to this version.

See the full whatsnew for a list of all the changes.

Pandas 3.0 supports Python 3.11 and higher. The release can be installed from PyPI:

python -m pip install --upgrade pandas==3.0.*

Or from conda-forge

conda install -c conda-forge pandas=3.0

Please report any issues with the release on the pandas issue tracker.

Thanks to all the contributors who made this release possible.

Commits

• ab90747 RLS: 3.0.2 (#64934)
• 6f27013 Backport PR #64931 on branch 3.0.x (DOC/BLD: temporary disable upload of docs...
• 48ddc60 Backport PR #64664 on branch 3.0.x (BUG: DataFrame.sum() crashes on empty Dat...
• 8774488 [backport 3.0.x] PERF: fix slow python loop in validation for ArrowStringArra...
• 33af6cc Backport PR #64133 on branch 3.0.x (BUG: str.find returns byte offset instead...
• 4ef49d8 [backport 3.0.x] BUG: fix convert_dtypes dropping values from sliced mixed-dt...
• 0668f34 [backport 3.0.x] BUG: Fix HDFStore.put with StringDtype columns and compressi...
• 23f2f44 [backport 3.0.x] BUG: Suppress unnecessary RuntimeWarning in to_datetime with...
• 83ba804 Backport PR #64886: BUG: Compute Variance of Complex Numbers Correctly (#64892)
• bb5ca1a Backport PR #64386 on branch 3.0.x (BUG: fix sort_index AssertionError with R...
• Additional commits viewable in compare view

Updates pytest to 9.0.2

Release notes

Sourced from pytest's releases.

9.0.2

pytest 9.0.2 (2025-12-06)

Bug fixes

• #13896: The terminal progress feature added in pytest 9.0.0 has been disabled by default, except on Windows, due to compatibility issues with some terminal emulators.

  You may enable it again by passing -p terminalprogress. We may enable it by default again once compatibility improves in the future.

  Additionally, when the environment variable TERM is dumb, the escape codes are no longer emitted, even if the plugin is enabled.

• #13904: Fixed the TOML type of the tmp_path_retention_count settings in the API reference from number to string.

• #13946: The private config.inicfg attribute was changed in a breaking manner in pytest 9.0.0. Due to its usage in the ecosystem, it is now restored to working order using a compatibility shim. It will be deprecated in pytest 9.1 and removed in pytest 10.

• #13965: Fixed quadratic-time behavior when handling unittest subtests in Python 3.10.

Improved documentation

• #4492: The API Reference now contains cross-reference-able documentation of pytest's command-line flags <command-line-flags>.

Commits

• 3d10b51 Prepare release version 9.0.2
• 188750b Merge pull request #14030 from pytest-dev/patchback/backports/9.0.x/1e4b01d1f...
• b7d7bef Merge pull request #14014 from bluetech/compat-note
• bd08e85 Merge pull request #14013 from pytest-dev/patchback/backports/9.0.x/922b60377...
• bc78386 Add CLI options reference documentation (#13930)
• 5a4e398 Fix docs typo (#14005) (#14008)
• d7ae6df Merge pull request #14006 from pytest-dev/maintenance/update-plugin-list-tmpl...
• 556f6a2 pre-commit: fix rst-lint after new release (#13999) (#14001)
• c60fbe6 Fix quadratic-time behavior when handling unittest subtests in Python 3.10 ...
• 73d9b01 Merge pull request #13995 from nicoddemus/patchback/backports/9.0.x/1b5200c0f...
• Additional commits viewable in compare view

Updates pytest-rerunfailures from 15.1 to 16.1

Changelog

Sourced from pytest-rerunfailures's changelog.

16.1 (2025-10-10)

• Drop support for Python 3.9.

• Changed "localhost" to "127.0.0.1" to avoid bad hostname resolution.

• Added --force-reruns to override rerun count globally. Fixes [#306](https://github.com/pytest-dev/pytest-rerunfailures/issues/306) <https://github.com/pytest-dev/pytest-rerunfailures/issues/306>_.

16.0.1 (2025-09-02)

• Reverted the ability to access error attributes because of an incompatibility with pytest-xdist <https://github.com/pytest-dev/pytest-xdist/issues/843>. Fixes [#302](https://github.com/pytest-dev/pytest-rerunfailures/issues/302) <https://github.com/pytest-dev/pytest-rerunfailures/issues/302>, [#303](https://github.com/pytest-dev/pytest-rerunfailures/issues/303) <https://github.com/pytest-dev/pytest-rerunfailures/issues/303>_.

16.0 (2025-08-29)

Breaking changes ++++++++++++++++

• Drop support for pytest < 8.

Features ++++++++

• Add support for pytest 8.4.x.

• Add support for upcoming Python 3.14.

• Allow @pytest.mark.flaky(condition) to accept a callable or a string to be evaluated. The evaluated string has access to the exception instance via the error object. ([#230](https://github.com/pytest-dev/pytest-rerunfailures/issues/230) <https://github.com/pytest-dev/pytest-rerunfailures/issues/230>_)

Commits

• b015092 Preparing release 16.1
• c1666dd Prepare release.
• 8d04ad9 Fix NotImplementedError crash when using xdist schedulers without `mark_tes...
• cb8ede7 Add a --force-reruns to override rerun count globally (#307)
• 5e01132 Bump actions/setup-python from 5 to 6 in the actions group (#310)
• 88e0023 Drop support for Python 3.9. (#308)
• df47974 Change 'localhost' to '127.0.0.1' (#305)
• f149c7d Back to development: 16.1
• f97618f Preparing release 16.0.1
• c60d17d Prepare release.
• Additional commits viewable in compare view

Updates scikit-learn from 1.7.1 to 1.8.0

Release notes

Sourced from scikit-learn's releases.

Release 1.8.0

We're happy to announce the 1.8.0 release.

You can read the release highlights under https://scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_8_0.html and the long version of the change log under https://scikit-learn.org/stable/whats_new/v1.8.html

This version supports Python versions 3.11 to 3.14 and features support of free-threaded CPython.

You can upgrade with pip as usual:

pip install -U scikit-learn

The conda-forge builds can be installed using:

conda install -c conda-forge scikit-learn

Scikit-learn 1.7.2

We're happy to announce the 1.7.2 release.

This release contains a few bug fixes and is the first version supporting Python 3.14.

You can see the changelog here: https://scikit-learn.org/stable/whats_new/v1.7.html#version-1-7-2

You can upgrade with pip as usual:

pip install -U scikit-learn

The conda-forge builds can be installed using:

conda install -c conda-forge scikit-learn

Thanks to everyone who contributed to this release !

Commits

• 646da0f [cd build]
• 4f4f283 Generate changelog
• 967dcde Set version
• cb1424b DOC Release highlights for 1.8 (#32809)
• 5645b27 🔒 🤖 CI Update lock files for main CI build(s) 🔒 🤖 (#32859)
• 6b9fb11 🔒 🤖 CI Update lock files for free-threaded CI build(s) 🔒 :rob...
• a0f6d88 🔒 🤖 CI Update lock files for array-api CI build(s) 🔒 🤖 ...
• c1de8fc FIX Make get_namespace handle pandas dataframe input (#32838)
• 764249a Fix _safe_indexing with non integer arrays on array API inputs (#32840)
• eca5e0a FIX Add new default max_samples=None in Bagging estimators (#32825)
• Additional commits viewable in compare view

Updates datasets from 4.3.0 to 4.8.4

Release notes

Sourced from datasets's releases.

4.5.0

Dataset Features

• Add lance format support by @​eddyxu in huggingface/datasets#7913

  • Support for both Lance dataset (including metadata / manifests) and standalone .lance files
  • e.g. with lance-format/fineweb-edu
  Description has been truncated

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[chatgpt-codex-connector]

Reinstate datasets 4.1.0 exclusion in extras constraints

This change removes the previous !=4.1.0 guard from the package extras, even though the Studio runtime requirements still explicitly exclude 4.1.0 (studio/backend/requirements/no-torch-runtime.txt). That inconsistency re-allows a known-bad dataset version for unsloth[huggingfacenotorch] / colab-new installs, so constrained environments can resolve to datasets==4.1.0 and hit the same incompatibility the runtime file is still protecting against.

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[chatgpt-codex-connector]

Keep extras compatible with Python 3.10 environments

Pinning scikit-learn==1.8.0 in extras.txt can break Studio dependency installation on Python 3.10 environments (for example when users run Linux setup with a --python 3.10 venv), because this major bump narrows interpreter support compared with the previous 1.7.x line. Since install_python_stack.py installs this requirements file as part of normal setup, the install can fail before Studio starts.

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[chatgpt-codex-connector]

Keep constraints consistent with extras-no-deps pins

install_python_stack.py installs extras-no-deps.txt with -c single-env/constraints.txt (the pip_install(..., req=..., constrain=True) default), so these new pins must remain compatible with that file. Pinning transformers==5.5.0 and trl==1.0.0 here conflicts with extras-no-deps.txt still requiring transformers==4.57.6 and trl==0.23.1, which makes pip/uv fail with ResolutionImpossible and abort dependency setup.

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[chatgpt-codex-connector]

Re-block datasets versions that crash at import time

This new specifier (datasets>=4.0,<4.6) now allows datasets 4.4.x and 4.5.0, but unsloth/import_fixes.py::patch_datasets() explicitly raises NotImplementedError for 4.4.0 <= datasets <= 4.5.0, and that patch runs during import unsloth (unsloth/__init__.py). In practice, installs via unsloth[huggingfacenotorch] (and the mirrored colab-new extra) can now resolve to a version that immediately breaks import, so these known-bad versions need to stay excluded in the extras bounds.

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