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Bumps the production group with 17 updates:

Package From To
numpy 2.4.2 2.5.4
pydantic 2.12.5 2.14.1
scikit-fingerprints 1.18.0 2.1.0
scikit-learn 1.8.0 1.9.1
scipy 1.17.1 1.18.1
umap-learn 0.5.11 0.5.12
mlflow-skinny 3.10.0 3.17.2
plotly 6.5.2 7.1.0
mlflow 3.10.0 3.17.2
fastparquet 2026.3.0 2026.9.0
torch-geometric 2.7.0 2.8.1
optuna 4.7.0 5.0.0
optuna-integration 4.7.0 5.0.0
transformers 4.57.6 5.21.0
chemprop 2.2.2 2.3.1
myst-parser 4.0.1 5.1.0
sphinx-autoapi 3.8.0 3.8.1

Updates numpy from 2.4.2 to 2.5.4

Release notes

Sourced from numpy's releases.

v2.5.4 (Oct 10, 2026)

NumPy 2.5.4 Release Notes

Released on 2026-10-10.

NumPy 2.5.4 is a patch release that fixes bugs discovered after the 2.5.3 release. Highlights are:

  • Many typing fixes and improvements,
  • A workaround for the MSVC 19.51 bug, see below.

This release supports Python versions 3.12-3.15.

Improvements

  • numpy.linalg.svd and numpy.linalg.lstsq now raise for inputs containing infinities instead of returning garbage results.

  • Fixed hangs in numpy.linalg.svd and numpy.linalg.lstsq for certain inputs containing infinities for recent versions of some LAPACK implementations.

  • numpy.linalg.cond now handles non-finite inputs more consistently.

(gh-32593)

StringDType hashing with NaN sentinels

StringDType instances with equivalent floating-point NaN sentinels now have equal hashes. Previously, distinct NaN objects could produce equal dtype instances with different hashes, causing dictionary lookups and set deduplication to fail.

(gh-32563)

Changes

MaskedArray resets a fill_value that cannot be represented in a new dtype

A fill_value copied from a source array is now reset to the default fill_value for the new dtype when it cannot be represented in that dtype. Previously the copied value could be stale: ufuncs that change dtype left the result holding a fill_value typed for the old dtype, which raised a TypeError only when something later validated it (such as .view()), and a floating point fill_value that overflows an integer dtype was kept as an out-of-range value together with a RuntimeWarning. Both now fall back to the default, including when a masked array is passed to MaskedArray with a different dtype. A fill_value given explicitly by the user is still validated and raises as before. This can now raise a ComplexWarning if the fill_value is complex and the new dtype is real.

... (truncated)

Commits
  • a3d0ef1 Merge pull request #32969 from charris/prepare-2.5.4
  • 087b536 MAINT: Make OpenBLAS version check use 2.5.x branch.
  • 91acd87 REL: Prepare for the NumPy 2.5.4 release.
  • 9cc555b Merge pull request #32956 from charris/backport-typing-1
  • e04b972 TYP: dtype[void].names: allow setting with list (#32943)
  • d929969 TYP: timedelta64: datetime.timedelta construction isn't deprecated (#...
  • 839467f TYP: ma.getmaskarray: accept array-likes (#32934)
  • 64b721b TYP: polynomial: accept scalar coef in the poly constructors (#32931)
  • 06b7ad2 TYP: void: accept any dtype: str in constructor calls (#32928)
  • c7bcd2c TYP: place: widen mask (#32926)
  • Additional commits viewable in compare view

Updates pydantic from 2.12.5 to 2.14.1

Release notes

Sourced from pydantic's releases.

v2.14.1 2026-10-11

What's Changed

Performance

  • Avoid Python tuple allocation during model fields validation by @​Viicos in #13955
  • Avoid unnecessary extra dict allocation in model validation by @​Viicos in #13956

Fixes

Full Changelog: pydantic/pydantic@v2.14.0...v2.14.1

v2.14.0 2026-10-08

What's Changed

The highlights of the v2.14 release are available in the blog post. Several minor changes (considered non-breaking changes according to our versioning policy) are also included in this release. Make sure to look into them before upgrading.

This release drops support for Python 3.9 and adds support for Python 3.15.

Two security fixes are fixed by this release: GHSA-gj4f-r7mf-jjxh and GHSA-955g-x97g-8mcp.

New Features

  • Add support for multiple_of constraint in fraction and timedelta core schemas by @​Viicos in #13873
  • Add __namespace__ parameter to create_model() by @​Viicos in #13895

Changes

Fixes

... (truncated)

Changelog

Sourced from pydantic's changelog.

v2.14.0 (2026-10-08)

GitHub release

What's Changed

The highlights of the v2.14 release are available in the blog post. Several minor changes (considered non-breaking changes according to our versioning policy) are also included in this release. Make sure to look into them before upgrading.

This release drops support for Python 3.9 and adds support for Python 3.15.

New Features

  • Add support for multiple_of constraint in fraction and timedelta core schemas by @​Viicos in #13873
  • Add __namespace__ parameter to create_model() by @​Viicos in #13895

Changes

Fixes

  • Call enum constructors in both validation modes by @​Viicos in #13792
  • Fix documentation examples not raising and remove unused string_sub_type unused error code by @​Viicos in #13821
  • Catch OverflowError during ByteSize validation by @​Viicos in #13850
  • Require multiple_of constraints to be positive by @​Viicos in #13862
  • Always pop field name and model type stacks during schema generation by @​saquibjawedbit in #13859
  • Handle TypeError gracefully during docstring extraction by @​Viicos in #13874
  • Fix config propagation of stdlib dataclasses and TypedDicts in JSON Schema by @​Viicos in #13891
  • Don't apply ser_json_timedelta to all datetime types in serialization inference by @​Viicos in #13892
  • Encode JSON Schema defaults with a consistent configuration by @​Viicos in #13893
  • Propagate init and kw_only=False from Field() to stdlib dataclass fields by @​Viicos in #13898
  • Respect propagated extra config in the JSON Schema of stdlib dataclasses by @​Viicos in #13899
  • Handle OS errors during ZoneInfo validation by @​Viicos in #13912
  • Handle exceptions during Decimal validation by @​Viicos in #13940
  • Rebuild incomplete types during serialization inference by @​Viicos in #13922
  • Reject large exponents in Fraction validation by @​Viicos in #13944
  • Avoid validating URL prefix multiple times in multi host URLs by @​Viicos in #13945

New Contributors

... (truncated)

Commits
  • b2212c7 Prepare release v2.14.1
  • 968fb2b Fix docs conversion table
  • 6adc8b3 Support named tuples in Sequence validation
  • 7637fbc Reject out-of-range int inputs for timedelta
  • dfdbfcb Enforce the max_digits whole-digits limit in the Python Decimal validator
  • e2456d3 Support closed and extra_items via inheritance in TypedDict
  • 317655d Harden CI security
  • 3ba1dd4 Fix TypeError on ForwardRef on Python 3.10.0
  • 43681ab Bump samuelcolvin/check-python-version action to v5.1
  • d6bc53a Avoid unnecessary extra dict allocation in model validation
  • Additional commits viewable in compare view

Updates scikit-fingerprints from 1.18.0 to 2.1.0

Release notes

Sourced from scikit-fingerprints's releases.

scikit-fingerprints 2.1.0

New features

  • Many new regression datasets: ExpansionRx - OpenADMET, ASAP Discovery - OpenADMET, Biogen ADME benchmark
  • Initial support for fingerprints based on pretrained neural networks. Currently, CLAMP has been implemented, with extensible interface.
  • Added MAGPIE fingerprint

Breaking changes

  • Butina split has been substantially rewritten, with prior implementation not necessarily reflecting the typical Butina clustering implementation. This will give different results on 2.1.0 compared to previous versions.
  • Removed deprecated functions, e.g. AUROC

Fixes, small modifications, internal changes

  • Better README
  • A bunch of new benchmarks
  • Faster CI
  • Faster datasets downloading
  • Faster LINGO fingerprint
  • Fixes to conformer handling in input/output

New Contributors

Full Changelog: MLCIL/scikit-fingerprints@v2.0.0...v2.1.0

scikit-fingerprints 2.0.0

This is a major release to signify how scikit-fingerprints grew in scope and functionality since 1.0.0. It now covers not only molecular fingerprints, but also molecular filters, datasets, distances & similarities, applicability domain checkers, and much more. While this v2.0.0 does not bring significant breaking changes overall, it does change many smaller functionalities, in particular MAP4 fingerprint. Further, we want to underscore the wider scope of the library now, with many planned extensions down the line in 2.x versions.

New features

  • ensure_mols now supports InChI strings, which also means all fingerprints etc. safely take InChI input in addition to SMILES and Mol objects
  • TDC clearance_hepatocyte_az dataset removed due to low data quality
  • First clustering method: MaxMin clustering
  • Filtering only valid sequences in LRGB
  • Multithreading for MolFromSDFTransformer for new RDKit versions

Breaking changes

  • MAP4 fingerprint debugged, results will strongly differ from previous ones
  • random_state removed from classes that didn't use it

Fixes, small modifications, internal changes

  • A lot of small fixes, with code and docs style unification
  • Faster tests and CI
  • Many new benchmarks

New Contributors

... (truncated)

Commits

Updates scikit-learn from 1.8.0 to 1.9.1

Release notes

Sourced from scikit-learn's releases.

Scikit-learn 1.9.1

We're happy to announce the 1.9.1 release.

This release contains a few bug fixes and is the first version supporting Python 3.15.

You can see the changelog here: https://scikit-learn.org/stable/whats_new/v1.9.html#version-1-9-1

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 !

Scikit-learn 1.9.0

We're happy to announce the 1.9.0 release.

You can read the release highlights under https://scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_9_0.html and the long version of the change log under https://scikit-learn.org/stable/whats_new/v1.9.html

This release adds narwhals as a new dependency that will help to improve dataframe interoperability across the project.

This version supports Python versions 3.11 to 3.14.

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
Commits
  • 866c0f5 generate changelog
  • 12f135f update upper bounds
  • 43ff2f2 bump version
  • b851524 DOC Mark dev index as orphan (#34916)
  • 01d56d4 DOC Fix wikipedia principal eigenvector example references (#34915)
  • b86a1e2 🔒 🤖 CI Update lock files for array-api CI build(s) 🔒 🤖 ...
  • d282698 🔒 🤖 CI Update lock files for main CI build(s) 🔒 🤖 (#34897)
  • eb34279 🔒 🤖 CI Update lock files for free-threaded CI build(s) 🔒 :rob...
  • 7581303 FIX: Fix QuantileTransformer(ignore_implicit_zeros=True) sub-sampling behav...
  • ac47f4d FIX: avoid EfficiencyWarning in OPTICS with metric='precomputed' (#34692)
  • Additional commits viewable in compare view

Updates scipy from 1.17.1 to 1.18.1

Release notes

Sourced from scipy's releases.

SciPy 1.18.1 Release Notes

SciPy 1.18.1 is a bug-fix release with no new features compared to 1.18.0. This release includes binaries on PyPI for Python 3.15, and the minimum required version of the GCC toolchain has been increased to 10.3.0.

Authors

  • Name (commits)
  • Wasim Akram (2) +
  • Jake Bowhay (1)
  • Michael Bratsch (1)
  • Dietrich Brunn (1)
  • Evgeni Burovski (1)
  • Aadya Chinubhai (1)
  • Lucas Colley (3)
  • Tekin Ertekin (1) +
  • Fuyugithub (2) +
  • Ralf Gommers (11)
  • Joren Hammudoglu (1)
  • Ijtihed Kilani (1) +
  • Andrew Nelson (2)
  • Ilhan Polat (1)
  • Tyler Reddy (39)
  • romao05 (1) +
  • Michael Simacek (1) +
  • Jacob Vanderplas (2)

A total of 18 people contributed to this release. People with a "+" by their names contributed a patch for the first time. This list of names is automatically generated, and may not be fully complete.

Note that the source and binary assets associated with this release were published to PyPI using trusted publishing, and so the trusted assets and their hashes are made available more securely at https://pypi.org/project/scipy/1.18.1/ rather than providing them here in a less secure manner.

A complete list of issues and pull requests associated with this release is available in the associated README.txt.

SciPy 1.18.0 Release Notes

SciPy 1.18.0 is the culmination of 6 months of hard work. It contains many new features, numerous bug-fixes, improved test coverage and better documentation. There have been a number of deprecations and API changes in this release, which are documented below. All users are encouraged to upgrade to this release, as there are a large number of bug-fixes and optimizations. Before upgrading, we recommend that users check that their own code does not use deprecated SciPy functionality (to do so, run your code with python -Wd and check for DeprecationWarning s).

... (truncated)

Commits
  • e4e854e REL: SciPy 1.18.1 rel commit
  • 3c8e5f8 BLD, MAINT: pythran bounds for 1.18.1 (#25978)
  • 54c0f95 BLD, MAINT: pythran bounds for 1.18.1
  • 45a355d Merge pull request #25884 from tylerjereddy/treddy_backports_1.18.1
  • a717e28 DOC: PR 25884 revisions
  • bb489c0 DOC: PR 25884 revisions
  • 09bca24 BLD: package: pin meson on win-64 to avoid clang-cl bug (#25913)
  • 095fe56 DOC, BLD: PR 25884 revisions
  • e66ea64 DOC: update minimum GCC version in toolchain roadmap
  • c021653 TST: tolerance bumps and skips on 32-bit platforms
  • Additional commits viewable in compare view

Updates umap-learn from 0.5.11 to 0.5.12

Release notes

Sourced from umap-learn's releases.

release-0.5.12

What's Changed

New Contributors

Full Changelog: lmcinnes/umap@release-0.5.11...release-0.5.12

Commits

Updates mlflow-skinny from 3.10.0 to 3.17.2

Release notes

Sourced from mlflow-skinny's releases.

MLflow 3.17.2 is a patch release that contains a minor feature enhancement and bug fixes.

Features:

Bug fixes:

  • [Tracking] Reseed sampler and forward batch settings on MlflowSparkStudy executors (#26714, @​iyashk)
  • [Tracking] Fix MlflowStorage marking Optuna trials finished before their values are saved (#26713, @​iyashk)

MLflow 3.17.1 is a patch release that contains some minor feature enhancements, bug fixes, and documentation updates.

Features:

  • [Docs / Evaluation] Support Decision API in make_judge() (#26578, @​B-Step62)
  • [Evaluation] Add mlflow.genai.databricks.review_queues for managing review queues on Databricks (#26414, @​harupy)

Bug fixes:

  • [Tracing] Fix Claude Code OTel trace rendering in the MLflow UI (#26547, @​joshuawong-db)
  • [Evaluation] Load latest Databricks scorers from the scheduled-scorers REST config so feedback records the scorer version (#26542, @​joshuawong-db)

Small bug fixes and documentation updates:

#26680, @​joshuawong-db; #26584, @​copilot-swe-agent; #26705, @​kriscon-db

MLflow 3.17.0 includes several major features and improvements.

Major New Features

Database upgrade: SQL-backed servers require a coordinated schema upgrade with all writers stopped and a restorable backup, even when daily rollups remain disabled. Run mlflow db upgrade <database-url> before restarting all replicas on the new MLflow version. Mixed-version rolling upgrades are not supported. Follow the database upgrade instructions.

Other Assorted Features & Improvements:

... (truncated)

Changelog

Sourced from mlflow-skinny's changelog.

3.17.2 (2026-10-20)

MLflow 3.17.2 is a patch release that contains a minor feature enhancement and bug fixes.

Features:

Bug fixes:

  • [Tracking] Reseed sampler and forward batch settings on MlflowSparkStudy executors (#26714, @​iyashk)
  • [Tracking] Fix MlflowStorage marking Optuna trials finished before their values are saved (#26713, @​iyashk)

3.17.1 (2026-10-13)

MLflow 3.17.1 is a patch release that contains some minor feature enhancements, bug fixes, and documentation updates.

Features:

  • [Docs / Evaluation] Support Decision API in make_judge() (#26578, @​B-Step62)
  • [Evaluation] Add mlflow.genai.databricks.review_queues for managing review queues on Databricks (#26414, @​harupy)

Bug fixes:

  • [Tracing] Fix Claude Code OTel trace rendering in the MLflow UI (#26547, @​joshuawong-db)
  • [Evaluation] Load latest Databricks scorers from the scheduled-scorers REST config so feedback records the scorer version (#26542, @​joshuawong-db)

Small bug fixes and documentation updates:

#26680, @​joshuawong-db; #26584, @​copilot-swe-agent; #26705, @​kriscon-db

3.17.0 (2026-10-06)

MLflow 3.17.0 includes several major features and improvements.

Major New Features

Database upgrade: SQL-backed servers require a coordinated schema upgrade with all writers stopped and a restorable backup, even when daily rollups remain disabled. Run mlflow db upgrade <database-url> before restarting all replicas on the new MLflow version. Mixed-version rolling upgrades are not supported. Follow the database upgrade instructions.

Other Assorted Features & Improvements:

... (truncated)

Commits
  • d0b397f Reseed sampler and forward batch settings on MlflowSparkStudy executors (#2...
  • b58d40d Fix MlflowStorage marking Optuna trials finished before their values are sa...
  • 3be0c9d Record dataset, scorer, and agent lineage on mlflow.genai.evaluate runs (#2...
  • eaf7df1 Bump version to 3.17.2 (#26911)
  • 7fc49ae Cherry-picks for v3.17.1 (#26706)
  • 47335e1 Bump version to 3.17.1 (#26705)
  • 6dd94c6 Bump version to 3.17.0 (#26464)
  • 83764b3 Update ML package versions for 3.17.0 (#26458)
  • 40cea47 Replace triage’s nginx gateway proxy with an in-memory Node proxy (#26457)
  • b56ead6 Include skills submodule in wheel builds (#26456)
  • Additional commits viewable in compare view

Updates plotly from 6.5.2 to 7.1.0

Release notes

Sourced from plotly's releases.

v7.1.0

Added

  • Support marginal_x/marginal_y="heatmap" in density_heatmap, drawing a single-row/column heatmap strip in the margin colored by the same z/histfunc aggregate as the main plot and sharing its color scale [#5706], with thanks to @​lucasjamar for the contribution!
  • Add support for custom tick values in mpl_to_plotly when the matplotlib tick positions don't follow an arithmetic progression, including custom tick labels and tick values on date axes [#5262], with thanks to @​robertoffmoura for the contribution!

Fixed

  • Fix Plotly Express treating unsigned integer columns (uint8, uint16, uint32, uint64) in pandas DataFrames as categorical, which caused px.bar and other functions to pick the wrong orientation and render unexpected plots [#4291, #4344], with thanks to @​Belagum for the contribution!
  • Fix mpl_to_plotly not setting paper_bgcolor and plot_bgcolor from the matplotlib figure and axes backgrounds, so converted figures match the source figure's background colors [#5285], with thanks to @​robertoffmoura for the contribution!
  • Fix rendering issue causing a too-large div when calling Figure.show() in Google Colab [#5718]
  • Fix the sphinx-gallery scraper so that it generates thumbnails for figures shown with fig.show() or displayed as the last expression of a code block [#5701], with thanks to @​larsoner for the contribution!
    • The scaper now warns once (instead of failing the build) when static image export is unavailable
  • The sphinx-gallery scraper no longer scrapes files belonging to other examples during parallel builds [#5701], with thanks to @​larsoner for the contribution!

Updated

  • Update plotly.js from version 4.0.0 to version 4.1.1 [#5722, #5730]. See the plotly.js release notes for v4.1.0 and v4.1.1 for details. Notable changes include:
    • Add an opt-in modebar button for downloading Plotly figures as JSON [#7990, #8022]
    • Add legend.groupdoubleclick to set the group behavior for a legend double-click [#7997]
    • Increase default double-click delay threshold to 500ms (from 300) [#8014]
    • Fix issue with per-point marker color for hover labels in scattergl, quiver traces [#8027]
    • Update maplibre-gl to v6 to address CVE-2026-85061 [#8035]
      • Note: Safari 15, Chrome 56, Firefox 51 and later are now required for map traces
  • Update hex_to_rgb function to raise error for invalid-length hex codes, and emit warning for hex codes containing alpha [#5729], with thanks to @​dylanpulver for the contribution!

v7.0.0

Fixed

  • Fix hex_to_rgb parsing of 3-digit shorthand hexadecimal colors such as #FFF [#5662], with thanks to @​genrichez for the contribution!
  • Improve px.*_map() auto-fitting behavior when zoom and center are not specified [#5686]
  • Add <!doctype html> to the to_html() template to comply with modern web standards [#5693], with thanks to @​mishrakushal for the contribution!
  • Apply histfunc/z aggregation to marginal_x/marginal_y="histogram" subplots in density_heatmap/density_contour, instead of always showing raw bin counts [#3521], with thanks to @​lucasjamar for the contribution!
  • Fix mpl_to_plotly<...

    Description has been truncated

@dependabot
build(deps): bump the production group with 17 updates
7dad9b0 
Bumps the production group with 17 updates:

| Package | From | To |
| --- | --- | --- |
| [numpy](https://github.com/numpy/numpy) | `2.4.2` | `2.5.4` |
| [pydantic](https://github.com/pydantic/pydantic) | `2.12.5` | `2.14.1` |
| [scikit-fingerprints](https://github.com/scikit-fingerprints/scikit-fingerprints) | `1.18.0` | `2.1.0` |
| [scikit-learn](https://github.com/scikit-learn/scikit-learn) | `1.8.0` | `1.9.1` |
| [scipy](https://github.com/scipy/scipy) | `1.17.1` | `1.18.1` |
| [umap-learn](https://github.com/lmcinnes/umap) | `0.5.11` | `0.5.12` |
| [mlflow-skinny](https://github.com/mlflow/mlflow) | `3.10.0` | `3.17.2` |
| [plotly](https://github.com/plotly/plotly.py) | `6.5.2` | `7.1.0` |
| [mlflow](https://github.com/mlflow/mlflow) | `3.10.0` | `3.17.2` |
| [fastparquet](https://github.com/dask/fastparquet) | `2026.3.0` | `2026.9.0` |
| [torch-geometric](https://github.com/pyg-team/pytorch_geometric) | `2.7.0` | `2.8.1` |
| [optuna](https://github.com/optuna/optuna) | `4.7.0` | `5.0.0` |
| [optuna-integration](https://github.com/optuna/optuna-integration) | `4.7.0` | `5.0.0` |
| [transformers](https://github.com/huggingface/transformers) | `4.57.6` | `5.21.0` |
| [chemprop](https://github.com/chemprop/chemprop) | `2.2.2` | `2.3.1` |
| [myst-parser](https://github.com/executablebooks/MyST-Parser) | `4.0.1` | `5.1.0` |
| [sphinx-autoapi](https://github.com/readthedocs/sphinx-autoapi) | `3.8.0` | `3.8.1` |


Updates `numpy` from 2.4.2 to 2.5.4
- [Release notes](https://github.com/numpy/numpy/releases)
- [Changelog](https://github.com/numpy/numpy/blob/main/doc/RELEASE_WALKTHROUGH.rst)
- [Commits](numpy/numpy@v2.4.2...v2.5.4)

Updates `pydantic` from 2.12.5 to 2.14.1
- [Release notes](https://github.com/pydantic/pydantic/releases)
- [Changelog](https://github.com/pydantic/pydantic/blob/main/HISTORY.md)
- [Commits](pydantic/pydantic@v2.12.5...v2.14.1)

Updates `scikit-fingerprints` from 1.18.0 to 2.1.0
- [Release notes](https://github.com/scikit-fingerprints/scikit-fingerprints/releases)
- [Commits](MLCIL/scikit-fingerprints@v1.18.0...v2.1.0)

Updates `scikit-learn` from 1.8.0 to 1.9.1
- [Release notes](https://github.com/scikit-learn/scikit-learn/releases)
- [Commits](scikit-learn/scikit-learn@1.8.0...1.9.1)

Updates `scipy` from 1.17.1 to 1.18.1
- [Release notes](https://github.com/scipy/scipy/releases)
- [Commits](scipy/scipy@v1.17.1...v1.18.1)

Updates `umap-learn` from 0.5.11 to 0.5.12
- [Release notes](https://github.com/lmcinnes/umap/releases)
- [Changelog](https://github.com/lmcinnes/umap/blob/master/doc/release_notes.rst)
- [Commits](lmcinnes/umap@release-0.5.11...release-0.5.12)

Updates `mlflow-skinny` from 3.10.0 to 3.17.2
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v3.10.0...v3.17.2)

Updates `plotly` from 6.5.2 to 7.1.0
- [Release notes](https://github.com/plotly/plotly.py/releases)
- [Changelog](https://github.com/plotly/plotly.py/blob/main/CHANGELOG.md)
- [Commits](plotly/plotly.py@v6.5.2...v7.1.0)

Updates `mlflow` from 3.10.0 to 3.17.2
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v3.10.0...v3.17.2)

Updates `fastparquet` from 2026.3.0 to 2026.9.0
- [Commits](dask/fastparquet@2026.3.0...2026.9.0)

Updates `torch-geometric` from 2.7.0 to 2.8.1
- [Release notes](https://github.com/pyg-team/pytorch_geometric/releases)
- [Changelog](https://github.com/pyg-team/pytorch_geometric/blob/master/CHANGELOG.md)
- [Commits](pyg-team/pytorch_geometric@2.7.0...2.8.1)

Updates `optuna` from 4.7.0 to 5.0.0
- [Release notes](https://github.com/optuna/optuna/releases)
- [Commits](optuna/optuna@v4.7.0...v5.0.0)

Updates `optuna-integration` from 4.7.0 to 5.0.0
- [Release notes](https://github.com/optuna/optuna-integration/releases)
- [Commits](optuna/optuna-integration@v4.7.0...v5.0.0)

Updates `transformers` from 4.57.6 to 5.21.0
- [Release notes](https://github.com/huggingface/transformers/releases)
- [Commits](huggingface/transformers@v4.57.6...v5.21)

Updates `chemprop` from 2.2.2 to 2.3.1
- [Release notes](https://github.com/chemprop/chemprop/releases)
- [Commits](chemprop/chemprop@v2.2.2...v2.3.1)

Updates `myst-parser` from 4.0.1 to 5.1.0
- [Release notes](https://github.com/executablebooks/MyST-Parser/releases)
- [Changelog](https://github.com/executablebooks/MyST-Parser/blob/master/CHANGELOG.md)
- [Commits](executablebooks/MyST-Parser@v4.0.1...v5.1.0)

Updates `sphinx-autoapi` from 3.8.0 to 3.8.1
- [Release notes](https://github.com/readthedocs/sphinx-autoapi/releases)
- [Changelog](https://github.com/readthedocs/sphinx-autoapi/blob/main/CHANGELOG.rst)
- [Commits](readthedocs/sphinx-autoapi@v3.8.0...v3.8.1)

---
updated-dependencies:
- dependency-name: numpy
  dependency-version: 2.5.4
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: production
- dependency-name: pydantic
  dependency-version: 2.14.1
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: production
- dependency-name: scikit-fingerprints
  dependency-version: 2.1.0
  dependency-type: direct:production
  update-type: version-update:semver-major
  dependency-group: production
- dependency-name: scikit-learn
  dependency-version: 1.9.1
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: production
- dependency-name: scipy
  dependency-version: 1.18.1
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: production
- dependency-name: umap-learn
  dependency-version: 0.5.12
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: production
- dependency-name: mlflow-skinny
  dependency-version: 3.17.2
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: production
- dependency-name: plotly
  dependency-version: 7.1.0
  dependency-type: direct:production
  update-type: version-update:semver-major
  dependency-group: production
- dependency-name: mlflow
  dependency-version: 3.17.2
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: production
- dependency-name: fastparquet
  dependency-version: 2026.9.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: production
- dependency-name: torch-geometric
  dependency-version: 2.8.1
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: production
- dependency-name: optuna
  dependency-version: 5.0.0
  dependency-type: direct:production
  update-type: version-update:semver-major
  dependency-group: production
- dependency-name: optuna-integration
  dependency-version: 5.0.0
  dependency-type: direct:production
  update-type: version-update:semver-major
  dependency-group: production
- dependency-name: transformers
  dependency-version: 5.21.0
  dependency-type: direct:production
  update-type: version-update:semver-major
  dependency-group: production
- dependency-name: chemprop
  dependency-version: 2.3.1
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: production
- dependency-name: myst-parser
  dependency-version: 5.1.0
  dependency-type: direct:production
  update-type: version-update:semver-major
  dependency-group: production
- dependency-name: sphinx-autoapi
  dependency-version: 3.8.1
  dependency-type: direct:production
  update-type: version-update:semver-patch
  dependency-group: production
...

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot Bot added dependencies Pull requests that update a dependency file python:uv Pull requests that update python:uv code labels Oct 30, 2026
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