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Bump the pip group across 1 directory with 5 updates#1
BayoAdejare merged 1 commit intomainfrom
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@dependabot dependabot bot commented on behalf of github Mar 19, 2026

Bumps the pip group with 5 updates in the / directory:

Package From To
scikit-learn 1.4.2 1.5.0
lightgbm 4.3.0 4.6.0
mlflow 2.13.0 3.9.0rc0
requests 2.32.2 2.32.4
geopandas 0.14.4 1.1.2

Updates scikit-learn from 1.4.2 to 1.5.0

Release notes

Sourced from scikit-learn's releases.

Scikit-learn 1.5.0

We're happy to announce the 1.5.0 release.

You can read the release highlights under https://scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_5_0.html and the long version of the change log under https://scikit-learn.org/stable/whats_new/v1.5.html

This version supports Python versions 3.9 to 3.12.

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

Updates lightgbm from 4.3.0 to 4.6.0

Release notes

Sourced from lightgbm's releases.

v4.6.0

Changes

💡 New Features

🔨 Breaking

  • [R-package] require lgb.Dataset, remove support for passing 'colnames' and 'categorical_feature' for lgb.train() and lgb.cv() @​jameslamb (#6714)
  • [python-package] support sub-classing scikit-learn estimators @​jameslamb (#6783)
  • [python-package] do not copy column-major numpy arrays when creating Dataset from list of arrays @​jmoralez (#6773)
  • [python-package] remove support for passing 'feature_name' and 'categorical_feature' through train() and cv() @​jameslamb (#6706)
  • [python-package] require scikit-learn>=0.24.2, make scikit-learn estimators compatible with scikit-learn>=1.6.0dev @​vnherdeiro (#6651)
  • [ci] Require CMake 3.28 and replace FetchContent_Populate with FetchContent_MakeAvailable @​StrikerRUS (#6550)

🚀 Efficiency Improvement

  • [python-package] do not copy column-major numpy arrays when predicting @​jmoralez (#6751)
  • [python-package] do not copy column-major numpy arrays when creating Dataset @​jmoralez (#6721)

🐛 Bug Fixes

  • [python-package] Separately check whether pyarrow and cffi are installed @​mlondschien (#6785)
  • [c++] Fixed Predictor lifecycle and trees initialization in Contrib mode @​AndreyOrb (#6778)
  • [python-package] Infer feature names from pyarrow.Table @​mlondschien (#6781)
  • [python-package] Fix inconsistency in predict() output shape for 1-tree models @​RektPunk (#6753)
  • [fix] resolve potential attack in linker connection building @​shiyu1994 (#6752)
  • [R-package] Avoid bashisms (non-POSIX code) in R-package/configure @​smoser (#6746)
  • [c++] fix parallel_tree_learner_split_info @​moming39 (#6738)
  • [c++] Fix dump_model() information for root node @​neNasko1 (#6569)
  • [cmake] [R-package] include R-for-macOS vendored libs dir in OpenMP search path (fixes #6628) @​jameslamb (#6629)
  • [R-package] only warn about early stopping and DART boosting being incompatible if early stopping was requested @​serkor1 (#6619)
  • [cmake] fixes static build for macos with OpenMP enabled (fixes #6601) @​Mottl (#6600)

📖 Documentation

... (truncated)

Commits
  • d02a01a release v4.6.0 (#6796)
  • d24260f [R-package] require lgb.Dataset, remove support for passing 'colnames' and 'c...
  • c6d90bc [python-package] support sub-classing scikit-learn estimators (#6783)
  • 768f642 [c++] update to fmt 11.1.2, fast_double_parser 0.8.0 (#6802)
  • 1531d87 [ci] fix valgrind workflow (#6816)
  • 188f1be [ci] validate pyproject file by json schema (#6813)
  • 81922a7 [ci] [python-package] update pre-commit hooks to latest versions (#6817)
  • 2db0b25 [python-package] Separately check whether pyarrow and cffi are installed ...
  • c9de57b [CUDA] fix setting of CUDA architectures and enable support for NVIDIA Blackw...
  • f2b959c [ci]: Bump release-drafter/release-drafter from 6.0.0 to 6.1.0 in the ci-depe...
  • Additional commits viewable in compare view

Updates mlflow from 2.13.0 to 3.9.0rc0

Release notes

Sourced from mlflow's releases.

v3.9.0rc0

We're excited to announce MLflow 3.9.0rc0, a pre-release including several notable updates:

Major New Features:

  • 🔮 MLflow Assistant: Figuring out the next steps to debug your apps and agents can be challenging. We're excited to introduce the MLflow Assistant, an in-product chatbot that can help you identify, diagnose, and fix issues. The assistant is backed by Claude Code, and directly passes context from the MLflow UI to Claude. Click on the floating "Assistant" button in the bottom right of the MLflow UI to get started!
  • 📈 Trace Overview Dashboard: You can now get insights into your agent's performance at a glance with the new "Overview" tab in GenAI experiments. Many pre-built statistics are available out of the box, including performance metrics (e.g. latency, request count), quality metrics (based on assessments), and tool call summaries. If there are any additional charts you'd like to see, please feel free to raise an issue in the MLflow repository!
  • ✨ AI Gateway: We're revamping our AI Gateway feature! AI Gateway provides a unified interface for your API requests, allowing you to route queries to your LLM provider(s) of choice. In MLflow 3.9.0rc0, the Gateway server is now located directly in the tracking server, so you don't need to spin up a new process. Additional features such as passthrough endpoints, traffic splits, and fallback models are also available, with more to come soon! For more detailed information, please take a look at the docs.
  • 🔎 Online Monitoring with LLM Judges: Configure LLM judges to automatically run on your traces, without having to write a line of code! You can either use one of our pre-defined judges, or provide your own prompt and instructions to create custom metrics. Head to the new "Judges" tab within the GenAI Experiment UI to get started.
  • 🤖 Judge Builder UI: Define and iterate on custom LLM judge prompts directly from the UI! Within the new "Judges" tab, you can create your own prompt for an LLM judge, and test-run it on your traces to see what the output would be. Once you're happy with it, you can either use it for online monitoring (as mentioned above), or use it via the Python SDK for your evals.
  • 🔗 Distributed Tracing: Trace context can now be propagated across different services and processes, allowing you to truly track request lifecycles from end to end. The related APIs are defined in the mlflow.tracing.distributed module (with more documentation to come soon).
  • 📚 MemAlign - a new judge optimizer algorithm: We're excited to introduce MemAlignOptimizer, a new algorithm that makes your judges smarter over time. It learns general guidelines from past feedback while dynamically retrieving relevant examples at runtime, giving you more accurate evaluations.

Stay tuned for the full release, which will be packed with even more features and bugfixes.

To try out this release candidate, please run:

pip install mlflow==3.9.0rc0

Please try it out and report any issues on the issue tracker.

v3.8.1

MLflow 3.8.1 includes several bug fixes and documentation updates.

Bug fixes:

Small bug fixes and documentation updates:

#19539, #19451, #19409, @​smoorjani; #19493, @​alkispoly-db

v3.8.0

MLflow 3.8.0 includes several major features and improvements

Major Features

  • ⚙️ Prompt Model Configuration: Prompts can now include model configuration, allowing you to associate specific model settings with prompt templates for more reproducible LLM workflows. (#18963, #19174, #19279, @​chenmoneygithub)
  • ⏳ In-Progress Trace Display: The Traces UI now supports displaying spans from in-progress traces with auto-polling, enabling real-time debugging and monitoring of long-running LLM applications. (#19265, @​B-Step62)
  • ⚖️ DeepEval and RAGAS Judges Integration: New get_judge API enables using DeepEval and RAGAS evaluation metrics as MLflow scorers, providing access to 20+ evaluation metrics including answer relevancy, faithfulness, and hallucination detection. (#18988, @​smoorjani, #19345, @​SomtochiUmeh)
  • 🛡️ Conversational Safety Scorer: New built-in scorer for evaluating safety of multi-turn conversations, analyzing entire conversation histories for hate speech, harassment, violence, and other safety concerns. (#19106, @​joelrobin18)
  • ⚡ Conversational Tool Call Efficiency Scorer: New built-in scorer for evaluating tool call efficiency in multi-turn agent interactions, detecting redundant calls, missing batching opportunities, and poor tool selections. (#19245, @​joelrobin18)

Important Notice

  • Collection of UI Telemetry. From MLflow 3.8.0 onwards, MLflow will collect anonymized data about UI interactions, similar to the telemetry we collect for the Python SDK. If you manage your own server, UI telemetry is automatically disabled by setting the existing environment variables: MLFLOW_DISABLE_TELEMETRY=true or DO_NOT_TRACK=true. If you do not manage your own server (e.g. you use a managed service or are not the admin), you can still opt out personally via the new "Settings" tab in the MLflow UI. For more information, please read the documentation on usage tracking.

... (truncated)

Changelog

Sourced from mlflow's changelog.

3.9.0rc0 (2026-01-15)

We're excited to announce MLflow 3.9.0rc0, a pre-release including several notable updates:

Major New Features:

  • 🔮 MLflow Assistant: Figuring out the next steps to debug your apps and agents can be challenging. We're excited to introduce the MLflow Assistant, an in-product chatbot that can help you identify, diagnose, and fix issues. The assistant is backed by Claude Code, and directly passes context from the MLflow UI to Claude. Click on the floating "Assistant" button in the bottom right of the MLflow UI to get started!
  • 📈 Trace Overview Dashboard: You can now get insights into your agent's performance at a glance with the new "Overview" tab in GenAI experiments. Many pre-built statistics are available out of the box, including performance metrics (e.g. latency, request count), quality metrics (based on assessments), and tool call summaries. If there are any additional charts you'd like to see, please feel free to raise an issue in the MLflow repository!
  • ✨ AI Gateway: We're revamping our AI Gateway feature! AI Gateway provides a unified interface for your API requests, allowing you to route queries to your LLM provider(s) of choice. In MLflow 3.9.0rc0, the Gateway server is now located directly in the tracking server, so you don't need to spin up a new process. Additional features such as passthrough endpoints, traffic splits, and fallback models are also available, with more to come soon! For more detailed information, please take a look at the docs.
  • 🔎 Online Monitoring with LLM Judges: Configure LLM judges to automatically run on your traces, without having to write a line of code! You can either use one of our pre-defined judges, or provide your own prompt and instructions to create custom metrics. Head to the new "Judges" tab within the GenAI Experiment UI to get started.
  • 🤖 Judge Builder UI: Define and iterate on custom LLM judge prompts directly from the UI! Within the new "Judges" tab, you can create your own prompt for an LLM judge, and test-run it on your traces to see what the output would be. Once you're happy with it, you can either use it for online monitoring (as mentioned above), or use it via the Python SDK for your evals.
  • 🔗 Distributed Tracing: Trace context can now be propagated across different services and processes, allowing you to truly track request lifecycles from end to end. The related APIs are defined in the mlflow.tracing.distributed module (with more documentation to come soon).
  • 📚 MemAlign - a new judge optimizer algorithm: We're excited to introduce MemAlignOptimizer, a new algorithm that makes your judges smarter over time. It learns general guidelines from past feedback while dynamically retrieving relevant examples at runtime, giving you more accurate evaluations.

Stay tuned for the full release, which will be packed with even more features and bugfixes.

To try out this release candidate, please run:

pip install mlflow==3.9.0rc0

3.8.1 (2025-12-26)

MLflow 3.8.1 includes several bug fixes and documentation updates.

Bug fixes:

Small bug fixes and documentation updates:

#19539, #19451, #19409, @​smoorjani; #19493, @​alkispoly-db

3.8.0 (2025-12-19)

MLflow 3.8.0 includes several major features and improvements

Major Features

  • ⚙️ Prompt Model Configuration: Prompts can now include model configuration, allowing you to associate specific model settings with prompt templates for more reproducible LLM workflows. (#18963, #19174, #19279, @​chenmoneygithub)
  • ⏳ In-Progress Trace Display: The Traces UI now supports displaying spans from in-progress traces with auto-polling, enabling real-time debugging and monitoring of long-running LLM applications. (#19265, @​B-Step62)
  • ⚖️ DeepEval Judges Integration: New get_judge API enables using DeepEval's evaluation metrics as MLflow scorers, providing access to 20+ evaluation metrics including answer relevancy, faithfulness, and hallucination detection. (#18988, @​smoorjani)
  • 🛡️ Conversational Safety Scorer: New built-in scorer for evaluating safety of multi-turn conversations, analyzing entire conversation histories for hate speech, harassment, violence, and other safety concerns. (#19106, @​joelrobin18)
  • ⚡ Conversational Tool Call Efficiency Scorer: New built-in scorer for evaluating tool call efficiency in multi-turn agent interactions, detecting redundant calls, missing batching opportunities, and poor tool selections. (#19245, @​joelrobin18)

Important Notice

  • Collection of UI Telemetry. From MLflow 3.8.0 onwards, MLflow will collect anonymized data about UI interactions, similar to the telemetry we collect for the Python SDK. If you manage your own server, UI telemetry is automatically disabled by setting the existing environment variables: MLFLOW_DISABLE_TELEMETRY=true or DO_NOT_TRACK=true. If you do not manage your own server (e.g. you use a managed service or are not the admin), you can still opt out personally via the new "Settings" tab in the MLflow UI. For more information, please read the documentation on usage tracking.

... (truncated)

Commits

Updates requests from 2.32.2 to 2.32.4

Release notes

Sourced from requests's releases.

v2.32.4

2.32.4 (2025-06-10)

Security

  • CVE-2024-47081 Fixed an issue where a maliciously crafted URL and trusted environment will retrieve credentials for the wrong hostname/machine from a netrc file. (#6965)

Improvements

  • Numerous documentation improvements

Deprecations

  • Added support for pypy 3.11 for Linux and macOS. (#6926)
  • Dropped support for pypy 3.9 following its end of support. (#6926)

v2.32.3

2.32.3 (2024-05-29)

Bugfixes

  • Fixed bug breaking the ability to specify custom SSLContexts in sub-classes of HTTPAdapter. (#6716)
  • Fixed issue where Requests started failing to run on Python versions compiled without the ssl module. (#6724)
Changelog

Sourced from requests's changelog.

2.32.4 (2025-06-10)

Security

  • CVE-2024-47081 Fixed an issue where a maliciously crafted URL and trusted environment will retrieve credentials for the wrong hostname/machine from a netrc file.

Improvements

  • Numerous documentation improvements

Deprecations

  • Added support for pypy 3.11 for Linux and macOS.
  • Dropped support for pypy 3.9 following its end of support.

2.32.3 (2024-05-29)

Bugfixes

  • Fixed bug breaking the ability to specify custom SSLContexts in sub-classes of HTTPAdapter. (#6716)
  • Fixed issue where Requests started failing to run on Python versions compiled without the ssl module. (#6724)
Commits
  • 021dc72 Polish up release tooling for last manual release
  • 821770e Bump version and add release notes for v2.32.4
  • 59f8aa2 Add netrc file search information to authentication documentation (#6876)
  • 5b4b64c Add more tests to prevent regression of CVE 2024 47081
  • 7bc4587 Add new test to check netrc auth leak (#6962)
  • 96ba401 Only use hostname to do netrc lookup instead of netloc
  • 7341690 Merge pull request #6951 from tswast/patch-1
  • 6716d7c remove links
  • a7e1c74 Update docs/conf.py
  • c799b81 docs: fix dead links to kenreitz.org
  • Additional commits viewable in compare view

Updates geopandas from 0.14.4 to 1.1.2

Release notes

Sourced from geopandas's releases.

Version 1.1.2

What's Changed

Bug fixes:

  • Fix an issue that caused an error in GeoDataFrame.from_features when there is no properties field (#3599).
  • Fix read_file and to_file errors (#3682)
  • Fix read_parquet with to_pandas_kwargs for complex (list/struct) arrow types (#3640)
  • value_counts on GeoSeries now preserves CRS in index (#3669)
  • Fix f-string placeholders appearing in error messages when pyogrio cannot be imported (#3682).
  • Fix read_parquet with to_pandas_kwargs for complex (list/struct) arrow types (#3640).
  • .to_json now provides a clearer error message when called on a GeoDataFrame without an active geometry column (#3648).
  • Calling del gdf["geometry"] now will downcast to a pd.DataFrame if there are no geometry columns left in the dataframe (#3648).
  • Fix SQL injection in to_postgis via geometry column name (#3681).

Full Changelog: geopandas/geopandas@v1.1.1...v1.1.2

v1.1.1

A patch release containing minor regression fixes.

What's Changed

Full Changelog: geopandas/geopandas@v1.1.0...v1.1.1

v1.1.0

Notes on dependencies:

  • GeoPandas 1.1 now requires Python 3.10 or greater and pandas 2.0, numpy 1.24, pyproj 3.5, are now the minimum required version for these dependencies. Furthermore, the minimum tested version for optional dependencies has been updated to fiona 1.8.21, scipy 1.9, matplotlib 3.7, mapclassify 2.5, folium 0.12 and SQLAlchemy 2.0. Older versions of these libraries may continue to work, but are no longer considered supported (#3371).

New features and improvements:

  • Added options to return the result of SpatialIndex.query in a form of a dense or a sparse boolean array. This adds optional dependency on scipy for the sparse output. Note that this also changes the previously undocumented behaviour of the output_format keyword (#1674).
  • Add grid_size parameter to union_all and dissolve (#3445).

... (truncated)

Changelog

Sourced from geopandas's changelog.

Version 1.1.2 (December 22, 2025)

Bug fixes:

  • Fix an issue that caused an error in GeoDataFrame.from_features when there is no properties field (#3599).
  • Fix read_file and to_file errors (#3682)
  • Fix read_parquet with to_pandas_kwargs for complex (list/struct) arrow types (#3640)
  • value_counts on GeoSeries now preserves CRS in index (#3669)
  • Fix f-string placeholders appearing in error messages when pyogrio cannot be imported (#3682).
  • Fix read_parquet with to_pandas_kwargs for complex (list/struct) arrow types (#3640).
  • .to_json now provides a clearer error message when called on a GeoDataFrame without an active geometry column (#3648).
  • Calling del gdf["geometry"] now will downcast to a pd.DataFrame if there are no geometry columns left in the dataframe (#3648).
  • Fix SQL injection in to_postgis via geometry column name (#3681).

Version 1.1.1 (June 27, 2025)

Bug fixes:

  • Fix regression in the GeoDataFrame constructor when np.nan is given as an only geometry (#3591).
  • Fix regression in overlay with how="identity" when input dataframes have column names that are equal (#3596).

Version 1.1.0 (June 1, 2025)

Notes on dependencies:

  • GeoPandas 1.1 now requires Python 3.10 or greater and pandas 2.0, numpy 1.24, pyproj 3.5, are now the minimum required version for these dependencies. Furthermore, the minimum tested version for optional dependencies has been updated to fiona 1.8.21, scipy 1.9, matplotlib 3.7, mapclassify 2.5, folium 0.12 and SQLAlchemy 2.0. Older versions of these libraries may continue to work, but are no longer considered supported (#3371).

New features and improvements:

  • Added options to return the result of SpatialIndex.query in a form of a dense or a sparse boolean array. This adds optional dependency on scipy for the sparse output. Note that this also changes the previously undocumented behaviour of the output_format keyword (#1674).
  • Add grid_size parameter to union_all and dissolve (#3445).
  • GeoDataFrame.plot now supports pd.Index as an input for the column keyword (#3463).
  • Added disjoint_subset union algorithm for union_all and dissolve (#3534).
  • Added constrained_delaunay_triangles method to GeoSeries/GeoDataFrame (#3552).
  • Added to_pandas_kwargs argument to from_arrow, read_parquet and read_feather to allow better control of conversion of non-geometric Arrow data to DataFrames (#3466).
  • Added is_valid_coverage and invalid_coverage_edges to GeoSeries/GeoDataFrame to allow validation of polygonal coverage (#3545).
  • Added maximum_inscribed_circle method from shapely to GeoSeries/GeoDataFrame (#3544).

... (truncated)

Commits
  • 81214bf RLS: backport fixes for 1.1.2 (#3693)
  • 62dd4a2 COMPAT: pandas 3 refactor breaks finalize (#3611) (#3621)
  • e9b58ce RLS: v1.1.1
  • c6bf8b3 MAINT: enable pydocstyle ruff rules - automatic and easy fixes (#3598)
  • 339c7f7 TST: use nadgrids=null to suppress influence of grid files (#3588)
  • 2a7fad9 REGR: overlay with identity doesn't handle equal input column names correctly...
  • 1a1585d REGR: fix GeoDataFrame constructor when np.nan given as only geometry (#3591)
  • c36eba0 RSL: changelog for 1.1.0 release (#3586)
  • 2d6b332 remove remote url xfail (#3585)
  • ce86559 DOC: Drafted new documentation page outlining how to create inset maps and in...
  • Additional commits viewable in compare view

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Bump the pip group across 1 directory with 5 updates
da8e6de 
Bumps the pip group with 5 updates in the / directory:

| Package | From | To |
| --- | --- | --- |
| [scikit-learn](https://github.com/scikit-learn/scikit-learn) | `1.4.2` | `1.5.0` |
| [lightgbm](https://github.com/microsoft/LightGBM) | `4.3.0` | `4.6.0` |
| [mlflow](https://github.com/mlflow/mlflow) | `2.13.0` | `3.9.0rc0` |
| [requests](https://github.com/psf/requests) | `2.32.2` | `2.32.4` |
| [geopandas](https://github.com/geopandas/geopandas) | `0.14.4` | `1.1.2` |



Updates `scikit-learn` from 1.4.2 to 1.5.0
- [Release notes](https://github.com/scikit-learn/scikit-learn/releases)
- [Commits](scikit-learn/scikit-learn@1.4.2...1.5.0)

Updates `lightgbm` from 4.3.0 to 4.6.0
- [Release notes](https://github.com/microsoft/LightGBM/releases)
- [Commits](lightgbm-org/LightGBM@v4.3.0...v4.6.0)

Updates `mlflow` from 2.13.0 to 3.9.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.13.0...v3.9.0rc0)

Updates `requests` from 2.32.2 to 2.32.4
- [Release notes](https://github.com/psf/requests/releases)
- [Changelog](https://github.com/psf/requests/blob/main/HISTORY.md)
- [Commits](psf/requests@v2.32.2...v2.32.4)

Updates `geopandas` from 0.14.4 to 1.1.2
- [Release notes](https://github.com/geopandas/geopandas/releases)
- [Changelog](https://github.com/geopandas/geopandas/blob/main/CHANGELOG.md)
- [Commits](geopandas/geopandas@v0.14.4...v1.1.2)

---
updated-dependencies:
- dependency-name: scikit-learn
  dependency-version: 1.5.0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: lightgbm
  dependency-version: 4.6.0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: mlflow
  dependency-version: 3.9.0rc0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: requests
  dependency-version: 2.32.4
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: geopandas
  dependency-version: 1.1.2
  dependency-type: direct:production
  dependency-group: pip
...

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 Mar 19, 2026
@BayoAdejare BayoAdejare merged commit 8cb8e43 into main Mar 20, 2026
3 of 7 checks passed
@dependabot dependabot bot deleted the dependabot/pip/pip-8a5eea8a68 branch March 20, 2026 14:13
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