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Published 20 hours ago • verified publisher icon Business-Wizard

build(deps): bump the pip group group with 7 updates

Open dependabot[bot] opened this issue 11 months ago • 0 comments

Bumps the pip group group with 7 updates:

Package From To
flask 1.1.2 2.2.5
scikit-learn 0.23.2 1.0.1
tensorflow 2.7.2 2.11.1
fonttools 4.39.4 4.43.0
jinja2 2.11.3 3.1.3
pillow 9.5.0 10.2.0
werkzeug 1.0.1 3.0.1

Updates flask from 1.1.2 to 2.2.5

Release notes

Sourced from flask's releases.

2.2.5

This is a security fix release for the 2.2.x release branch. Note that 2.3.x is the currently supported release branch; please upgrade to the latest version if possible.

2.2.4

This is a fix release for the 2.2.x release branch.

2.2.3

This is a fix release for the 2.2.x release branch.

2.2.2

This is a fix release for the 2.2.0 feature release.

2.2.1

This is a fix release for the 2.2.0 feature release.

2.2.0

This is a feature release, which includes new features and removes previously deprecated code. The 2.2.x branch is now the supported bug fix branch, the 2.1.x branch will become a tag marking the end of support for that branch. We encourage everyone to upgrade, and to use a tool such as pip-tools to pin all dependencies and control upgrades.

2.1.3

2.1.2

This is a fix release for the 2.1.0 feature release.

2.1.1

This is a fix release for the 2.1.0 feature release.

... (truncated)

Changelog

Sourced from flask's changelog.

Version 2.2.5

Released 2023-05-02

  • Update for compatibility with Werkzeug 2.3.3.
  • Set Vary: Cookie header when the session is accessed, modified, or refreshed.

Version 2.2.4

Released 2023-04-25

  • Update for compatibility with Werkzeug 2.3.

Version 2.2.3

Released 2023-02-15

  • Autoescape is enabled by default for .svg template files. :issue:4831
  • Fix the type of template_folder to accept pathlib.Path. :issue:4892
  • Add --debug option to the flask run command. :issue:4777

Version 2.2.2

Released 2022-08-08

  • Update Werkzeug dependency to >= 2.2.2. This includes fixes related to the new faster router, header parsing, and the development server. :pr:4754
  • Fix the default value for app.env to be "production". This attribute remains deprecated. :issue:4740

Version 2.2.1

Released 2022-08-03

  • Setting or accessing json_encoder or json_decoder raises a deprecation warning. :issue:4732

Version 2.2.0

... (truncated)

Commits

Updates scikit-learn from 0.23.2 to 1.0.1

Release notes

Sourced from scikit-learn's releases.

scikit-learn 1.0.1

We're happy to announce the 1.0.1 release with several bugfixes:

You can see the changelog here: https://scikit-learn.org/dev/whats_new/v1.0.html#version-1-0-1

You can upgrade with pip as usual:

pip install -U scikit-learn

The conda-forge builds will be available shortly, which you can then install using:

conda install -c conda-forge scikit-learn

scikit-learn 1.0

We're happy to announce the 1.0 release. You can read the release highlights under https://scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_0_0.html and the long version of the change log under https://scikit-learn.org/stable/whats_new/v1.0.html#changes-1-0

This version supports Python versions 3.7 to 3.9.

scikit-learn 0.24.2

We're happy to announce the 0.24.2 release with several bugfixes:

You can see the changelog here: https://scikit-learn.org/stable/whats_new/v0.24.html#version-0-24-2

You can upgrade with pip as usual:

pip install -U scikit-learn

The conda-forge builds will be available shortly, which you can then install using:

conda install -c conda-forge scikit-learn

scikit-learn 0.24.1

We're happy to announce the 0.24.1 release with several bugfixes:

You can see the changelog here: https://scikit-learn.org/stable/whats_new/v0.24.html#version-0-24-1

You can upgrade with pip as usual:

pip install -U scikit-learn

The conda-forge builds will be available shortly, which you can then install using:

conda install -c conda-forge scikit-learn

scikit-learn 0.24.0

We're happy to announce the 0.24 release. You can read the release highlights under https://scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_0_24_0.html and the long version of the change log under https://scikit-learn.org/stable/whats_new/v0.24.html#version-0-24-0

... (truncated)

Commits
  • 0d37891 Trigger wheel builder workflow: [cd build]
  • 7737cb9 DOC update the News section in website (#21417)
  • 8971a19 DOC Ensures that MultiTaskElasticNetCV passes numpydoc validation (#21405)
  • d6e24ee DOC Ensures that LabelSpreading passes numpydoc validation (#21414)
  • 14fda2f DOC Ensures that PassiveAggressiveRegressor passes numpydoc validation (#21413)
  • 112ae4e DOC Ensures that OrthogonalMatchingPursuitCV passes numpydoc validation (#21412)
  • cd927c0 FIX delete feature_names_in_ when refitting on a ndarray (#21389)
  • ae223ee bumpversion to 1.0.1
  • 9227162 MNT remove 1.1 changelog due to rebase conflict
  • 5d75547 MNT fix changelog 1.0.1 (#21416)
  • Additional commits viewable in compare view

Updates tensorflow from 2.7.2 to 2.11.1

Release notes

Sourced from tensorflow's releases.

TensorFlow 2.11.1

Release 2.11.1

Note: TensorFlow 2.10 was the last TensorFlow release that supported GPU on native-Windows. Starting with TensorFlow 2.11, you will need to install TensorFlow in WSL2, or install tensorflow-cpu and, optionally, try the TensorFlow-DirectML-Plugin.

  • Security vulnerability fixes will no longer be patched to this Tensorflow version. The latest Tensorflow version includes the security vulnerability fixes. You can update to the latest version (recommended) or patch security vulnerabilities yourself steps. You can refer to the release notes of the latest Tensorflow version for a list of newly fixed vulnerabilities. If you have any questions, please create a GitHub issue to let us know.

This release also introduces several vulnerability fixes:

TensorFlow 2.11.0

Release 2.11.0

Breaking Changes

  • The tf.keras.optimizers.Optimizer base class now points to the new Keras optimizer, while the old optimizers have been moved to the tf.keras.optimizers.legacy namespace.

    If you find your workflow failing due to this change, you may be facing one of the following issues:

    • Checkpoint loading failure. The new optimizer handles optimizer state differently from the old optimizer, which simplifies the logic of checkpoint saving/loading, but at the cost of breaking checkpoint backward compatibility in some cases. If you want to keep using an old checkpoint, please change your optimizer to tf.keras.optimizer.legacy.XXX (e.g. tf.keras.optimizer.legacy.Adam).
    • TF1 compatibility. The new optimizer, tf.keras.optimizers.Optimizer, does not support TF1 any more, so please use the legacy optimizer tf.keras.optimizer.legacy.XXX. We highly recommend migrating your workflow to TF2 for stable support and new features.
    • Old optimizer API not found. The new optimizer, tf.keras.optimizers.Optimizer, has a different set of public APIs from the old optimizer. These API changes are mostly related to getting rid of slot variables and TF1 support. Please check the API documentation to find alternatives to the missing API. If you must call the deprecated API, please change your optimizer to the legacy optimizer.
    • Learning rate schedule access. When using a tf.keras.optimizers.schedules.LearningRateSchedule, the new optimizer's learning_rate property returns the current learning rate value instead of a LearningRateSchedule object as before. If you need to access the LearningRateSchedule object, please use optimizer._learning_rate.
    • If you implemented a custom optimizer based on the old optimizer. Please set your optimizer to subclass tf.keras.optimizer.legacy.XXX. If you want to migrate to the new optimizer and find it does not support your optimizer, please file an issue in the Keras GitHub repo.
    • Errors, such as Cannot recognize variable.... The new optimizer requires all optimizer variables to be created at the first apply_gradients() or minimize() call. If your workflow calls the optimizer to update different parts of the model in multiple stages, please call optimizer.build(model.trainable_variables) before the training loop.
    • Timeout or performance loss. We don't anticipate this to happen, but if you see such issues, please use the legacy optimizer, and file an issue in the Keras GitHub repo.

    The old Keras optimizer will never be deleted, but will not see any new feature additions. New optimizers (for example, tf.keras.optimizers.Adafactor) will only be implemented based on the new tf.keras.optimizers.Optimizer base class.

  • tensorflow/python/keras code is a legacy copy of Keras since the TensorFlow v2.7 release, and will be deleted in the v2.12 release. Please remove any import of tensorflow.python.keras and use the public API with from tensorflow import keras or import tensorflow as tf; tf.keras.

Major Features and Improvements

... (truncated)

Changelog

Sourced from tensorflow's changelog.

Release 2.11.1

Note: TensorFlow 2.10 was the last TensorFlow release that supported GPU on native-Windows. Starting with TensorFlow 2.11, you will need to install TensorFlow in WSL2, or install tensorflow-cpu and, optionally, try the TensorFlow-DirectML-Plugin.

  • Security vulnerability fixes will no longer be patched to this Tensorflow version. The latest Tensorflow version includes the security vulnerability fixes. You can update to the latest version (recommended) or patch security vulnerabilities yourself steps. You can refer to the release notes of the latest Tensorflow version for a list of newly fixed vulnerabilities. If you have any questions, please create a GitHub issue to let us know.

This release also introduces several vulnerability fixes:

Release 2.11.0

Breaking Changes

  • tf.keras.optimizers.Optimizer now points to the new Keras optimizer, and old optimizers have moved to the tf.keras.optimizers.legacy namespace. If you find your workflow failing due to this change, you may be facing one of the following issues:

    • Checkpoint loading failure. The new optimizer handles optimizer state differently from the old optimizer, which simplies the logic of checkpoint saving/loading, but at the cost of breaking checkpoint backward compatibility in some cases. If you want to keep using an old checkpoint, please change your optimizer to tf.keras.optimizers.legacy.XXX (e.g. tf.keras.optimizers.legacy.Adam).
    • TF1 compatibility. The new optimizer does not support TF1 any more, so please use the legacy optimizer tf.keras.optimizer.legacy.XXX. We highly recommend to migrate your workflow to TF2 for stable support and new features.
    • API not found. The new optimizer has a different set of public APIs from the old optimizer. These API changes are mostly related to getting rid of slot variables and TF1 support. Please check the API

... (truncated)

Commits
  • a3e2c69 Merge pull request #60016 from tensorflow/fix-relnotes
  • 13b85dc Fix release notes
  • 48b18db Merge pull request #60014 from tensorflow/disable-test-that-ooms
  • eea48f5 Disable a test that results in OOM+segfault
  • a632584 Merge pull request #60000 from tensorflow/venkat-patch-3
  • 93dea7a Update RELEASE.md
  • a2ba9f1 Updating Release.md with Legal Language for Release Notes
  • fae41c7 Merge pull request #59998 from tensorflow/fix-bad-cherrypick-again
  • 2757416 Fix bad cherrypick
  • c78616f Merge pull request #59992 from tensorflow/fix-2.11-build
  • Additional commits viewable in compare view

Updates fonttools from 4.39.4 to 4.43.0

Release notes

Sourced from fonttools's releases.

4.43.0

  • [subset] Set up lxml XMLParser(resolve_entities=False) when parsing OT-SVG documents to prevent XML External Entity (XXE) attacks (9f61271dc): https://codeql.github.com/codeql-query-help/python/py-xxe/
  • [varLib.iup] Added workaround for a Cython bug in iup_delta_optimize that was leading to IUP tolerance being incorrectly initialised, resulting in sub-optimal deltas (60126435d, cython/cython#5732).
  • [varLib] Added new command-line entry point fonttools varLib.avar to add an avar table to an existing VF from axes mappings in a .designspace file (0a3360e52).
  • [instancer] Fixed bug whereby no longer used variation regions were not correctly pruned after VarData optimization (#3268).
  • Added support for Python 3.12 (#3283).

4.42.1

  • [t1Lib] Fixed several Type 1 issues (#3238, #3240).
  • [otBase/packer] Allow sharing tables reached by different offset sizes (#3241, #3236, 457f11c2).
  • [varLib/merger] Fix Cursive attachment merging error when all anchors are NULL (#3248, #3247).
  • [ttLib] Fixed warning when calling addMultilingualName and ttFont parameter was not passed on to findMultilingualName (#3253).

4.42.0

  • [varLib] Use sentinel value 0xFFFF to mark a glyph advance in hmtx/vmtx as non participating, allowing sparse masters to contain glyphs for variation purposes other than {H,V}VAR (#3235).
  • [varLib/cff] Treat empty glyphs in non-default masters as missing, thus not participating in CFF2 delta computation, similarly to how varLib already treats them for gvar (#3234).
  • Added varLib.avarPlanner script to deduce 'correct' avar v1 axis mappings based on glyph average weights (#3223).

4.41.1

  • [subset] Fixed perf regression in v4.41.0 by making NameRecordVisitor only visit tables that do contain nameID references (#3213, #3214).
  • [varLib.instancer] Support instancing fonts containing null ConditionSet offsets in FeatureVariationRecords (#3211, #3212).
  • [statisticsPen] Report font glyph-average weight/width and font-wide slant.
  • [fontBuilder] Fixed head.created date incorrectly set to 0 instead of the current timestamp, regression introduced in v4.40.0 (#3210).
  • [varLib.merger] Support sparse CursivePos masters (#3209).

4.41.0

  • [fontBuilder] Fixed bug in setupOS2 with default panose attribute incorrectly being set to a dict instead of a Panose object (#3201).
  • [name] Added method to removeUnusedNameRecords in the user range (#3185).
  • [varLib.instancer] Fixed issue with L4 instancing (moving default) (#3179).
  • [cffLib] Use latin1 so we can roundtrip non-ASCII in {Full,Font,Family}Name (#3202).
  • [designspaceLib] Mark as optional in docs (as it is in the code).
  • [glyf-1] Fixed drawPoints() bug whereby last cubic segment becomes quadratic (#3189, #3190).
  • [fontBuilder] Propagate the 'hidden' flag to the fvar Axis instance (#3184).
  • [fontBuilder] Update setupAvar() to also support avar 2, fixing _add_avar() call site (#3183).
  • Added new voltLib.voltToFea submodule (originally Tiro Typeworks' "Volto") for converting VOLT OpenType Layout sources to FEA format (#3164).

4.40.0

  • Published native binary wheels to PyPI for all the python minor versions and platform and architectures currently supported that would benefit from this. They will include precompiled Cython-accelerated modules (e.g. cu2qu) without requiring to compile them from source. The pure-python wheel and source distribution will continue to be published as always (pip will automatically chose them when no binary wheel is available for the given platform, e.g. pypy). Use pip install --no-binary=fonttools fonttools to expliclity request pip to install from the pure-python source.
  • [designspaceLib|varLib] Add initial support for specifying axis mappings and build avar2 table from those (#3123).
  • [feaLib] Support variable ligature caret position (#3130).
  • [varLib|glyf] Added option to --drop-implied-oncurves; test for impliable oncurve points either before or after rounding (#3146, #3147, #3155, #3156).
  • [TTGlyphPointPen] Don't error with empty contours, simply ignore them (#3145).
  • [sfnt] Fixed str vs bytes remnant of py3 transition in code dealing with de/compiling WOFF metadata (#3129).
  • [instancer-solver] Fixed bug when moving default instance with sparse masters (#3139, #3140).
  • [feaLib] Simplify variable scalars that don’t vary (#3132).
  • [pens] Added filter pen that explicitly emits closing line when lastPt != movePt (#3100).
  • [varStore] Improve optimize algorithm and better document the algorithm (#3124, #3127).
    Added quantization option (#3126).
  • Added CI workflow config file for building native binary wheels (#3121).
  • [fontBuilder] Added glyphDataFormat=0 option; raise error when glyphs contain cubic outlines but glyphDataFormat was not explicitly set to 1 (#3113, #3119).

... (truncated)

Changelog

Sourced from fonttools's changelog.

4.43.0 (released 2023-09-29)

  • [subset] Set up lxml XMLParser(resolve_entities=False) when parsing OT-SVG documents to prevent XML External Entity (XXE) attacks (9f61271dc): https://codeql.github.com/codeql-query-help/python/py-xxe/
  • [varLib.iup] Added workaround for a Cython bug in iup_delta_optimize that was leading to IUP tolerance being incorrectly initialised, resulting in sub-optimal deltas (60126435d, cython/cython#5732).
  • [varLib] Added new command-line entry point fonttools varLib.avar to add an avar table to an existing VF from axes mappings in a .designspace file (0a3360e52).
  • [instancer] Fixed bug whereby no longer used variation regions were not correctly pruned after VarData optimization (#3268).
  • Added support for Python 3.12 (#3283).

4.42.1 (released 2023-08-20)

  • [t1Lib] Fixed several Type 1 issues (#3238, #3240).
  • [otBase/packer] Allow sharing tables reached by different offset sizes (#3241, #3236).
  • [varLib/merger] Fix Cursive attachment merging error when all anchors are NULL (#3248, #3247).
  • [ttLib] Fixed warning when calling addMultilingualName and ttFont parameter was not passed on to findMultilingualName (#3253).

4.42.0 (released 2023-08-02)

  • [varLib] Use sentinel value 0xFFFF to mark a glyph advance in hmtx/vmtx as non participating, allowing sparse masters to contain glyphs for variation purposes other than {H,V}VAR (#3235).
  • [varLib/cff] Treat empty glyphs in non-default masters as missing, thus not participating in CFF2 delta computation, similarly to how varLib already treats them for gvar (#3234).
  • Added varLib.avarPlanner script to deduce 'correct' avar v1 axis mappings based on glyph average weights (#3223).

4.41.1 (released 2023-07-21)

  • [subset] Fixed perf regression in v4.41.0 by making NameRecordVisitor only visit tables that do contain nameID references (#3213, #3214).
  • [varLib.instancer] Support instancing fonts containing null ConditionSet offsets in FeatureVariationRecords (#3211, #3212).
  • [statisticsPen] Report font glyph-average weight/width and font-wide slant.
  • [fontBuilder] Fixed head.created date incorrectly set to 0 instead of the current timestamp, regression introduced in v4.40.0 (#3210).
  • [varLib.merger] Support sparse CursivePos masters (#3209).

4.41.0 (released 2023-07-12)

... (truncated)

Commits
  • 145460e Release 4.43.0
  • 64f3fd8 Update changelog [skip ci]
  • 7aea49e Merge pull request #3283 from hugovk/main
  • 4470c44 Bump requirements.txt to support Python 3.12
  • 0c87cba Bump scipy for Python 3.12 support
  • eda6fa5 Add support for Python 3.12
  • 0e033b0 Bump reportlab from 3.6.12 to 3.6.13 in /Doc
  • 6012643 [iup] Work around cython bug
  • b14268a [iup] Remove copy/pasta
  • 0a3360e [varLib.avar] New module to compile avar from .designspace file
  • Additional commits viewable in compare view

Updates jinja2 from 2.11.3 to 3.1.3

Release notes

Sourced from jinja2's releases.

3.1.3

This is a fix release for the 3.1.x feature branch.

3.1.2

This is a fix release for the 3.1.0 feature release.

3.1.1

3.1.0

This is a feature release, which includes new features and removes previously deprecated features. The 3.1.x branch is now the supported bugfix branch, the 3.0.x branch has become a tag marking the end of support for that branch. We encourage everyone to upgrade, and to use a tool such as pip-tools to pin all dependencies and control upgrades. We also encourage upgrading to MarkupSafe 2.1.1, the latest version at this time.

3.0.3

3.0.2

3.0.1

3.0.0

New major versions of all the core Pallets libraries, including Jinja 3.0, have been released! :tada:

This represents a significant amount of work, and there are quite a few changes. Be sure to carefully read the changelog, and use tools such as pip-compile and Dependabot to pin your dependencies and control your updates.

3.0.0rc2

Fixes an issue with the deprecated Markup subclass, #1401.

3.0.0rc1

Changelog

Sourced from jinja2's changelog.

Version 3.1.3

Released 2024-01-10

  • Fix compiler error when checking if required blocks in parent templates are empty. :pr:1858
  • xmlattr filter does not allow keys with spaces. GHSA-h5c8-rqwp-cp95
  • Make error messages stemming from invalid nesting of {% trans %} blocks more helpful. :pr:1918

Version 3.1.2

Released 2022-04-28

  • Add parameters to Environment.overlay to match __init__. :issue:1645
  • Handle race condition in FileSystemBytecodeCache. :issue:1654

Version 3.1.1

Released 2022-03-25

  • The template filename on Windows uses the primary path separator. :issue:1637

Version 3.1.0

Released 2022-03-24

  • Drop support for Python 3.6. :pr:1534

  • Remove previously deprecated code. :pr:1544

    • WithExtension and AutoEscapeExtension are built-in now.
    • contextfilter and contextfunction are replaced by pass_context. evalcontextfilter and evalcontextfunction are replaced by pass_eval_context. environmentfilter and environmentfunction are replaced by pass_environment.
    • Markup and escape should be imported from MarkupSafe.
    • Compiled templates from very old Jinja versions may need to be recompiled.
    • Legacy resolve mode for Context subclasses is no longer supported. Override resolve_or_missing instead of

... (truncated)

Commits

Updates pillow from 9.5.0 to 10.2.0

Release notes

Sourced from pillow's releases.

10.2.0

https://pillow.readthedocs.io/en/stable/releasenotes/10.2.0.html

Changes

... (truncated)

Changelog

Sourced from pillow's changelog.

10.2.0 (2024-01-02)

  • Add keep_rgb option when saving JPEG to prevent conversion of RGB colorspace #7553 [bgilbert, radarhere]

  • Trim glyph size in ImageFont.getmask() #7669, #7672 [radarhere, nulano]

  • Deprecate IptcImagePlugin helpers #7664 [nulano, hugovk, radarhere]

  • Allow uncompressed TIFF images to be saved in chunks #7650 [radarhere]

  • Concatenate multiple JPEG EXIF markers #7496 [radarhere]

  • Changed IPTC tile tuple to match other plugins #7661 [radarhere]

  • Do not assign new fp attribute when exiting context manager #7566 [radarhere]

  • Support arbitrary masks for uncompressed RGB DDS images #7589 [radarhere, akx]

  • Support setting ROWSPERSTRIP tag #7654 [radarhere]

  • Apply ImageFont.MAX_STRING_LENGTH to ImageFont.getmask() #7662 [radarhere]

  • Optimise ImageColor using functools.lru_cache #7657 [hugovk]

  • Restricted environment keys for ImageMath.eval() #7655 [wiredfool, radarhere]

  • Optimise ImageMo...

    Description has been truncated

dependabot[bot] avatar Mar 03 '24 01:03 dependabot[bot]