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Bump the pip group across 1 directory with 10 updates - #173

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Bump the pip group across 1 directory with 10 updates#173
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Bumps the pip group with 10 updates in the /backend/scripts directory:

Package From To
grpcio 1.21.1 1.53.2
numpy 1.16.4 1.22.0
pillow 6.0.0 10.3.0
pyyaml 5.1.1 5.4
tensorflow 1.14.0 2.11.1
werkzeug 0.15.4 3.0.3
certifi 2019.6.16 2023.7.22
idna 2.8 3.7
requests 2.22.0 2.32.0
urllib3 1.25.3 1.26.18

Updates grpcio from 1.21.1 to 1.53.2

Release notes

Sourced from grpcio's releases.

Release v1.53.2

This is release gRPC Core 1.53.2 (glockenspiel).

For gRPC documentation, see grpc.io. For previous releases, see Releases.

This release contains refinements, improvements, and bug fixes.

Core

Release v1.53.1

This is release gRPC Core 1.53.1 (glockenspiel).

For gRPC documentation, see grpc.io. For previous releases, see Releases.

This release contains refinements, improvements, and bug fixes.

Release v1.53.0

This is release 1.53.0 (glockenspiel) of gRPC Core.

For gRPC documentation, see grpc.io. For previous releases, see Releases.

This release contains refinements, improvements, and bug fixes, with highlights listed below.

Core

  • xDS: fix crash when removing the last endpoint from the last locality in weighted_target. (#32592)
  • filter stack: pass peer name up via recv_initial_metadata batch. (#31933)
  • [EventEngine] Add advice against blocking work in callbacks. (#32397)
  • [http2] Dont drop connections on metadata limit exceeded. (#32309)
  • xDS: reject aggregate cluster with empty cluster list. (#32238)
  • Fix Python epoll1 Fork Support. (#32196)
  • server: introduce ServerMetricRecorder API and move per-call reporting from a C++ interceptor to a C-core filter. (#32106)
  • [EventEngine] Add invalid handle types to the public API. (#32202)
  • [EventEngine] Refactoring the EventEngine Test Suite: Part 1. (#32127)
  • xDS: fix WeightedClusters total weight handling. (#32134)

C++

  • Update minimum MSVC version to 2019. (#32615)
  • Use CMake variables for paths in pkg-config files. (#31671)

... (truncated)

Changelog

Sourced from grpcio's changelog.

gRPC Release Schedule

Below is the release schedule for gRPC Java, Go and Core and its dependent languages C++, C#, Objective-C, PHP, Python and Ruby.

Releases are scheduled every six weeks on Tuesdays on a best effort basis. In some unavoidable situations a release may be delayed or released early or a language may skip a release altogether and do the next release to catch up with other languages. See the past releases in the links above. A six-week cycle gives us a good balance between delivering new features/fixes quickly and keeping the release overhead low.

The gRPC release support policy can be found here.

Releases are cut from release branches. For Core and Java repos, the release branch is cut two weeks before the scheduled release date. For Go, the branch is cut just before the release. An RC (release candidate) is published for Core and its dependent languages just after the branch cut. This RC is later promoted to release version if no further changes are made to the release branch. We do our best to keep head of master branch stable at all times regardless of release schedule. Daily build packages from master branch for C#, PHP, Python, Ruby and Protoc plugins are published on packages.grpc.io. If you depend on gRPC in production we recommend to set up your CI system to test the RCs and, if possible, the daily builds.

Names of gRPC releases are here.

Release Scheduled Branch Cut Scheduled Release Date
v1.17.0 Nov 19, 2018 Dec 4, 2018
v1.18.0 Jan 2, 2019 Jan 15, 2019
v1.19.0 Feb 12, 2019 Feb 26, 2019
v1.20.0 Mar 26, 2019 Apr 9, 2019
v1.21.0 May 7, 2019 May 21, 2019
v1.22.0 Jun 18, 2019 Jul 2, 2019
v1.23.0 Jul 30, 2019 Aug 13, 2019
v1.24.0 Sept 10, 2019 Sept 24, 2019
v1.25.0 Oct 22, 2019 Nov 5, 2019
v1.26.0 Dec 3, 2019 Dec 17, 2019
v1.27.0 Jan 14, 2020 Jan 28, 2020
v1.28.0 Feb 25, 2020 Mar 10, 2020
v1.29.0 Apr 7, 2020 Apr 21, 2020
v1.30.0 May 19, 2020 Jun 2, 2020
v1.31.0 Jul 14, 2020 Jul 28, 2020
v1.32.0 Aug 25, 2020 Sep 8, 2020
v1.33.0 Oct 6, 2020 Oct 20, 2020
v1.34.0 Nov 17, 2020 Dec 1, 2020
v1.35.0 Dec 29, 2020 Jan 12, 2021
v1.36.0 Feb 9, 2021 Feb 23, 2021
v1.37.0 Mar 23, 2021 Apr 6, 2021
v1.38.0 May 4, 2021 May 18, 2021
v1.39.0 Jun 15, 2021 Jun 29, 2021
v1.40.0 Jul 27, 2021 Aug 10, 2021
v1.41.0 Sep 7, 2021 Sep 21, 2021
v1.42.0 Oct 19, 2021 Nov 2, 2021
v1.43.0 Nov 30, 2021 Dec 14, 2021
v1.44.0 Jan 11, 2022 Jan 25, 2022
v1.45.0 Feb 22, 2022 Mar 8, 2022
Commits
  • afb307f [v1.53.x][Interop] Backport Python image update (#33864)
  • 7a9373b [Backport] [dependency] Restrict cython to less than 3.X (#33770)
  • fdb64a6 [v1.53][Build] Update Phusion baseimage (#33767) (#33836)
  • cdf4186 [PSM Interop] Legacy tests: fix xDS test client build (v1.53.x backport) (#33...
  • ce5b93a [PSM Interop] Legacy test builds always pull the driver from master (v1.53.x ...
  • b24b6ea [release] Bump release version to 1.53.2 (#33709)
  • 1e86ca5 [backport][iomgr][EventEngine] Improve server handling of file descriptor exh...
  • aff3066 [PSM interop] Don't fail url_map target if sub-target already failed (v1.53.x...
  • 539d75c [PSM interop] Don't fail target if sub-target already failed (#33222) (v1.53....
  • 3e79c88 [Release] Bump version to 1.53.1 (on v1.53.x branch) (#33047)
  • Additional commits viewable in compare view

Updates numpy from 1.16.4 to 1.22.0

Release notes

Sourced from numpy's releases.

v1.22.0

NumPy 1.22.0 Release Notes

NumPy 1.22.0 is a big release featuring the work of 153 contributors spread over 609 pull requests. There have been many improvements, highlights are:

  • Annotations of the main namespace are essentially complete. Upstream is a moving target, so there will likely be further improvements, but the major work is done. This is probably the most user visible enhancement in this release.
  • A preliminary version of the proposed Array-API is provided. This is a step in creating a standard collection of functions that can be used across application such as CuPy and JAX.
  • NumPy now has a DLPack backend. DLPack provides a common interchange format for array (tensor) data.
  • New methods for quantile, percentile, and related functions. The new methods provide a complete set of the methods commonly found in the literature.
  • A new configurable allocator for use by downstream projects.

These are in addition to the ongoing work to provide SIMD support for commonly used functions, improvements to F2PY, and better documentation.

The Python versions supported in this release are 3.8-3.10, Python 3.7 has been dropped. Note that 32 bit wheels are only provided for Python 3.8 and 3.9 on Windows, all other wheels are 64 bits on account of Ubuntu, Fedora, and other Linux distributions dropping 32 bit support. All 64 bit wheels are also linked with 64 bit integer OpenBLAS, which should fix the occasional problems encountered by folks using truly huge arrays.

Expired deprecations

Deprecated numeric style dtype strings have been removed

Using the strings "Bytes0", "Datetime64", "Str0", "Uint32", and "Uint64" as a dtype will now raise a TypeError.

(gh-19539)

Expired deprecations for loads, ndfromtxt, and mafromtxt in npyio

numpy.loads was deprecated in v1.15, with the recommendation that users use pickle.loads instead. ndfromtxt and mafromtxt were both deprecated in v1.17 - users should use numpy.genfromtxt instead with the appropriate value for the usemask parameter.

(gh-19615)

... (truncated)

Commits

Updates pillow from 6.0.0 to 10.3.0

Release notes

Sourced from pillow's releases.

10.3.0

https://pillow.readthedocs.io/en/stable/releasenotes/10.3.0.html

Changes

... (truncated)

Changelog

Sourced from pillow's changelog.

10.3.0 (2024-04-01)

  • CVE-2024-28219: Use strncpy to avoid buffer overflow #7928 [radarhere, hugovk]

  • Deprecate eval(), replacing it with lambda_eval() and unsafe_eval() #7927 [radarhere, hugovk]

  • Raise ValueError if seeking to greater than offset-sized integer in TIFF #7883 [radarhere]

  • Add --report argument to __main__.py to omit supported formats #7818 [nulano, radarhere, hugovk]

  • Added RGB to I;16, I;16L, I;16B and I;16N conversion #7918, #7920 [radarhere]

  • Fix editable installation with custom build backend and configuration options #7658 [nulano, radarhere]

  • Fix putdata() for I;16N on big-endian #7209 [Yay295, hugovk, radarhere]

  • Determine MPO size from markers, not EXIF data #7884 [radarhere]

  • Improved conversion from RGB to RGBa, LA and La #7888 [radarhere]

  • Support FITS images with GZIP_1 compression #7894 [radarhere]

  • Use I;16 mode for 9-bit JPEG 2000 images #7900 [scaramallion, radarhere]

  • Raise ValueError if kmeans is negative #7891 [radarhere]

  • Remove TIFF tag OSUBFILETYPE when saving using libtiff #7893 [radarhere]

  • Raise ValueError for negative values when loading P1-P3 PPM images #7882 [radarhere]

  • Added reading of JPEG2000 palettes #7870 [radarhere]

  • Added alpha_quality argument when saving WebP images #7872 [radarhere]

... (truncated)

Commits
  • 5c89d88 10.3.0 version bump
  • 63cbfcf Update CHANGES.rst [ci skip]
  • 2776126 Merge pull request #7928 from python-pillow/lcms
  • aeb51cb Merge branch 'main' into lcms
  • 5beb0b6 Update CHANGES.rst [ci skip]
  • cac6ffa Merge pull request #7927 from python-pillow/imagemath
  • f5eeeac Name as 'options' in lambda_eval and unsafe_eval, but '_dict' in deprecated eval
  • facf3af Added release notes
  • 2a93aba Use strncpy to avoid buffer overflow
  • a670597 Update CHANGES.rst [ci skip]
  • Additional commits viewable in compare view

Updates pyyaml from 5.1.1 to 5.4

Changelog

Sourced from pyyaml's changelog.

5.4 (2021-01-19)

5.3.1 (2020-03-18)

  • yaml/pyyaml#386 -- Prevents arbitrary code execution during python/object/new constructor

5.3 (2020-01-06)

5.2 (2019-12-02)

  • Repair incompatibilities introduced with 5.1. The default Loader was changed, but several methods like add_constructor still used the old default yaml/pyyaml#279 -- A more flexible fix for custom tag constructors yaml/pyyaml#287 -- Change default loader for yaml.add_constructor yaml/pyyaml#305 -- Change default loader for add_implicit_resolver, add_path_resolver
  • Make FullLoader safer by removing python/object/apply from the default FullLoader yaml/pyyaml#347 -- Move constructor for object/apply to UnsafeConstructor
  • Fix bug introduced in 5.1 where quoting went wrong on systems with sys.maxunicode <= 0xffff yaml/pyyaml#276 -- Fix logic for quoting special characters
  • Other PRs: yaml/pyyaml#280 -- Update CHANGES for 5.1

5.1.2 (2019-07-30)

  • Re-release of 5.1 with regenerated Cython sources to build properly for Python 3.8b2+
Commits
  • 58d0cb7 5.4 release
  • a60f7a1 Fix compatibility with Jython
  • ee98abd Run CI on PR base branch changes
  • ddf2033 constructor.timezone: _copy & deepcopy
  • fc914d5 Avoid repeatedly appending to yaml_implicit_resolvers
  • a001f27 Fix for CVE-2020-14343
  • fe15062 Add 3.9 to appveyor file for completeness sake
  • 1e1c7fb Add a newline character to end of pyproject.toml
  • 0b6b7d6 Start sentences and phrases for capital letters
  • c976915 Shell code improvements
  • Additional commits viewable in compare view

Updates tensorflow from 1.14.0 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 werkzeug from 0.15.4 to 3.0.3

Release notes

Sourced from werkzeug's releases.

3.0.3

This is the Werkzeug 3.0.3 security release, which fixes security issues and bugs but does not otherwise change behavior and should not result in breaking changes.

PyPI: https://pypi.org/project/Werkzeug/3.0.3/ Changes: https://werkzeug.palletsprojects.com/en/3.0.x/changes/#version-3-0-3 Milestone: https://github.com/pallets/werkzeug/milestone/35?closed=1

  • Only allow localhost, .localhost, 127.0.0.1, or the specified hostname when running the dev server, to make debugger requests. Additional hosts can be added by using the debugger middleware directly. The debugger UI makes requests using the full URL rather than only the path. GHSA-2g68-c3qc-8985
  • Make reloader more robust when "" is in sys.path. #2823
  • Better TLS cert format with adhoc dev certs. #2891
  • Inform Python < 3.12 how to handle itms-services URIs correctly, rather than using an overly-broad workaround in Werkzeug that caused some redirect URIs to be passed on without encoding. #2828
  • Type annotation for Rule.endpoint and other uses of endpoint is Any. #2836

3.0.2

This is a fix release for the 3.0.x feature branch.

3.0.1

This is a security release for the 3.0.x feature branch.

3.0.0

This is a feature release, which includes new features, removes previously deprecated code, and adds new deprecations. The 3.0.x branch is now the supported fix branch, the 2.3.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. Test with warnings treated as errors to be able to adapt to deprecation warnings early.

2.3.8

This is a security release for the 2.3.x feature branch.

2.3.7

This is a fix release for the 2.3.x feature branch.

2.3.6

This is a fix release for the 2.3.x feature branch.

2.3.5

This is a fix release for the 2.3.x feature branch.

... (truncated)

Changelog

Sourced from werkzeug's changelog.

Version 3.0.3

Released 2024-05-05

  • Only allow localhost, .localhost, 127.0.0.1, or the specified hostname when running the dev server, to make debugger requests. Additional hosts can be added by using the debugger middleware directly. The debugger UI makes requests using the full URL rather than only the path. :ghsa:2g68-c3qc-8985

  • Make reloader more robust when "" is in sys.path. :pr:2823

  • Better TLS cert format with adhoc dev certs. :pr:2891

  • Inform Python < 3.12 how to handle itms-services URIs correctly, rather than using an overly-broad workaround in Werkzeug that caused some redirect URIs to be passed on without encoding. :issue:2828

  • Type annotation for Rule.endpoint and other uses of endpoint is Any. :issue:2836

  • Make reloader more robust when "" is in sys.path. :pr:2823

Version 3.0.2

Released 2024-04-01

  • Ensure setting merge_slashes to False results in NotFound for repeated-slash requests against single slash routes. :issue:2834
  • Fix handling of TypeError in TypeConversionDict.get() to match ValueError. :issue:2843
  • Fix response_wrapper type check in test client. :issue:2831
  • Make the return type of MultiPartParser.parse more precise. :issue:2840
  • Raise an error if converter arguments cannot be parsed. :issue:2822

Version 3.0.1

Released 2023-10-24

  • Fix slow multipart parsing for large parts potentially enabling DoS attacks.

Version 3.0.0

Released 2023-09-30

  • Remove previously deprecated code. :pr:2768

... (truncated)

Commits

Updates certifi from 2019.6.16 to 2023.7.22

Commits

Updates idna from 2.8 to 3.7

Release notes

Sourced from idna's releases.

v3.7

What's Changed

  • Fix issue where specially crafted inputs to encode() could take exceptionally long amount of time to process. [CVE-2024-3651]

Thanks to Guido Vranken for reporting the issue.

Full Changelog: kjd/idna@v3.6...v3.7

Changelog

Sourced from idna's changelog.

3.7 (2024-04-11) ++++++++++++++++

  • Fix issue where specially crafted inputs to encode() could take exceptionally long amount of time to process. [CVE-2024-3651]

Thanks to Guido Vranken for reporting the issue.

3.6 (2023-11-25) ++++++++++++++++

  • Fix regression to include tests in source distribution.

3.5 (2023-11-24) ++++++++++++++++

    Description has been truncated

@dependabot
72bdd9c 
---
updated-dependencies:
- dependency-name: grpcio
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: numpy
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: pillow
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: pyyaml
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: tensorflow
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: werkzeug
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: certifi
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: idna
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: requests
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: urllib3
  dependency-type: direct:production
  dependency-group: pip
...

Signed-off-by: dependabot[bot] <[email protected]>
@dependabot dependabot Bot added dependencies Pull requests that update a dependency file python Pull requests that update Python code labels May 20, 2024
@dependabot @github

dependabot Bot commented on behalf of github Jun 17, 2024

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Superseded by #179.

@dependabot dependabot Bot closed this Jun 17, 2024
@dependabot
dependabot Bot deleted the dependabot/pip/backend/scripts/pip-aaa70fc907 branch June 17, 2024 22:48
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