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.
explicit build-backend workaround for pip build isolation bug
"AttributeError: 'module' object has no attribute 'legacy'" on pip install
httplib2/httplib2#169
feature: Http().redirect_codes set, works after follow(_all)_redirects check
This allows one line workaround for old gcloud library that uses 308
response without redirect semantics.
httplib2/httplib2#156
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)
++++++++++++++++
Update to Unicode 15.1.0
String codec name is now "idna2008" as overriding the system codec
"idna" was not working.
Fix typing error for codec encoding
"setup.cfg" has been added for this release due to some downstream
lack of adherence to PEP 517. Should be removed in a future release
so please prepare accordingly.
Removed reliance on a symlink for the "idna-data" tool to comport
with PEP 517 and the Python Packaging User Guide for sdist archives.
Added security reporting protocol for project
Thanks Jon Ribbens, Diogo Teles Sant'Anna, Wu Tingfeng for contributions
to this release.
3.4 (2022-09-14)
++++++++++++++++
Update to Unicode 15.0.0
Migrate to pyproject.toml for build information (PEP 621)
Correct another instance where generic exception was raised instead of
IDNAError for malformed input
Source distribution uses zeroized file ownership for improved
reproducibility
Thanks to Seth Michael Larson for contributions to this release.
3.3 (2021-10-13)
++++++++++++++++
Update to Unicode 14.0.0
Update to in-line type annotations
Throw IDNAError exception correctly for some malformed input
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.
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.
Versions of Requests between v2.3.0 and v2.30.0 are vulnerable to potential
forwarding of Proxy-Authorization headers to destination servers when
following HTTPS redirects.
When proxies are defined with user info (https://user:pass@proxy:8080), Requests
will construct a Proxy-Authorization header that is attached to the request to
authenticate with the proxy.
In cases where Requests receives a redirect response, it previously reattached
the Proxy-Authorization header incorrectly, resulting in the value being
sent through the tunneled connection to the destination server. Users who rely on
defining their proxy credentials in the URL are strongly encouraged to upgrade
to Requests 2.31.0+ to prevent unintentional leakage and rotate their proxy
credentials once the change has been fully deployed.
Users who do not use a proxy or do not supply their proxy credentials through
the user information portion of their proxy URL are not subject to this
vulnerability.
Versions of Requests between v2.3.0 and v2.30.0 are vulnerable to potential
forwarding of Proxy-Authorization headers to destination servers when
following HTTPS redirects.
When proxies are defined with user info (https://user:pass@proxy:8080), Requests
will construct a Proxy-Authorization header that is attached to the request to
authenticate with the proxy.
In cases where Requests receives a redirect response, it previously reattached
the Proxy-Authorization header incorrectly, resulting in the value being
sent through the tunneled connection to the destination server. Users who rely on
defining their proxy credentials in the URL are strongly encouraged to upgrade
to Requests 2.31.0+ to prevent unintentional leakage and rotate their proxy
credentials once the change has been fully deployed.
Users who do not use a proxy or do not supply their proxy credentials through
the user information portion of their proxy URL are not subject to this
vulnerability.
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:
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.
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:
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
Made body stripped from HTTP requests changing the request method to GET after HTTP 303 "See Other" redirect responses. (GHSA-g4mx-q9vg-27p4)
1.26.17
Added the Cookie header to the list of headers to strip from requests when redirecting to a different host. As before, different headers can be set via Retry.remove_headers_on_redirect. (GHSA-v845-jxx5-vc9f)
1.26.16
Fixed thread-safety issue where accessing a PoolManager with many distinct origins would cause connection pools to be closed while requests are in progress (#2954)
Fixed parsing of port 0 (zero) returning None, instead of 0 (#2850)
Removed deprecated HTTPResponse.getheaders() calls in urllib3.contrib module.
1.26.13
Deprecated the HTTPResponse.getheaders() and HTTPResponse.getheader() methods.
Fixed an issue where parsing a URL with leading zeroes in the port would be rejected even when the port number after removing the zeroes was valid.
Fixed a deprecation warning when using cryptography v39.0.0.
Removed the <4 in the Requires-Python packaging metadata field.
1.26.12
Deprecated the urllib3[secure] extra and the urllib3.contrib.pyopenssl module. Both will be removed in v2.x. See this GitHub issue for justification and info on how to migrate.
1.26.11
If you or your organization rely on urllib3 consider supporting us via GitHub Sponsors.
:closed_lock_with_key: This is the first release to be signed with Sigstore! You can verify the distributables using the .sig and <...
_Description has been truncated_
dependabot[bot]
commented
3 months ago
Bumps the pip group with 11 updates in the /models/claim_breadth directory:
1.8.21.11.32018.1.182023.7.220.16.00.18.31.10.11.53.20.9.20.19.02.63.71.14.21.22.02.18.42.31.01.7.02.11.11.221.26.180.14.13.0.3Updates
avrofrom 1.8.2 to 1.11.3Release notes
Sourced from avro's releases.
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Commits
Updates
certififrom 2018.1.18 to 2023.7.22Commits
8fb96ed2023.07.22afe7722Bump actions/setup-python from 4.6.1 to 4.7.0 (#230)2038739Bump dessant/lock-threads from 3.0.0 to 4.0.1 (#229)44df761Hash pin Actions and enable dependabot (#228)8b3d7ba2023.05.0753da240ci: Add Python 3.12-dev to the testing (#224)c2fc3b1Create a Security Policy (#222)c211ef4Set up permissions to github workflows (#218)2087de5Don't let deprecation warning fail CI (#219)e0b9fc5remove paragraphs about 1024-bit roots from READMEUpdates
futurefrom 0.16.0 to 0.18.3Release notes
Sourced from future's releases.
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Changelog
Sourced from future's changelog.
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Commits
af1db97Merge pull request #613 from PythonCharmers/lwan/0.18.3-release079ee9bPrepare for 0.18.3 release02f7a81Merge pull request #610 from wshanks/wshanks-patch-1c91d70bBackport fix for bpo-3880480523f3Merge pull request #569 from jmadler/master5e5af71Merge pull request #582 from r3m0t/patch-617e4bbdMerge pull request #596 from abjonnes/fix-print-trailing-comma1b427baMerge branch 'xZise-official-count' into masterc8eb497Merge branch 'official-count' of https://github.com/xZise/python-future into ...dffc579Fix bug in fix_print.py fixerUpdates
grpciofrom 1.10.1 to 1.53.2Release notes
Sourced from grpcio's releases.
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Changelog
Sourced from grpcio's changelog.
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)Updates
httplib2from 0.9.2 to 0.19.0Changelog
Sourced from httplib2's changelog.
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Commits
81e80d0v0.19.0 releasec3aed1efix release script, interactive partbd9ee25parse auth headers using pyparsing instead of regexp33090abinitial fuzz testing integration with OSS-Fuzz595e248auth: WSSE token needs to be string not bytes9bf300cv0.18.1 releasecb2940aexplicit build-backend workaround pip build isolation bug 626494f48efcheck-manifest build tool828c26dSecurity Policy8373177v0.18.0 releaseUpdates
idnafrom 2.6 to 3.7Release notes
Sourced from idna's releases.
Changelog
Sourced from idna's changelog.
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Commits
1d365e1Release v3.7c1b3154Merge pull request #172 from kjd/optimize-contextj0394ec7Merge branch 'master' into optimize-contextjcd58a23Merge pull request #152 from elliotwutingfeng/dev5beb28bMore efficient resolution of joiner contexts1b12148Update ossf/scorecard-action to v2.3.1d516b87Update Github actions/checkout to v4c095c75Merge branch 'master' into dev60a0a4cFix typo in GitHub Actions workflow key5918a0eMerge branch 'master' into devUpdates
numpyfrom 1.14.2 to 1.22.0Release notes
Sourced from numpy's releases.
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Commits
4adc87dMerge pull request #20685 from charris/prepare-for-1.22.0-releasefd66547REL: Prepare for the NumPy 1.22.0 release.125304bwipc283859Merge pull request #20682 from charris/backport-204165399c03Merge pull request #20681 from charris/backport-20954f9c45f8Merge pull request #20680 from charris/backport-20663794b36fUpdate armccompiler.pyd93b14eUpdate test_public_api.py7662c07Update init.py311ab52Update armccompiler.pyUpdates
requestsfrom 2.18.4 to 2.31.0Release notes
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Changelog
Sourced from requests's changelog.
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Commits
147c851v2.31.074ea7cfMerge pull request from GHSA-j8r2-6x86-q33q3022253test on pypy 3.8 and pypy 3.9 on windows and macos (#6424)b639e66test on py3.12 (#6448)d3d5044Fixed a small typo (#6452)2ad18e0v2.30.0f2629e9Remove strict parameter (#6434)87d63dev2.29.051716c4enable the warnings plugin (#6416)a7da1abtry on ubuntu 22.04 (#6418)Updates
tensorflowfrom 1.7.0 to 2.11.1Release notes
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Changelog
Sourced from tensorflow's changelog.
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Commits
a3e2c69Merge pull request #60016 from tensorflow/fix-relnotes13b85dcFix release notes48b18dbMerge pull request #60014 from tensorflow/disable-test-that-oomseea48f5Disable a test that results in OOM+segfaulta632584Merge pull request #60000 from tensorflow/venkat-patch-393dea7aUpdate RELEASE.mda2ba9f1Updating Release.md with Legal Language for Release Notesfae41c7Merge pull request #59998 from tensorflow/fix-bad-cherrypick-again2757416Fix bad cherrypickc78616fMerge pull request #59992 from tensorflow/fix-2.11-buildUpdates
urllib3from 1.22 to 1.26.18Release notes
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