Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

chore(deps): update all dependencies #35

Closed
wants to merge 1 commit into from
Closed

Conversation

renovate[bot]
Copy link
Contributor

@renovate renovate bot commented Oct 1, 2022

Mend Renovate

This PR contains the following updates:

Package Change Age Adoption Passing Confidence Type Update
certifi ==2022.6.15 -> ==2022.9.24 age adoption passing confidence minor
email-validator ==1.2.1 -> ==1.3.0 age adoption passing confidence minor
idna (changelog) ==3.3 -> ==3.4 age adoption passing confidence minor
importlib-metadata ==4.12.0 -> ==5.0.0 age adoption passing confidence major
jenkins/jenkins 2.346.3-jdk11 -> 2.361.2-jdk11 age adoption passing confidence final minor
jsonschema (changelog) ==4.15.0 -> ==4.16.0 age adoption passing confidence minor
marshmallow (changelog) ==3.17.1 -> ==3.18.0 age adoption passing confidence minor
mypy (source, changelog) ^0.971 -> ^0.982 age adoption passing confidence dev-dependencies minor
numpy (source) ==1.23.2 -> ==1.23.4 age adoption passing confidence patch
pyjwt ==2.4.0 -> ==2.6.0 age adoption passing confidence minor
pymongo ==4.2.0 -> ==4.3.2 age adoption passing confidence minor
python-dotenv ==0.20.0 -> ==0.21.0 age adoption passing confidence minor
pytz ==2022.2.1 -> ==2022.5 age adoption passing confidence minor
zipp ==3.8.1 -> ==3.9.0 age adoption passing confidence minor

Release Notes

certifi/python-certifi

v2022.9.24

Compare Source

v2022.9.14

Compare Source

v2022.6.15.2

Compare Source

v2022.6.15.1

Compare Source

JoshData/python-email-validator

v1.3.0

Compare Source

  • Deliverability checks now check for 'v=spf1 -all' SPF records as a way to reject more bad domains.
  • Special use domain names now raise EmailSyntaxError instead of EmailUndeliverableError since they are performed even if check_deliverability is off.
  • New module-level attributes are added to override the default values of the keyword arguments and the special-use domains list.
  • The keyword arguments of the public methods are now marked as keyword-only, ending support for Python 2.x.
  • pyIsEmail's test cases are added to the tests.
  • Recommend that check_deliverability be set to False for validation on login pages.
  • Added an undocumented globally_deliverable option.
kjd/idna

v3.4

Compare Source

python/importlib_metadata

v5.0.0

Compare Source

======

v4.13.0

Compare Source

=======

  • #​396: Added compatibility for PathDistributions originating
    from Python 3.8 and 3.9.
python-jsonschema/jsonschema

v4.16.0

Compare Source

=======

  • Improve the base URI behavior when resolving a $ref to a resolution URI
    which is different from the resolved schema's declared $id.
  • Accessing jsonschema.draftN_format_checker is deprecated. Instead, if you
    want access to the format checker itself, it is exposed as
    jsonschema.validators.DraftNValidator.FORMAT_CHECKER on any
    jsonschema.protocols.Validator.
marshmallow-code/marshmallow

v3.18.0

Compare Source

python/mypy

v0.982

Compare Source

v0.981

Compare Source

numpy/numpy

v1.23.4

Compare Source

NumPy 1.23.4 Release Notes

NumPy 1.23.4 is a maintenance release that fixes bugs discovered after
the 1.23.3 release and keeps the build infrastructure current. The main
improvements are fixes for some annotation corner cases, a fix for a
long time nested_iters memory leak, and a fix of complex vector dot
for very large arrays. The Python versions supported for this release
are 3.8-3.11.

Note that the mypy version needs to be 0.981+ if you test using Python
3.10.7, otherwise the typing tests will fail.

Contributors

A total of 8 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.

  • Bas van Beek
  • Charles Harris
  • Matthew Barber
  • Matti Picus
  • Ralf Gommers
  • Ross Barnowski
  • Sebastian Berg
  • Sicheng Zeng +

Pull requests merged

A total of 13 pull requests were merged for this release.

  • #​22368: BUG: Add __array_api_version__ to numpy.array_api namespace
  • #​22370: MAINT: update sde toolkit to 9.0, fix download link
  • #​22382: BLD: use macos-11 image on azure, macos-1015 is deprecated
  • #​22383: MAINT: random: remove get_info from "extending with Cython"...
  • #​22384: BUG: Fix complex vector dot with more than NPY_CBLAS_CHUNK elements
  • #​22387: REV: Loosen lookfor's import try/except again
  • #​22388: TYP,ENH: Mark numpy.typing protocols as runtime checkable
  • #​22389: TYP,MAINT: Change more overloads to play nice with pyright
  • #​22390: TST,TYP: Bump mypy to 0.981
  • #​22391: DOC: Update delimiter param description.
  • #​22392: BUG: Memory leaks in numpy.nested_iters
  • #​22413: REL: Prepare for the NumPy 1.23.4 release.
  • #​22424: TST: Fix failing aarch64 wheel builds.

Checksums

MD5
90a3d95982490cfeeef22c0f7cbd874f  numpy-1.23.4-cp310-cp310-macosx_10_9_x86_64.whl
c3cae63394db6c82fd2cb5700fc5917d  numpy-1.23.4-cp310-cp310-macosx_11_0_arm64.whl
b3ff0878de205f56c38fd7dcab80081f  numpy-1.23.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
e2b086ca2229209f2f996c2f9a38bf9c  numpy-1.23.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
44cc8bb112ca737520cf986fff92dfb0  numpy-1.23.4-cp310-cp310-win32.whl
21c8e5fdfba2ff953e446189379cf0c9  numpy-1.23.4-cp310-cp310-win_amd64.whl
27445a9c85977cb8efa682a4b993347f  numpy-1.23.4-cp311-cp311-macosx_10_9_x86_64.whl
11ef4b7dfdaa37604cb881f3ca4459db  numpy-1.23.4-cp311-cp311-macosx_11_0_arm64.whl
b3c77344274f91514f728a454fd471fa  numpy-1.23.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
43aef7f984cd63d95c11fb74dd59ef0b  numpy-1.23.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
637fe21b585228c9670d6e002bf8047f  numpy-1.23.4-cp311-cp311-win32.whl
f529edf9b849d6e3b8cdb5120ae5b81a  numpy-1.23.4-cp311-cp311-win_amd64.whl
76c61ce36317a7e509663829c6844fd9  numpy-1.23.4-cp38-cp38-macosx_10_9_x86_64.whl
2133f6893eef41cd9331c7d0271044c4  numpy-1.23.4-cp38-cp38-macosx_11_0_arm64.whl
5ccb3aa6fb8cb9e20ec336e315d01dec  numpy-1.23.4-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
da71f34a4df0b98e4d9e17906dd57b07  numpy-1.23.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
a318978f51fb80a17c2381e39194e906  numpy-1.23.4-cp38-cp38-win32.whl
eac810d6bc43830bf151ea55cd0ded93  numpy-1.23.4-cp38-cp38-win_amd64.whl
4cf0a6007abe42564c7380dbf92a26ce  numpy-1.23.4-cp39-cp39-macosx_10_9_x86_64.whl
2e005bedf129ce8bafa6f550537f3740  numpy-1.23.4-cp39-cp39-macosx_11_0_arm64.whl
10aa210311fcd19a03f6c5495824a306  numpy-1.23.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
6301298a67999657a0878b64eeed09f2  numpy-1.23.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
76144e575a3c3863ea22e03cdf022d8a  numpy-1.23.4-cp39-cp39-win32.whl
8291dd66ef5451b4db2da55c21535757  numpy-1.23.4-cp39-cp39-win_amd64.whl
7cc095b18690071828b5b620d5ec40e7  numpy-1.23.4-pp38-pypy38_pp73-macosx_10_9_x86_64.whl
63742f15e8bfa215c893136bbfc6444f  numpy-1.23.4-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
4ed382e55abc09c89a34db047692f6a6  numpy-1.23.4-pp38-pypy38_pp73-win_amd64.whl
d9ffd2c189633486ec246e61d4b947a0  numpy-1.23.4.tar.gz
SHA256
95d79ada05005f6f4f337d3bb9de8a7774f259341c70bc88047a1f7b96a4bcb2  numpy-1.23.4-cp310-cp310-macosx_10_9_x86_64.whl
926db372bc4ac1edf81cfb6c59e2a881606b409ddc0d0920b988174b2e2a767f  numpy-1.23.4-cp310-cp310-macosx_11_0_arm64.whl
c237129f0e732885c9a6076a537e974160482eab8f10db6292e92154d4c67d71  numpy-1.23.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
a8365b942f9c1a7d0f0dc974747d99dd0a0cdfc5949a33119caf05cb314682d3  numpy-1.23.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
2341f4ab6dba0834b685cce16dad5f9b6606ea8a00e6da154f5dbded70fdc4dd  numpy-1.23.4-cp310-cp310-win32.whl
d331afac87c92373826af83d2b2b435f57b17a5c74e6268b79355b970626e329  numpy-1.23.4-cp310-cp310-win_amd64.whl
488a66cb667359534bc70028d653ba1cf307bae88eab5929cd707c761ff037db  numpy-1.23.4-cp311-cp311-macosx_10_9_x86_64.whl
ce03305dd694c4873b9429274fd41fc7eb4e0e4dea07e0af97a933b079a5814f  numpy-1.23.4-cp311-cp311-macosx_11_0_arm64.whl
8981d9b5619569899666170c7c9748920f4a5005bf79c72c07d08c8a035757b0  numpy-1.23.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
7a70a7d3ce4c0e9284e92285cba91a4a3f5214d87ee0e95928f3614a256a1488  numpy-1.23.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
5e13030f8793e9ee42f9c7d5777465a560eb78fa7e11b1c053427f2ccab90c79  numpy-1.23.4-cp311-cp311-win32.whl
7607b598217745cc40f751da38ffd03512d33ec06f3523fb0b5f82e09f6f676d  numpy-1.23.4-cp311-cp311-win_amd64.whl
7ab46e4e7ec63c8a5e6dbf5c1b9e1c92ba23a7ebecc86c336cb7bf3bd2fb10e5  numpy-1.23.4-cp38-cp38-macosx_10_9_x86_64.whl
a8aae2fb3180940011b4862b2dd3756616841c53db9734b27bb93813cd79fce6  numpy-1.23.4-cp38-cp38-macosx_11_0_arm64.whl
8c053d7557a8f022ec823196d242464b6955a7e7e5015b719e76003f63f82d0f  numpy-1.23.4-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
a0882323e0ca4245eb0a3d0a74f88ce581cc33aedcfa396e415e5bba7bf05f68  numpy-1.23.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
dada341ebb79619fe00a291185bba370c9803b1e1d7051610e01ed809ef3a4ba  numpy-1.23.4-cp38-cp38-win32.whl
0fe563fc8ed9dc4474cbf70742673fc4391d70f4363f917599a7fa99f042d5a8  numpy-1.23.4-cp38-cp38-win_amd64.whl
c67b833dbccefe97cdd3f52798d430b9d3430396af7cdb2a0c32954c3ef73894  numpy-1.23.4-cp39-cp39-macosx_10_9_x86_64.whl
f76025acc8e2114bb664294a07ede0727aa75d63a06d2fae96bf29a81747e4a7  numpy-1.23.4-cp39-cp39-macosx_11_0_arm64.whl
12ac457b63ec8ded85d85c1e17d85efd3c2b0967ca39560b307a35a6703a4735  numpy-1.23.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
95de7dc7dc47a312f6feddd3da2500826defdccbc41608d0031276a24181a2c0  numpy-1.23.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
f2f390aa4da44454db40a1f0201401f9036e8d578a25f01a6e237cea238337ef  numpy-1.23.4-cp39-cp39-win32.whl
f260da502d7441a45695199b4e7fd8ca87db659ba1c78f2bbf31f934fe76ae0e  numpy-1.23.4-cp39-cp39-win_amd64.whl
61be02e3bf810b60ab74e81d6d0d36246dbfb644a462458bb53b595791251911  numpy-1.23.4-pp38-pypy38_pp73-macosx_10_9_x86_64.whl
296d17aed51161dbad3c67ed6d164e51fcd18dbcd5dd4f9d0a9c6055dce30810  numpy-1.23.4-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
4d52914c88b4930dafb6c48ba5115a96cbab40f45740239d9f4159c4ba779962  numpy-1.23.4-pp38-pypy38_pp73-win_amd64.whl
ed2cc92af0efad20198638c69bb0fc2870a58dabfba6eb722c933b48556c686c  numpy-1.23.4.tar.gz

v1.23.3

Compare Source

NumPy 1.23.3 Release Notes

NumPy 1.23.3 is a maintenance release that fixes bugs discovered after
the 1.23.2 release. There is no major theme for this release, the main
improvements are for some downstream builds and some annotation corner
cases. The Python versions supported for this release are 3.8-3.11.

Note that we will move to MacOS 11 for the NumPy 1.23.4 release, the
10.15 version currently used will no longer be supported by our build
infrastructure at that point.

Contributors

A total of 16 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.

  • Aaron Meurer
  • Bas van Beek
  • Charles Harris
  • Ganesh Kathiresan
  • Gavin Zhang +
  • Iantra Solari+
  • Jyn Spring 琴春 +
  • Matti Picus
  • Rafael Cardoso Fernandes Sousa
  • Rafael Sousa +
  • Ralf Gommers
  • Rin Cat (鈴猫) +
  • Saransh Chopra +
  • Sayed Adel
  • Sebastian Berg
  • Serge Guelton

Pull requests merged

A total of 14 pull requests were merged for this release.

  • #​22136: BLD: Add Python 3.11 wheels to aarch64 build
  • #​22148: MAINT: Update setup.py for Python 3.11.
  • #​22155: CI: Test NumPy build against old versions of GCC(6, 7, 8)
  • #​22156: MAINT: support IBM i system
  • #​22195: BUG: Fix circleci build
  • #​22214: BUG: Expose heapsort algorithms in a shared header
  • #​22215: BUG: Support using libunwind for backtrack
  • #​22216: MAINT: fix an incorrect pointer type usage in f2py
  • #​22220: BUG: change overloads to play nice with pyright.
  • #​22221: TST,BUG: Use fork context to fix MacOS savez test
  • #​22222: TYP,BUG: Reduce argument validation in C-based __class_getitem__
  • #​22223: TST: ensure np.equal.reduce raises a TypeError
  • #​22224: BUG: Fix the implementation of numpy.array_api.vecdot
  • #​22230: BUG: Better report integer division overflow (backport)

Checksums

MD5
a60bf0b1d440bf18d87c49409036d05a  numpy-1.23.3-cp310-cp310-macosx_10_9_x86_64.whl
59b43423a692f5351c6a43b852b210d7  numpy-1.23.3-cp310-cp310-macosx_11_0_arm64.whl
f482a4be6954b1b606320f0ffc1995dd  numpy-1.23.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
a82e2ecc4060a37dae5424e624eabfe3  numpy-1.23.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
84916178e5f4d073d0008754cba7f300  numpy-1.23.3-cp310-cp310-win32.whl
605da65b9b66dfce8b62d847cb3841f7  numpy-1.23.3-cp310-cp310-win_amd64.whl
57cf29f781be955a9cd0de8d07fbce56  numpy-1.23.3-cp311-cp311-macosx_10_9_x86_64.whl
f395dcf622dff0ba44777cbae0442189  numpy-1.23.3-cp311-cp311-macosx_11_0_arm64.whl
55d6a6439913ba84ad89268e0ad59fa0  numpy-1.23.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
202bc3a8617f479ebe60ca0dec29964b  numpy-1.23.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
a42c3d058bcef47b26841bf9472a89bf  numpy-1.23.3-cp311-cp311-win32.whl
237dbd94e5529065c0c5cc4e47ceeb7e  numpy-1.23.3-cp311-cp311-win_amd64.whl
d0587d5b28d3fa7e0ec8fd3df76e4bd4  numpy-1.23.3-cp38-cp38-macosx_10_9_x86_64.whl
054234695ed3d955fb01f661db2c14fc  numpy-1.23.3-cp38-cp38-macosx_11_0_arm64.whl
4e75ac61e34f1bf23e7cbd6e2bfc7a32  numpy-1.23.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
29ccb3a732027ee1abe23a9562c32d0c  numpy-1.23.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
12817838edc1e1bea27df79f3a83da5d  numpy-1.23.3-cp38-cp38-win32.whl
ef430e830a9fea7d8db0218b901671f6  numpy-1.23.3-cp38-cp38-win_amd64.whl
b001f7e17df798f9b949bbe259924c77  numpy-1.23.3-cp39-cp39-macosx_10_9_x86_64.whl
bc1782f5d79187d63d14ed69a6a411e9  numpy-1.23.3-cp39-cp39-macosx_11_0_arm64.whl
f8fb0178bc34a198d5ce4e166076e1fc  numpy-1.23.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
fb80d38c37aae1e4d416cd4de068ff0a  numpy-1.23.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
318d0a2a27b7e361295c0382a0ff4a94  numpy-1.23.3-cp39-cp39-win32.whl
880dc73de09fccda0650e9404fa83608  numpy-1.23.3-cp39-cp39-win_amd64.whl
3b5a51f78718a1a82d2750ec159f9acf  numpy-1.23.3-pp38-pypy38_pp73-macosx_10_9_x86_64.whl
56a0c90a303979d5bf8fc57e86e57ccb  numpy-1.23.3-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
5338d997a3178750834e742a257dfa4a  numpy-1.23.3-pp38-pypy38_pp73-win_amd64.whl
6efc60a3f6c1b74c849d53fbcc07807b  numpy-1.23.3.tar.gz
SHA256
c9f707b5bb73bf277d812ded9896f9512a43edff72712f31667d0a8c2f8e71ee  numpy-1.23.3-cp310-cp310-macosx_10_9_x86_64.whl
ffcf105ecdd9396e05a8e58e81faaaf34d3f9875f137c7372450baa5d77c9a54  numpy-1.23.3-cp310-cp310-macosx_11_0_arm64.whl
0ea3f98a0ffce3f8f57675eb9119f3f4edb81888b6874bc1953f91e0b1d4f440  numpy-1.23.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
004f0efcb2fe1c0bd6ae1fcfc69cc8b6bf2407e0f18be308612007a0762b4089  numpy-1.23.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
98dcbc02e39b1658dc4b4508442a560fe3ca5ca0d989f0df062534e5ca3a5c1a  numpy-1.23.3-cp310-cp310-win32.whl
39a664e3d26ea854211867d20ebcc8023257c1800ae89773cbba9f9e97bae036  numpy-1.23.3-cp310-cp310-win_amd64.whl
1f27b5322ac4067e67c8f9378b41c746d8feac8bdd0e0ffede5324667b8a075c  numpy-1.23.3-cp311-cp311-macosx_10_9_x86_64.whl
2ad3ec9a748a8943e6eb4358201f7e1c12ede35f510b1a2221b70af4bb64295c  numpy-1.23.3-cp311-cp311-macosx_11_0_arm64.whl
bdc9febce3e68b697d931941b263c59e0c74e8f18861f4064c1f712562903411  numpy-1.23.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
301c00cf5e60e08e04d842fc47df641d4a181e651c7135c50dc2762ffe293dbd  numpy-1.23.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
7cd1328e5bdf0dee621912f5833648e2daca72e3839ec1d6695e91089625f0b4  numpy-1.23.3-cp311-cp311-win32.whl
8355fc10fd33a5a70981a5b8a0de51d10af3688d7a9e4a34fcc8fa0d7467bb7f  numpy-1.23.3-cp311-cp311-win_amd64.whl
bc6e8da415f359b578b00bcfb1d08411c96e9a97f9e6c7adada554a0812a6cc6  numpy-1.23.3-cp38-cp38-macosx_10_9_x86_64.whl
22d43376ee0acd547f3149b9ec12eec2f0ca4a6ab2f61753c5b29bb3e795ac4d  numpy-1.23.3-cp38-cp38-macosx_11_0_arm64.whl
a64403f634e5ffdcd85e0b12c08f04b3080d3e840aef118721021f9b48fc1460  numpy-1.23.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
efd9d3abe5774404becdb0748178b48a218f1d8c44e0375475732211ea47c67e  numpy-1.23.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
f8c02ec3c4c4fcb718fdf89a6c6f709b14949408e8cf2a2be5bfa9c49548fd85  numpy-1.23.3-cp38-cp38-win32.whl
e868b0389c5ccfc092031a861d4e158ea164d8b7fdbb10e3b5689b4fc6498df6  numpy-1.23.3-cp38-cp38-win_amd64.whl
09f6b7bdffe57fc61d869a22f506049825d707b288039d30f26a0d0d8ea05164  numpy-1.23.3-cp39-cp39-macosx_10_9_x86_64.whl
8c79d7cf86d049d0c5089231a5bcd31edb03555bd93d81a16870aa98c6cfb79d  numpy-1.23.3-cp39-cp39-macosx_11_0_arm64.whl
e5d5420053bbb3dd64c30e58f9363d7a9c27444c3648e61460c1237f9ec3fa14  numpy-1.23.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
d5422d6a1ea9b15577a9432e26608c73a78faf0b9039437b075cf322c92e98e7  numpy-1.23.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
c1ba66c48b19cc9c2975c0d354f24058888cdc674bebadceb3cdc9ec403fb5d1  numpy-1.23.3-cp39-cp39-win32.whl
78a63d2df1d947bd9d1b11d35564c2f9e4b57898aae4626638056ec1a231c40c  numpy-1.23.3-cp39-cp39-win_amd64.whl
17c0e467ade9bda685d5ac7f5fa729d8d3e76b23195471adae2d6a6941bd2c18  numpy-1.23.3-pp38-pypy38_pp73-macosx_10_9_x86_64.whl
91b8d6768a75247026e951dce3b2aac79dc7e78622fc148329135ba189813584  numpy-1.23.3-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
94c15ca4e52671a59219146ff584488907b1f9b3fc232622b47e2cf832e94fb8  numpy-1.23.3-pp38-pypy38_pp73-win_amd64.whl
51bf49c0cd1d52be0a240aa66f3458afc4b95d8993d2d04f0d91fa60c10af6cd  numpy-1.23.3.tar.gz
jpadilla/pyjwt

v2.6.0

Changed


Fixed
~~~~~

Added
~~~~~

v2.5.0

Compare Source

Changed


Fixed
~~~~~

- Invalidate token on the exact second the token expires `#&#8203;797 <https://github.com/jpadilla/pyjwt/pull/797>`_

Added
~~~~~
- Adding validation for `issued_at` when `iat > (now + leeway)` as `ImmatureSignatureError` by @&#8203;sriharan16 in https://github.com/jpadilla/pyjwt/pull/794
mongodb/mongo-python-driver

v4.3.2

Compare Source

Release notes: https://www.mongodb.com/community/forums/t/pymongo-4-3-2-released/194266

theskumar/python-dotenv

v0.21.0

Compare Source

Added
Fixed
jaraco/zipp

v3.9.0

Compare Source

======

  • #​81: Path objects are now pickleable if they've been
    constructed from pickleable objects. Any restored objects
    will re-construct the zip file with the original arguments.

Configuration

📅 Schedule: Branch creation - "before 7am on the first day of the month" (UTC), Automerge - At any time (no schedule defined).

🚦 Automerge: Disabled by config. Please merge this manually once you are satisfied.

Rebasing: Whenever PR becomes conflicted, or you tick the rebase/retry checkbox.

👻 Immortal: This PR will be recreated if closed unmerged. Get config help if that's undesired.


  • If you want to rebase/retry this PR, click this checkbox.

This PR has been generated by Mend Renovate. View repository job log here.

@renovate renovate bot force-pushed the renovate/all branch 5 times, most recently from a6df61a to d1f02b6 Compare October 5, 2022 12:57
@renovate renovate bot force-pushed the renovate/all branch 2 times, most recently from 67ddde3 to 79f3b79 Compare October 12, 2022 16:35
@renovate renovate bot force-pushed the renovate/all branch 2 times, most recently from 2610218 to fed6acb Compare October 18, 2022 15:16
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

1 participant