Skip to main content

Access your OS root certificates with the atmost ease

Project description

Wassima 🔒

I named this library after my wife, whom I trust the most. ❤️

Download Count Total

This project offers you a great alternative to certifi. It is a simple yet efficient wrapper around MIT licensed rustls-native-certs.

This project allows you to access your original operating system trust store, thus helping you to verify the remote peer certificates.

It works as-is out-of-the-box for MacOS, Windows, and Linux. Available on PyPy and Python 3.7+

If your particular operating system is not supported, we will make this happen! Open an issue on the repository.

For now, it is not supported to call your OS certificate verify native function. Use your Python native capabilities for it.

✨ Installation

Using pip:

pip install wassima -U

Get started

A) Create a SSLContext

import wassima

ctx = wassima.create_default_ssl_context()
# ... The context magically contain your system root CAs, the rest is up to you!

B) Retrieve individually root CAs in a binary form (DER)

import wassima

certs = wassima.root_der_certificates()
# ... It contains a list of certificate represented in bytes

C) Retrieve individually root CAs in a string form (PEM)

import wassima

certs = wassima.root_pem_certificates()
# ... It contains a list of certificate represented in string

D) Retrieve a single bundle (concatenated) list of PEM certificates like certifi does

import wassima

bundle = wassima.generate_ca_bundle()
# ... It contains a string with all of your root CAs!
# It is not a path but the file content itself.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

wassima-1.0.0.tar.gz (9.9 kB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

wassima-1.0.0-pp310-pypy310_pp73-win_amd64.whl (125.0 kB view details)

Uploaded PyPyWindows x86-64

wassima-1.0.0-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.1 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ x86-64

wassima-1.0.0-pp310-pypy310_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.3 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ s390x

wassima-1.0.0-pp310-pypy310_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.3 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ ppc64le

wassima-1.0.0-pp310-pypy310_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl (1.1 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ ARMv7l

wassima-1.0.0-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.2 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ ARM64

wassima-1.0.0-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl (1.2 MB view details)

Uploaded PyPymanylinux: glibc 2.5+ i686

wassima-1.0.0-pp310-pypy310_pp73-macosx_11_0_arm64.whl (260.1 kB view details)

Uploaded PyPymacOS 11.0+ ARM64

wassima-1.0.0-pp310-pypy310_pp73-macosx_10_7_x86_64.whl (267.7 kB view details)

Uploaded PyPymacOS 10.7+ x86-64

wassima-1.0.0-pp39-pypy39_pp73-win_amd64.whl (124.9 kB view details)

Uploaded PyPyWindows x86-64

wassima-1.0.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.1 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ x86-64

wassima-1.0.0-pp39-pypy39_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.3 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ s390x

wassima-1.0.0-pp39-pypy39_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.3 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ ppc64le

wassima-1.0.0-pp39-pypy39_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl (1.1 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ ARMv7l

wassima-1.0.0-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.2 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ ARM64

wassima-1.0.0-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl (1.2 MB view details)

Uploaded PyPymanylinux: glibc 2.5+ i686

wassima-1.0.0-pp39-pypy39_pp73-macosx_11_0_arm64.whl (260.1 kB view details)

Uploaded PyPymacOS 11.0+ ARM64

wassima-1.0.0-pp39-pypy39_pp73-macosx_10_7_x86_64.whl (267.7 kB view details)

Uploaded PyPymacOS 10.7+ x86-64

wassima-1.0.0-pp38-pypy38_pp73-win_amd64.whl (125.3 kB view details)

Uploaded PyPyWindows x86-64

wassima-1.0.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.2 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ x86-64

wassima-1.0.0-pp38-pypy38_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.3 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ s390x

wassima-1.0.0-pp38-pypy38_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.3 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ ppc64le

wassima-1.0.0-pp38-pypy38_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl (1.1 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ ARMv7l

wassima-1.0.0-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.2 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ ARM64

wassima-1.0.0-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.whl (1.2 MB view details)

Uploaded PyPymanylinux: glibc 2.5+ i686

wassima-1.0.0-pp38-pypy38_pp73-macosx_11_0_arm64.whl (260.0 kB view details)

Uploaded PyPymacOS 11.0+ ARM64

wassima-1.0.0-pp38-pypy38_pp73-macosx_10_7_x86_64.whl (268.0 kB view details)

Uploaded PyPymacOS 10.7+ x86-64

wassima-1.0.0-pp37-pypy37_pp73-win_amd64.whl (126.7 kB view details)

Uploaded PyPyWindows x86-64

wassima-1.0.0-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.2 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ x86-64

wassima-1.0.0-pp37-pypy37_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.3 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ s390x

wassima-1.0.0-pp37-pypy37_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.3 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ ppc64le

wassima-1.0.0-pp37-pypy37_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl (1.2 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ ARMv7l

wassima-1.0.0-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.2 MB view details)

Uploaded PyPymanylinux: glibc 2.17+ ARM64

wassima-1.0.0-pp37-pypy37_pp73-manylinux_2_5_i686.manylinux1_i686.whl (1.2 MB view details)

Uploaded PyPymanylinux: glibc 2.5+ i686

wassima-1.0.0-pp37-pypy37_pp73-macosx_11_0_arm64.whl (263.2 kB view details)

Uploaded PyPymacOS 11.0+ ARM64

wassima-1.0.0-pp37-pypy37_pp73-macosx_10_7_x86_64.whl (270.9 kB view details)

Uploaded PyPymacOS 10.7+ x86-64

wassima-1.0.0-cp37-abi3-win_amd64.whl (124.9 kB view details)

Uploaded CPython 3.7+Windows x86-64

wassima-1.0.0-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.7+manylinux: glibc 2.17+ x86-64

wassima-1.0.0-cp37-abi3-manylinux_2_17_s390x.manylinux2014_s390x.whl (1.3 MB view details)

Uploaded CPython 3.7+manylinux: glibc 2.17+ s390x

wassima-1.0.0-cp37-abi3-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (1.3 MB view details)

Uploaded CPython 3.7+manylinux: glibc 2.17+ ppc64le

wassima-1.0.0-cp37-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl (1.1 MB view details)

Uploaded CPython 3.7+manylinux: glibc 2.17+ ARMv7l

wassima-1.0.0-cp37-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.2 MB view details)

Uploaded CPython 3.7+manylinux: glibc 2.17+ ARM64

wassima-1.0.0-cp37-abi3-manylinux_2_5_i686.manylinux1_i686.whl (1.2 MB view details)

Uploaded CPython 3.7+manylinux: glibc 2.5+ i686

wassima-1.0.0-cp37-abi3-macosx_11_0_arm64.whl (259.8 kB view details)

Uploaded CPython 3.7+macOS 11.0+ ARM64

wassima-1.0.0-cp37-abi3-macosx_10_7_x86_64.whl (267.7 kB view details)

Uploaded CPython 3.7+macOS 10.7+ x86-64

File details

Details for the file wassima-1.0.0.tar.gz.

File metadata

  • Download URL: wassima-1.0.0.tar.gz
  • Upload date:
  • Size: 9.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: maturin/1.2.3

File hashes

Hashes for wassima-1.0.0.tar.gz
Algorithm Hash digest
SHA256 0627b99bd8f61fbb03d9be8f4c02607920cdc958318f1668a43769b386ee769b
MD5 f218f3bc3b8fe22dd44eec5ea5459ece
BLAKE2b-256 28b94dbae3ead921ab0ff07d65afc27998cbf7a232f92a740587acc0dfd1cd13

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp310-pypy310_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp310-pypy310_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 23d5e7ce6065d3bcbc75dd3e58657f901f10fdb1c92cc24befb505d0e859c272
MD5 13e2b9a662cae1f7855782cd23a741ea
BLAKE2b-256 cf74dbebff5b11b1504b11ee03218da32afc66f3bd677eccf3c770c36c729d00

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 a9812c6afe5f5922e8f6d70c2ff2d74cb0df9df5f0e71aa77701f0820fe344e1
MD5 39b85376a32210324817079c20bf91fa
BLAKE2b-256 6c1353e7d07527a650bd6896ed3a206cbe1b49f6348112e22f764dd898bba787

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp310-pypy310_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp310-pypy310_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 bb22d5e9023e2c9821f562985cf0132eaaf805ee57831dac0ca7e2cbfc02d091
MD5 7d3088314bacf862cae428f14b171741
BLAKE2b-256 22afba5827142d8fb4536ad920aebc376138ccd3b8bb91f8aeb5632ceb2b3fc2

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp310-pypy310_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp310-pypy310_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 33b308294cdd4654e9002b9ecf39e197fdf971a7b364926174a67162191165e8
MD5 8a0993f293fb5025d28a986be58491d6
BLAKE2b-256 7e72cb061d60fb598f46f8db50ff7e2beca2ad8449e804758a5385421dd25f6b

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp310-pypy310_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp310-pypy310_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl
Algorithm Hash digest
SHA256 90ada431610c58034120514c4a59480dee37d3bef6d88caf82133a6a21ee36cb
MD5 2ec66f4a812e2f7d6098e872d560a0b8
BLAKE2b-256 c2851a2084fe937b7da13aec3df3fe51aff23c4d7972ed4dbf81edd3d48a2c1a

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 6c98bc39c7ea7b2ee0c7d1f5c21792bbddd2dde919043f5ff2af5b4e8e8a5c74
MD5 b70ab6d08942fbbce0f2f3ff8e5b3d33
BLAKE2b-256 01506c1e4fa9ff1ab421aa3cc2f6a5e4cbf34d02aea18e16f4cc70f2490beae7

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 086f03e833aa5944d419a2dc6e5d41da1dce0c0eeadc99fc743728bdbca0df79
MD5 9e7d700369a5ec538b5b867ff1bba5ed
BLAKE2b-256 f622d7f94ac8fb808b7ab0282169a14bafd19ad54ac22817d3fb93279bd4989b

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp310-pypy310_pp73-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp310-pypy310_pp73-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 f94c32462a47d8ab52bbffb7bd01893894e49c23324742c34c107d13d56d930a
MD5 9f1a1825b5914736c8c18764a54dff1b
BLAKE2b-256 059a9af3b6d6234aafb5a066fd1d2c50642ef6a77b0c1c4ff9d709f3a691652e

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp310-pypy310_pp73-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp310-pypy310_pp73-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 af9e1c4d502988c313b1bba565742107d6182cd07d6468867a5efe21d367597f
MD5 ae75dd6bed6d2512bf12bb11d3438763
BLAKE2b-256 1fd200eb2151de0d58878be7f094b98f59b1fd6c16dcc34fd361e950090152c4

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp39-pypy39_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp39-pypy39_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 7ede2ad651c815ed690cde792c4ffce2fc0d713921d0ad5fbba6f46e5ebd43cc
MD5 7412a0a7876374132fe984fdc6f9fdd7
BLAKE2b-256 94bf92fbdacd84297131f82d7745934a9bbc3e9ca608b87bb451a306720ee486

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 a138e9cde9ce551174f211e0483397e0e4f08cf7dd5127d464197c1a10d63593
MD5 fa704c7dba7917a3a94844b349ca0a42
BLAKE2b-256 1bdb3c269e42dea8b75dabc55f7fe3a9515ec07c75d52c84412a82c5e119c8a5

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp39-pypy39_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp39-pypy39_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 2f4f1c4356e7b1ce77684f890744f43319c0329f23f584cc6848dbbed9396156
MD5 60d4bb5d8d7a0331cfb4d2dd293ab9f8
BLAKE2b-256 2a4f2541fbc5658bfafebd7bb84afd25c7f02bd0ffc32e393f4cc836b519db72

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp39-pypy39_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp39-pypy39_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 e03dcd94c0294c8d2ffe992e0fe3f18694bc1f72225a45a7a3e4abc9294d67b7
MD5 e971be418f5a285ba2000cb2462ec75c
BLAKE2b-256 bc51ad7d816dc463221ad8e5613c76b81272f2021b71460af5ab8c9d7ae7d957

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp39-pypy39_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp39-pypy39_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl
Algorithm Hash digest
SHA256 b45959d89964a9838f8da2fd1656ece6850db0aa2a6fe2165c84fad19484220e
MD5 0e72868fd852d6e292e0602b6dbfc677
BLAKE2b-256 364ec6e998c3ae77c967e8a5862a7cee23c54a62e7817ab80e62626bfa0a0c0c

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 3cd2332e5c709ccf09d691887d44be44bc250b163ed1b27f6bbc44802c5bfe4f
MD5 1a280f288f6c6f0f393f4d038f04f474
BLAKE2b-256 d1077a56c6733b300967f9daadf4de9ccf1e82367f61104b6a13070d74110014

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 36a21a6dcfceec0a28e42704f84b6aa38b0ada18d0491d2f062ae567892161d3
MD5 633f8e05cdbe0eef1363e6e8ce637b2d
BLAKE2b-256 7273684e38a3d49c3112fbd5466f0371bf9c84445d8771d31e691632974a349b

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp39-pypy39_pp73-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp39-pypy39_pp73-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 eb6800caf0fbe37d67fc58f409aab1aac14eeb7939b28c3a8eee89dc0890dbe3
MD5 c293bc62488a81269e944d8fa1b5eef9
BLAKE2b-256 b45e6e64092c8e44cb537b203904070c6e79ae52616c635c97431de95e3c0023

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp39-pypy39_pp73-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp39-pypy39_pp73-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 1040def755b2437443c66be2a80c7ed81c5cd107b12df4ae6bd83f657c82b441
MD5 7ea0bca293cc3c80d1492f341218006d
BLAKE2b-256 96b36e769049124cb7221766ac69c0f548998dfead6f8e80a155aae44aa4bf62

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp38-pypy38_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp38-pypy38_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 c745fb445150eb4ab9460ec67220b32d15ec654a4faca57fbd53e143da716f7a
MD5 0ce3ddc135e237915fa5ae99a53b713a
BLAKE2b-256 a66649f1a79fcb1efbb41cff1ac78648f160020530af8cd85e9c2ac96e00d3f3

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 68a269f51c03f333d1b727636e6557f1c9876f94d71cd2d530e362a3e5ae10f8
MD5 b8e5b07135f85a58d472b8cbc3954ec6
BLAKE2b-256 c239842d085a1d650fb868e3a979282c5448104840cb31fead520dddab28a168

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp38-pypy38_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp38-pypy38_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 b6007cbed2f0881f439a073c721e40c7763bfb78ac342fe75a5ba3ddac7894aa
MD5 799dcc794f581f595792cbecb9938aff
BLAKE2b-256 9d30f6f34cd9431184ad3bd93ff6f50e7e086c7239af0646167595a1016e11ce

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp38-pypy38_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp38-pypy38_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 871aad33aa157cba0340c7903e6f852f10fe343664eee129124553af0addbd8b
MD5 2af7991e4362d63d20ac2212b3d36bf8
BLAKE2b-256 ccf46060758ff5047d4cd8b2c5ef5b786ed384247b8c4547b6f0e3948eddc2f0

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp38-pypy38_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp38-pypy38_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl
Algorithm Hash digest
SHA256 e7fcfe102e10ca4f66a7e011bb152b53ae6ee81c40d3768513e662bd5545a77f
MD5 af9a2b90cb864fcf98c5817c0695ee81
BLAKE2b-256 e23a19877c233cad72632786195b4c65d2b3a8be15a0a48ad801d01cdbba49fe

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 e4f67bf2b3eb55c9e1cf109af1afed9958f155c1ee02e6cde216a7e32ec837a9
MD5 db27e293b159c40ae57fc51e2bbc1a5e
BLAKE2b-256 f3df7f5371055f5e58ef1b26696fa7cc5e6a8e93395692dfb5a74b3cabf75abc

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 ecbc63c6181fdbd3b4684b3cc16bfa59a8ba9dbcb32e29c984ed1eadf7d93fab
MD5 d6776395ef92155aa065d787ff3ed8a9
BLAKE2b-256 01f8023ed7230c7b5e116072142eb05492ae8881d74a1e45b5d6483352a21d06

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp38-pypy38_pp73-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp38-pypy38_pp73-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 6fcb0c43650acf3ff5ec1e13e87adf89f877070c78c3992075c5f91ec3527a6c
MD5 345cd701a558903ad26a16301d8afaf6
BLAKE2b-256 b7aa68a0ec8f16988f6d576aaef1b756bbe8980cfe49026cf89501ddd8c44e30

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp38-pypy38_pp73-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp38-pypy38_pp73-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 50f706567ff366ef4671678b4712a95c27c202619984113ef5b95c8ed080a663
MD5 251df4e18fe414063d2211b796b60273
BLAKE2b-256 d59069a5dceb2f67a9a080a7da3d229bd4413d6ee757031fa04b58254d363166

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp37-pypy37_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp37-pypy37_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 099c76ccc0b8efc08e6a7705a3b1d6085f8256b9402ed193d2867a8355a5ec5f
MD5 39424c720c3dcedad02f956520ab1091
BLAKE2b-256 224cc65743e29b78daf609d7fb04f486f56d01f5def298a7be55374e0d94a91b

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 df0be029fc6ddfa34349e7d950d7c84ebbdcdb6a47cefa6cb4d1b6b9463f4786
MD5 2942b78375ce94bb0edce85f35664a76
BLAKE2b-256 937a9e16965ee10c55d4004bc5deb6ba2b6ac2371c0440f7da534213a067f961

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp37-pypy37_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp37-pypy37_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 1a8844ee777c388d97981ea82023602ad1c45ac50673f5650cf9620551f65f45
MD5 385f81d7b8ca2687ebc78a83f3252a42
BLAKE2b-256 19ee8e97f2809376e8c4872680f988697d771cb6a6ce1d0340ff469d2c93b697

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp37-pypy37_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp37-pypy37_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 74c3ddce6d837e3ae4ea83f170672211c9e9c308a67b053d88927ce91def46fb
MD5 2136d7a78b9653b0a9139646fb1746e3
BLAKE2b-256 63cc128deb47354c83ef060c8dd96ddd055083414e82dfe2c165afe11edb9112

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp37-pypy37_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp37-pypy37_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl
Algorithm Hash digest
SHA256 e5c9ef7e7d128549a5426dd55e3afc8e5584765781018ccf4454460015af7892
MD5 19fc54326c5e5fc3c838f276abdc3552
BLAKE2b-256 b6dc2774b5476392340fe960be17c9f1077d61aba99838fcb08dbe852d43d7e0

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 23cf399a83e403ec795f4d3feedf8d3a66b951f4db57321d6a6185dd773b076d
MD5 6f7ea100218ce90c03a6c9f936d0dc5f
BLAKE2b-256 bbe068c68b39ea4efcffc90110287a643463d612435dfab75aec996a23eedb0d

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp37-pypy37_pp73-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp37-pypy37_pp73-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 457d1246f5c0f5a574c4791204fd7670ee23e3bd81dbaa569136a2b68381d482
MD5 394b470c9fd264f5a99edde55e39f492
BLAKE2b-256 775d6b148fd580c07526ad7981f7d8efd5eb4717601d71644e10354ba2ee45d7

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp37-pypy37_pp73-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp37-pypy37_pp73-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 ad8d8b7328f0c4fbb0f76b24f31ccbad24ef23275586dc9c747451b75d350615
MD5 9cac1b3382e4a6d4f56b0bb8cd471ba4
BLAKE2b-256 41351efed2759ad21f0f8254269dc353c8cb8d8edc657cfa03379b62cbce0154

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-pp37-pypy37_pp73-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-pp37-pypy37_pp73-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 dee70e69cd5dc787347fa32f40541fcd5387daf1fb0ecb0e1749c94c4aca91fa
MD5 0ad54a24477aaf2dc7ceb3b44c738912
BLAKE2b-256 073ad633155bb35a5bc3d391f2c1af941d984295aef97d719abba02c3f590031

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-cp37-abi3-win_amd64.whl.

File metadata

  • Download URL: wassima-1.0.0-cp37-abi3-win_amd64.whl
  • Upload date:
  • Size: 124.9 kB
  • Tags: CPython 3.7+, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: maturin/1.2.3

File hashes

Hashes for wassima-1.0.0-cp37-abi3-win_amd64.whl
Algorithm Hash digest
SHA256 3ac2e5dc2966383cb230015cd0d86992f106594dcbef533d04b2b7bd392da554
MD5 536b0833f2803392e7cd3fcebfb55779
BLAKE2b-256 2ccf6c092a510c9543407861ed4dba67aec2c5c236faa255741bbd1f02b8086f

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 9b41dfc52df440097ccf51b9fa875e4ce17a24e7e717c923d8116614649571fe
MD5 7be54dc8c61db0b1e93cf171eb730096
BLAKE2b-256 a52af6e250010e85cbe799aa9dca3aeaed7c204e29eb71bb23597401a201de70

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-cp37-abi3-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-cp37-abi3-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 6f62c310a6b408a1ae9849b90ac2420ecb7c7fb21154dc2c6a20edf5e691f84d
MD5 52a456da33fddb91779f0b9987acd2a5
BLAKE2b-256 6cd22a6eba13bca0c257e3cf8c99a183dbfa957a1a284ff052f57a6b453a79ad

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-cp37-abi3-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-cp37-abi3-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 d3f206fb846bc50da68d2722b65af40b19520c684c57386970009c8484a38afa
MD5 31fdb3d9b46761da9f74f6bcbd13d9ce
BLAKE2b-256 7d5f5c4eaf892b47cde9f7936d7e869087d67e972e56400c901f80f8c0f28520

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-cp37-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-cp37-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl
Algorithm Hash digest
SHA256 a7ca5d283056ff27a3e263ed730347e94ad3e7359e9aa927df368558256b099b
MD5 56c7a1dc56f1e0ff4ee319d4b6a74e12
BLAKE2b-256 75c669a018db9f9b252539614cac438c699c9ec7c8c1c436b35a45e62fdabc7f

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-cp37-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-cp37-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 1abd96964636ca0793c9abe49aea79262f337650ec2ad9db593d5bd35bcc477a
MD5 3a122ec2bcadfbbc97048af65b006829
BLAKE2b-256 73f840e75997128db45e18fb3f383924f74c2f2cccd495fa568497acaa5ff9d7

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-cp37-abi3-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-cp37-abi3-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 467bc58b638e7424a20c54cedbacc34c6a6c85f49a61cd5918adac082e00a381
MD5 b6e33713ba9ca0d287ba69df3fe79524
BLAKE2b-256 59d6f2cfa4d385875b70b96487472d51e429a6995a09f44dc0f3bd0ba63dd339

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-cp37-abi3-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-cp37-abi3-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 e24c4191aed88bffd1463d80c0957ec4eb36325033a042c50be4c3907bc40056
MD5 c04ca2090b14da328c07e1e11d5a7e75
BLAKE2b-256 bd47a301b0678a93d0ed49e1e8ac3ef8c19fa3c27cc078480352eb971cad5992

See more details on using hashes here.

File details

Details for the file wassima-1.0.0-cp37-abi3-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for wassima-1.0.0-cp37-abi3-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 05f3afe3d424c28b2e8fb456a10f2692d0ba28cab1ed539aeeb5cc9d77a4ba70
MD5 7739aaf5651bff5ea49cf288b3242dce
BLAKE2b-256 e995211a8f9394e594a5a2130c833240cad2128d008fcc9295759569bffb3248

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page