Skip to main content

Python implementation of fast azimuthal integration

Project description

Main development website: https://github.com/silx-kit/pyFAI

Github Actions Appveyor Status myBinder Launcher Zenodo DOI RTD docs

PyFAI is an azimuthal integration library that tries to be fast (as fast as C and even more using OpenCL and GPU). It is based on histogramming of the 2theta/Q positions of each (center of) pixel weighted by the intensity of each pixel, but parallel version uses a SparseMatrix-DenseVector multiplication. Neighboring output bins get also a contribution of pixels next to the border thanks to pixel splitting. Finally pyFAI provides also tools to calibrate the experimental setup using Debye-Scherrer rings of a reference compound.

References

Installation

With PIP

As most Python packages, pyFAI is available via PIP:

pip install pyFAI[gui]

It is advised to run this in a vitural environment . Provide the –user option to perform an installation local to your user-space (not recommended). Under UNIX, you may have to run the command via sudo to gain root access and perform a system wide installation (which is neither recommended).

With conda

pyFAI is also available via conda:

conda install pyfai -c conda-forge

To install conda please see either conda or Anaconda.

From source code

The current development version of pyFAI can be downloaded from Github. Presently the source code has been distributed as a zip package. Download it one and unpack it:

unzip pyFAI-main.zip

All files are unpacked into the directory pyFAI-main:

cd pyFAI-main

Install dependencies:

pip install -r requirements.txt

Build it & test it:

python3 run_tests.py

For its tests, pyFAI downloads test images from the internet. Depending on your network connection and your local network configuration, you may have to setup a proxy configuration like this (not needed at ESRF):

export http_proxy=http://proxy.site.org:3128

Finally, install pyFAI in the virtualenv after testing it:

pip install .

The newest development version can also be obtained by checking out from the git repository:

git clone https://github.com/silx-kit/pyFAI.git
cd pyFAI
pip install .

If you want pyFAI to make use of your graphic card, please install pyopencl

Documentation

Documentation can be build using this command and Sphinx (installed on your computer):

python3 build-doc.py

Dependencies

Python 3.9, … 3.13 are well tested and officially supported. For full functionality of pyFAI the following modules need to be installed.

Those dependencies can simply be installed by:

pip install -r requirements.txt

Ubuntu and Debian-like Linux distributions

To use pyFAI on Ubuntu/Debian the needed python modules can be installed either through the Synaptic Package Manager (found in System -> Administration) or using apt-get on from the command line in a terminal:

sudo apt-get install pyfai

The extra Ubuntu packages needed are:

  • python3-numpy

  • python3-scipy

  • python3-matplotlib

  • python3-dev

  • python3-fabio

  • python3-pyopencl

  • python3-qtpy

  • python3-silx

  • python3-numexpr

using apt-get these can be installed as:

sudo apt-get build-dep pyfai

MacOSX

One needs to manually install a recent version of Python (>=3.8) prior to installing pyFAI. Apple provides only an outdated version of Python 2.7 which is now incomatible. If you want to build pyFAI from sources, you will also need Xcode which is available from the Apple store. The compiled extension will use only one core due to the limitation of the compiler. OpenCL is hence greately adviced on Apple systems. Then install the missing dependencies with pip:

pip install -r requirements.txt

Windows

Under Windows, one needs to install Python (>=3.8) prior to pyFAI. The Visual Studio C++ compiler is also needed when building from sources. Then install the missing dependencies with pip:

pip install  -r requirements.txt

Getting help

A mailing-list, pyfai@esrf.fr, is available to get help on the program and how to use it. One needs to subscribe by sending an email to sympa@esrf.fr with a subject “subscribe pyfai”.

Maintainers

  • Jérôme Kieffer (ESRF)

  • Edgar Gutierrez Fernandez (ESRF)

  • Loïc Huder (ESRF)

Contributors

  • Valentin Valls (ESRF)

  • Frédéric-Emmanuel Picca (Soleil)

  • Thomas Vincent (ESRF)

  • Dimitris Karkoulis (Formerly ESRF)

  • Aurore Deschildre (Formerly ESRF)

  • Giannis Ashiotis (Formerly ESRF)

  • Zubair Nawaz (Formerly Sesame)

  • Jon Wright (ESRF)

  • Amund Hov (Formerly ESRF)

  • Dodogerstlin @github

  • Gunthard Benecke (Desy)

  • Gero Flucke (Desy)

  • Maciej Jankowski (ESRF)

Indirect contributors (ideas…)

  • Peter Boesecke

  • Manuel Sánchez del Río

  • Vicente Armando Solé

  • Brian Pauw

  • Veijo Honkimaki

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

pyfai-2025.12.0.tar.gz (68.4 MB view details)

Uploaded Source

Built Distributions

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

pyfai-2025.12.0-cp314-cp314t-win_amd64.whl (6.0 MB view details)

Uploaded CPython 3.14tWindows x86-64

pyfai-2025.12.0-cp314-cp314t-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl (6.6 MB view details)

Uploaded CPython 3.14tmanylinux: glibc 2.24+ x86-64manylinux: glibc 2.28+ x86-64

pyfai-2025.12.0-cp314-cp314-win_amd64.whl (5.4 MB view details)

Uploaded CPython 3.14Windows x86-64

pyfai-2025.12.0-cp314-cp314-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl (7.0 MB view details)

Uploaded CPython 3.14manylinux: glibc 2.24+ x86-64manylinux: glibc 2.28+ x86-64

pyfai-2025.12.0-cp314-cp314-macosx_11_0_arm64.whl (5.2 MB view details)

Uploaded CPython 3.14macOS 11.0+ ARM64

pyfai-2025.12.0-cp313-cp313-win_amd64.whl (5.3 MB view details)

Uploaded CPython 3.13Windows x86-64

pyfai-2025.12.0-cp313-cp313-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl (7.0 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.24+ x86-64manylinux: glibc 2.28+ x86-64

pyfai-2025.12.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (6.9 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.17+ ppc64le

pyfai-2025.12.0-cp313-cp313-macosx_11_0_arm64.whl (5.2 MB view details)

Uploaded CPython 3.13macOS 11.0+ ARM64

pyfai-2025.12.0-cp313-cp313-macosx_10_13_x86_64.whl (5.6 MB view details)

Uploaded CPython 3.13macOS 10.13+ x86-64

pyfai-2025.12.0-cp312-cp312-win_amd64.whl (5.3 MB view details)

Uploaded CPython 3.12Windows x86-64

pyfai-2025.12.0-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl (7.0 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.24+ x86-64manylinux: glibc 2.28+ x86-64

pyfai-2025.12.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (6.9 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.17+ ppc64le

pyfai-2025.12.0-cp312-cp312-macosx_11_0_arm64.whl (5.2 MB view details)

Uploaded CPython 3.12macOS 11.0+ ARM64

pyfai-2025.12.0-cp312-cp312-macosx_10_13_x86_64.whl (5.6 MB view details)

Uploaded CPython 3.12macOS 10.13+ x86-64

pyfai-2025.12.0-cp311-cp311-win_amd64.whl (5.4 MB view details)

Uploaded CPython 3.11Windows x86-64

pyfai-2025.12.0-cp311-cp311-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl (7.3 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.24+ x86-64manylinux: glibc 2.28+ x86-64

pyfai-2025.12.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (7.3 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.17+ ppc64le

pyfai-2025.12.0-cp311-cp311-macosx_11_0_arm64.whl (5.3 MB view details)

Uploaded CPython 3.11macOS 11.0+ ARM64

pyfai-2025.12.0-cp311-cp311-macosx_10_9_x86_64.whl (5.8 MB view details)

Uploaded CPython 3.11macOS 10.9+ x86-64

pyfai-2025.12.0-cp310-cp310-win_amd64.whl (5.4 MB view details)

Uploaded CPython 3.10Windows x86-64

pyfai-2025.12.0-cp310-cp310-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl (7.4 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.24+ x86-64manylinux: glibc 2.28+ x86-64

pyfai-2025.12.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (7.3 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ ppc64le

pyfai-2025.12.0-cp310-cp310-macosx_11_0_arm64.whl (5.3 MB view details)

Uploaded CPython 3.10macOS 11.0+ ARM64

pyfai-2025.12.0-cp310-cp310-macosx_10_9_x86_64.whl (5.9 MB view details)

Uploaded CPython 3.10macOS 10.9+ x86-64

File details

Details for the file pyfai-2025.12.0.tar.gz.

File metadata

  • Download URL: pyfai-2025.12.0.tar.gz
  • Upload date:
  • Size: 68.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.1

File hashes

Hashes for pyfai-2025.12.0.tar.gz
Algorithm Hash digest
SHA256 8c1feb3d768dea0120139ee691dd8e4c7d7c61a2bf20b60a3f76c703591c7297
MD5 cfd3dc17f7c53c7e87d69084bb27c204
BLAKE2b-256 78d20541edd295c2994f5fb3c796b3bc4427ce96000bdd6023c1c0681380d2bd

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp314-cp314t-win_amd64.whl.

File metadata

  • Download URL: pyfai-2025.12.0-cp314-cp314t-win_amd64.whl
  • Upload date:
  • Size: 6.0 MB
  • Tags: CPython 3.14t, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.1

File hashes

Hashes for pyfai-2025.12.0-cp314-cp314t-win_amd64.whl
Algorithm Hash digest
SHA256 dc921fee3d887dcb617dcf78356d39bcbf3f47f234dd3c132c004e965838866b
MD5 040c97031f05c09cc3421af14815e291
BLAKE2b-256 3ee1e6238cb30f6512b508f6711f98c1f07f31476658dacaa6b843072620ac3a

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp314-cp314t-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pyfai-2025.12.0-cp314-cp314t-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 b005e748742330f0bf72ba6e5f40f47162737e616880350811f8af64e3f8822e
MD5 ac9c8f3a08f68fe86e3c56c4e1accd2f
BLAKE2b-256 b5c97ee8ae62b2e70f169cca0ba8633a69a17c2be8416426d60b8cc7e411ed89

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp314-cp314-win_amd64.whl.

File metadata

  • Download URL: pyfai-2025.12.0-cp314-cp314-win_amd64.whl
  • Upload date:
  • Size: 5.4 MB
  • Tags: CPython 3.14, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.1

File hashes

Hashes for pyfai-2025.12.0-cp314-cp314-win_amd64.whl
Algorithm Hash digest
SHA256 90564293bc340134e94ac968eed36752c22eec9b26397877a38ae1583d594d2e
MD5 8e96ab05d550cf62d749c94b1161a692
BLAKE2b-256 8a094e30ef218ea8db4509ca02261be01421c9e6f4f80316fefb61bd57174843

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp314-cp314-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pyfai-2025.12.0-cp314-cp314-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 ab6ac8f9754c3b224f672282563ac340b5408578f5bf0abd7994d194d27e3347
MD5 e15fbf743ba82961cd741f3b100f0174
BLAKE2b-256 fabad72f3ae76543793fa3e71f5e88b8ca17d4efb2d2d4a45d8eb81b48d46279

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp314-cp314-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyfai-2025.12.0-cp314-cp314-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 07347ae9334c0e73052f21f1ee5eba4e7dce05680e072d7d3edcb7c7e0f17a5a
MD5 acbe82767800584a8e615abc95f5cf92
BLAKE2b-256 75def0a48d68b90ff8d137c09690de9c4fd3de7ae1a3fe1350e21c5f5c8765a9

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp313-cp313-win_amd64.whl.

File metadata

  • Download URL: pyfai-2025.12.0-cp313-cp313-win_amd64.whl
  • Upload date:
  • Size: 5.3 MB
  • Tags: CPython 3.13, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.1

File hashes

Hashes for pyfai-2025.12.0-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 4099b6fa908f33edc19d1bc4d19cc989c8748b6fd93db57143e3d6f53b4eedef
MD5 8f2fe64787d335c3860776e33cd21c65
BLAKE2b-256 b4ad6a5643b3a2c3f7bc24a71bee5e3b9dc0dbecd53f44b3181acf9d974ef5ef

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp313-cp313-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pyfai-2025.12.0-cp313-cp313-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 95cd9784a3c4d4ae8bb37414b27cd76b59b4f4c5e97f7a90ee0962f2be4d8d34
MD5 613121ef578e8a19a3b378497987fcb0
BLAKE2b-256 ab2014907dbd9436bccf01156d3204ddbccc2d640015f4425670c80040773c03

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for pyfai-2025.12.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 122422a4c395061ce2df0b3fdef4c317b59ca7803d5b3f2dd5ab5379672a2bd4
MD5 f7280d599cfaeb650adc106c6b02bc8d
BLAKE2b-256 c8cf74c4184dddff726344a9335e39b342282f62eb6d14e80cc3efb94cd6d86a

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp313-cp313-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyfai-2025.12.0-cp313-cp313-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 1de9bc3272908a4eeae62ab92f2d5c3738fbae8379009de2564b95d8edd43987
MD5 56c2d23e4934792cd6ed9c8d6e433792
BLAKE2b-256 adb337b7b9a17cde77ac35da0a667e21158c5591f7c15e8abb194d527b595031

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp313-cp313-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for pyfai-2025.12.0-cp313-cp313-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 35439c1ebac0d66132c39c75f0065f78bd86b3e7a9109b9cf29dffe267705964
MD5 91f9196573051c5c823f48aa6c494a8f
BLAKE2b-256 5f69ab2d8a99059116aedb46422b8202bd3628364c298708d989a5cc78850d7d

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: pyfai-2025.12.0-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 5.3 MB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.1

File hashes

Hashes for pyfai-2025.12.0-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 576662495437777e4ec7ecd66929bf45191f10e3f28a0bc14350e51b4915fa35
MD5 804a67fa68ca9dcab9f7c4f525064996
BLAKE2b-256 1e2eeee6b13926bfe759d79fe3a25654ebfa391f8973802aca7df929cefba63b

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pyfai-2025.12.0-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 d65faa7563433ab2827c2f7bc9256e2b704c5374b21d17404712efe8151073ff
MD5 01a52152dd9c0d45179eabc1ad6808be
BLAKE2b-256 e86954353dc9a2526a4638560e4531c6a8809f6af09940d02ba3dee0de5b7e97

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for pyfai-2025.12.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 acd07f6c94a3b87b2ffd1f7fb18aff9d2306cc8732d758758273de58e8e666a8
MD5 2681524b06ebf5bfbfa131d116b2cf43
BLAKE2b-256 7078e3a4b6cdbf2f3f521c824f88bba6ffcae704c9c6f81b55a627eb8677fa59

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyfai-2025.12.0-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 af6bf7a6e82c7e0aa8cc2dea2bd30d666cfa915d422f1daa53684b4092c430c4
MD5 2603096fffb36103fc4099f221c6cf84
BLAKE2b-256 8dacb024b0cb4cd24c1c7548c10d3f0f97b765a486d697b7a9bf0cd4a8e95265

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp312-cp312-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for pyfai-2025.12.0-cp312-cp312-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 1058942a0aa77b107c5dd5cecce0556cda4c32736b0afa2c479e9cee9f3a035f
MD5 4db27f7f2effaaa6be509b272824a53c
BLAKE2b-256 e4c86548ff06bf9c337290b341b629af39dd0a31636328f76fa031fdced56085

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: pyfai-2025.12.0-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 5.4 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.1

File hashes

Hashes for pyfai-2025.12.0-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 d9e3f8574d5aae944ed0611980619aa9fb6fdf245bf7bf6da5e0a78a7c46e199
MD5 daea2e485f0267d6fb6ed5bb1513bef2
BLAKE2b-256 1cb8f7fe56fcd99adb955d682655ae41529d0f34f1ce8a499e1ccc1cb9721cb5

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp311-cp311-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pyfai-2025.12.0-cp311-cp311-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 630cc88b2128a8eb312b06e192fb2a2ae18425a6f468c30ce319756ca928cade
MD5 47ecf0dfe9135886002d85678af0e7b7
BLAKE2b-256 2d9973cb7dfdea5b5c42160146e88fcfd3e7819b1d6c109180fd41b577cedb8b

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for pyfai-2025.12.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 f47bc81f8002542932df4b4e02ddfde129a649ec3123e7c49577bdfe74d65d44
MD5 28d3405563d0cf82a68c6d885f383faf
BLAKE2b-256 01abac91927ee71335ad4bfd4df5cb24cccf667c075849f21bf3cd410c07ec0d

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyfai-2025.12.0-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 95d2fb3a44831b6d8b1d9fa088f1474461a8d49ba1eeec9fa2d2d44d0c8bbd34
MD5 212b5a8c1b720ef4ed8f91f044d719de
BLAKE2b-256 e02a23d6cfdbc2eecb7df66a7583cabd62c9284d09cce33a19657793de6fa19a

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyfai-2025.12.0-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 4eb8df79a8b2a60176d8e0b9af25d297a5353211ef2f6defdd0fc87e6e759742
MD5 6f18b86f7c47cd87f0dc66be5fd0427e
BLAKE2b-256 4d02ea0d97918ed5a6aa0da8ae363a1c5f3394329d7ab8a36bad65c54ea6c0ea

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: pyfai-2025.12.0-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 5.4 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.1

File hashes

Hashes for pyfai-2025.12.0-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 60c5bdfd282d7a84fca8ab6392eb30a3a489d23f4935e7349055f0b745326080
MD5 401a496803e7c085ef64cb57dc806797
BLAKE2b-256 cdb8ea92d5e5a1de4539a1c54d7606d3096cb1c39ae12fc1eb91d3065a30d164

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp310-cp310-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pyfai-2025.12.0-cp310-cp310-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 aa265591f4b22c02b07a2e376bac1501e0a17269a5b6bfcc1ed237cec15ace56
MD5 4b292ea3b3d9ad98f9b834b328849ca0
BLAKE2b-256 413b6502709000ea7c65c3d737a09536d720b1617e29940f419eb010f3854ac3

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for pyfai-2025.12.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 7acca947693b80900a8dc120de92d67df5317a28ab7f22c82e1c256a0dddb328
MD5 553654b91d5dce8e01b90e41a0338aa1
BLAKE2b-256 4e1de91c67ec807fd5f2e7e9ac4b92c88ff661b1da2545f4456f00cc1c9629ef

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyfai-2025.12.0-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 7da40cd40826cf68481b89c781413a2ea539cfb1271f0f97756fbd75ea7e61c9
MD5 78a47f347d91d82cae4447ee90cd99cf
BLAKE2b-256 d3a1b3d038b73409390bdd42636a80f7468376d6a9a0efa62ca188e698c69e04

See more details on using hashes here.

File details

Details for the file pyfai-2025.12.0-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyfai-2025.12.0-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 60b4ab9bd2c2f7a8f86f7f4f166a1e6fb13bba1b9fce59ad6d688b28b2ac928a
MD5 42e439792b756a13d43e2a9f4f319aca
BLAKE2b-256 6763b2e509cbd3de02bfa794095ff5ae6c5db7566fb46b5d2ac9a182f1e7decb

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