Skip to main content

Software library for X-ray data analysis

Project description

The purpose of the silx project is to provide a collection of Python packages to support the development of data assessment, reduction and analysis applications at synchrotron radiation facilities. silx aims to provide reading/writing tools for different file formats, data reduction routines and a set of Qt widgets to browse and visualise data.

The current version features:

  • Support of HDF5, SPEC and FabIO images file formats.

  • OpenCL-based data processing: image alignment (SIFT), image processing (median filter, histogram), filtered backprojection for tomography, convolution

  • Data reduction: histogramming, fitting, median filter

  • A set of Qt widgets, including:

    • 1D and 2D visualization widgets with a set of associated tools using multiple backends (matplotlib or OpenGL)

    • OpenGL-based widgets to visualize data in 3D (scalar field with isosurface and cut plane, scatter plot)

    • a unified browser for HDF5, SPEC and image file formats supporting inspection and visualization of n-dimensional datasets.

  • a set of applications:

    • a unified viewer (silx view filename) for HDF5, SPEC and image file formats

      silxView

    • a unified converter to HDF5 format (silx convert filename)

Installation

To install silx (and all its dependencies), run:

pip install silx[full]

To install silx with a minimal set of dependencies, run:

pip install silx

Or using Anaconda on Linux and MacOS:

conda install silx -c conda-forge

Unofficial packages for different distributions are available:

Detailed installation instructions are available in the documentation.

Documentation

The documentation of latest release and the documentation of the nightly build are available at http://www.silx.org/doc/silx/

Testing

silx features a comprehensive test-suite used in continuous integration for all major operating systems:

  • Github Actions CI status: Github Actions Status

  • Appveyor CI status: Appveyor Status

Please refer to the documentation on testing for details.

Examples

Some examples of sample code using silx are provided with the silx documentation.

License

The source code of silx is licensed under the MIT license. See the LICENSE and copyright files for details.

Citation

silx releases can be cited via their DOI on Zenodo: zenodo DOI

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

silx-2.0.0.tar.gz (18.9 MB view details)

Uploaded Source

Built Distributions

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

silx-2.0.0-cp312-cp312-win_amd64.whl (4.2 MB view details)

Uploaded CPython 3.12Windows x86-64

silx-2.0.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.8 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.17+ x86-64

silx-2.0.0-cp312-cp312-macosx_10_9_universal2.whl (6.2 MB view details)

Uploaded CPython 3.12macOS 10.9+ universal2 (ARM64, x86-64)

silx-2.0.0-cp311-cp311-win_amd64.whl (4.3 MB view details)

Uploaded CPython 3.11Windows x86-64

silx-2.0.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (14.0 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.17+ x86-64

silx-2.0.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (14.3 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.17+ ppc64le

silx-2.0.0-cp311-cp311-macosx_10_9_universal2.whl (6.2 MB view details)

Uploaded CPython 3.11macOS 10.9+ universal2 (ARM64, x86-64)

silx-2.0.0-cp310-cp310-win_amd64.whl (4.3 MB view details)

Uploaded CPython 3.10Windows x86-64

silx-2.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.3 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ x86-64

silx-2.0.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (13.5 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ ppc64le

silx-2.0.0-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (12.4 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.12+ x86-64

silx-2.0.0-cp310-cp310-macosx_10_9_universal2.whl (6.2 MB view details)

Uploaded CPython 3.10macOS 10.9+ universal2 (ARM64, x86-64)

silx-2.0.0-cp39-cp39-win_amd64.whl (4.2 MB view details)

Uploaded CPython 3.9Windows x86-64

silx-2.0.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.3 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ x86-64

silx-2.0.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (13.6 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ ppc64le

silx-2.0.0-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (12.5 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.12+ x86-64

silx-2.0.0-cp39-cp39-macosx_10_9_x86_64.whl (4.5 MB view details)

Uploaded CPython 3.9macOS 10.9+ x86-64

silx-2.0.0-cp39-cp39-macosx_10_9_universal2.whl (6.2 MB view details)

Uploaded CPython 3.9macOS 10.9+ universal2 (ARM64, x86-64)

silx-2.0.0-cp38-cp38-win_amd64.whl (4.2 MB view details)

Uploaded CPython 3.8Windows x86-64

silx-2.0.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.5 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.17+ x86-64

silx-2.0.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (13.9 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.17+ ppc64le

silx-2.0.0-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (13.1 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.12+ x86-64

silx-2.0.0-cp38-cp38-macosx_11_0_universal2.whl (6.2 MB view details)

Uploaded CPython 3.8macOS 11.0+ universal2 (ARM64, x86-64)

silx-2.0.0-cp38-cp38-macosx_10_9_x86_64.whl (4.5 MB view details)

Uploaded CPython 3.8macOS 10.9+ x86-64

silx-2.0.0-cp37-cp37m-win_amd64.whl (4.2 MB view details)

Uploaded CPython 3.7mWindows x86-64

silx-2.0.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.6 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.17+ x86-64

silx-2.0.0-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (12.9 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.17+ ppc64le

silx-2.0.0-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (11.8 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.12+ x86-64

silx-2.0.0-cp37-cp37m-macosx_10_9_x86_64.whl (4.5 MB view details)

Uploaded CPython 3.7mmacOS 10.9+ x86-64

File details

Details for the file silx-2.0.0.tar.gz.

File metadata

  • Download URL: silx-2.0.0.tar.gz
  • Upload date:
  • Size: 18.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.12.0

File hashes

Hashes for silx-2.0.0.tar.gz
Algorithm Hash digest
SHA256 ad3dd42f62b0727507894399c8708cbe42c19972d3b191f1ae99426fcc766970
MD5 14cac0b75ba4d9e1afa36d879bb2cb46
BLAKE2b-256 7cfc7ffbd26e59c09df8b9048c14c93ee5ac131f2e28423eb5e54d26b4551c3b

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: silx-2.0.0-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 4.2 MB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.12.0

File hashes

Hashes for silx-2.0.0-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 0bc604ef6e16bd689bd7438ecc0dcfa7f2f76f535479de7b325fc145b533aab7
MD5 eafe53136055e7f87508df3395bd2767
BLAKE2b-256 a0e230eb201c7d179e83016478ba841103d9542752ddc8f8826c609d61bbe92e

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for silx-2.0.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 22cd053f8a47c23c39f68c234f2a7a6c829806c773645873ee51f404f73d039f
MD5 12e3238ce9cea99601db87ffe8aa5b72
BLAKE2b-256 0102da6706df561797bbf91b7364783762e99dd60dda714c6f227a8b9666515f

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp312-cp312-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for silx-2.0.0-cp312-cp312-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 f016fb298d2ffcdd482b4691f7c8fc104ff710d57842741ad99f9ad22a06abc1
MD5 c2971043d2781f68e0ab070867744505
BLAKE2b-256 2baddcc9b4c75518fe8c84ffa11208836eae035afdf9f36c064dc3276837b5fa

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: silx-2.0.0-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 4.3 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.12.0

File hashes

Hashes for silx-2.0.0-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 faa0c33587a88fdb9497c82f6816a0b414f0dce3861a809b4663b4b4b8ba802e
MD5 4e527db968d76687d628c19210e290d4
BLAKE2b-256 368cf5a9570e4ff346c0012edf4745912f836ae43f0fb9a4bb365f779b85d0c6

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for silx-2.0.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 fd5b815cc8f95d48c8730c5f255ce8ced08764235ef6603dddb9b9bf421b80fa
MD5 cc2d5ce7d578457d732d3b6a92247cd9
BLAKE2b-256 53cbfe54eb1d21ff057b0ede5bb2efe6f532307f8d46d44e973527f03a2d920a

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for silx-2.0.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 3d69dc7456988b770b1de97e9b7af800af0a5c0cb266853e81e1798d08a300d9
MD5 ed5bce47e734f6a72f65ab21c311f265
BLAKE2b-256 e981d04b00f2acf11b3fefa0158e1cf1f7a666672842aa283c74e6b70e7f65de

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp311-cp311-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for silx-2.0.0-cp311-cp311-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 f808d6835699a43446ab6e36c915f268c3090d32f559fc1341eaf8400800fc56
MD5 c28f86655cf9e2d51f9764a839389163
BLAKE2b-256 a7f260fe0c911f447cc9a314576c9ce1e44c62ca2d650a37da64b79b11865951

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: silx-2.0.0-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 4.3 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.12.0

File hashes

Hashes for silx-2.0.0-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 784e73d1f0f71cd02717373b38009bfd16d53bb359fb4a528fa600d776ea00ac
MD5 04a90ebb406b1ea0a62fbbafb84d41b0
BLAKE2b-256 74068680c039b1e45f26231e73bfbcc57f46899f3a28172cb07e6ddc138ba8b2

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for silx-2.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 259cde889902cf5e7e1684a9dc3d0da91315c210a99510f9cd7be8e4891353ff
MD5 bc3248eda20bd2a5b8084479a343ff20
BLAKE2b-256 51b096ba7ed61bf1d3fe51deb5c8ee476e34594ecfb366581224514281051921

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for silx-2.0.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 9bfbd888ba00334c38630f61a6223e13974273146b425116e50f116176cd0497
MD5 cf485a4281b94b1e9b8af58e62ccd3f6
BLAKE2b-256 d0f098f9248cb322df7ba0806a8c701e4bc33556e817c811c7c2646c4c3a7eac

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for silx-2.0.0-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 345a43b893216e22027a4189d06bf8877621f0f07626bb635adad47786ab4fc2
MD5 e4b9676af55a40146638a2db7d72a69f
BLAKE2b-256 8bcb0d68f3651ce04900cea6ba8a32aa3e5e42885109890a383b06ca84039527

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp310-cp310-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for silx-2.0.0-cp310-cp310-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 91f228ccedea44c3f4dda0fc11b3a379a6862b259110cd1606679c0239cef7a7
MD5 93f543caad93b223c039b119a18f50e5
BLAKE2b-256 4647f21cf773674e4997d89a59a2527826cddf97bc9cc395f5b82a15bcaec3ed

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: silx-2.0.0-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 4.2 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.12.0

File hashes

Hashes for silx-2.0.0-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 d6eaeb9e3844d1b028458eef5abbfcd73fe4265cfa5190f1a19cc5caba2f00d2
MD5 82ccd7b89d5e70bd3043751fc93f37d3
BLAKE2b-256 e946fbc18b3596114bae4551393075a9a940ffbd57e53c8f97785de31845c04b

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for silx-2.0.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 fd0a24338ced17a7672fa663952207cb144fbd8b277675f30bab26ea36e33852
MD5 88700008dc74e48538bc8ecceef8e911
BLAKE2b-256 5ada54771abcdf12e84482685d41d9ef1edc583ac9fed7af32055c9a837d541c

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for silx-2.0.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 05ecd36d8b9b93cdf0037236b0a78d8f16e9a8acc8e0797c78883ca988824c55
MD5 893c6886fb8beae93ef63e50b95bc69c
BLAKE2b-256 1de26aceee8ff044041f8ba5a9773835ac8b85c4e69556fd94640359f4fd19ed

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for silx-2.0.0-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 3a3fe2eb145fb0542b5e7a1b9292f1e66852944d51e35f8f2e4f21394d44e5f7
MD5 3a1ce87efe69918e371053df08b5a58b
BLAKE2b-256 1dbaac47e82c77e0a80898404d37ca335d2777f2b7fc709b232489d4b83f4d83

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: silx-2.0.0-cp39-cp39-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 4.5 MB
  • Tags: CPython 3.9, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.12.0

File hashes

Hashes for silx-2.0.0-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 ac4b235eeb395bb70bc230fb2c29bf91e2483c82832dcc48db750946fe35465f
MD5 43fbd2c435583c4f8986fb9d233a895a
BLAKE2b-256 20daba493e1aef224b06eda8b6072d26ad8b9ce329d0cec933dd01c8527db5dd

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp39-cp39-macosx_10_9_universal2.whl.

File metadata

  • Download URL: silx-2.0.0-cp39-cp39-macosx_10_9_universal2.whl
  • Upload date:
  • Size: 6.2 MB
  • Tags: CPython 3.9, macOS 10.9+ universal2 (ARM64, x86-64)
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.12.0

File hashes

Hashes for silx-2.0.0-cp39-cp39-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 b8b3e9d4b48eedd8df86a9cdece304eebae209be5265336e3c8e0e34a954f141
MD5 36f68f0c72d13cc961ccecc41f9226fa
BLAKE2b-256 7c01b8b01942760d3bfc884a70b700ca92efbe6ef50c3ba17d379b05f4fac6bf

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: silx-2.0.0-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 4.2 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.12.0

File hashes

Hashes for silx-2.0.0-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 061b0f6627cfb41fa68fc293478df7375149a822a3fe517f4cd095d50236dd1a
MD5 144ee6d98603df833e411e6d48a83680
BLAKE2b-256 2b663b44e69faf3373f2869b7c84304b8b5ebecd0b31203dca8f1165bf8e5cb8

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for silx-2.0.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 f06516b018ba21e1726d94a6502bb27601e2811ba858ff729956e396c9b1d118
MD5 6828d059a97a3b93b6ba9118a1731df8
BLAKE2b-256 2b517a62ef24bb32d95c15eab55f5d45bf9809cf02750fd078a5eb03a6e5b8fa

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for silx-2.0.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 9ea958faedeebc5dbed86017312ae3f8a6e4e3c6b85e7cd5bcf7774757d72b3e
MD5 4710b9ac6223f127bd814a2b9dfba811
BLAKE2b-256 077cce1e83935797c812e4efc3313c45f55a8ef44a2c5b25245b251df4465f3e

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for silx-2.0.0-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 30e8fc0fde2b7107cb5c3bd9da53a0fd6b380454015375388edb7dd94ad124d4
MD5 d280ba9f47fd35c8c134630af5a696e6
BLAKE2b-256 3fe82d0ff5f6966fb0f3bfc5851adcf26bbc89a88998f871b35c80e09344b475

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp38-cp38-macosx_11_0_universal2.whl.

File metadata

  • Download URL: silx-2.0.0-cp38-cp38-macosx_11_0_universal2.whl
  • Upload date:
  • Size: 6.2 MB
  • Tags: CPython 3.8, macOS 11.0+ universal2 (ARM64, x86-64)
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.12.0

File hashes

Hashes for silx-2.0.0-cp38-cp38-macosx_11_0_universal2.whl
Algorithm Hash digest
SHA256 cd3eacb6aa45956b550960e160743fdf6785095b16cd369b59a684c9ef49e433
MD5 25fb9cef10d912ccf9d4faf7e0d920e4
BLAKE2b-256 948cc5971289bf1a013b3c75d8c90800e1d5c321d6d1dc391773a9a059da8909

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: silx-2.0.0-cp38-cp38-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 4.5 MB
  • Tags: CPython 3.8, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.12.0

File hashes

Hashes for silx-2.0.0-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 5adbe80156c6ebb310a0c3028e0ea7f2b3e904c9d8ae6c3495681fab0d91f99b
MD5 6ec0f51d10f96941319fa69afb78d332
BLAKE2b-256 e2aec61c8aa0efc89b7996a4a9228eb6d3331e67045bd996e6869ae2759a3b54

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: silx-2.0.0-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 4.2 MB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.12.0

File hashes

Hashes for silx-2.0.0-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 548316eeea33e0635bc5f021d30701e309ca125400bc321efb3cfa1f6b8b4338
MD5 bf677428fe2d62e73ee28ec832cb41fe
BLAKE2b-256 aad62e938fef40e0635b2a5ade045a97118c0e530dc917471290aac2dc94fe02

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for silx-2.0.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 c85292bf23bf4897daae37061e44225a11e4a51f85bd9e0e4d2dbb31c72a4e94
MD5 994cf76ed3c091e64982f9ce2843a439
BLAKE2b-256 32fa2935b61c47937aba1972c452e126e99431656edd9dba5c7991c072ab80f9

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for silx-2.0.0-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 9a7811844e3318b7c4ae61172d2247726cae041f1b1b5f4e08b94de015b1c55b
MD5 f3ee28398f93f262a6565b13f4450d9a
BLAKE2b-256 2bbe94a8e5b63216ae5e434abd3e2ddf735577c6bd2687ba746f805ae62d862a

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for silx-2.0.0-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 1cfff6127d4fcb48e8a7254c1c068fbcb06eddc38057abbf262aeeaed9044393
MD5 66a70d7d2271e7299fb7913da988464b
BLAKE2b-256 83cf9cb7d3466eb198f926d06de79f4da17789b4b8b04188114e153ac53fa3ef

See more details on using hashes here.

File details

Details for the file silx-2.0.0-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for silx-2.0.0-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 452f2ec33e4bafb225da32d864d30dd54cf421c4cf6fa7e2e774d8db58915fc1
MD5 f413683aad7b496d28475bbe78d5dedf
BLAKE2b-256 80f6de8c027b267e6d9c3909f4f4a86ac57b01bfb73e3018783df61e46153a89

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