Skip to main content

JPEG-LS for Python via CharLS C++ Library

Project description

pyjpegls

Note
This is a fork of the original CharPyLS repository created to be able to add fixes and adaptions, as that repo is not maintained anymore. The rest of this file is unchanged from the original readme.

JPEG-LS for Python via CharLS C++ Library

I wrote this interface to enable easy access to the awesome JPEG-LS lossless image compression algorithm from within my Python application. I had no need to read/write anyone else's JPEG-LS image files, but rather I needed to compress some data structures internal to my application. This data was similar in nature to greyscale imagery such that it was an easy choice to leverage the existing CharLS C++ library I found on codeplex.com. I did eventually incorporate some basic file I/O functionality for my unit tests, and that's why I list Pillow below as a dependency.

I have tested this code on Windows 7 x64, Windows 8 x64, and Ubuntu x64. Note, even though this package has the odd name "CharPyLS", you will import it into your module as "jpeg_ls". Here is a quick example of using this tool to compress an image to a buffer in memory. For more details, check out the examples included within the source code.

    # Read in an image from an existing PNG file.
    fname_img = 'test/image.png'
    data_image = data_io.read_PIL(fname_img)

    # Compress image data to a sequence of bytes.
    data_buffer = jpeg_ls.encode(data_image)

    # Sizes.
    size_png = os.path.getsize(fname_img)
    print('Size of RGB 8-bit image data:  {:n}'.format(len(data_image.tostring())))
    print('Size of PNG encoded data file: {:n}'.format(size_png))
    print('Size of JPEG-LS encoded data:  {:n}'.format(len(data_buffer)))

    # Decompress.
    data_image_b = jpeg_ls.decode(data_buffer)

    # Compare.
    is_same = (data_image == data_image_b).all()
    print('Restored data is identical to original: {:s}'.format(str(is_same)))

The output generated by the above example should look like the following:

Size of RGB 8-bit image data:  5038848
Size of PNG encoded data file: 2409950
Size of JPEG-LS encoded data:  2088357
Restored data is identical to original: True

About JPEG-LS

  • From Wikipedia article: JPEG-LS (ISO-14495-1/ITU-T.87) is an accepted lossless image compression standard derived from the Hewlett Packard LOCO algorithm.
  • From CharLS codeplex site: CharLS is an optimized implementation of the JPEG-LS standard for lossless and near-lossless image compression. JPEG-LS is a low-complexity standard that matches JPEG 2000 compression ratios. In terms of speed, CharLS outperforms open source and commercial JPEG LS implementations.

Dependencies

  • Numpy
  • Cython (only for building and installing, not for everyday use)
  • Pillow (friendly fork of PIL, used here for file I/O with the example and during unit tests)
  • CharLS (source included as subfolder)

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

pyjpegls-1.4.0.tar.gz (1.2 MB view details)

Uploaded Source

Built Distributions

pyjpegls-1.4.0-cp312-cp312-win_amd64.whl (1.2 MB view details)

Uploaded CPython 3.12 Windows x86-64

pyjpegls-1.4.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.8 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ x86-64

pyjpegls-1.4.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.7 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ ARM64

pyjpegls-1.4.0-cp312-cp312-macosx_11_0_arm64.whl (1.3 MB view details)

Uploaded CPython 3.12 macOS 11.0+ ARM64

pyjpegls-1.4.0-cp312-cp312-macosx_10_9_x86_64.whl (1.3 MB view details)

Uploaded CPython 3.12 macOS 10.9+ x86-64

pyjpegls-1.4.0-cp311-cp311-win_amd64.whl (1.2 MB view details)

Uploaded CPython 3.11 Windows x86-64

pyjpegls-1.4.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.7 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

pyjpegls-1.4.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.7 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ ARM64

pyjpegls-1.4.0-cp311-cp311-macosx_11_0_arm64.whl (1.3 MB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

pyjpegls-1.4.0-cp311-cp311-macosx_10_9_x86_64.whl (1.3 MB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

pyjpegls-1.4.0-cp310-cp310-win_amd64.whl (1.2 MB view details)

Uploaded CPython 3.10 Windows x86-64

pyjpegls-1.4.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.7 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

pyjpegls-1.4.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.7 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ARM64

pyjpegls-1.4.0-cp310-cp310-macosx_11_0_arm64.whl (1.3 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

pyjpegls-1.4.0-cp310-cp310-macosx_10_9_x86_64.whl (1.3 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

pyjpegls-1.4.0-cp39-cp39-win_amd64.whl (1.2 MB view details)

Uploaded CPython 3.9 Windows x86-64

pyjpegls-1.4.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.7 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

pyjpegls-1.4.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.7 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ARM64

pyjpegls-1.4.0-cp39-cp39-macosx_11_0_arm64.whl (1.3 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

pyjpegls-1.4.0-cp39-cp39-macosx_10_9_x86_64.whl (1.3 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

pyjpegls-1.4.0-cp38-cp38-win_amd64.whl (1.2 MB view details)

Uploaded CPython 3.8 Windows x86-64

pyjpegls-1.4.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.7 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

pyjpegls-1.4.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.7 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ARM64

pyjpegls-1.4.0-cp38-cp38-macosx_11_0_arm64.whl (1.3 MB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

pyjpegls-1.4.0-cp38-cp38-macosx_10_9_x86_64.whl (1.3 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

File details

Details for the file pyjpegls-1.4.0.tar.gz.

File metadata

  • Download URL: pyjpegls-1.4.0.tar.gz
  • Upload date:
  • Size: 1.2 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.4

File hashes

Hashes for pyjpegls-1.4.0.tar.gz
Algorithm Hash digest
SHA256 010300754163f4a68f65e6d5ae463080ab1e54d70fd3a1f7d6520db39dfccd96
MD5 052e05965ece3c983ddbb2a85fc81181
BLAKE2b-256 bc6db07db11457745f1bf40b279ccd23d2245a3f74f0f7c980c741fac3cebe57

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: pyjpegls-1.4.0-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 1.2 MB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.4

File hashes

Hashes for pyjpegls-1.4.0-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 df98163d03e6427c815ad6010df42955cf4b10d674fe9b3e0189699605fc9b86
MD5 52cffd06f37259ba45b7247b24f5e40a
BLAKE2b-256 5b47f88c71f01ac25ab6bebb15f833d10c2b1368b5d2bc9efa4fc487b687075e

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyjpegls-1.4.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 e07b9fff4e0fc835342ed526cfc91de2b2466fd87ba897ec70fb52beeb068ed0
MD5 9f4d966a8baf68a72bf18b65f5566e8e
BLAKE2b-256 de6afb77db54cb32a5adcbed0176e20c4d6d970a29b28fc386d918c35ecfd3c8

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyjpegls-1.4.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 60b76e635904d78677a0ef5f31e666e84241d7fd925ac6afb1bbff554cb195b8
MD5 176f820eb39171e63ad7cea1e9dc214d
BLAKE2b-256 237ed2ee6c51970c2db16e5c78b587ae793593a3c2eb82aa90df918acf26d449

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyjpegls-1.4.0-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 2eb5ecbb31c9543a2b239e6275ac3f0a8f9298317e05b6250b378548d8344855
MD5 192df3fbc832830956738ab30be76cbd
BLAKE2b-256 23f11c75a5e71c1ac9ff66f4e5c63fa6f7586505ebfe21cff3dd7bfbc9d4ec60

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp312-cp312-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyjpegls-1.4.0-cp312-cp312-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 396945723b9a587bc19f8dde9d1463e1eae65ca14b1b70899d231f6e22f01c58
MD5 050978cca308c8f2907372f38aca2e50
BLAKE2b-256 ad4f01ce84e8b2f0307cea06fe4a2340be0709b9822b8373f49a35949a839cf2

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: pyjpegls-1.4.0-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 1.2 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.4

File hashes

Hashes for pyjpegls-1.4.0-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 257b81b1cb3957666716d30a1a05f42ab8e5976d10a3ad581124bc5502047950
MD5 2c291a451ae17333e3e5b80a899300c5
BLAKE2b-256 98db94088ba8ea40e129d0bcf4c2f0409fcf9da8cae0a239f157e4290fea03aa

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyjpegls-1.4.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 82445185a7d00356c3b98759200257c0c875a57b0127321e9a4ba811d5d9fdef
MD5 42f7f71752fc811f51ebf543e6da475b
BLAKE2b-256 49dec0ab028b79d72ca99b8db50dc3373224c8997bf2164211df633de6b21f45

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyjpegls-1.4.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 387bd204d0c25fb40c9743e7c337d96e618419e7b750e0e2f3e2661dc02ddf96
MD5 618431d67e38ab8cf4a1c923f94a6939
BLAKE2b-256 a7adf01a1ba451d52c9c5c8277ffc43490d95e306c596cd2fc64f6d20ad98399

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyjpegls-1.4.0-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 991ce9a393390e60125468b173fd0fb22ed9f1e79bd3148e83ab022a3b18ebe3
MD5 e4ae5301c41eec00dc08d2275d5165da
BLAKE2b-256 1cae8b727bfea02b3ee51b943d5d1eec9e4c3e7ba96cce5bd2d1cba197ff4502

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyjpegls-1.4.0-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 6d43b9d1b47b8305e8d7c19445ce005c7c93cd269996f85338905624e6bb7193
MD5 ffbda88fdef647c2cf15e43ce40761c1
BLAKE2b-256 0915233d33ae3637f1b7d2e0b914aa12879518f1477a1cb26952844e534b6412

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: pyjpegls-1.4.0-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 1.2 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.4

File hashes

Hashes for pyjpegls-1.4.0-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 072516b081a97bce0503a543b343c2e96275478e67dec42412a26010a856499e
MD5 b9155fb80b648fef3ea67d5739ad8ea2
BLAKE2b-256 ad0e62135ee27c8bc2be2cb97f22d2f545f912d4d6ba02ee44c53d2495d0a1fa

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyjpegls-1.4.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 2cce0adc0e848cef8f070a8bcec8e610eeb4e0205aece1aa48e4a91e399623f7
MD5 110c4a38445caab3142e1ad9857ececb
BLAKE2b-256 8dfd0ecc693265ed70038378c2f116d85b8fd376b9dfe023b23657e3ae90c08d

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyjpegls-1.4.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 e1c2fe1a1abe4d6400bd2140c780db57d55c8ecf9d08a103aafb92c81c531b3b
MD5 8b67dd7a93761cf03a360f53824ad795
BLAKE2b-256 9e92afba4685e09f63a3c9b9dcd7c5a21e6b062833baa151c7e554932e6f84d0

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyjpegls-1.4.0-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 7a26e62cc8aa36764baaa09bcfc1577181f2eef8846974213f787d27e308e990
MD5 2da8318d5425eab4d86cbdd55a97bc26
BLAKE2b-256 f8bdb92151d7fe9cef26d755c6feb2ac2df6048a430e72485ea5e3493c54d93f

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyjpegls-1.4.0-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 13c270b34876ff1c4c21d7d0543e24c502ee1730d9504f2b790606522dc4d627
MD5 e2aff3b3d4094eed5e1d33d10fe1811b
BLAKE2b-256 540e0092d3ef4d100256480a1c12160e9859d7b38eeccd562e79a9b551039cd8

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: pyjpegls-1.4.0-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 1.2 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.4

File hashes

Hashes for pyjpegls-1.4.0-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 eb7235b6f21520066a96539ccb2f554ca1f49634d40c6109fb1c988a51594987
MD5 2101394b4e031b922df6d42cc83c2f7f
BLAKE2b-256 db775bc2859f16830007808e4084afbde0c54b4c168debc56150b1025f6a40f0

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyjpegls-1.4.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 a33257e19c452af359f5de81eeb15240b1469c0bfd1edd0ac7d55b66af2fd6d9
MD5 1d8bcba838743801e25ef42bf3e4d292
BLAKE2b-256 26dfbb1fc382650ea76fa95c8a10c6e2fbdf1387e00aa738e14a1387c3a70cc5

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyjpegls-1.4.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 a83ccbc5893764db42021760e0ca25e664bf17061418cd476cd2051b784263a4
MD5 0eeac5837f2f63b084c44e0d7f8647fc
BLAKE2b-256 0adbe22aff5ea7f9992be5cf848858ba250e239da1eafbcb725ab45f7bb4dace

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyjpegls-1.4.0-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 4ed05b7cdff0062f08a30349a3b852379b9b6479b21d209cf3e6acb1b033a9d7
MD5 23556dd8bf0ca60fad915551138645a1
BLAKE2b-256 d3528e1bdf47f32b6b3fccf3c893df06d6136c902a0467b5865c6541ed888531

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyjpegls-1.4.0-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 64098550fd4807b3e94cc1e8fe1530cd2f557ebb8d8b703d88504a81e10a9eaf
MD5 676054eccdc22e2bc19dc184e6f9b446
BLAKE2b-256 4a91ef4634d011012696f1c12ac98163f554a9cbdffde869b90b64af734c1898

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: pyjpegls-1.4.0-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 1.2 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.4

File hashes

Hashes for pyjpegls-1.4.0-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 01a468a346ee31057b509102a1393edc742bf56f363bd7e8f18b707733f7ea39
MD5 4cdc54ce23e9fc92497b238d34394f4a
BLAKE2b-256 670b3ab5f9f5ba304818d765215bece92540fce5d8f7c74b1e81fb9c5af6f1ec

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyjpegls-1.4.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 d0b7225b29bd66edaac8326600a068c13d6b19a7dc089bbd6abd357be35393f9
MD5 2ec442df280092979152ed154b2711bc
BLAKE2b-256 f1f000c7521d971f1885a2aa06cb3280e54ab457ee308f51a4119ba2163834bd

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyjpegls-1.4.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 0b9674b44788d8e463f5f0b670eee0d456ffc7af0fdefadc41ad54b399662bf0
MD5 e8ca47c8e4bcdf57f8c4b88b728b4acc
BLAKE2b-256 a389e00d198b10192037d4392bbbdf25c8e07ca2035c654bac2f4226a92095ec

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pyjpegls-1.4.0-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 488b0f77017493110dca36e288c5147a4d2a70c9aa0c86c5fd5be8f0a9279979
MD5 827683a7ee817c195fda758439e4919b
BLAKE2b-256 06fd043c82620c0c0acd242d547591f2021b00d51e1f623afb92fe101ef202ce

See more details on using hashes here.

File details

Details for the file pyjpegls-1.4.0-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyjpegls-1.4.0-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 ddf954ca781daf3a2f4a3dee2529dd2ef5be12a1fc1304121e61942b247eeed2
MD5 5efd0ea3bb409104e8062e20de1f1ac5
BLAKE2b-256 d30f96e7023622fe50f4e417cbc53fa9dcdc86dd9c7163e5e1037657e87c1423

See more details on using hashes here.

Supported by

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