Python library written in C++ for calculation of local atomic structural environment

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for smenon from gravatar.com smenon Avatar for srmnitc from gravatar.com srmnitc

Unverified details

These details have not been verified by PyPI
Project links
Meta
Classifiers

Project description

pyscal - python Structural Environment Calculator

Complete documentation with examples available here.

pyscal is a python module for the calculation of local atomic structural environments including Steinhardt's bond orientational order parameters during post-processing of atomistic simulation data. The core functionality of pyscal is written in C++ with python wrappers using pybind11 which allows for fast calculations with possibilities for easy expansion in python.

Steinhardt's order parameters are widely used for identification of crystal structures. They are also used to identify if an atom is solid or liquid.

Installation

pyscal can be installed directly using conda by the following statement-

    conda install -c conda-forge pyscal

From repository

pyscal can be built from the repository by-

    git clone https://github.com/pyscal/pyscal.git
    cd pyscal
    python setup.py install --user

Citing the work

If you use pyscal in your work, the citation of the following article will be greatly appreciated:

Sarath Menon, Grisell Díaz Leines and Jutta Rogal (2019). pyscal: A python module for structural analysis of atomic environments. Journal of Open Source Software, 4(43), 1824, https://doi.org/10.21105/joss.01824

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for smenon from gravatar.com smenon Avatar for srmnitc from gravatar.com srmnitc

Unverified details

These details have not been verified by PyPI
Project links
Meta
Classifiers

Release history Release notifications | RSS feed

3.2.7

3.2.6

3.2.5

3.2.4

3.2.3

3.2.2

3.2.1

3.1.12

3.1.11

3.1.10

3.1.9

3.1.8

3.1.7

3.1.3

3.1.2

This version

3.1.1

3.1.0

3.0.1

3.0.0.dev6 pre-release

Download files

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

Source Distribution

pyscal3-3.1.1.tar.gz (73.7 kB view details)

Uploaded Source

Built Distributions

pyscal3-3.1.1-pp39-pypy39_pp73-win_amd64.whl (248.9 kB view details)

Uploaded PyPy Windows x86-64

pyscal3-3.1.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (454.1 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

pyscal3-3.1.1-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (471.8 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686

pyscal3-3.1.1-pp39-pypy39_pp73-macosx_10_9_x86_64.whl (387.4 kB view details)

Uploaded PyPy macOS 10.9+ x86-64

pyscal3-3.1.1-pp38-pypy38_pp73-win_amd64.whl (249.2 kB view details)

Uploaded PyPy Windows x86-64

pyscal3-3.1.1-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (456.0 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

pyscal3-3.1.1-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (471.3 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686

pyscal3-3.1.1-pp38-pypy38_pp73-macosx_10_9_x86_64.whl (387.4 kB view details)

Uploaded PyPy macOS 10.9+ x86-64

pyscal3-3.1.1-pp37-pypy37_pp73-win_amd64.whl (249.0 kB view details)

Uploaded PyPy Windows x86-64

pyscal3-3.1.1-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (454.3 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

pyscal3-3.1.1-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (472.3 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686

pyscal3-3.1.1-pp37-pypy37_pp73-macosx_10_9_x86_64.whl (386.9 kB view details)

Uploaded PyPy macOS 10.9+ x86-64

pyscal3-3.1.1-cp311-cp311-win_amd64.whl (249.9 kB view details)

Uploaded CPython 3.11 Windows x86-64

pyscal3-3.1.1-cp311-cp311-win32.whl (221.8 kB view details)

Uploaded CPython 3.11 Windows x86

pyscal3-3.1.1-cp311-cp311-musllinux_1_1_x86_64.whl (972.0 kB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ x86-64

pyscal3-3.1.1-cp311-cp311-musllinux_1_1_i686.whl (1.0 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ i686

pyscal3-3.1.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (453.8 kB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

pyscal3-3.1.1-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl (467.6 kB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ i686

pyscal3-3.1.1-cp311-cp311-macosx_10_9_x86_64.whl (390.8 kB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

pyscal3-3.1.1-cp310-cp310-win_amd64.whl (247.8 kB view details)

Uploaded CPython 3.10 Windows x86-64

pyscal3-3.1.1-cp310-cp310-win32.whl (220.9 kB view details)

Uploaded CPython 3.10 Windows x86

pyscal3-3.1.1-cp310-cp310-musllinux_1_1_x86_64.whl (971.5 kB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ x86-64

pyscal3-3.1.1-cp310-cp310-musllinux_1_1_i686.whl (1.0 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ i686

pyscal3-3.1.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (451.8 kB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

pyscal3-3.1.1-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl (466.5 kB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ i686

pyscal3-3.1.1-cp310-cp310-macosx_10_9_x86_64.whl (389.5 kB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

pyscal3-3.1.1-cp39-cp39-win_amd64.whl (246.6 kB view details)

Uploaded CPython 3.9 Windows x86-64

pyscal3-3.1.1-cp39-cp39-win32.whl (221.0 kB view details)

Uploaded CPython 3.9 Windows x86

pyscal3-3.1.1-cp39-cp39-musllinux_1_1_x86_64.whl (972.4 kB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ x86-64

pyscal3-3.1.1-cp39-cp39-musllinux_1_1_i686.whl (1.0 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ i686

pyscal3-3.1.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (452.7 kB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

pyscal3-3.1.1-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl (467.9 kB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ i686

pyscal3-3.1.1-cp39-cp39-macosx_10_9_x86_64.whl (389.6 kB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

pyscal3-3.1.1-cp38-cp38-win_amd64.whl (247.8 kB view details)

Uploaded CPython 3.8 Windows x86-64

pyscal3-3.1.1-cp38-cp38-win32.whl (220.9 kB view details)

Uploaded CPython 3.8 Windows x86

pyscal3-3.1.1-cp38-cp38-musllinux_1_1_x86_64.whl (971.7 kB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ x86-64

pyscal3-3.1.1-cp38-cp38-musllinux_1_1_i686.whl (1.0 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ i686

pyscal3-3.1.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (451.6 kB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

pyscal3-3.1.1-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl (465.7 kB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ i686

pyscal3-3.1.1-cp38-cp38-macosx_10_9_x86_64.whl (389.3 kB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

File details

Details for the file pyscal3-3.1.1.tar.gz.

File metadata

  • Download URL: pyscal3-3.1.1.tar.gz
  • Upload date:
  • Size: 73.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for pyscal3-3.1.1.tar.gz
Algorithm Hash digest
SHA256 b8ded5c0ca57f855ce82840daa997affe899efe41381e163481e67a43c0a152f
MD5 574dee7b9d59e93fe92e5b4a45e6b245
BLAKE2b-256 a23e24a34d984c4b6d9158e97e59aa450521071ee3baef40ab2c1b999f5e2ed4

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-pp39-pypy39_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-pp39-pypy39_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 d4bcf549f042cad2df93623439b68d79565adf4aa149cdd46184e2c622f8a497
MD5 15b1d52595ab5eba8289f377245765fa
BLAKE2b-256 7c61f745b8297c9de8e459471d05e9409f431f8a49b36ae73daec32749504e5b

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 f9b9f7c655b9c5e344b7fe08f2e5b0fde1e415b44818c6814923db96c6e88699
MD5 a941a3c31fc943e66050e8093faa3434
BLAKE2b-256 e9c55a680f2858f49357a6e7a47626bd6ef7ea1e3d52b35f74f4d498489d2cf4

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 403d9ce67b3bb14ebfac7daab604773613e09989f9a738551467a7ce15c0c301
MD5 c7fd2cfa55ffa332c04f40ec5ed8d944
BLAKE2b-256 33c5fc469967e99209f16d506a15dad18b190608f00170721912b90c6b980ce5

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-pp39-pypy39_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-pp39-pypy39_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 a728b7fb5bd2e3b59b8efb2d82e6fb18985890a9b08d76941751b3148d275c73
MD5 63b7933e4a999f3e43de5af4c15db2e5
BLAKE2b-256 dda9a2ebde384c79790f4eaf9e2e883700c94bed8d6c0fd2234c3fdcabfd1e27

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-pp38-pypy38_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-pp38-pypy38_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 a9af4f31e3cfc92235207166262f6770600bc1697378fabac2121d7e57f57afc
MD5 108832846f11dce81ccac5042914da99
BLAKE2b-256 865483856dd2dda090923d422d48edfc10ebd67f8235a95a2b8e834e1c21850f

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 51ef87495096c72d43e3cec0eae9e4d79bf118cbc9e9b6c24f8ceeb882e73cd7
MD5 6d16167da240801986a3284fddaef153
BLAKE2b-256 48cf1839c3902fba2b65bd7783fe05862ec094555ea8463985e9ebdb6d8eacff

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 85338fb9df352605ecf83541a872da8dbc4950587f6b8123a96aa76a045804b1
MD5 0c55546b0bb78080e5aa47717c22cf69
BLAKE2b-256 5e3b44e4c2e0c6e6933d4c61548765c954dba2e26eae61fdf1894012b3f1a930

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-pp38-pypy38_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-pp38-pypy38_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 97ecde57377b0a37d74a31029bd8d3ab752c8f31aa1060692fd0d6d51009d945
MD5 ea00e2ca939ebe25fa3c4cf861c9b5b5
BLAKE2b-256 643da2d05d039b1a65a68fcce1f08b059bf9861db72ece78aa56389097bb7d72

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-pp37-pypy37_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-pp37-pypy37_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 afaf23904435da60a699c960d90c7f082096d0a3bc20945659936d53be46e6c8
MD5 1f2a3c76517957ceaca0a4f8da935bba
BLAKE2b-256 a55a771de5cb298576db0b7201fced9a705386d958836db1c49b28e03dea5933

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 2d5084a5b078d6d08f47a581b0012769e23a1f50ebea7301477efed5a849d96a
MD5 909f34da1a959b79d1dc4ca4fd8b49eb
BLAKE2b-256 a34280717ae260664327c25f3086e63f607fba66f7476ed6dfdb5ca5e36a46bf

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 10c14538dd05122043f741d7c76ebe8d6d1460fcf4ee85b3940b6a24d54a6b82
MD5 6020c3df06449edd9d03fec57c8623ee
BLAKE2b-256 165748de0397690eddbb26a9c6c3ac65685ce0916c1f975df5a14826973f5002

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-pp37-pypy37_pp73-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-pp37-pypy37_pp73-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 9acccf8a7de377c542a77c298e6c5f0013cdbff0241b22da0da02028b4461cef
MD5 286677972e16a1264d9abea46ea1bc75
BLAKE2b-256 f7266c1d9e007f9e43a0c8ed9d6211442796ab6a9d447dad3ce3d33f98579b6e

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: pyscal3-3.1.1-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 249.9 kB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for pyscal3-3.1.1-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 e71cab99068bee525cb1ba4337f44e82bce4c4e3ab4f93ddf7ae9e40e9c1ebf5
MD5 c82735b7c5cca2b960747a82506eb0ef
BLAKE2b-256 2259bba12a23e6206a87937cc0f0435dcf01bf01e31fabb8e58c28971c094bad

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp311-cp311-win32.whl.

File metadata

  • Download URL: pyscal3-3.1.1-cp311-cp311-win32.whl
  • Upload date:
  • Size: 221.8 kB
  • Tags: CPython 3.11, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for pyscal3-3.1.1-cp311-cp311-win32.whl
Algorithm Hash digest
SHA256 6314ac4d221b7ef834b63dca5c5dd731dbd6af611d59142e386ff972494443ae
MD5 3aef35a9d514f0a239199eff05680e96
BLAKE2b-256 20db5bfa4c6c78f5fb859da90694c6e7d70f9fa401ee612afa52526c4f069d62

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp311-cp311-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-cp311-cp311-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 9b70127e1431a9f7d3d174d9d41bbde58cfc9464c2e82d1f20ed7972da830e6c
MD5 26e697692eaf6e73619a9fa704701ea2
BLAKE2b-256 7623f2b9b6c2bd521252970b2a10034f56143bedf19f5b0682f4cd1370e7d08f

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp311-cp311-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-cp311-cp311-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 42de84cdb08793f145a19d5e24fcee80e908aa201ca3cbc5ade253861b94a829
MD5 3cdc2d2881ca6f28e0c4777d9c2390c6
BLAKE2b-256 e1617ddc41485b2fb33fac56ecc2f4b59e9bca04771b84358acd483e291dddb4

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 f8750533c1c470b59d4b8450d2ffe4ca204c7da345510bc0d611de2300ee3f04
MD5 61f00ffb37c0417208d14338779fc5d4
BLAKE2b-256 eb25aa71755f7c4ece9f1403553fe1546a21414c72420df570d05292d3b96c19

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 6726fab18ddc7e61556d074b62a177d9020766b7510337db863e7b73632a9631
MD5 f25616b803f873a8f9e0168a5b47166a
BLAKE2b-256 4de71e066c96d7c698efdc46097408acdc361652b9051fa945e2fbc45eab63f8

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 305602bcdee2c43538058eb7869473f7ba7e09e7cfb5959f31fcfba7f7006517
MD5 6b4c39fc97cae15aadc584d75e7db3c8
BLAKE2b-256 707603339b5d34ea4d09e7050080809db966067801e76e99a786d6c6b334be07

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: pyscal3-3.1.1-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 247.8 kB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for pyscal3-3.1.1-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 9e39fa1cd87481fe4b36dde18a483d579f89220a47501e44d63e83b8c7993663
MD5 0601388908ca677e23dc334cd1978059
BLAKE2b-256 19aea49c52816ad217cf064aed66e24f4071a0b778f19cb0d95016e8cf69f4b1

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp310-cp310-win32.whl.

File metadata

  • Download URL: pyscal3-3.1.1-cp310-cp310-win32.whl
  • Upload date:
  • Size: 220.9 kB
  • Tags: CPython 3.10, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for pyscal3-3.1.1-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 7515f5b18ea598b16e5db8d8aaf6588cc4e0eced3ad8db2d62e2905a34aa6cbc
MD5 a6882bfa3f7fe07511fab27f4ae171ac
BLAKE2b-256 4c4eb873d6df7c1abf366d9a477b39e98efce9549edce41ac7e2ffaed2ab7b27

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp310-cp310-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-cp310-cp310-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 5331227c5c351427385083c261aa26b8a5db92edb87927ae5441ce04c38105e8
MD5 c1eddf66357a69e06ed4a32f68d64fbd
BLAKE2b-256 5a0cb4b64718f43f9f4e38bc5126d05e865436e5d784a2bd0fd6b7e15bacb627

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp310-cp310-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-cp310-cp310-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 52391a748bce498f6615c4a3461b5db73926e3911b9cd572dd3d1c0f83ea6a3a
MD5 c65cc019dc27ad70d42981f89b3417c0
BLAKE2b-256 67c8e88ba3ef4528b4de7f68a673ea8c60a97e0e01e002aee857190912ac5082

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 de466c6c5290e4ad6124380067097d0fbb200d705322b3528fe7945abafedebb
MD5 3a5f880c22d856a88c09a114ac2303e5
BLAKE2b-256 29f999e7563612f74d688f1334edeeca3f29649ad5aed982768d827eade1f878

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 91a8c4997c04698f36ec463637444f396bffd30db1e42e190c26805bec0edba5
MD5 e2f9e6fb868d7623fcb3e601957a48d8
BLAKE2b-256 c4c03e1f7bfaeb872450bd330573e9164b4da18c09fc42b042a09b7c36c27040

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 b7b2d1a613dbfdb400e63da7d56a226e0a7bdb07f735a5357af6c31324b20cb3
MD5 c67c098ff0142ef01784348c6e3cd440
BLAKE2b-256 2e6dcc73f5b6a6380c391ccf241164b97c76fc60a3fc2aa442fec2ddc175a9b6

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: pyscal3-3.1.1-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 246.6 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for pyscal3-3.1.1-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 6966876a45d0c549e3b876eea4615bfd2ba38a36a55147944ebdada79a079f10
MD5 f5e33c5efc99831394d878f457462a9a
BLAKE2b-256 707ee97b2e8ba006b41860f484d57bb522fb9bf3b99e53e5c31772d4e0f00988

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp39-cp39-win32.whl.

File metadata

  • Download URL: pyscal3-3.1.1-cp39-cp39-win32.whl
  • Upload date:
  • Size: 221.0 kB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for pyscal3-3.1.1-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 6dc16d05c02a6305f50867a62aba73f17298ed6d4951e7f7d55a6d51c43aa5ef
MD5 749a7e65437fd05dded3db983fcba962
BLAKE2b-256 72d8dbfdcb423a5591fe7362a70f82d603772470e4322c6575f6bd6b00e8aa9d

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp39-cp39-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-cp39-cp39-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 6b51319c7ba9ac50dd4b821d65060ad2b77a90055bbb8177a42a7a15234ea226
MD5 9185da555d3ecb23a60b96a88b836dd9
BLAKE2b-256 a4fa6b1c1af29564c2f625be7247685a8b98df26c89d5b0fd5540cf249f0fb90

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp39-cp39-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-cp39-cp39-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 0bee106da6220eb85b4208072e5ffc4a918189f4f7f8d0a6069d587c711d3b75
MD5 5d17ef3a4e515d88d0608e94c14441cc
BLAKE2b-256 32f42f555fd180906fe5c9ebd874c1bb905bee07fa1d01280b52d3f3dacad4fd

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 f6fceded97f4ae2145816843c6589ef1a4e63518d1d45e3ea15c801a72ebd407
MD5 cb0fb0b2a400026eaeb43c674de457ec
BLAKE2b-256 0bdb7ccfb6ab4590571c10c7831b43f795a9dc50ef6f852106d55fc362e6e437

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 9f3e536f64feda973396a88e8f6c3f3940e829d79db3ffd0f28746f260d16a86
MD5 c631645ce8d29c0c23859ca1e959f2b7
BLAKE2b-256 718959547975bb848b058abba6bb0327c09cd188bab8e4f611e12cbff7a6c3df

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 bc73eab0ef73225926ed7fbf4c7d711b54058773d5c1d7fd63be82abefa8ec26
MD5 35f5e76804192d0c866dc5869804e86a
BLAKE2b-256 17e642248d904ff636a61756938c94da8f520ab262b3842cee98ca50a845cd18

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: pyscal3-3.1.1-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 247.8 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for pyscal3-3.1.1-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 d3bec721086b19341f705f9eeb2d2d0f614dc5eb55f4936aa7926c74223fb748
MD5 32a2f756afcbf004d7c7bb102b794150
BLAKE2b-256 12f21814ffa60c6b2facf05a480a21b1d809e5bdfc5d187006a49738baee8570

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp38-cp38-win32.whl.

File metadata

  • Download URL: pyscal3-3.1.1-cp38-cp38-win32.whl
  • Upload date:
  • Size: 220.9 kB
  • Tags: CPython 3.8, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for pyscal3-3.1.1-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 dac96e6cfb7ee30abe30dc87daec101339c4539456225ff3f3631cdb2a7fe11a
MD5 cf5129de46664b3d476db13917beba88
BLAKE2b-256 eb763dd6670cd1ebcd6e1d71a7f6e0e954f0e4b105a138ec6d28ba1efdbcffe6

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp38-cp38-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-cp38-cp38-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 6991fa3cef751da33146065bbc9f85899e55b647a615f6745d6be13518783654
MD5 c1ee6b0ab08ca2b007938c0469dd75f8
BLAKE2b-256 b93fbd5e8eb51c1618cc9c13b7463b9d5cc9d2201ed8b7eed1192d11ba6de477

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp38-cp38-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-cp38-cp38-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 ca8ee0d06815e713af536cf172a157684652d68d6cb6f888c781156cd905ba52
MD5 c8ff3bbe36be837bc97a0477c0d9cd3f
BLAKE2b-256 50b26992b27ba3a286edade84a61ccd70edc127ca4783478b303165a0cb57a6b

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 4b92c9ce508cfb36abf404d89ef018ffcde9b64498620fe426bb8c3193bff74b
MD5 aca796c93859994f2a87128ed7e214f2
BLAKE2b-256 7eb1d6d5d46a8235891928c777b689068a1bd7fa284d2d148a24343ec0ece4e5

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 96688ae70e9790a8aeece2f0ad5d58b2e1079783a420eef5d0cdb72321bd7388
MD5 6884eaccad571aa4ed997ee1a75a88d1
BLAKE2b-256 5b5843d316d31d8198466fdad631756fbbc7329d1648aac7ffa38fbf18331bfe

See more details on using hashes here.

File details

Details for the file pyscal3-3.1.1-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyscal3-3.1.1-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 9347d3eab772bb6f0c84027abf77e501a4c60efc504a42f80836d3fd6ad5fb85
MD5 5ebcccf93cc5e95b1c84165fc7e628a5
BLAKE2b-256 2fbbd1aee14da9c3fc036526ae3c171a0d4a9fa9737e4c260abed1fd4c79b7de

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