CALPHAD tools for designing thermodynamic models, calculating phase diagrams and investigating phase equilibria.

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for bocklund from gravatar.com bocklund Avatar for rotis from gravatar.com rotis

Unverified details

These details have not been verified by PyPI
Project links
Meta
Classifiers
Report project as malware

Project description

Join the chat at https://gitter.im/pycalphad/pycalphad Test Coverage Build Status Development Status Latest version Supported Python versions License

Note: Unsolicited pull requests are _happily_ accepted!

pycalphad is a free and open-source Python library for designing thermodynamic models, calculating phase diagrams and investigating phase equilibria within the CALPHAD method. It provides routines for reading Thermo-Calc TDB files and for solving the multi-component, multi-phase Gibbs energy minimization problem.

The purpose of this project is to provide any interested people the ability to tinker with and improve the nuts and bolts of CALPHAD modeling without having to be a computer scientist or expert programmer.

For assistance in setting up your Python environment and/or collaboration opportunities, please contact the author by e-mail or using the issue tracker on GitHub.

pycalphad is licensed under the MIT License. See LICENSE.txt for details.

Required Dependencies:

  • Python 3.7+

  • matplotlib, numpy, scipy, sympy, symengine, xarray, pyparsing, tinydb

Installation

See Installation Instructions.

Examples

Jupyter notebooks with examples are available on NBViewer and pycalphad.org.

Documentation

See the documentation on pycalphad.org.

Getting Help

Questions about installing and using pycalphad can be addressed in the pycalphad Google Group. Technical issues and bugs should be reported on on GitHub. A public chat channel is available on Gitter.

Citing

If you use pycalphad in your research, please consider citing the following work:

Otis, R. & Liu, Z.-K., (2017). pycalphad: CALPHAD-based Computational Thermodynamics in Python. Journal of Open Research Software. 5(1), p.1. DOI: http://doi.org/10.5334/jors.140

Acknowledgements

Development has been made possible in part through NASA Space Technology Research Fellowship (NSTRF) grant NNX14AL43H, and is supervised by Prof. Zi-Kui Liu in the Department of Materials Science and Engineering at the Pennsylvania State University. We would also like to acknowledge technical assistance on array computations from Denis Lisov.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for bocklund from gravatar.com bocklund Avatar for rotis from gravatar.com rotis

Unverified details

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

Release history Release notifications | RSS feed

0.11.1

0.11.0

0.10.5

0.10.4.post1

0.10.3

0.10.2

0.10.1

0.10.0

0.9.2

This version

0.9.1

0.9.0

0.8.5

0.8.4

0.8.3

0.8.2

0.8.1.post1

0.8.1

0.8

0.7.1.post2

0.7.1.post1

0.7.1

0.7

0.6.1

0.6

0.5.2.post1

0.5.2

0.5.1

0.5

0.4.2

0.4.1

0.4

0.3.6

0.3.5

0.3.4

0.3.3

0.3.2

0.3.1

0.3

0.2.5

0.2.4

0.2.3

0.2.2

0.2.1

0.2

0.1.1.post1

0.1.1

0.0.1

Download files

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

Source Distribution

pycalphad-0.9.1.tar.gz (2.4 MB view details)

Uploaded Source

Built Distributions

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

pycalphad-0.9.1-cp39-cp39-win_amd64.whl (710.2 kB view details)

Uploaded CPython 3.9Windows x86-64

pycalphad-0.9.1-cp39-cp39-win32.whl (615.3 kB view details)

Uploaded CPython 3.9Windows x86

pycalphad-0.9.1-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (3.1 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.12+ x86-64manylinux: glibc 2.5+ x86-64

pycalphad-0.9.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl (3.0 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.12+ i686manylinux: glibc 2.5+ i686

pycalphad-0.9.1-cp39-cp39-macosx_11_0_arm64.whl (721.0 kB view details)

Uploaded CPython 3.9macOS 11.0+ ARM64

pycalphad-0.9.1-cp39-cp39-macosx_10_9_x86_64.whl (786.8 kB view details)

Uploaded CPython 3.9macOS 10.9+ x86-64

pycalphad-0.9.1-cp39-cp39-macosx_10_9_universal2.whl (1.3 MB view details)

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

pycalphad-0.9.1-cp38-cp38-win_amd64.whl (716.4 kB view details)

Uploaded CPython 3.8Windows x86-64

pycalphad-0.9.1-cp38-cp38-win32.whl (620.4 kB view details)

Uploaded CPython 3.8Windows x86

pycalphad-0.9.1-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (3.3 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.12+ x86-64manylinux: glibc 2.5+ x86-64

pycalphad-0.9.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl (3.2 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.12+ i686manylinux: glibc 2.5+ i686

pycalphad-0.9.1-cp38-cp38-macosx_11_0_arm64.whl (710.0 kB view details)

Uploaded CPython 3.8macOS 11.0+ ARM64

pycalphad-0.9.1-cp38-cp38-macosx_10_9_x86_64.whl (774.2 kB view details)

Uploaded CPython 3.8macOS 10.9+ x86-64

pycalphad-0.9.1-cp38-cp38-macosx_10_9_universal2.whl (1.3 MB view details)

Uploaded CPython 3.8macOS 10.9+ universal2 (ARM64, x86-64)

pycalphad-0.9.1-cp37-cp37m-win_amd64.whl (697.9 kB view details)

Uploaded CPython 3.7mWindows x86-64

pycalphad-0.9.1-cp37-cp37m-win32.whl (602.0 kB view details)

Uploaded CPython 3.7mWindows x86

pycalphad-0.9.1-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.12+ x86-64manylinux: glibc 2.5+ x86-64

pycalphad-0.9.1-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl (2.7 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.12+ i686manylinux: glibc 2.5+ i686

pycalphad-0.9.1-cp37-cp37m-macosx_10_9_x86_64.whl (769.0 kB view details)

Uploaded CPython 3.7mmacOS 10.9+ x86-64

File details

Details for the file pycalphad-0.9.1.tar.gz.

File metadata

  • Download URL: pycalphad-0.9.1.tar.gz
  • Upload date:
  • Size: 2.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.9.6

File hashes

Hashes for pycalphad-0.9.1.tar.gz
Algorithm Hash digest
SHA256 29b9ea7a5afd149a933707c1831fa5c1e53620db05544f91f5b3e7ecbde0738f
MD5 7d76967441c07d33075d2f5289186120
BLAKE2b-256 b2aa51ba58b94acf44fc59e9f0392cdde801461ec299604e704dae0e3f472b13

See more details on using hashes here.

File details

Details for the file pycalphad-0.9.1-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: pycalphad-0.9.1-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 710.2 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.9.6

File hashes

Hashes for pycalphad-0.9.1-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 e7fea22ce33be3047b711f450e12a434a636b4db45f205e3329f2cc2b43604cb
MD5 5696d1d594eb775924803bb5848fafc1
BLAKE2b-256 90851c9d43176597b4468543b535a81f6aceb9565ba7aead80eb01303e393689

See more details on using hashes here.

File details

Details for the file pycalphad-0.9.1-cp39-cp39-win32.whl.

File metadata

  • Download URL: pycalphad-0.9.1-cp39-cp39-win32.whl
  • Upload date:
  • Size: 615.3 kB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.9.6

File hashes

Hashes for pycalphad-0.9.1-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 f770b285c83fbef35c18cdba61fa9b2ca01227ed91e23e276462e92d9c21f9dc
MD5 bb0d6f6423b98c03509ac389c2a30def
BLAKE2b-256 7cdcd6f5ea1836011a99a80604b6eaa3b3b04b76eaaa3fb550b03ab28f2ec8dc

See more details on using hashes here.

File details

Details for the file pycalphad-0.9.1-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for pycalphad-0.9.1-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 7f6235645661cc7ac2846829e246b64506201ac3c92ba724a0dfe87bb2309227
MD5 c5521ee78f3b973c9168075d37b92c3e
BLAKE2b-256 b7723dabe84c75abbe807bda6ed115d296dbd10d1b517ee3ed97c1767f9c3c41

See more details on using hashes here.

File details

Details for the file pycalphad-0.9.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl.

File metadata

File hashes

Hashes for pycalphad-0.9.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl
Algorithm Hash digest
SHA256 ab4e9af8d7d3ed8a6dc34e971ffa28355c9c46023d03ffb6c61cae87dfd31c4e
MD5 aa6b0c198f46bd7730cbba0fe72a027b
BLAKE2b-256 66d12bd04c54d8faeb932feb8195665971f65bb893109f04cf691bce43908b6d

See more details on using hashes here.

File details

Details for the file pycalphad-0.9.1-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

  • Download URL: pycalphad-0.9.1-cp39-cp39-macosx_11_0_arm64.whl
  • Upload date:
  • Size: 721.0 kB
  • Tags: CPython 3.9, macOS 11.0+ ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.9.6

File hashes

Hashes for pycalphad-0.9.1-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 412d0efaab38abdccec562ac15585b345bc6d57c2e7739c8de06bf79e06fe78f
MD5 f9daa0eb74ddad170e53905475980f6f
BLAKE2b-256 f0516f7e4da81946ee32277ab725032589f083bbac731c31c55f5ef423ed16ef

See more details on using hashes here.

File details

Details for the file pycalphad-0.9.1-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: pycalphad-0.9.1-cp39-cp39-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 786.8 kB
  • Tags: CPython 3.9, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.9.6

File hashes

Hashes for pycalphad-0.9.1-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 4e58fe7b0c9e2afbb9552268a7eec56a9d6e5a6b106d1e0d627f155e0d28a58c
MD5 8e170999132ff75c2ab56e839c8c26d0
BLAKE2b-256 5cffc8a0571b1b9fc4aa2ccce6b061df820e9dd8324452238714b4709fdcd8ab

See more details on using hashes here.

File details

Details for the file pycalphad-0.9.1-cp39-cp39-macosx_10_9_universal2.whl.

File metadata

  • Download URL: pycalphad-0.9.1-cp39-cp39-macosx_10_9_universal2.whl
  • Upload date:
  • Size: 1.3 MB
  • Tags: CPython 3.9, macOS 10.9+ universal2 (ARM64, x86-64)
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.9.6

File hashes

Hashes for pycalphad-0.9.1-cp39-cp39-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 bfa5febcdd61fdf7c0d59fa6cd2071004da450161a6c633a78e22700e466e8bd
MD5 3b81a830e588131183cc0c439e24555f
BLAKE2b-256 38fe998465b19092aa039280c67f153334d2ba757e2cf713642ebe05f92a8fc3

See more details on using hashes here.

File details

Details for the file pycalphad-0.9.1-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: pycalphad-0.9.1-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 716.4 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.9.6

File hashes

Hashes for pycalphad-0.9.1-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 ad2f89d86775f4d7edb2d90c59fb417f8e1c1f9ef569c297c726387c97a266b3
MD5 53e086a3b96036883498fc1e88b2510f
BLAKE2b-256 603ac129a6e5c7a0e34b0960d27bdb9e419ec0ab67a69131c56c1a62a394e784

See more details on using hashes here.

File details

Details for the file pycalphad-0.9.1-cp38-cp38-win32.whl.

File metadata

  • Download URL: pycalphad-0.9.1-cp38-cp38-win32.whl
  • Upload date:
  • Size: 620.4 kB
  • Tags: CPython 3.8, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.9.6

File hashes

Hashes for pycalphad-0.9.1-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 bceb48349be90f07920145a11f217f0802a59031494f5c2d8a20b199f69ab522
MD5 b60dd9ffc503a3d7abfb76d4606f087c
BLAKE2b-256 044b34e979cee5bfa2458dc33665dc2d69cb64583fea4009e3e53ec1993ce7c9

See more details on using hashes here.

File details

Details for the file pycalphad-0.9.1-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for pycalphad-0.9.1-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 d57e277b6bae971beb77e2a2903da6aef568244f9c2a1731ab57b40791c63695
MD5 20d3d9b813031ffad3d9d38937e494db
BLAKE2b-256 837fd6a402445c61bdd10243462d6bc9c7cd59c7a9f2d94716ecce7c27aab12e

See more details on using hashes here.

File details

Details for the file pycalphad-0.9.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl.

File metadata

File hashes

Hashes for pycalphad-0.9.1-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl
Algorithm Hash digest
SHA256 490b6347fd8be13db350d3312d5600e66dda1ba00f365609cccda7f6038a4fbb
MD5 c6994894221b96925d1598f8f37a73ae
BLAKE2b-256 ed4a7712a74ed43a2da357099d13321ac519097511f8a65878880965d3ab7bee

See more details on using hashes here.

File details

Details for the file pycalphad-0.9.1-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

  • Download URL: pycalphad-0.9.1-cp38-cp38-macosx_11_0_arm64.whl
  • Upload date:
  • Size: 710.0 kB
  • Tags: CPython 3.8, macOS 11.0+ ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.9.6

File hashes

Hashes for pycalphad-0.9.1-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 5e9d2c2f0c6e35cd743d178fe42b21b817d6936f8674ddfe884145d217e9e8d3
MD5 dc2f6e96326bbb69f0f16891d8782bb0
BLAKE2b-256 68e91c1c5789934a5eed06863134c48316f4916b4d9cb45a46fb430f02733de0

See more details on using hashes here.

File details

Details for the file pycalphad-0.9.1-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: pycalphad-0.9.1-cp38-cp38-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 774.2 kB
  • Tags: CPython 3.8, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.9.6

File hashes

Hashes for pycalphad-0.9.1-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 cb928adc31ec7f9023838401f1d79b0c0ce76c961fbd0e5d8ea23b95ab59bc5e
MD5 8d6e77a24944de895c928d621dc85e32
BLAKE2b-256 026578b0d4a9c03847a02184c592adc190f0c293987a29476272627e8d50cd01

See more details on using hashes here.

File details

Details for the file pycalphad-0.9.1-cp38-cp38-macosx_10_9_universal2.whl.

File metadata

  • Download URL: pycalphad-0.9.1-cp38-cp38-macosx_10_9_universal2.whl
  • Upload date:
  • Size: 1.3 MB
  • Tags: CPython 3.8, macOS 10.9+ universal2 (ARM64, x86-64)
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.9.6

File hashes

Hashes for pycalphad-0.9.1-cp38-cp38-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 9d339ec8e4f31518ef9b3cbb931910923a5be55a1f34fe71830c166386e8fd0b
MD5 7bcc95fc643b29d22f782da2cbba160c
BLAKE2b-256 9a32d696c672c23637604b31f4fb5bb70ff280f6420987b399b4d20f6d4f13cc

See more details on using hashes here.

File details

Details for the file pycalphad-0.9.1-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: pycalphad-0.9.1-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 697.9 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.9.6

File hashes

Hashes for pycalphad-0.9.1-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 8b2f34f0567933e7bebadfcc7d9d46f5e05404fce6f222e615966518be33ea46
MD5 47331005ef1036cee03a0547e4cb4d7d
BLAKE2b-256 814db4949045714432b5a257be77acae55bdebe78b9406a53f72bc705b202837

See more details on using hashes here.

File details

Details for the file pycalphad-0.9.1-cp37-cp37m-win32.whl.

File metadata

  • Download URL: pycalphad-0.9.1-cp37-cp37m-win32.whl
  • Upload date:
  • Size: 602.0 kB
  • Tags: CPython 3.7m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.9.6

File hashes

Hashes for pycalphad-0.9.1-cp37-cp37m-win32.whl
Algorithm Hash digest
SHA256 d846500316884161a80c03dca43f55829aceb42660214bf1efcc84e18c8dcbd2
MD5 f10d76c2a2d578dd9794c6e432228d47
BLAKE2b-256 321555bcad827dfe20db4aaf65c0b0163efcd5eb3f3e829b475496df0e8fd5fe

See more details on using hashes here.

File details

Details for the file pycalphad-0.9.1-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for pycalphad-0.9.1-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 2735d8618c7ad188689a4d430c8f7e945f913db4aeaed0cc99a3664ef79b4083
MD5 1ea3bb04e2ab806d083e20a28934c11e
BLAKE2b-256 e8fbbdbbb9b8c61cff2fc8f5620fc27eaab167f1f97e30c3ac7ec1f201999003

See more details on using hashes here.

File details

Details for the file pycalphad-0.9.1-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl.

File metadata

File hashes

Hashes for pycalphad-0.9.1-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl
Algorithm Hash digest
SHA256 c6f05a9d035a590421b258ab45fd64de160fed72a2a17d35449ffe210f2b27c4
MD5 ef3bf73c44235cc4263c72756d2d168d
BLAKE2b-256 33ceaa79124bcd45c28767a54828a0330b8ccd020fb85a7885bc974e0b463177

See more details on using hashes here.

File details

Details for the file pycalphad-0.9.1-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: pycalphad-0.9.1-cp37-cp37m-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 769.0 kB
  • Tags: CPython 3.7m, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.3 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.9.6

File hashes

Hashes for pycalphad-0.9.1-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 caf3759ea85d12bf888396e6c93f6149c10c59a415c4142496824448924c0b4b
MD5 0ffb4df2ee48c9410c669c1e2541664f
BLAKE2b-256 66e80ec57c86a6484d32c8aa353b4c26324aec3b15d8c0ab87fd52e197d1d723

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