Python Materials Genomics is a robust materials analysis code that defines core object representations for structures

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for janosh from gravatar.com janosh Avatar for mkhorton from gravatar.com mkhorton Avatar for Shyue.Ping.Ong from gravatar.com Shyue.Ping.Ong

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License (MIT)
  • Author: Pymatgen Development Team
  • Maintainer: Janosh Riebesell
  • Tags ABINIT, VASP, analysis, crystal, diagrams, electronic, gaussian, materials, nwchem, phase, project, qchem, science, structure
  • Requires: Python >=3.9
  • Provides-Extra: abinit, ase, ci, docs, electronic-structure, mlp, numba, optional, tblite, vis
Classifiers

Reason this release was yanked:

Backward incompatible change introduced.

Project description

Logo

CI Status codecov PyPI Downloads Conda Downloads Requires Python 3.9+ Paper

Pymatgen (Python Materials Genomics) is a robust, open-source Python library for materials analysis. These are some of the main features:

  1. Highly flexible classes for the representation of Element, Site, Molecule and Structure objects.
  2. Extensive input/output support, including support for VASP, ABINIT, CIF, Gaussian, XYZ, and many other file formats.
  3. Powerful analysis tools, including generation of phase diagrams, Pourbaix diagrams, diffusion analyses, reactions, etc.
  4. Electronic structure analyses, such as density of states and band structure.
  5. Integration with the Materials Project REST API.

Pymatgen is free to use. However, we also welcome your help to improve this library by making your contributions. These contributions can be in the form of additional tools or modules you develop, or feature requests and bug reports. The following are resources for pymatgen:

Why use pymatgen?

  1. It is (fairly) robust. Pymatgen is used by thousands of researchers and is the analysis code powering the Materials Project. The analysis it produces survives rigorous scrutiny every single day. Bugs tend to be found and corrected quickly. Pymatgen also uses Github Actions for continuous integration, which ensures that every new code passes a comprehensive suite of unit tests.
  2. It is well documented. A fairly comprehensive documentation has been written to help you get to grips with it quickly.
  3. It is open. You are free to use and contribute to pymatgen. It also means that pymatgen is continuously being improved. We will attribute any code you contribute to any publication you specify. Contributing to pymatgen means your research becomes more visible, which translates to greater impact.
  4. It is fast. Many of the core numerical methods in pymatgen have been optimized by vectorizing in numpy/scipy. This means that coordinate manipulations are fast. Pymatgen also comes with a complete system for handling periodic boundary conditions.
  5. It will be around. Pymatgen is not a pet research project. It is used in the well-established Materials Project. It is also actively being developed and maintained by the Materials Virtual Lab, the ABINIT group and many other research groups.
  6. A growing ecosystem of developers and add-ons. Pymatgen has contributions from materials scientists all over the world. We also now have an architecture to support add-ons that expand pymatgen's functionality even further. Check out the contributing page and add-ons page for details and examples.

Installation

The version at the Python Package Index PyPI is always the latest stable release that is relatively bug-free and can be installed via pip:

pip install pymatgen

If you'd like to use the latest unreleased changes on the main branch, you can install directly from GitHub:

pip install -U git+https://github.com/materialsproject/pymatgen

The minimum Python version is 3.9. Some extra functionality (e.g., generation of POTCARs) does require additional setup (see the pymatgen docs).

Change Log

See GitHub releases, docs/CHANGES.md or commit history in increasing order of details.

Using pymatgen

Please refer to the official pymatgen docs for tutorials and examples.

How to cite pymatgen

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

Shyue Ping Ong, William Davidson Richards, Anubhav Jain, Geoffroy Hautier, Michael Kocher, Shreyas Cholia, Dan Gunter, Vincent Chevrier, Kristin A. Persson, Gerbrand Ceder. Python Materials Genomics (pymatgen): A Robust, Open-Source Python Library for Materials Analysis. Computational Materials Science, 2013, 68, 314-319. doi:10.1016/j.commatsci.2012.10.028

In addition, some of pymatgen's functionality is based on scientific advances/principles developed by the computational materials scientists in our team. Please refer to the pymatgen docs on how to cite them.

Soliciting contributions to 2nd pymatgen paper

If you are a long-standing pymatgen contributor and would like to be involved in working on an updated pymatgen publication, please fill out this co-author registration form or contact @shyuep, @mkhorton and @janosh with questions.

License

Pymatgen is released under the MIT License. The terms of the license are as follows:

The MIT License (MIT) Copyright (c) 2011-2012 MIT & LBNL

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

About the Pymatgen Development Team

Shyue Ping Ong (@shyuep) of the Materials Virtual Lab started Pymatgen in 2011 and is still the project lead. Janosh Riebesell (@janosh) and Matthew Horton (@mkhorton) are co-maintainers.

The pymatgen development team is the set of all contributors to the pymatgen project, including all subprojects.

Our Copyright Policy

Pymatgen uses a shared copyright model. Each contributor maintains copyright over their contributions to pymatgen. But, it is important to note that these contributions are typically only changes to the repositories. Thus, the pymatgen source code, in its entirety is not the copyright of any single person or institution. Instead, it is the collective copyright of the entire pymatgen Development Team. If individual contributors want to maintain a record of what changes/contributions they have specific copyright on, they should indicate their copyright in the commit message of the change, when they commit the change to one of the pymatgen repositories.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for janosh from gravatar.com janosh Avatar for mkhorton from gravatar.com mkhorton Avatar for Shyue.Ping.Ong from gravatar.com Shyue.Ping.Ong

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License (MIT)
  • Author: Pymatgen Development Team
  • Maintainer: Janosh Riebesell
  • Tags ABINIT, VASP, analysis, crystal, diagrams, electronic, gaussian, materials, nwchem, phase, project, qchem, science, structure
  • Requires: Python >=3.9
  • Provides-Extra: abinit, ase, ci, docs, electronic-structure, mlp, numba, optional, tblite, vis
Classifiers

Release history Release notifications | RSS feed

2024.11.13

2024.10.29

2024.10.27

2024.10.25

2024.10.22

2024.10.3

2024.9.17.1

2024.9.17

2024.9.10

2024.8.9

This version

2024.8.8 yanked

Reason this release was yanked:

Backward incompatible change introduced.

2024.7.18

2024.6.10

2024.6.4

2024.5.31 yanked

2024.5.1

2024.4.13

2024.4.12

2024.3.1

2024.2.23

2024.2.20

2024.2.8

2024.1.27

2024.1.26

2023.12.18

2023.11.12

2023.11.10

2023.10.11

2023.10.4

2023.10.3

2023.9.25

2023.9.10

2023.9.2

2023.8.10

2023.7.20

2023.7.17

2023.7.14

2023.7.11

2023.6.28 yanked

Reason this release was yanked:

Bad release without wheels for some systems.

2023.6.23

2023.5.31

2023.5.10

2023.5.8

2023.3.23

2023.3.10

2023.2.28

2023.2.22

2023.1.30

2023.1.20

2023.1.9

2022.11.7

2022.11.1

2022.10.22

2022.9.21

2022.9.8

2022.8.23

2022.7.25

2022.7.24.1

2022.7.24 yanked

Reason this release was yanked:

remove defunct MPRester2 in favor of more streamlined handling of new and legacy API

2022.7.19

2022.7.8

2022.5.26

2022.5.19

2022.5.18.1

2022.5.18

2022.5.17

2022.4.26

2022.4.19

2022.3.29

2022.3.24

2022.3.22

2022.3.7

2022.2.10

2022.2.7

2022.2.1

2022.1.24

2022.1.20

2022.1.9

2022.1.8

2022.0.17

2022.0.16

2022.0.15

2022.0.14

2022.0.13

2022.0.12

2022.0.11

2022.0.10

2022.0.9

2022.0.8

2022.0.7

2022.0.6

2022.0.5

2022.0.4

2022.0.3

2022.0.2 yanked

Reason this release was yanked:

Buggy version

2022.0.1 yanked

Reason this release was yanked:

Buggy version

2022.0.0 yanked

Reason this release was yanked:

Buggy version

2021.3.9

2021.3.5

2021.3.4 yanked

Reason this release was yanked:

Breaking change in this version. Reverted in 2021.3.5.

2021.3.3

2021.2.16

2021.2.14

2021.2.13

2021.2.8.1

2021.2.8

2020.12.31

2020.12.18

2020.12.3

2020.11.11

2020.10.20

2020.10.9.1

2020.10.9

2020.9.14

2020.8.13

2020.8.3

2020.7.18

2020.7.16

2020.7.14

2020.7.10

2020.7.3

2020.6.8

2020.4.29

2020.4.2

2020.3.13

2020.3.2

2020.1.28

2020.1.10

2019.12.22

2019.12.3

2019.11.11

2019.10.16

2019.10.4

2019.10.3

2019.10.2

2019.9.16

2019.9.12

2019.9.8

2019.9.7

2019.8.23

2019.8.14

2019.7.30

2019.7.21

2019.7.2

2019.6.20

2019.6.5

2019.5.28

2019.5.8

2019.5.1

2019.4.11

2019.3.27

2019.3.13

2019.2.28

2019.2.24

2019.2.4

2019.1.24

2019.1.13

2018.12.12

2018.11.30

2018.11.6

2018.10.18

2018.9.30

2018.9.19

2018.9.12

2018.9.1

2018.8.10

2018.8.7

2018.7.23

2018.7.15

2018.6.27

2018.6.11

2018.5.22

2018.5.21

2018.5.14

2018.5.3

2018.4.20

2018.4.6

2018.3.23

2018.3.14

2018.3.13

2018.3.2

2018.2.13

2018.1.29

2018.1.19

2017.12.30

2017.12.16

2017.12.15

2017.12.8

2017.12.6

2017.11.30

2017.11.27

2017.11.9

2017.11.6

2017.10.16

2017.9.23

2017.9.3

2017.9.1

2017.8.21

2017.8.20

2017.8.16

2017.8.14

2017.8.4

2017.7.21

2017.7.4

2017.6.24

2017.6.22

2017.6.8

4.7.7

4.7.6

4.7.5

4.7.4

4.7.3

4.7.2

4.7.1

4.7.0

4.6.2

4.6.1

4.6.0

4.5.7

4.5.6

4.5.5

4.5.4

4.5.3

4.5.2

4.5.1

4.5.0

4.4.12

4.4.11

4.4.10

4.4.9

4.4.8

4.4.7

4.4.6

4.4.5

4.4.4

4.4.3

4.4.2

4.4.1

4.4.0

4.3.2

4.3.1

4.3.0

4.2.5

4.2.4

4.2.3

4.2.2

4.2.1

4.2.0

4.1.1

4.1.0

4.0.2

4.0.1

4.0.0

3.7.1

3.7.0

3.6.1

3.6.0

3.5.3

3.5.2

3.5.1

3.5.0

3.4.0

3.3.6

3.3.5

3.3.4

3.3.3

3.3.2

3.3.1

3.3.0

3.2.10

3.2.9

3.2.8

3.2.7

3.2.6

3.2.5

3.2.4

3.2.3

3.2.2

3.2.1

3.2.0

3.1.9

3.1.8

3.1.7

3.1.6

3.1.5

3.1.4

3.1.3

3.1.2

3.1.1

3.1.0

3.0.13

3.0.12

3.0.11

3.0.10

3.0.9

3.0.8

3.0.7

3.0.6

3.0.5

3.0.4

3.0.3

3.0.2

3.0.1

3.0.0

2.10.6

2.10.5

2.10.4

2.10.3

2.10.2

2.10.1

2.10.0

2.9.14

2.9.13

2.9.12

2.9.11

2.9.10

2.9.9

2.9.8

2.9.7

2.9.6

2.9.5

2.9.4

2.9.3

2.9.2

2.9.1

2.9.0

2.8.10

2.8.9

2.8.8

2.8.7

2.8.6

2.8.5

2.8.3

2.8.2

2.8.1

2.8.0

2.7.9

2.7.8

2.7.7

2.7.6

2.7.5

2.7.4

2.7.3

2.7.2b pre-release

2.7.1

2.7.0

2.6.6

2.6.5

2.6.4

2.6.3

2.6.2

2.6.1

2.5.5

2.5.4

2.5.3

2.5.2

2.5.1

2.5.0

2.4.3

2.4.2

2.4.1

2.4.0

2.3.2

2.3.1

2.3.0

2.2.6

2.2.4

2.2.3

2.2.2

2.2.1

2.2.0

2.1.2

2.1.0

2.0.0

1.9.0

1.8.3

1.8.2

1.8.0

1.7.2

1.7.0

1.6.0

1.5.0

1.2.9

1.2.8

1.2.4

1.2.3

1.2.2

1.2.1

1.2.0

1.1.2

1.1.1

1.1.0

1.0.5

1.0.4

Download files

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

Source Distribution

pymatgen-2024.8.8.tar.gz (3.1 MB view details)

Uploaded Source

Built Distributions

pymatgen-2024.8.8-cp312-cp312-win_amd64.whl (3.6 MB view details)

Uploaded CPython 3.12 Windows x86-64

pymatgen-2024.8.8-cp312-cp312-win32.whl (3.6 MB view details)

Uploaded CPython 3.12 Windows x86

pymatgen-2024.8.8-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (5.0 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ x86-64

pymatgen-2024.8.8-cp312-cp312-macosx_11_0_arm64.whl (3.6 MB view details)

Uploaded CPython 3.12 macOS 11.0+ ARM64

pymatgen-2024.8.8-cp311-cp311-win_amd64.whl (3.6 MB view details)

Uploaded CPython 3.11 Windows x86-64

pymatgen-2024.8.8-cp311-cp311-win32.whl (3.6 MB view details)

Uploaded CPython 3.11 Windows x86

pymatgen-2024.8.8-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (5.0 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

pymatgen-2024.8.8-cp311-cp311-macosx_11_0_arm64.whl (3.6 MB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

pymatgen-2024.8.8-cp310-cp310-win_amd64.whl (3.6 MB view details)

Uploaded CPython 3.10 Windows x86-64

pymatgen-2024.8.8-cp310-cp310-win32.whl (3.6 MB view details)

Uploaded CPython 3.10 Windows x86

pymatgen-2024.8.8-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.9 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

pymatgen-2024.8.8-cp310-cp310-macosx_11_0_arm64.whl (3.6 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

pymatgen-2024.8.8-cp39-cp39-win_amd64.whl (3.6 MB view details)

Uploaded CPython 3.9 Windows x86-64

pymatgen-2024.8.8-cp39-cp39-win32.whl (3.6 MB view details)

Uploaded CPython 3.9 Windows x86

pymatgen-2024.8.8-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.9 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

pymatgen-2024.8.8-cp39-cp39-macosx_11_0_arm64.whl (3.6 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

File details

Details for the file pymatgen-2024.8.8.tar.gz.

File metadata

  • Download URL: pymatgen-2024.8.8.tar.gz
  • Upload date:
  • Size: 3.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.5

File hashes

Hashes for pymatgen-2024.8.8.tar.gz
Algorithm Hash digest
SHA256 3b5c1ad44d2931f332feb6cf4e210f5663e106065b753c8e448d711e30ba70e5
MD5 b3661ed486595d8c8db310ad5edc7cfb
BLAKE2b-256 d72569e100fd31bacdd92e8de0b4629e30d691d95e6847fe7ef6fd9854746fdd

See more details on using hashes here.

File details

Details for the file pymatgen-2024.8.8-cp312-cp312-win_amd64.whl.

File metadata

File hashes

Hashes for pymatgen-2024.8.8-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 bc1eeb10393885adfadd4603f777af6c10d2bd0664d0c92a55b19d838f70fe2b
MD5 2d7afccde36f51f933bf9db655c8b7c9
BLAKE2b-256 b5772d11f6f1e60e2d79f7cff809d33ade29357e1b92965d0a5af917f413b99b

See more details on using hashes here.

File details

Details for the file pymatgen-2024.8.8-cp312-cp312-win32.whl.

File metadata

  • Download URL: pymatgen-2024.8.8-cp312-cp312-win32.whl
  • Upload date:
  • Size: 3.6 MB
  • Tags: CPython 3.12, Windows x86
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.5

File hashes

Hashes for pymatgen-2024.8.8-cp312-cp312-win32.whl
Algorithm Hash digest
SHA256 8d91046d7d60076e7a8483bfbbb683012bd9cdc7df4064fef12d28b95db95c71
MD5 b61a2d610311943361666c4591eb4bfe
BLAKE2b-256 93b822be16a459c8484c3e8120ec5786c4a093d6e7296b41268ec7335c14b2b3

See more details on using hashes here.

File details

Details for the file pymatgen-2024.8.8-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pymatgen-2024.8.8-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 78df33ff5fceca5abb0f3f8ef16c87daaedaf597b066dfecb3dbe7f47a597f86
MD5 f94cb454fbaf2c6338bab5db03298bbb
BLAKE2b-256 ea569892ba3b92eb7e19b498bf791433589aec59a32c9c8f7b809fde05b801c6

See more details on using hashes here.

File details

Details for the file pymatgen-2024.8.8-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pymatgen-2024.8.8-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 adcffaa11aab0dac414e612303eba732978ab07a9631c0a397d504940413d555
MD5 2cb9336660affdd451d6b406a7c5b8f4
BLAKE2b-256 fe5441b36ab09d3cc235746d50b29e2a065ae9e1f381c3f03712db9b696187fc

See more details on using hashes here.

File details

Details for the file pymatgen-2024.8.8-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for pymatgen-2024.8.8-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 7291cd9e92d8d8f8a07b0b33b7adf91352a88ecb5a5134a8326fa649ff3956de
MD5 c977e1a6257637c45eb396e0144eceba
BLAKE2b-256 c5df8ab17e3ddc464e7bcc7e86a66d366af8060c6bc23ba9b7df02d25e5f2269

See more details on using hashes here.

File details

Details for the file pymatgen-2024.8.8-cp311-cp311-win32.whl.

File metadata

  • Download URL: pymatgen-2024.8.8-cp311-cp311-win32.whl
  • Upload date:
  • Size: 3.6 MB
  • Tags: CPython 3.11, Windows x86
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.5

File hashes

Hashes for pymatgen-2024.8.8-cp311-cp311-win32.whl
Algorithm Hash digest
SHA256 71f6a6b9518dbf39826738fcdbfec53d26bb41c94b1c55c5d9a6de7c1183fcb6
MD5 4414662f43588cb2aff11a0f4423e8d2
BLAKE2b-256 64d8869571a95bae413c0705fcd276a7a8bfcd2989a0af30136ac4f2c74c7c28

See more details on using hashes here.

File details

Details for the file pymatgen-2024.8.8-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pymatgen-2024.8.8-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 633f26cadf889473bf614869a646b8f441bab39dfe1ada8774cce0ad1a6bda45
MD5 ac689ea55e27582c726cf98370415593
BLAKE2b-256 0d9543c0e06f9b3aadd7e47c931fb1a420e2acd6fff71b4b8c2b59c51d7802d2

See more details on using hashes here.

File details

Details for the file pymatgen-2024.8.8-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pymatgen-2024.8.8-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 9dd836cedb80c34c9f06319290f49a571d20f38d31677af89c6f906262123797
MD5 5ad8b7670cc9ddc8f0afe8b4e20f846c
BLAKE2b-256 8e4238a4ba35353400d26afb3bc9df136a6b3bdad367a8fe22dc45eeffe0c747

See more details on using hashes here.

File details

Details for the file pymatgen-2024.8.8-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for pymatgen-2024.8.8-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 7506b9bc54f41ffdfccdc8a7845f1393b19258ccd6809c280bd305f0c92e9a0d
MD5 be195a5357a6b902bb316996e7fc0727
BLAKE2b-256 6f2e7c0136097e2426c857f2b9bdc13a48ee0693ddf8aee45043f544ea3e40a7

See more details on using hashes here.

File details

Details for the file pymatgen-2024.8.8-cp310-cp310-win32.whl.

File metadata

  • Download URL: pymatgen-2024.8.8-cp310-cp310-win32.whl
  • Upload date:
  • Size: 3.6 MB
  • Tags: CPython 3.10, Windows x86
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.5

File hashes

Hashes for pymatgen-2024.8.8-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 b7543e0b76a114b360c07ec9b0bd83f076543d84c6994df0f6176c856fee6e54
MD5 8851b4fbbe4e025cc26ea100dd55c87b
BLAKE2b-256 2e781ad0390dedc56a8ba7ca60b8bcee7f1972018b5629dec868eaa6bc6dc7fd

See more details on using hashes here.

File details

Details for the file pymatgen-2024.8.8-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pymatgen-2024.8.8-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 8b5c8ac390d218c686872edacdb3a6adb169c056b37a10727f82c09fe972c949
MD5 e64cc513c759c13ed50bc164d9c2fac4
BLAKE2b-256 b773a88fd6a42b52460ebf62fdc84aba0da76f2ada36e9d0faa56557150136a0

See more details on using hashes here.

File details

Details for the file pymatgen-2024.8.8-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pymatgen-2024.8.8-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 3ceee63c5130e20bd53386fc34020654560f8705a7545a5a68093e33dfdeeba8
MD5 d2efd9a2dd08cd1a26f7010fed22797a
BLAKE2b-256 65ab2acf97edbf78c2e7d51a76cb535fc7ab90b7c82c942d88adc6e7a324abdb

See more details on using hashes here.

File details

Details for the file pymatgen-2024.8.8-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for pymatgen-2024.8.8-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 505d04f03a57a48ea0f09e9279fe5d3e007f8cea7c38610aac64d5b936fdd956
MD5 d9ae0997da7ed9dae631031c3c723053
BLAKE2b-256 0f534b2d4141633e7daad08a05e8cca0734476abe8b0c2ffbe0e2917e1d8fcc6

See more details on using hashes here.

File details

Details for the file pymatgen-2024.8.8-cp39-cp39-win32.whl.

File metadata

  • Download URL: pymatgen-2024.8.8-cp39-cp39-win32.whl
  • Upload date:
  • Size: 3.6 MB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.5

File hashes

Hashes for pymatgen-2024.8.8-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 fc3a42447d0ed555b1561f5f189b674f837c8466e63d42bf52ec6ab1f31d8759
MD5 fc40a4dfba370249832699843160028d
BLAKE2b-256 d21b3293bff80c5302708f631db7e6e2720a9fb026d789210d5f3d88939eb928

See more details on using hashes here.

File details

Details for the file pymatgen-2024.8.8-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pymatgen-2024.8.8-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 a7ea9ebece64583201102a92f6050f535d322ccce15fdd5d6ad990354755d7fa
MD5 b5d9b2e6c50b04e25210c144885e6317
BLAKE2b-256 034c95f991abe45ce7e0be4d23bcfa9b5277de5d5363d0c8e01863e8d081a377

See more details on using hashes here.

File details

Details for the file pymatgen-2024.8.8-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pymatgen-2024.8.8-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 1eabd22a7c9b07db49cb4846619dfdc7beede67edc3d37bb19466aca22a84464
MD5 6e845e018e4ca6c3c9c588395659e48c
BLAKE2b-256 a1e805b7bc235825ffe13c99926f4192d8c6535d01cc5f46d869eea8742815cc

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