Python Materials Genomics is a robust materials analysis code that defines core object representations for structures and molecules with support for many electronic structure codes. It is currently the core analysis code powering the Materials Project (https://materialsproject.org).

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
Classifiers

Project description

Logo

CI Status Coveralls PyPI Downloads Conda Downloads Requires Python 3.8+

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 extremely fast and are in fact comparable to codes written in other languages. 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 3.8. Some extra functionality (e.g., generation of POTCARs) does require additional setup (see the pymatgen page).

Change Log

Please check GitHub releases and commit history for the latest changes. A legacy changelog is still up at https://pymatgen.org/change_log.

Using pymatgen

Please refer to the official pymatgen page 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 pymatgen's documentation on how to cite them.

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 of the Materials Virtual Lab started Pymatgen in 2011 and is still the project lead.

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
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

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

This version

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-2023.5.10.tar.gz (9.7 MB view details)

Uploaded Source

Built Distributions

pymatgen-2023.5.10-cp311-cp311-win_amd64.whl (10.2 MB view details)

Uploaded CPython 3.11 Windows x86-64

pymatgen-2023.5.10-cp311-cp311-win32.whl (10.2 MB view details)

Uploaded CPython 3.11 Windows x86

pymatgen-2023.5.10-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.5 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

pymatgen-2023.5.10-cp311-cp311-macosx_10_9_x86_64.whl (10.2 MB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

pymatgen-2023.5.10-cp310-cp310-win_amd64.whl (10.2 MB view details)

Uploaded CPython 3.10 Windows x86-64

pymatgen-2023.5.10-cp310-cp310-win32.whl (10.2 MB view details)

Uploaded CPython 3.10 Windows x86

pymatgen-2023.5.10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.4 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

pymatgen-2023.5.10-cp310-cp310-macosx_10_9_x86_64.whl (10.2 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

pymatgen-2023.5.10-cp39-cp39-win_amd64.whl (10.2 MB view details)

Uploaded CPython 3.9 Windows x86-64

pymatgen-2023.5.10-cp39-cp39-win32.whl (10.2 MB view details)

Uploaded CPython 3.9 Windows x86

pymatgen-2023.5.10-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.5 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

pymatgen-2023.5.10-cp39-cp39-macosx_11_0_arm64.whl (10.2 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

pymatgen-2023.5.10-cp39-cp39-macosx_10_9_x86_64.whl (10.2 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

pymatgen-2023.5.10-cp38-cp38-win_amd64.whl (10.2 MB view details)

Uploaded CPython 3.8 Windows x86-64

pymatgen-2023.5.10-cp38-cp38-win32.whl (10.2 MB view details)

Uploaded CPython 3.8 Windows x86

pymatgen-2023.5.10-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.5 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

pymatgen-2023.5.10-cp38-cp38-macosx_10_9_x86_64.whl (10.2 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

File details

Details for the file pymatgen-2023.5.10.tar.gz.

File metadata

  • Download URL: pymatgen-2023.5.10.tar.gz
  • Upload date:
  • Size: 9.7 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.16

File hashes

Hashes for pymatgen-2023.5.10.tar.gz
Algorithm Hash digest
SHA256 81bf2646c14933fe425acfb7afe947ef5411c3144caae7263fe7347f4b797e2a
MD5 1b660b63184f0c5087e1dbddd13f0978
BLAKE2b-256 acb7e374f521e3cccd6b46db8b2c0f2697fdf60e8e2d2b4dc9ce330a0c31e3c9

See more details on using hashes here.

File details

Details for the file pymatgen-2023.5.10-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for pymatgen-2023.5.10-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 a631ff10e69cfbf251170fb1da46e503a3dbfc28cde067998f34aeafe760bade
MD5 f15716e2971ca125744186a3982614e6
BLAKE2b-256 bd9b377cf0e30196b28906c2e501a655be90256eb3fcd2762094dfc937212e37

See more details on using hashes here.

File details

Details for the file pymatgen-2023.5.10-cp311-cp311-win32.whl.

File metadata

File hashes

Hashes for pymatgen-2023.5.10-cp311-cp311-win32.whl
Algorithm Hash digest
SHA256 12544cba3b72519fe764c88fc7df2cae93448782a3b8d139887cbda013f044f1
MD5 411d80fe5d0c53cddc2ea7407105e65b
BLAKE2b-256 6d64b59e83a3352ba802b18b3565aad08b3b798484ed627edcab02aefd75d08c

See more details on using hashes here.

File details

Details for the file pymatgen-2023.5.10-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pymatgen-2023.5.10-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 df42c06788c6c3ca70f909db9f4d65ec7f7e50316d0163161576e503ec3ff346
MD5 0c9d456fab3e39f78756d71eb5575a18
BLAKE2b-256 15d2c1bc852722da5f596b4a9d84d69123ee4496675f088af982d130151f0381

See more details on using hashes here.

File details

Details for the file pymatgen-2023.5.10-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pymatgen-2023.5.10-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 4566a30be7cd6f74e54c1c786aef9ebaf3bf97bba741d166c7c97070c3aa9388
MD5 37b2b0c6dc03583272528feb53eb676b
BLAKE2b-256 9906c4ec5247515c0249a7bd3efa708cd909d2fbe40db2f10cb1fe1e8ca4d5e4

See more details on using hashes here.

File details

Details for the file pymatgen-2023.5.10-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for pymatgen-2023.5.10-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 d48936096df7dfaa765efdd7dca1eda4bd049723656382543bd20de213f39441
MD5 fb0b373245526c5bb264362fb408f36c
BLAKE2b-256 2248009efff02df01dd1a8779c0b7c442883ea9fd2f8ee76fb3f1ce91fd31f35

See more details on using hashes here.

File details

Details for the file pymatgen-2023.5.10-cp310-cp310-win32.whl.

File metadata

File hashes

Hashes for pymatgen-2023.5.10-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 db57e6d5f4d4e6f43c2ccc05c49d2881152dc9c9cc00cee4146090e7b9075952
MD5 3e65c6045f208769d02fed66dc66c25a
BLAKE2b-256 8ebcc0121ffbfbcd44eefe428258d006410a52dc482e031f1806cb24c8696d8c

See more details on using hashes here.

File details

Details for the file pymatgen-2023.5.10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pymatgen-2023.5.10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 e9a6651e884df8badc8f417346bdcb85625596094f5da1ac68c51ee35b460366
MD5 906f5a0ecd2d2e83ec4b949715c980a6
BLAKE2b-256 9c8443ba6652458e0231ce4959d0ff9bb29e9e8fb6f0803c75baf88844040c9f

See more details on using hashes here.

File details

Details for the file pymatgen-2023.5.10-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pymatgen-2023.5.10-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 dffbc65763208e32b388e7bfa275b1f6b638a66163cd457e8c54e8aa17bf3266
MD5 a3723bd46ea6818b25a215405081ea2c
BLAKE2b-256 99c72efce32172eb23fcccaf7b7364dea72c542f7eefc064681747f2b67512c0

See more details on using hashes here.

File details

Details for the file pymatgen-2023.5.10-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for pymatgen-2023.5.10-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 cee2c05bf501e96e1be13605539535712b20cd9041b5bc764658cdfe0b4f9570
MD5 f71bc3368118ab075348532aa6c982ec
BLAKE2b-256 476085695304f7792dfa55affd880d2149b89c2f856c8736a3b4d7fdfb06daea

See more details on using hashes here.

File details

Details for the file pymatgen-2023.5.10-cp39-cp39-win32.whl.

File metadata

  • Download URL: pymatgen-2023.5.10-cp39-cp39-win32.whl
  • Upload date:
  • Size: 10.2 MB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.6

File hashes

Hashes for pymatgen-2023.5.10-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 339c72ac95aa8d594ea843f9f75c36cf088ddf9c46cae2931c6c550d0022d1c4
MD5 fc8edd307d5eb6701980dbf95ad15260
BLAKE2b-256 5d91e5a87d298114a5e1d1667b19f12631bc539cf3f887e3cbd45e22c18e7053

See more details on using hashes here.

File details

Details for the file pymatgen-2023.5.10-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pymatgen-2023.5.10-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 918ba1988af139a3949c312c0cdd16c7650480e39feb786a237e5c9a0c19c94b
MD5 122479d58e782a7214566494aad148f7
BLAKE2b-256 3dfb6ef2421d9d9a829f5212d2b8086084257fec9ceb2bf8bdf1000760024abd

See more details on using hashes here.

File details

Details for the file pymatgen-2023.5.10-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pymatgen-2023.5.10-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 2c49c6e4d9c77c39015f2f50be07171126b72e924f0b3f086be9be10a7c01059
MD5 3c1b7b7e719587cd5ce9b6110be4a6ef
BLAKE2b-256 f932aaceb09f28da135a81d4243291cb7c76fad0be7f29fc01a03a5e645debc0

See more details on using hashes here.

File details

Details for the file pymatgen-2023.5.10-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pymatgen-2023.5.10-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 0848b01605b5a9e5cc552033795161e19bb440d584f3acec6ecdd1beac193c25
MD5 2115ef99fd7cd18de86e0e206e129e4f
BLAKE2b-256 9cebe7244c345617916b0abe5c070a18728cedcebb7f104ca4759cc4544cbf5c

See more details on using hashes here.

File details

Details for the file pymatgen-2023.5.10-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for pymatgen-2023.5.10-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 03b935cebe1413fcf58d8bb8b6920ae97812ffbf55db42217e662778bac91802
MD5 0c8765a481b53cbc767d967f9c6ec0c0
BLAKE2b-256 3229ee37400fe50b3fe60f58b046ee983ae19f95ac0d9b730149cb26a9d3d1ad

See more details on using hashes here.

File details

Details for the file pymatgen-2023.5.10-cp38-cp38-win32.whl.

File metadata

  • Download URL: pymatgen-2023.5.10-cp38-cp38-win32.whl
  • Upload date:
  • Size: 10.2 MB
  • Tags: CPython 3.8, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.6

File hashes

Hashes for pymatgen-2023.5.10-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 3a7b7489efb4e5fa89d2978d380f06815bd7f103213b1c0a4278667fd9091e20
MD5 fbc5cd07bfe983ba01884c9702dc775d
BLAKE2b-256 b4196d021f0a103d35cd73709160ad9abe4bb20b6cabe64c24f6f7b57ef49e76

See more details on using hashes here.

File details

Details for the file pymatgen-2023.5.10-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pymatgen-2023.5.10-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 755167e62dd98e0d039dd04e4804684318d9cd1c9187f380a7758a60dc1da953
MD5 67de39cb0d2b1eaa1bcf790b2fb12f1b
BLAKE2b-256 20e2ac81881574a268d0d2ab432620eeb590cf2316e21c46ba7b5c749fde30ac

See more details on using hashes here.

File details

Details for the file pymatgen-2023.5.10-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pymatgen-2023.5.10-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 e850646f421df236d61ae050aa1c1d2dc459f6a7671477cac397eba2290236e8
MD5 3ef8b96bcf90c1323f89529056536c9f
BLAKE2b-256 db42c60e3d4a13cd99dca06180f03d5a9db96e82a61570b81c859e3abc2d535d

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