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
Project links
GitHub Statistics
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 >=3.10
  • Provides-Extra: abinit, ase, ci, docs, electronic-structure, mlp, numba, numpy-v1, optional, tblite, vis
Classifiers

Project description

Logo

CI Status codecov PyPI Downloads Conda Downloads Requires Python 3.10+ 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 3.10. 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
Project links
GitHub Statistics
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 >=3.10
  • Provides-Extra: abinit, ase, ci, docs, electronic-structure, mlp, numba, numpy-v1, 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

This version

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

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 Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

pymatgen-2024.9.10-cp312-cp312-win_amd64.whl (3.6 MB view details)

Uploaded CPython 3.12 Windows x86-64

pymatgen-2024.9.10-cp312-cp312-win32.whl (3.6 MB view details)

Uploaded CPython 3.12 Windows x86

pymatgen-2024.9.10-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-2024.9.10-cp312-cp312-macosx_11_0_arm64.whl (3.6 MB view details)

Uploaded CPython 3.12 macOS 11.0+ ARM64

pymatgen-2024.9.10-cp311-cp311-win_amd64.whl (3.6 MB view details)

Uploaded CPython 3.11 Windows x86-64

pymatgen-2024.9.10-cp311-cp311-win32.whl (3.6 MB view details)

Uploaded CPython 3.11 Windows x86

pymatgen-2024.9.10-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-2024.9.10-cp311-cp311-macosx_11_0_arm64.whl (3.6 MB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

pymatgen-2024.9.10-cp310-cp310-win_amd64.whl (3.6 MB view details)

Uploaded CPython 3.10 Windows x86-64

pymatgen-2024.9.10-cp310-cp310-win32.whl (3.6 MB view details)

Uploaded CPython 3.10 Windows x86

pymatgen-2024.9.10-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-2024.9.10-cp310-cp310-macosx_11_0_arm64.whl (3.6 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

File details

Details for the file pymatgen-2024.9.10-cp312-cp312-win_amd64.whl.

File metadata

File hashes

Hashes for pymatgen-2024.9.10-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 c60e6205b56b1614e721d39e6ed28e3928c09f5f6adfc7fe9683959e1d24ce57
MD5 e4b34bfed4f9bd2fa72d71cc9d98e11e
BLAKE2b-256 60e3c71084a27d00276f5475b14c2872b0d9392a1b0f9123e545415045f2a28f

See more details on using hashes here.

File details

Details for the file pymatgen-2024.9.10-cp312-cp312-win32.whl.

File metadata

File hashes

Hashes for pymatgen-2024.9.10-cp312-cp312-win32.whl
Algorithm Hash digest
SHA256 e8cc0e34dbc3c3a67b49010213488f8a5a91997fae5cb97df0aca3536c8d284d
MD5 d0615f2f51132c3e068a69149f647e7a
BLAKE2b-256 ddf0ef164a13860dd81149136662c792892a52a9af7345d85b70200edb90db26

See more details on using hashes here.

File details

Details for the file pymatgen-2024.9.10-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pymatgen-2024.9.10-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 07e3ead3033f39e3bb0b6d610dc0c1960132a6f9514b2a0d0102015e6490427d
MD5 82c8bf16063f3ac1ed6d95aaaccb9930
BLAKE2b-256 78c5146a61d6e5a0cc6ea46bd6db34cb9bb9d1975f9d4e962fe1fc1e6c183f5b

See more details on using hashes here.

File details

Details for the file pymatgen-2024.9.10-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pymatgen-2024.9.10-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 bf69561d9b3cb08f84383fec10d8e6c6f102c728a795a791c87457d663f1050a
MD5 dd7c874985196ee4abba6b30ea9ba978
BLAKE2b-256 22e185f970e1dff8d6f4beb129019751e30a88f564f40df910182c22b6e0dba2

See more details on using hashes here.

File details

Details for the file pymatgen-2024.9.10-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for pymatgen-2024.9.10-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 fcba8df11327f8c0646abb2684416a725355da8db46507e3fcc98e6d3a431372
MD5 a8bca1095479be5d4fa190d9eaa185f9
BLAKE2b-256 c7772143a10bb60097155fe710d06d5b355d716612942062286824a2db553b86

See more details on using hashes here.

File details

Details for the file pymatgen-2024.9.10-cp311-cp311-win32.whl.

File metadata

File hashes

Hashes for pymatgen-2024.9.10-cp311-cp311-win32.whl
Algorithm Hash digest
SHA256 139ad0b32f3462ad52ff67c1e0acca9ca9ba17eb63ed34fde424a8ced52a39f9
MD5 1955d79e0ff3b37c769cd44214288ed9
BLAKE2b-256 ae2d3e2dbbf584961b953b0f1d2d5a43fee0fb80820e5fabafa1d2fc1c3fe731

See more details on using hashes here.

File details

Details for the file pymatgen-2024.9.10-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pymatgen-2024.9.10-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 578959ef92c260b3ed87ce988ee6d3c47913ec18a943460727fd2da8e711c34d
MD5 e4fa3bc1ba8a14411230f050ba7ff5db
BLAKE2b-256 f75f889608124b84783352a9ce207aab6f06333c26e565d295c42dda6d014da1

See more details on using hashes here.

File details

Details for the file pymatgen-2024.9.10-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pymatgen-2024.9.10-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 9eb3741db591ed9bb33e861f0abd356e729619c6666736228035060c6657ae5c
MD5 05e9b3d179f6bb9cbf064b17291c0d0a
BLAKE2b-256 5e833270ffbd1ad4f276a18cfd229237b0191b3dddf51df2b056dad03221442e

See more details on using hashes here.

File details

Details for the file pymatgen-2024.9.10-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for pymatgen-2024.9.10-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 d62e9b85e934656bba1a6f17795c45f4efe18a61d2aa95a0b88a5db112369cad
MD5 422f43ce17a74eef270d2cb1a22971be
BLAKE2b-256 c4b907b0702b2641e8e4a136334fee4ea0a7d36a3f6f0ae77af07c3fce1371e7

See more details on using hashes here.

File details

Details for the file pymatgen-2024.9.10-cp310-cp310-win32.whl.

File metadata

File hashes

Hashes for pymatgen-2024.9.10-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 eef62a40ba5e3334128b9aa55679c80c6831dc51b89c9b3265e8626034f9c05d
MD5 b6641deead658aea834d7cbebe090ed1
BLAKE2b-256 7fdc802fa3394f149a4686042737efddd8d7c15a209b34504e20462cfc91f11b

See more details on using hashes here.

File details

Details for the file pymatgen-2024.9.10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pymatgen-2024.9.10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 e69afa91e9a14d43190eff8ddd1b11048e938483019ad2ff5c13dbe9df010267
MD5 8848cff84cf8c5df1e5d0c75e544db92
BLAKE2b-256 c7fef7e564cbaf973d8e41e57ef7abf3c6089bfe9b0dba1b530fc10627d0555e

See more details on using hashes here.

File details

Details for the file pymatgen-2024.9.10-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pymatgen-2024.9.10-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 9ac461f55058e6ac861dda2950fa75773e8927631c9b670cd8099b1272afbe6c
MD5 796f971be782a4e0bd1b4bea273ba5d8
BLAKE2b-256 34654f2174375063273bd02d38cdc5247bd360e270c65d8f9e6b01518c4fc02d

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