# Metatensor
[](https://github.com/lab-cosmo/metatensor/actions?query=branch%3Amaster)
[](https://lab-cosmo.github.io/metatensor/latest/)
[]( https://codecov.io/gh/lab-cosmo/metatensor)
Metatensor is a self-describing sparse tensor data format for atomistic machine
learning and beyond; storing values and gradients of these values together.
Think numpy `ndarray` or pytorch `Tensor` equipped with extra metadata for
atomic systems and other point clouds data. The core of this library is written
in Rust and we provide API for C, C++, and Python.
The main class of metatensor is the `TensorMap` data structure, defining a
custom block-sparse data format. If you are using metatensor from Python, we
additionally provide a collection of mathematical, logical and other utility
operations to make working with TensorMaps more convenient.
## Documentation
For details, tutorials, and examples, please have a look at our [documentation](https://lab-cosmo.github.io/metatensor/latest/).
## Contributors
Thanks goes to all people that make metatensor possible:
[](https://github.com/lab-cosmo/metatensor/graphs/contributors)
We always welcome new contributors. If you want to help us take a look at our
[contribution guidelines](CONTRIBUTING.rst) and afterwards you may start with an
open issue marked as [good first
issue](https://github.com/lab-cosmo/metatensor/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22).
Raw data
{
"_id": null,
"home_page": "",
"name": "metatensor",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.8",
"maintainer_email": "",
"keywords": "machine learning,molecular modeling",
"author": "Guillaume Fraux, Davide Tisi, Philip Loche, Joseph W. Abbott, Jigyasa Nigam, Chiheb Ben Mahmoud",
"author_email": "",
"download_url": "https://files.pythonhosted.org/packages/3e/58/172e96ccdca4d8d572579adc69b593dad79b74497c116ed86979257a5cbd/metatensor-0.2.0.tar.gz",
"platform": null,
"description": "# Metatensor\n\n[](https://github.com/lab-cosmo/metatensor/actions?query=branch%3Amaster)\n[](https://lab-cosmo.github.io/metatensor/latest/)\n[]( https://codecov.io/gh/lab-cosmo/metatensor)\n\nMetatensor is a self-describing sparse tensor data format for atomistic machine\nlearning and beyond; storing values and gradients of these values together.\nThink numpy `ndarray` or pytorch `Tensor` equipped with extra metadata for\natomic systems and other point clouds data. The core of this library is written\nin Rust and we provide API for C, C++, and Python.\n\nThe main class of metatensor is the `TensorMap` data structure, defining a\ncustom block-sparse data format. If you are using metatensor from Python, we\nadditionally provide a collection of mathematical, logical and other utility\noperations to make working with TensorMaps more convenient.\n\n## Documentation\n\nFor details, tutorials, and examples, please have a look at our [documentation](https://lab-cosmo.github.io/metatensor/latest/).\n\n## Contributors\n\nThanks goes to all people that make metatensor possible:\n\n[](https://github.com/lab-cosmo/metatensor/graphs/contributors)\n\nWe always welcome new contributors. If you want to help us take a look at our\n[contribution guidelines](CONTRIBUTING.rst) and afterwards you may start with an\nopen issue marked as [good first\nissue](https://github.com/lab-cosmo/metatensor/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22).\n",
"bugtrack_url": null,
"license": "BSD-3-Clause",
"summary": "Self-describing sparse tensor data format for atomistic machine learning and beyond",
"version": "0.2.0",
"project_urls": {
"changelog": "https://lab-cosmo.github.io/metatensor/latest/core/CHANGELOG.html",
"documentation": "https://lab-cosmo.github.io/metatensor/latest/",
"homepage": "https://lab-cosmo.github.io/metatensor/latest/",
"repository": "https://github.com/lab-cosmo/metatensor"
},
"split_keywords": [
"machine learning",
"molecular modeling"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "f728fd3f02ccb23764af794e953262127a7f2aed35073f460da6f279fe1c2b15",
"md5": "35f6b77f120b503502984edc4b366fc4",
"sha256": "60008fee73f49b349350d9d93dec63ea4e1cf30beceae17d543561d69a7ac393"
},
"downloads": -1,
"filename": "metatensor-0.2.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "35f6b77f120b503502984edc4b366fc4",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.8",
"size": 3702,
"upload_time": "2024-01-26T17:26:59",
"upload_time_iso_8601": "2024-01-26T17:26:59.518763Z",
"url": "https://files.pythonhosted.org/packages/f7/28/fd3f02ccb23764af794e953262127a7f2aed35073f460da6f279fe1c2b15/metatensor-0.2.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "3e58172e96ccdca4d8d572579adc69b593dad79b74497c116ed86979257a5cbd",
"md5": "b010f9637fa8b1246932138d991a7ee0",
"sha256": "ce3f8a34796d2aaa7e74b2d1392f64a05e85d1ca3e3878c1e9259e6a6a7a8138"
},
"downloads": -1,
"filename": "metatensor-0.2.0.tar.gz",
"has_sig": false,
"md5_digest": "b010f9637fa8b1246932138d991a7ee0",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.8",
"size": 5373,
"upload_time": "2024-01-26T17:27:15",
"upload_time_iso_8601": "2024-01-26T17:27:15.203138Z",
"url": "https://files.pythonhosted.org/packages/3e/58/172e96ccdca4d8d572579adc69b593dad79b74497c116ed86979257a5cbd/metatensor-0.2.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-01-26 17:27:15",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "lab-cosmo",
"github_project": "metatensor",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"tox": true,
"lcname": "metatensor"
}
JSON
