# tce-lib
[](https://muexly.github.io/tce-lib)
[](https://pypi.org/project/tce-lib/)
[](https://en.wikipedia.org/wiki/MIT_License)
[](https://github.com/astral-sh/ruff)
[](https://mypy-lang.org/)
[](https://docs.pytest.org/en/stable/)
[](https://deepwiki.com/MUEXLY/tce-lib)
<img src="https://raw.githubusercontent.com/MUEXLY/tce-lib/refs/heads/main/assets/logo.png" alt="tce-lib logo" style="width:50%;height:auto;">
## 🔎 What is tce-lib?
`tce-lib` is a library for creating and deploying tensor cluster expansion models of concentrated alloys following
our work on [arXiv](https://arxiv.org/abs/2509.04686). The core philosophy of `tce-lib` is to respect the
[strategy pattern](https://en.wikipedia.org/wiki/Strategy_pattern) as core to the library's functionality. This design
pattern stages workflows as sequences of strategies, of which the user can override each. This allows for the majority
of users to plug-and-play for an ordinary workflow, while still supporting fine-grained autonomy for more advanced
users.
## 📩 Installation
`tce-lib` is installable via the Python Package Index:
```shell
pip install tce-lib
```
or, from source:
```shell
git clone https://github.com/MUEXLY/tce-lib
pip install -e tce-lib/
```
## 📌 Citation
Please cite our work [here](https://arxiv.org/abs/2509.04686) if you use `tce-lib` in your work.
## 💙 Acknowledgements
Authors acknowledge support from the U.S. Department of Energy, Office of Basic Energy Sciences, Materials Science and Engineering Division under Award No. DE-SC0022980.
## 🐝 Found a bug?
Please open an issue [here](https://github.com/MUEXLY/tce/issues), with a description of the issue and a [minimal, reproducible example](https://stackoverflow.com/help/minimal-reproducible-example) of the issue.
## 📑 License
`tce-lib` is released under the MIT license.
Raw data
{
"_id": null,
"home_page": null,
"name": "tce-lib",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.10",
"maintainer_email": null,
"keywords": "alloys, ase, cluster expansion, density functional theory, machine learning, materials science, monte carlo, scientific computing",
"author": null,
"author_email": null,
"download_url": "https://files.pythonhosted.org/packages/b5/bb/01364a6506ce1ccac3121be2a5c070fcb317e36e298ac1f77104d4440a1a/tce_lib-0.8.4.tar.gz",
"platform": null,
"description": "# tce-lib\n\n[](https://muexly.github.io/tce-lib)\n[](https://pypi.org/project/tce-lib/)\n[](https://en.wikipedia.org/wiki/MIT_License)\n\n\n[](https://github.com/astral-sh/ruff)\n[](https://mypy-lang.org/)\n[](https://docs.pytest.org/en/stable/)\n\n\n[](https://deepwiki.com/MUEXLY/tce-lib)\n\n<img src=\"https://raw.githubusercontent.com/MUEXLY/tce-lib/refs/heads/main/assets/logo.png\" alt=\"tce-lib logo\" style=\"width:50%;height:auto;\">\n\n\n## \ud83d\udd0e What is tce-lib?\n\n`tce-lib` is a library for creating and deploying tensor cluster expansion models of concentrated alloys following\nour work on [arXiv](https://arxiv.org/abs/2509.04686). The core philosophy of `tce-lib` is to respect the \n[strategy pattern](https://en.wikipedia.org/wiki/Strategy_pattern) as core to the library's functionality. This design\npattern stages workflows as sequences of strategies, of which the user can override each. This allows for the majority \nof users to plug-and-play for an ordinary workflow, while still supporting fine-grained autonomy for more advanced \nusers. \n\n## \ud83d\udce9 Installation\n\n`tce-lib` is installable via the Python Package Index:\n\n```shell\npip install tce-lib\n```\n\nor, from source:\n\n```shell\ngit clone https://github.com/MUEXLY/tce-lib\npip install -e tce-lib/\n```\n\n## \ud83d\udccc Citation\n\nPlease cite our work [here](https://arxiv.org/abs/2509.04686) if you use `tce-lib` in your work.\n\n## \ud83d\udc99 Acknowledgements\n\nAuthors acknowledge support from the U.S. Department of Energy, Office of Basic Energy Sciences, Materials Science and Engineering Division under Award No. DE-SC0022980.\n\n## \ud83d\udc1d Found a bug?\n\nPlease open an issue [here](https://github.com/MUEXLY/tce/issues), with a description of the issue and a [minimal, reproducible example](https://stackoverflow.com/help/minimal-reproducible-example) of the issue.\n\n## \ud83d\udcd1 License\n\n`tce-lib` is released under the MIT license.\n",
"bugtrack_url": null,
"license": null,
"summary": "tensor cluster expansion library for solid solution modeling",
"version": "0.8.4",
"project_urls": {
"Homepage": "https://github.com/MUEXLY/tce-lib"
},
"split_keywords": [
"alloys",
" ase",
" cluster expansion",
" density functional theory",
" machine learning",
" materials science",
" monte carlo",
" scientific computing"
],
"urls": [
{
"comment_text": null,
"digests": {
"blake2b_256": "ca4f318aa863d0f2ee763a8061d8c36bb92844feb912669e77db26e7fe741b12",
"md5": "d682525d6a9f151dffb4a6ecd112f6dd",
"sha256": "9e0fdf6507d54a0cff38fad54ddcd2fc14d5581b5dbf6ee805b5d4c5355221a8"
},
"downloads": -1,
"filename": "tce_lib-0.8.4-py3-none-any.whl",
"has_sig": false,
"md5_digest": "d682525d6a9f151dffb4a6ecd112f6dd",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.10",
"size": 1979529,
"upload_time": "2025-10-21T22:28:30",
"upload_time_iso_8601": "2025-10-21T22:28:30.102474Z",
"url": "https://files.pythonhosted.org/packages/ca/4f/318aa863d0f2ee763a8061d8c36bb92844feb912669e77db26e7fe741b12/tce_lib-0.8.4-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "b5bb01364a6506ce1ccac3121be2a5c070fcb317e36e298ac1f77104d4440a1a",
"md5": "361638d01e2c0ff59ff50152655a339e",
"sha256": "c993b88a5da06c7ac78a332f6856425538515cd08ed0c9ea7e1b96d86fbc92c7"
},
"downloads": -1,
"filename": "tce_lib-0.8.4.tar.gz",
"has_sig": false,
"md5_digest": "361638d01e2c0ff59ff50152655a339e",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.10",
"size": 1065419,
"upload_time": "2025-10-21T22:28:31",
"upload_time_iso_8601": "2025-10-21T22:28:31.847561Z",
"url": "https://files.pythonhosted.org/packages/b5/bb/01364a6506ce1ccac3121be2a5c070fcb317e36e298ac1f77104d4440a1a/tce_lib-0.8.4.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2025-10-21 22:28:31",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "MUEXLY",
"github_project": "tce-lib",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "tce-lib"
}
JSON
