# numerical-collection-py
A collection of algorithms in numerical analysis for Python (originally implemented in C++).
![PyPI](https://img.shields.io/pypi/v/numerical-collection-py)
![PyPI - License](https://img.shields.io/pypi/l/numerical-collection-py)
[![pipeline status](https://gitlab.com/MusicScience37Projects/numerical-analysis/numerical-collection-py/badges/develop/pipeline.svg)](https://gitlab.com/MusicScience37Projects/numerical-analysis/numerical-collection-py/-/commits/develop)
[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://github.com/pre-commit/pre-commit)
[![coverage report](https://gitlab.com/MusicScience37Projects/numerical-analysis/numerical-collection-py/badges/develop/coverage.svg)](https://gitlab.com/MusicScience37Projects/numerical-analysis/numerical-collection-py/-/commits/develop)
## Repositories
- Main in GitLab: [https://gitlab.com/MusicScience37Projects/numerical-analysis/numerical-collection-py](https://gitlab.com/MusicScience37Projects/numerical-analysis/numerical-collection-py)
## Documentation
- [Documentation built on develop branch](https://musicscience37projects.gitlab.io/numerical-analysis/numerical-collection-py/)
Raw data
{
"_id": null,
"home_page": "https://gitlab.com/MusicScience37Projects/numerical-analysis/numerical-collection-py",
"name": "numerical-collection-py",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.10,<3.12",
"maintainer_email": "",
"keywords": "",
"author": "Kenta Kabashima",
"author_email": "kenta_program37@hotmail.co.jp",
"download_url": "https://files.pythonhosted.org/packages/2b/17/d589c1c105094e33f0cb090b5306ce21125be236d60d718bdec85c5d891e/numerical-collection-py-0.2.0.tar.gz",
"platform": null,
"description": "# numerical-collection-py\n\nA collection of algorithms in numerical analysis for Python (originally implemented in C++).\n\n![PyPI](https://img.shields.io/pypi/v/numerical-collection-py)\n![PyPI - License](https://img.shields.io/pypi/l/numerical-collection-py)\n[![pipeline status](https://gitlab.com/MusicScience37Projects/numerical-analysis/numerical-collection-py/badges/develop/pipeline.svg)](https://gitlab.com/MusicScience37Projects/numerical-analysis/numerical-collection-py/-/commits/develop)\n[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://github.com/pre-commit/pre-commit)\n[![coverage report](https://gitlab.com/MusicScience37Projects/numerical-analysis/numerical-collection-py/badges/develop/coverage.svg)](https://gitlab.com/MusicScience37Projects/numerical-analysis/numerical-collection-py/-/commits/develop)\n\n## Repositories\n\n- Main in GitLab: [https://gitlab.com/MusicScience37Projects/numerical-analysis/numerical-collection-py](https://gitlab.com/MusicScience37Projects/numerical-analysis/numerical-collection-py)\n\n## Documentation\n\n- [Documentation built on develop branch](https://musicscience37projects.gitlab.io/numerical-analysis/numerical-collection-py/)\n",
"bugtrack_url": null,
"license": "Apache-2.0",
"summary": "A collection of algorithms in numerical analysis for Python (originally implemented in C++).",
"version": "0.2.0",
"split_keywords": [],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "965e55d9540010aaa4c39235574363b782d77be97aa589a0a1e8dd63783e104c",
"md5": "36a65ef34889ab9b913c90c7b0844b63",
"sha256": "29d7b8fc32f7b9c752c6ef290ce64214dfb6be82fef5badbb0c76b6889554940"
},
"downloads": -1,
"filename": "numerical_collection_py-0.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
"has_sig": false,
"md5_digest": "36a65ef34889ab9b913c90c7b0844b63",
"packagetype": "bdist_wheel",
"python_version": "cp310",
"requires_python": ">=3.10,<3.12",
"size": 520624,
"upload_time": "2023-04-06T15:50:49",
"upload_time_iso_8601": "2023-04-06T15:50:49.265285Z",
"url": "https://files.pythonhosted.org/packages/96/5e/55d9540010aaa4c39235574363b782d77be97aa589a0a1e8dd63783e104c/numerical_collection_py-0.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "f7ee99295adccf2538087d0a09045cf43fac45b3fffdaedf2c128fa64e2902c6",
"md5": "2a9fa1344256f128a3fbf0b1bc93f244",
"sha256": "e0fdc2644573cb8773ae1e2064aee040cc535dd450155cbc17e4e6c68831d025"
},
"downloads": -1,
"filename": "numerical_collection_py-0.2.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
"has_sig": false,
"md5_digest": "2a9fa1344256f128a3fbf0b1bc93f244",
"packagetype": "bdist_wheel",
"python_version": "cp311",
"requires_python": ">=3.10,<3.12",
"size": 520634,
"upload_time": "2023-04-06T15:50:51",
"upload_time_iso_8601": "2023-04-06T15:50:51.116823Z",
"url": "https://files.pythonhosted.org/packages/f7/ee/99295adccf2538087d0a09045cf43fac45b3fffdaedf2c128fa64e2902c6/numerical_collection_py-0.2.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "2b17d589c1c105094e33f0cb090b5306ce21125be236d60d718bdec85c5d891e",
"md5": "7c6a865b38f27f64ec670cd438ca54b6",
"sha256": "e26ff1bb91c599bff933f21d8afb65e1d5d094de8d44fda126a59ec6b2158299"
},
"downloads": -1,
"filename": "numerical-collection-py-0.2.0.tar.gz",
"has_sig": false,
"md5_digest": "7c6a865b38f27f64ec670cd438ca54b6",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.10,<3.12",
"size": 20938,
"upload_time": "2023-04-06T15:50:52",
"upload_time_iso_8601": "2023-04-06T15:50:52.103981Z",
"url": "https://files.pythonhosted.org/packages/2b/17/d589c1c105094e33f0cb090b5306ce21125be236d60d718bdec85c5d891e/numerical-collection-py-0.2.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-04-06 15:50:52",
"github": false,
"gitlab": false,
"bitbucket": false,
"lcname": "numerical-collection-py"
}