PyCXpress


NamePyCXpress JSON
Version 0.0.6 PyPI version JSON
download
home_pagehttps://github.com/chaoqing/PyCXpress
SummaryPyCXpress is a high-performance hybrid framework that seamlessly integrates Python and C++ to harness the flexibility of Python and the speed of C++ for efficient and expressive computation, particularly in the realm of deep learning and numerical computing.
upload_time2024-04-27 06:44:28
maintainerNone
docs_urlNone
authorchaoqing
requires_python<4.0,>=3.8
licenseMIT
keywords cpp embdedding
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # PyCXpress

<div align="center">

[![Build status](https://github.com/chaoqing/PyCXpress/workflows/build/badge.svg?branch=master&event=push)](https://github.com/chaoqing/PyCXpress/actions?query=workflow%3Abuild)
[![Python Version](https://img.shields.io/pypi/pyversions/PyCXpress.svg)](https://pypi.org/project/PyCXpress/)
[![Dependencies Status](https://img.shields.io/badge/dependencies-up%20to%20date-brightgreen.svg)](https://github.com/chaoqing/PyCXpress/pulls?utf8=%E2%9C%93&q=is%3Apr%20author%3Aapp%2Fdependabot)

[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
[![Security: bandit](https://img.shields.io/badge/security-bandit-green.svg)](https://github.com/PyCQA/bandit)
[![Pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://github.com/chaoqing/PyCXpress/blob/master/.pre-commit-config.yaml)
[![Semantic Versions](https://img.shields.io/badge/%20%20%F0%9F%93%A6%F0%9F%9A%80-semantic--versions-e10079.svg)](https://github.com/chaoqing/PyCXpress/releases)
[![License](https://img.shields.io/github/license/chaoqing/PyCXpress)](https://github.com/chaoqing/PyCXpress/blob/master/LICENSE)
![Coverage Report](assets/images/coverage.svg)

PyCXpress is a high-performance hybrid framework that seamlessly integrates Python and C++ to harness the flexibility of Python and the speed of C++ for efficient and expressive computation, particularly in the realm of deep learning and numerical computing.

</div>

## 🛡 License

[![License](https://img.shields.io/github/license/chaoqing/PyCXpress)](https://github.com/chaoqing/PyCXpress/blob/master/LICENSE)

This project is licensed under the terms of the `MIT` license. See [LICENSE](https://github.com/chaoqing/PyCXpress/blob/master/LICENSE) for more details.

## 📃 Citation

```bibtex
@misc{PyCXpress,
  author = {chaoqing},
  title = {PyCXpress is a high-performance hybrid framework that seamlessly integrates Python and C++ to harness the flexibility of Python and the speed of C++ for efficient and expressive computation, particularly in the realm of deep learning and numerical computing.},
  year = {2024},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/chaoqing/PyCXpress}}
}
```

            

Raw data

            {
    "_id": null,
    "home_page": "https://github.com/chaoqing/PyCXpress",
    "name": "PyCXpress",
    "maintainer": null,
    "docs_url": null,
    "requires_python": "<4.0,>=3.8",
    "maintainer_email": null,
    "keywords": "CPP, Embdedding",
    "author": "chaoqing",
    "author_email": "chaoqingwang.nick@gmail.com",
    "download_url": "https://files.pythonhosted.org/packages/79/3e/1dafbbacef34f35d5ffcaba9ac1177bacc8133cd0bdf78d13fa82424fb63/pycxpress-0.0.6.tar.gz",
    "platform": null,
    "description": "# PyCXpress\n\n<div align=\"center\">\n\n[![Build status](https://github.com/chaoqing/PyCXpress/workflows/build/badge.svg?branch=master&event=push)](https://github.com/chaoqing/PyCXpress/actions?query=workflow%3Abuild)\n[![Python Version](https://img.shields.io/pypi/pyversions/PyCXpress.svg)](https://pypi.org/project/PyCXpress/)\n[![Dependencies Status](https://img.shields.io/badge/dependencies-up%20to%20date-brightgreen.svg)](https://github.com/chaoqing/PyCXpress/pulls?utf8=%E2%9C%93&q=is%3Apr%20author%3Aapp%2Fdependabot)\n\n[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)\n[![Security: bandit](https://img.shields.io/badge/security-bandit-green.svg)](https://github.com/PyCQA/bandit)\n[![Pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://github.com/chaoqing/PyCXpress/blob/master/.pre-commit-config.yaml)\n[![Semantic Versions](https://img.shields.io/badge/%20%20%F0%9F%93%A6%F0%9F%9A%80-semantic--versions-e10079.svg)](https://github.com/chaoqing/PyCXpress/releases)\n[![License](https://img.shields.io/github/license/chaoqing/PyCXpress)](https://github.com/chaoqing/PyCXpress/blob/master/LICENSE)\n![Coverage Report](assets/images/coverage.svg)\n\nPyCXpress is a high-performance hybrid framework that seamlessly integrates Python and C++ to harness the flexibility of Python and the speed of C++ for efficient and expressive computation, particularly in the realm of deep learning and numerical computing.\n\n</div>\n\n## \ud83d\udee1 License\n\n[![License](https://img.shields.io/github/license/chaoqing/PyCXpress)](https://github.com/chaoqing/PyCXpress/blob/master/LICENSE)\n\nThis project is licensed under the terms of the `MIT` license. See [LICENSE](https://github.com/chaoqing/PyCXpress/blob/master/LICENSE) for more details.\n\n## \ud83d\udcc3 Citation\n\n```bibtex\n@misc{PyCXpress,\n  author = {chaoqing},\n  title = {PyCXpress is a high-performance hybrid framework that seamlessly integrates Python and C++ to harness the flexibility of Python and the speed of C++ for efficient and expressive computation, particularly in the realm of deep learning and numerical computing.},\n  year = {2024},\n  publisher = {GitHub},\n  journal = {GitHub repository},\n  howpublished = {\\url{https://github.com/chaoqing/PyCXpress}}\n}\n```\n",
    "bugtrack_url": null,
    "license": "MIT",
    "summary": "PyCXpress is a high-performance hybrid framework that seamlessly integrates Python and C++ to harness the flexibility of Python and the speed of C++ for efficient and expressive computation, particularly in the realm of deep learning and numerical computing.",
    "version": "0.0.6",
    "project_urls": {
        "Homepage": "https://github.com/chaoqing/PyCXpress",
        "Repository": "https://github.com/chaoqing/PyCXpress"
    },
    "split_keywords": [
        "cpp",
        " embdedding"
    ],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "ea03f412d2b71bc18189e4dd58bbd19c3e10d51bad66c1e0b8fcdccb326ab48c",
                "md5": "97a74f8391197fa882517d8e6cf2830c",
                "sha256": "526b612beef2dc2b54308b8429c4bcabbbf0ea2cd8807816dd0b9a948ee3580d"
            },
            "downloads": -1,
            "filename": "pycxpress-0.0.6-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "97a74f8391197fa882517d8e6cf2830c",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": "<4.0,>=3.8",
            "size": 13934,
            "upload_time": "2024-04-27T06:44:24",
            "upload_time_iso_8601": "2024-04-27T06:44:24.566824Z",
            "url": "https://files.pythonhosted.org/packages/ea/03/f412d2b71bc18189e4dd58bbd19c3e10d51bad66c1e0b8fcdccb326ab48c/pycxpress-0.0.6-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "793e1dafbbacef34f35d5ffcaba9ac1177bacc8133cd0bdf78d13fa82424fb63",
                "md5": "543dafc4138b019763858c3b1f0fe10e",
                "sha256": "435a42f1b97d43781f6865366a78c0f39abe1f191a086cd18b13614a16b7413a"
            },
            "downloads": -1,
            "filename": "pycxpress-0.0.6.tar.gz",
            "has_sig": false,
            "md5_digest": "543dafc4138b019763858c3b1f0fe10e",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": "<4.0,>=3.8",
            "size": 12648,
            "upload_time": "2024-04-27T06:44:28",
            "upload_time_iso_8601": "2024-04-27T06:44:28.412387Z",
            "url": "https://files.pythonhosted.org/packages/79/3e/1dafbbacef34f35d5ffcaba9ac1177bacc8133cd0bdf78d13fa82424fb63/pycxpress-0.0.6.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2024-04-27 06:44:28",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "github_user": "chaoqing",
    "github_project": "PyCXpress",
    "travis_ci": false,
    "coveralls": false,
    "github_actions": true,
    "requirements": [],
    "lcname": "pycxpress"
}
        
Elapsed time: 0.33103s