| Name | xflow-py JSON |
| Version |
0.1.3.post0
JSON |
| download |
| home_page | None |
| Summary | A modular ML framework for training and evaluation tasks |
| upload_time | 2025-08-09 12:50:02 |
| maintainer | None |
| docs_url | None |
| author | Qiyuan Xu |
| requires_python | >=3.8 |
| license | MIT License
Copyright (c) 2025 Andrew Xu
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.
|
| keywords |
machine-learning
tensorflow
data-pipeline
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
<p align="center">
<a href="https://andrew-xqy.github.io/XFlow/">
<img src="https://raw.githubusercontent.com/Andrew-XQY/XFlow/9feba3930f468ca95b35401232a6febd66f2432c/images/logo.png"
alt="XFlow Logo" width="128" height="128">
</a>
<p align="center">
<a href="https://andrew-xqy.github.io/XFlow/"><b>Documentation</b></a>
·
<a href="https://github.com/Andrew-XQY/XFlow/issues">Report Bug</a>
·
<a href="https://github.com/Andrew-XQY/XFlow/issues">Request Feature</a>
</p>
</p>
---
## 🔍 About the Project
**XFlow** is a lightweight modular machine-learning framework, built with a clear high-level structure and developed through vibe coding.
Originally created for physics research, it's now evolving toward generic scientific applications ML workflows: **Data → Processing → Modeling**
**XFlow** keeps things simple and minimal.
> _Includes reusable modules for datasets, models, training loops, visualization, and logging._
---
## 🛠 Built With
<p>
<a href="https://www.python.org/"><img src="https://raw.githubusercontent.com/devicons/devicon/master/icons/python/python-original.svg" height="40px" width="40px" /></a>
<a href="https://www.tensorflow.org/"><img src="https://raw.githubusercontent.com/devicons/devicon/master/icons/tensorflow/tensorflow-original.svg" height="40px" width="40px" /></a>
<a href="https://keras.io/"><img src="https://cdn.jsdelivr.net/gh/devicons/devicon/icons/keras/keras-original.svg" height="40px" width="40px" /></a>
<a href="https://pytorch.org/"><img src="https://cdn.jsdelivr.net/gh/devicons/devicon/icons/pytorch/pytorch-original.svg" height="40px" width="40px" /></a>
</p>
</p>
- Python 3.12
- TensorFlow 2.x
- Keras 3.x
---
## 🚀 Getting Started
### Installation
Install from PyPI:
```bash
pip install xflow-py
```
Clone the repository and install in editable mode:
```bash
git clone https://github.com/Andrew-XQY/XFlow.git
cd XFlow
pip install -e .
```
---
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
Raw data
{
"_id": null,
"home_page": null,
"name": "xflow-py",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.8",
"maintainer_email": null,
"keywords": "machine-learning, tensorflow, data-pipeline",
"author": "Qiyuan Xu",
"author_email": null,
"download_url": "https://files.pythonhosted.org/packages/f9/4a/3082375c359ee821cf58787747c2149513a740d001950ffc0eee46c8a60e/xflow_py-0.1.3.post0.tar.gz",
"platform": null,
"description": "<p align=\"center\">\n <a href=\"https://andrew-xqy.github.io/XFlow/\">\n <img src=\"https://raw.githubusercontent.com/Andrew-XQY/XFlow/9feba3930f468ca95b35401232a6febd66f2432c/images/logo.png\"\n alt=\"XFlow Logo\" width=\"128\" height=\"128\">\n </a>\n <p align=\"center\">\n <a href=\"https://andrew-xqy.github.io/XFlow/\"><b>Documentation</b></a>\n \u00b7\n <a href=\"https://github.com/Andrew-XQY/XFlow/issues\">Report Bug</a>\n \u00b7\n <a href=\"https://github.com/Andrew-XQY/XFlow/issues\">Request Feature</a>\n </p>\n</p>\n\n\n\n\n\n\n---\n\n## \ud83d\udd0d About the Project\n\n**XFlow** is a lightweight modular machine-learning framework, built with a clear high-level structure and developed through vibe coding.\n\nOriginally created for physics research, it's now evolving toward generic scientific applications ML workflows: **Data \u2192 Processing \u2192 Modeling**\n\n**XFlow** keeps things simple and minimal.\n\n> _Includes reusable modules for datasets, models, training loops, visualization, and logging._\n\n---\n\n## \ud83d\udee0 Built With\n\n<p>\n <a href=\"https://www.python.org/\"><img src=\"https://raw.githubusercontent.com/devicons/devicon/master/icons/python/python-original.svg\" height=\"40px\" width=\"40px\" /></a>\n <a href=\"https://www.tensorflow.org/\"><img src=\"https://raw.githubusercontent.com/devicons/devicon/master/icons/tensorflow/tensorflow-original.svg\" height=\"40px\" width=\"40px\" /></a>\n <a href=\"https://keras.io/\"><img src=\"https://cdn.jsdelivr.net/gh/devicons/devicon/icons/keras/keras-original.svg\" height=\"40px\" width=\"40px\" /></a>\n <a href=\"https://pytorch.org/\"><img src=\"https://cdn.jsdelivr.net/gh/devicons/devicon/icons/pytorch/pytorch-original.svg\" height=\"40px\" width=\"40px\" /></a>\n</p>\n</p>\n\n- Python 3.12\n- TensorFlow 2.x\n- Keras 3.x\n\n---\n\n## \ud83d\ude80 Getting Started\n\n### Installation\n\nInstall from PyPI:\n\n```bash\npip install xflow-py\n```\n\nClone the repository and install in editable mode:\n\n```bash\ngit clone https://github.com/Andrew-XQY/XFlow.git\ncd XFlow\npip install -e .\n```\n\n---\n\n## License\n\nThis project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.\n",
"bugtrack_url": null,
"license": "MIT License\n \n Copyright (c) 2025 Andrew Xu\n \n Permission is hereby granted, free of charge, to any person obtaining a copy\n of this software and associated documentation files (the \"Software\"), to deal\n in the Software without restriction, including without limitation the rights\n to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n copies of the Software, and to permit persons to whom the Software is\n furnished to do so, subject to the following conditions:\n \n The above copyright notice and this permission notice shall be included in all\n copies or substantial portions of the Software.\n \n THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\n SOFTWARE.\n ",
"summary": "A modular ML framework for training and evaluation tasks",
"version": "0.1.3.post0",
"project_urls": {
"Homepage": "https://github.com/Andrew-XQY/XFlow"
},
"split_keywords": [
"machine-learning",
" tensorflow",
" data-pipeline"
],
"urls": [
{
"comment_text": null,
"digests": {
"blake2b_256": "b28a7f56488f9539a92d2a36c2d506f02ed9d30c7bc5c2d20946ff55be5aff00",
"md5": "20406875703a62e671b6a25d81db659b",
"sha256": "02ca40d4c0a306b14fc2a1bf9cf28b00d9d552706e3494563e6317fbb06bbe83"
},
"downloads": -1,
"filename": "xflow_py-0.1.3.post0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "20406875703a62e671b6a25d81db659b",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.8",
"size": 58820,
"upload_time": "2025-08-09T12:50:00",
"upload_time_iso_8601": "2025-08-09T12:50:00.821002Z",
"url": "https://files.pythonhosted.org/packages/b2/8a/7f56488f9539a92d2a36c2d506f02ed9d30c7bc5c2d20946ff55be5aff00/xflow_py-0.1.3.post0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "f94a3082375c359ee821cf58787747c2149513a740d001950ffc0eee46c8a60e",
"md5": "77172e0ff1891a8ef2371b8dc4b8b2fe",
"sha256": "ad12d24b301196f5150e87d4517d377548c209e994198233eb5148d39dc4cd7e"
},
"downloads": -1,
"filename": "xflow_py-0.1.3.post0.tar.gz",
"has_sig": false,
"md5_digest": "77172e0ff1891a8ef2371b8dc4b8b2fe",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.8",
"size": 94009,
"upload_time": "2025-08-09T12:50:02",
"upload_time_iso_8601": "2025-08-09T12:50:02.341821Z",
"url": "https://files.pythonhosted.org/packages/f9/4a/3082375c359ee821cf58787747c2149513a740d001950ffc0eee46c8a60e/xflow_py-0.1.3.post0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2025-08-09 12:50:02",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "Andrew-XQY",
"github_project": "XFlow",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "xflow-py"
}
