A modular ML framework for training and evaluation tasks
Project description
Documentation · Report Bug · Request Feature
📖 Table of Contents
🔍 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.
✨ Features
- Modular
core/for dataset/model/trainer abstraction - Plug-and-play task logic (
tasks/)
🛠 Built With
- Python 3.12
- TensorFlow 2.x
- Keras 3.x
🚀 Getting Started
Installation
Install from PyPI:
pip install xflow-py
Clone the repository and install in editable mode:
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 file for details.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file xflow_py-0.1.2.tar.gz.
File metadata
- Download URL: xflow_py-0.1.2.tar.gz
- Upload date:
- Size: 82.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
5c6daf914af1a35d9ce3c31d0c71ac193fd50c44e086c6cfa7f96af49fbe482c
|
|
| MD5 |
652e2cba766b843512ae93666310c1d4
|
|
| BLAKE2b-256 |
3deb6ad2a7254183d5b6ac91c97f556fff1d416fbf77913cc3069049098b033d
|
File details
Details for the file xflow_py-0.1.2-py3-none-any.whl.
File metadata
- Download URL: xflow_py-0.1.2-py3-none-any.whl
- Upload date:
- Size: 50.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
0a39dc2f93087eb9e9b2352e20d363022ff4869365a7d0ad09129588f738993c
|
|
| MD5 |
7ec4fc20e0557f84bce76067700343d9
|
|
| BLAKE2b-256 |
2a7f0208fc0918567cf7aba39e04ee18e5a11e04c840070afa5bc527ce1ad5bc
|
