Metadata-Version: 2.4
Name: skjson
Version: 0.1.0
Summary: Export scikit-learn models to JSON for cross-language inference
License-Expression: MIT
Requires-Python: >=3.9
Requires-Dist: numpy>=1.21
Requires-Dist: scikit-learn>=1.0
Provides-Extra: dev
Requires-Dist: pytest-cov; extra == 'dev'
Requires-Dist: pytest>=7.0; extra == 'dev'
Description-Content-Type: text/markdown

# skjson

Export scikit-learn models to JSON for cross-language inference.

## Installation

```bash
pip install skjson
```

## Quick Start

```python
import skjson
from sklearn.linear_model import LinearRegression
import numpy as np

# Train
model = LinearRegression().fit(np.array([[1], [2], [3]]), np.array([1, 2, 3]))

# Export
skjson.save(model, "model.json", feature_names=["x"])

# Load & predict (no sklearn needed)
predictor = skjson.load("model.json")
predictions = predictor.predict([[4], [5]])
```

## Future Directions

- Support for scikit-learn `Pipeline` objects and feature unions.
- npm package for inference using our json models
- Support for sklearn.neural_network models

## Note
- This project built with Google Gemini and Claude Opus.
- If you wish to contribute, please contact me. 