Metadata-Version: 2.4
Name: maten
Version: 0.1.0
Summary: Pure Python scientific computing — replaces NumPy, Pandas, Matplotlib & TensorFlow
Home-page: https://github.com/maten/maten
Author: maten contributors
License: MIT License
        
        Copyright (c) 2026 Maten Contributors
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
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Project-URL: Homepage, https://github.com/yourname/maten
Project-URL: Issues, https://github.com/yourname/maten/issues
Keywords: numpy,pandas,matplotlib,tensorflow,machine-learning,dataframe,tensor,neural-network,pure-python,zero-dependency
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Visualization
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Dynamic: license-file
Dynamic: requires-python

# Maten

A lightweight, dependency-free Python toolkit that provides NumPy-, Pandas-, Matplotlib-, and TensorFlow-like APIs for learning and prototyping.

## Features

- **maten.core** — N-dimensional tensors, element-wise math, and linear algebra
- **maten.frame** — Series, DataFrame, groupby, and CSV/JSON I/O
- **maten.plot** — SVG charts (line, bar, scatter, hist, pie, heatmap)
- **maten.neural** — Scalar autograd, layers, optimizers, and a simple trainer

## Installation

From the project root:

```bash
pip install .
```

Editable install for development:

```bash
pip install -e ".[dev]"
```

## Quick start

```python
import maten
from maten.core import Tensor, zeros
from maten.frame import DataFrame
from maten.plot import subplots, line
from maten.neural import Value

print(maten.__version__)
print(zeros(3))
print(DataFrame({"x": [1, 2, 3]}))

_, ax = subplots()
line(ax, [0, 1, 2], [0, 1, 4])
ax.save("demo.svg")

x = Value(2.0)
y = x * x
y.backward()
print(x.grad)  # 4.0
```

## Examples

```bash
python examples/core_demo.py
python examples/frame_demo.py
python examples/plot_demo.py
python examples/neural_demo.py
```

## Tests

```bash
pytest
```

## Documentation

- [Core](docs/core.md)
- [Frame](docs/frame.md)
- [Plot](docs/plot.md)
- [Neural](docs/neural.md)

## License

MIT — see [LICENSE](LICENSE).
