Metadata-Version: 2.4
Name: pure_cifar_10
Version: 0.1.0
Summary: Pure Python/NumPy CIFAR-10 dataset loader
Home-page: https://github.com/ratulb/pure_cifar_10
Author: Ratul Buragohain
Author-email: ratul75@hotmail.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
Requires-Dist: numpy>=2.0.0
Requires-Dist: tqdm>=4.66.0
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# pure_cifar_10

A pure Python, minimal-dependency loader for the CIFAR-10 dataset. This package provides the CIFAR-10 images and labels as NumPy arrays, with automatic downloading and caching, requiring only `numpy` and `tqdm`[citation:1][citation:2].

## Features
*   **Minimal Dependencies**: Only requires `numpy` and `tqdm`. No heavy machine learning frameworks like PyTorch or TensorFlow[citation:4].
*   **Automatic Handling**: Downloads the CIFAR-10 dataset automatically on first use and caches it locally.
*   **Pure NumPy**: Returns standard `numpy.ndarray` objects for easy integration into any pipeline.
*   **Progress Visualization**: Uses `tqdm` to show download and loading progress bars.
*   **Simple API**: Mirrors the clean, functional style of the `mnist_datasets` package.

## Installation
You can install the package directly from PyPI using pip:

```bash
pip install pure_cifar_10
