semvec/pypi-packages huggingface dataset:
kumc 0.1.1
Korea University Anam Hospital internal API for Python SDK
Requires Python: >=3.10

# Korea University Anam Hospital internal API for Python SDK
KUMC Internel API for Python SDK


## Usage

### Example code
```python
import json
import asyncio
from kumc import KUMCClient

async def main():
    app = KUMCClient()

    await app.sign_in()
    resp = await app.get_hospitalization_and_discharge_history(hpCd="AA", inqrStrtYmd=20220130)
    print(
        json.dumps(
            resp, 
            indent=4, 
            ensure_ascii=False
        )
    )


if __name__ == "__main__":
    asyncio.run(main())
```

## **Disclaimer**
This project has been developed for research purposes and the creators are not responsible for anything that happens as a result of using this project. We would also like to inform you that the project may be taken down at any time by the demands of KUMC.

## **License**
Licensed under the [LGPL-2.1](./LICENSE)
turbo-pixel-loader 0.1.0
High-performance AI data loader written in Rust
Requires Python: >=3.8

# Green AI 🚀

**The World's Fastest Image Loader for PyTorch & TensorFlow.**

[![PyPI version](https://badge.fury.io/py/green-ai.svg)](https://badge.fury.io/py/green-ai)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

## The Problem
Your GPUs are starving. Standard Python `DataLoader` pipelines are single-threaded and fight against the GIL (Global Interpreter Lock). While your H100 waits for data, you burn money.

## The Solution
**Green AI** is a high-performance ingestion engine written in Rust. It bypasses Python's overhead to load, decode, and batch images in parallel, delivering them to your model via Zero-Copy memory transfer.

### ⚡ Performance Benchmark (1,000 Images)

| Loader | Time | Speed | Status |
| :--- | :--- | :--- | :--- |
| **Standard Python (PIL)** | 17.48s | 57 img/sec | 🐢 Slow |
| **Green AI (Rust)** | **1.22s** | **819 img/sec** | 🚀 **14.3x Faster** |

*(Benchmarks run on local dataset, 512x512 RGB JPEGs)*

## 📦 Installation

```bash
pip install green-ai