semvec/pypi-packages huggingface dataset:
log-colors 0.1.1
A colorful logging library for Python
Requires Python: >=3.7

log_colors is a simple logging library that allows you to log in color.

### Creation
The logger can be instantiated in one of the following ways:
```python
# For the default use case
logger = log_colors()

# With a custom class name
logger = log_colors(filename="Custom Name")

# Setup to save to a file
logger = log_colors(log_file="/path/to/file")
```

### Usage
There are four logging methods
```python
# For a general message
logger.info("Info message")

# For an error message
logger.info("Error message")

# For a success message
logger.success("Success message")

#For a warning message
logger.warning("Warning message")
```
oven-language 0.1.8
Python-to-MLIR compiler for GPU kernel development and mathematical computing
Requires Python: >=3.8
Keywords: mlir, compiler, gpu, python, cuda, kernel, vectorization, mathematical-computing, llvm

# Oven Language

[![Python 3.8+](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org/downloads/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![PyPI version](https://badge.fury.io/py/oven-language.svg)](https://badge.fury.io/py/oven-language)
[![Tests](https://github.com/sjjeong94/oven-language/workflows/Tests/badge.svg)](https://github.com/sjjeong94/oven-language/actions)
[![Build](https://github.com/sjjeong94/oven-language/workflows/Build/badge.svg)](https://github.com/sjjeong94/oven-language/actions)

A Python-to-MLIR compiler for GPU kernel development.

## Installation

```bash
pip install oven-language
```

## Quick Start

```python
import oven.language as ol

def vector_add(a_ptr: ol.ptr, b_ptr: ol.ptr, c_ptr: ol.ptr):
    bsize = ol.get_bdim_x()
    bid = ol.get_bid_x()
    tid = ol.get_tid_x()
    idx = (bid * bsize + tid) * 4
    x_value = ol.vload(a_ptr, idx)
    y_value = ol.vload(b_ptr, idx)
    z_value = x_value + y_value
    ol.vstore(z_value, c_ptr, idx)
```

Compile to MLIR:
```bash
oven kernel.py
```

## Key Functions

- **Thread/Block IDs**: `ol.get_tid_x()`, `ol.get_bid_x()`
- **Memory**: `ol.load()`, `ol.store()`, `ol.vload()`, `ol.vstore()`
- **Math**: `ol.exp()`, `ol.log()`, `ol.sin()`, `ol.sigmoid()`
- **GPU**: `ol.barrier()`, `ol.smem()`

## Links

- [GitHub](https://github.com/sjjeong94/oven-language)
- [PyPI](https://pypi.org/project/oven-language/)
luminanet 1.0.0
LuminaNet: Pure Python Deep Learning Framework - Illuminate AI with Minimal Dependencies
Requires Python: >=3.7
Keywords: deep learning, neural networks, machine learning, pure python, termux, numpy, educational, luminanet


# LuminaNet 🌟

**Illuminate Your AI Journey with Pure Python Deep Learning**

[![PyPI version](https://img.shields.io/pypi/v/luminanet.svg)](https://pypi.org/project/luminanet/)
[![Python Versions](https://img.shields.io/pypi/pyversions/luminanet.svg)](https://pypi.org/project/luminanet/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Termux Compatible](https://img.shields.io/badge/Termux-Compatible-brightgreen.svg)](https://termux.com/)
[![GitHub stars](https://img.shields.io/github/stars/yourusername/luminanet.svg)](https://github.com/yourusername/luminanet/stargazers)

**LuminaNet** adalah framework deep learning pure Python yang dirancang untuk edukasi dan production dengan dependencies minimal. Hanya menggunakan **NumPy, SciPy, NLTK, dan Sastrawi**.

## 🎯 **Why LuminaNet?**

| Feature | LuminaNet | Others |
|---------|-----------|--------|
| **Dependencies** | 🟢 4 libraries | 🔴 10+ libraries |
| **Termux Support** | 🟢 Perfect | 🔴 Limited |
| **Pure Python** | 🟢 100% | 🟡 Mixed |
| **Educational** | 🟢 Excellent | 🟡 Good |
| **Indonesian NLP** | 🟢 Built-in | 🔴 None |

## 🚀 **Quick Installation**

### From PyPI
```bash
pip install luminanet
```

### From Source
```bash
git clone https://github.com/yourusername/luminanet.git
cd luminanet
pip install -e .
```

### For Termux (Android)
```bash
pkg install python python-pip
pip install numpy scipy nltk sastrawi
pip install luminanet
```

## 💡 **Quick Start**

```python
from luminanet import NeuralNetwork, Dense
import numpy as np

# XOR Example
X = np.array([[0, 0], [0, 1], [1, 0], [1, 1]])
y = np.array([[1, 0], [0, 1], [0, 1], [1, 0]])

model = NeuralNetwork("XORSolver")
model.add(Dense(4, activation='relu'))
model.add(Dense(2, activation='softmax'))
model.compile(optimizer='adam', loss='categorical_crossentropy')
model.train(X, y, epochs=1000)

print(model.predict(X))
```


## 🤝 **Contributing**

We welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for details.

## 📄 **License**

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## 👨‍💻 **Author**

Your Name - [GitHub](https://github.com/yourusername) - your.email@example.com

## 🙏 **Acknowledgments**

- NumPy team untuk komputasi numerik
- NLTK team untuk NLP capabilities  
- Sastrawi team untuk Indonesian language support
- Python community untuk ecosystem yang luar biasa