Metadata-Version: 2.1
Name: nosa-autostreamlit
Version: 0.1.0
Summary: Automated Machine Learning and Data Visualization Framework
Home-page: https://github.com/thesnak/nosa-autostreamlit
Author: Mohamed Mahmoud
Author-email: Mohamed Mahmoud <mohamed.mahmoud0726@gmail.com>
License: MIT License
        
        Copyright (c) 2024 Mohamed Mahmoud
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
Project-URL: Homepage, https://github.com/thesnak/nosa-autostreamlit
Project-URL: Repository, https://github.com/thesnak/nosa-autostreamlit
Keywords: machine-learning,data-visualization,streamlit
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: streamlit
Requires-Dist: pandas
Requires-Dist: numpy
Requires-Dist: plotly
Requires-Dist: scikit-learn
Requires-Dist: joblib
Provides-Extra: dev
Requires-Dist: pytest; extra == "dev"
Requires-Dist: black; extra == "dev"
Requires-Dist: flake8; extra == "dev"

# Nosa-autoStreamlit 🚀

## 📊 Automated Machine Learning and Data Visualization Framework

Nosa-autoStreamlit is an advanced Python framework that automates the creation of machine learning and data visualization Streamlit applications. Designed to simplify complex data science workflows with powerful, user-friendly tools.

![Python Version](https://img.shields.io/badge/python-3.8+-blue.svg)
![Streamlit](https://img.shields.io/badge/streamlit-1.10.0+-green.svg)
![License](https://img.shields.io/github/license/yourusername/nosa-autostreamlit)

## ✨ Features

### 🤖 Machine Learning Generator
- Supports classification and regression problems
- Advanced preprocessing techniques
- Multiple machine learning models
- Cross-validation
- Hyperparameter tuning
- Model saving and loading

### 📈 Data Visualization Generator
- Multiple visualization types
- Interactive Plotly plots
- Easy-to-use interface

## 🚀 Quick Start

### Installation

```bash
# Clone the repository
git clone https://github.com/yourusername/nosa-autostreamlit.git
cd nosa-autostreamlit

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`

# Install dependencies
pip install -r requirements.txt
```

### Machine Learning Example

```python
from nosa_autostreamlit.generators import AdvancedMachineLearningGenerator

# Create generator
generator = AdvancedMachineLearningGenerator()

# Load data
generator.load_data(
    data, 
    target_column='target', 
    problem_type='classification'
)

# Preprocess and train models
generator.advanced_preprocessing()
generator.train_multiple_models()
generator.generate_model_comparison_report()
```

### Data Visualization Example

```python
from nosa_autostreamlit.generators import DataVisualizationGenerator

# Create generator
generator = DataVisualizationGenerator()

# Load data
generator.load_data(data)

# Create visualizations
generator.create_histogram()
generator.create_scatterplot()
generator.create_boxplot()
```

### 🛠 Key Components
- **`machine_learning_generator.py`**: Core ML functionality
- **`data_visualization_generator.py`**: Visualization tools
- **`advanced_ml_comparison.py`**: Example ML workflow
- **`advanced_data_viz_example.py`**: Example visualization workflow


### 📦 Dependencies
- Streamlit
- Pandas
- NumPy
- Scikit-learn
- Plotly
- Joblib

### 🤝 Contributing
Contributions are welcome! Please follow these steps:

1. Fork the repository
2. Create a new branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

### 📄 License
Distributed under the MIT License. See LICENSE for more information.

### 📞 Contact
Your Name - mohamed.mahmoud0726@gmail.com

Project Link: https://github.com/thesnak/nosa-autostreamlit


Made with ❤️ by [Mohamed Mahmoud](https://github.com/thesnak)
