datapulse-dataset-generator 0.1.0
A library to generate realistic dummy datasets.
Requires Python: >=3.8

# 📊 Data Pulse

**Data Pulse** is a comprehensive Python library designed to generate realistic dummy datasets across 100+ domains. Whether you need financial data, healthcare records, marketing insights, or geospatial information, Data Pulse provides an easy-to-use interface for creating high-quality sample data.

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## 🚀 Features

✅ **100+ Dataset Types**: Generate a wide variety of datasets, including Financial, Medical, E-commerce, and more.  
✅ **Realistic Data**: Each dataset is populated with realistic values for testing and development.  
✅ **Fast & Scalable**: Generate up to **500,000 records** in seconds.  
✅ **Export Options**: Download datasets in CSV, JSON, or other formats.  
✅ **Customizable**: Tailor attributes to your specific needs with ease.  

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## 📦 Installation

You can install **Data Pulse** directly from PyPI using:

```bash
pip install data-pulse
```

Ensure Python 3.8 or newer is installed on your system.

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## 📊 Available Datasets

- Financial Data
- Sales Data
- Medical/Healthcare Data
- Customer Data
- Marketing Data
- E-commerce Data
- Weather Data
- Geospatial Data
- Demographic Data
- Social Media Data
- IoT (Internet of Things) Data
- Supply Chain Data
- Government/Public Sector Data
- Transportation Data
- Educational Data
- Manufacturing Data
- Energy Consumption Data
- Telecommunication Data
- Environmental Data
- Real Estate Data
- Cybersecurity Data
- Human Resources (HR) Data
- Insurance Data
- Logistics Data
- Sports Data
- Textual/NLP Data
- Image Data
- Video Data
- Audio Data
- Retail Data
- Survey Data
- Sentiment Analysis Data
- Biometric Data
- Genomic Data
- Banking Transaction Data
- Agricultural Data
- Tourism and Hospitality Data
- Consumer Behavior Data
- Cryptocurrency Data
- Air Quality Data
- Automotive Data
- Construction Data
- Event Data
- Satellite Data
- Climate Data
- Patent Data
- Credit Scoring Data
- Fraud Detection Data
- Pharmaceutical Data
- Political Data
- Wildlife Data
- Linguistic Data
- Census Data
- Electronic Health Record (EHR) Data
- Emergency Services Data
- Fisheries Data
- Disaster Response Data
- Food and Nutrition Data
- Space Science Data
- Cultural Heritage Data
- Media Consumption Data
- Voting and Election Data
- Academic Research Data
- Financial Market Data
- Water Resource Data
- Traffic and Mobility Data
- Historical Data
- Clinical Trial Data
- Renewable Energy Data
- Drug Development Data
- Software Usage Data
- Smart City Data
- Behavioral Data
- Airline Data
- Social Services Data
- Import/Export Data
- Digital Marketing Data
- Public Health Data
- Cyber Threat Intelligence Data
- Pension and Retirement Data
- Investment Data
- Consumer Product Data
- Wildlife Conservation Data
- IT Infrastructure Data
- Biomedical Imaging Data
- Livestock Data
- Food Supply Chain Data
- Online Learning Data
- Maritime Data
- Public Transportation Data
- Traffic Accident Data
- Copyright and Intellectual Property Data
- Urban Development Data
- Financial Crime Data
- Population Health Data
- Asset Management Data
- Gaming Data
- Call Center Data
- Legal Compliance Data

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## 🧑‍💻 Usage

Here's how to generate and download a dataset:

```python
from data_pulse import generate_sales_data

data = generate_sales_data(num_records=100)
print(data.head())

data.to_csv("sales_data.csv", index=False)
```

You can switch datasets by importing the corresponding generator function (e.g., `generate_financial_data`, `generate_medical_data`).

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## 📂 Example API Endpoint (Using Flask)

```python
from flask import Flask, send_file
import io
from data_pulse import generate_financial_data

app = Flask(__name__)

@app.route('/download_financial_data')
def download_financial_data():
    df = generate_financial_data(10000)
    output = io.BytesIO()
    df.to_csv(output, index=False)
    output.seek(0)
    return send_file(output, mimetype='text/csv', as_attachment=True, download_name='financial_data.csv')

if __name__ == '__main__':
    app.run(debug=True)
```

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## 📘 Documentation

For detailed usage instructions and examples, check the official documentation:  
👉 [Data Pulse Documentation](https://github.com/yourusername/data-pulse)

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## 🤝 Contributing

Contributions are welcome! If you want to add new datasets or improve existing ones:
1. Fork the repository
2. Create a new branch
3. Submit a pull request

Feel free to open issues for bug reports and feature requests.

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## 📜 License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.

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## 📧 Contact

If you have questions or feedback, feel free to reach out:
- **Email:** saadurr30@gmail.com
- **GitHub:** [yourusername](https://github.com/yourusername)