AI Trading Bot Data Fetcher & MongoDB and Binance API

This Python project retrieves real-time and historical cryptocurrency price data from the Binance API and stores it in a MongoDB database. It processes time-series data to generate short-term (1-minute interval) and long-term (5-minute interval) price trends. The script runs continuously, fetching and formatting price data for further analysis or integration with trading strategies.

Features

• Fetch real-time price data from Binance API.
• Store and retrieve price data in a MongoDB database.
• Generate short-term and long-term time-series datasets:
  • Short-Term: Last 300 data points at a 1-minute interval.
  • Long-Term: Last 300 data points at a 5-minute interval.
• Automatic data formatting for easy visualization or model input.
• Continuous execution with an interval-based update system.

Technology Stack

• Python 3.x
• MongoDB (Atlas Cloud or Local)
• Binance API (RESTful)
• Requests (HTTP API calls)
• Datetime & Timezone Handling

Installation & Setup

1. Clone the Repository

git clone https://github.com/FatherMonkey916/AI-Trading-Bot-Data-Fetcher
cd AI-Trading-Bot-Data-Fetcher

2. Install Dependencies

Make sure you have Python 3 installed, then install the required libraries:

pip install pymongo requests

3. Configure MongoDB Connection

Modify the MongoDB URI in the script (MONGODB_URI) with your credentials:

MONGODB_URI = "your_mongodb_connection_string"

Ensure your MongoDB database is accessible (Atlas or local).

4. Run the Script

python main.py

The script will continuously fetch price data every minute and update the database.

File Structure

binance-mongo-fetcher/
│── main.py               # Main script to fetch and process Binance data  
│── requirements.txt      # Python dependencies  
│── README.md             # Project documentation  
│── .gitignore            # Files to ignore in version control  

Future Enhancements

• Implement error handling & logging for better monitoring.
• Add support for multiple tokens dynamically.
• Store additional data fields (volume, open, high, low).
• Develop a web dashboard for visualization.

License

This project is open-source and available under the MIT License.