Dynamic Fee Model for Uniswap V3

This project implements a dynamic fee model for Uniswap V3 using real-time data from the Ethereum blockchain. It uses machine learning to predict optimal fees based on market conditions.

Setup

1. Clone the repository:

   git clone https://github.com/chandshantanu/dynamicfeeModel.git
   cd dynamicfeeModel
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Set up your environment variables:

   • Copy .env.example to .env
   • Fill in the required values in .env

Running the Project

Using Python directly:

python -m src.main

Using Docker:

1. Build the Docker image:

   docker-compose build
   

2. Run the container:

   docker-compose up -d
   

Running Tests

python -m unittest discover tests

Project Structure

• src/: Contains the main application code
• tests/: Contains unit tests
• abis/: Contains ABI files for smart contracts
• Dockerfile and docker-compose.yml: For containerization
• requirements.txt: Python dependencies

Contributing

Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests.

License

This project is licensed under the MIT License - see the LICENSE.md file for details.