This project is a robust trading and backtesting infrastructure designed to support the evaluation of various trading strategies on financial instruments like stocks and cryptocurrencies. It leverages a microservices architecture with Docker for flexibility and scalability, using tools like Airflow, Kafka, FastAPI, and PostgreSQL.

• Automated Data Pipeline: Fetches historical market data using yfinance, processes it, and stores it in a PostgreSQL database.
• Backtesting Engine: Evaluates trading strategies against historical or real-time market data.
• Strategy Management: Allows the creation and storage of custom trading strategies.
• Kimball Schema: Employs a Kimball data warehouse schema for efficient storage and analysis of data.
• Microservice Architecture: Utilizes Docker containers for modularity and scalability.
• Kafka Integration: Employs Kafka for real-time data streaming and message passing.
• FastAPI Backend: Provides a modern REST API for interacting with the system.
• WebSocket Support: Enables real-time updates and data streaming to the frontend.
• Scalability: Designed to handle increasing volumes of data and backtest scenarios.

• airflow/: Contains Airflow DAGs for orchestrating data pipelines and backtests.
• api/: Houses the FastAPI backend service.
• database_service/: Contains the database service logic for data access and storage.
• kafka_consumer/: Holds the Kafka consumer service for data ingestion.
• models/: Defines the SQLAlchemy models for the database schema.
• shared/: Stores shared modules (e.g., utility functions, configurations).
• src/: Contains source code for data fetching, backtesting logic, and strategies.
• tests/: Includes unit and integration tests for the project.

1. Prerequisites:
   • Docker and Docker Compose
   • Python 3.9+ (with required dependencies: see requirements.txt)

• Fork the repository
• Clone the repository you just forked using git clone

In your terminal:

cd Backtesting-Infrastructure-CryptoTrading
pip install -r requirements.txt

In your terminal run:

make up

This will start the services in compose.yaml file. You can check the status of the services by running:

docker ps

To check the logs of a service, run:

docker compose logs -f <service_name>

Where the service_name is the name of the service found in the compose.yaml file.

• Example of checking the logs of the api service:

  docker compose logs -f api

• Airflow UI: http:https://localhost:8080
• FastAPI Docs: http:https://localhost:8089/docs
• Database Service: http:https://localhost:8001
• Kafka Consumer: logs can be viewed using docker compose logs -f kafka-consumer

This project is licensed under the Apache License 2.0. See the LICENSE file for details.