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This project is an intelligent trading market analysis system based on Python and Web3. It utilizes a distributed data processing architecture with RabbitMQ and MySQL to achieve real-time market data analysis and trading strategy optimization.

API Documentation References: Binance OpenAPI Documentation, Huobi.pro OpenAPI Documentation.

• Data Crawling: Periodically fetches Binance market K-line data, supports multiple data sources and trading pairs.
• Technical Indicator Calculation: Computes various technical indicators, including KDJ, MACD, and moving averages.
• Scheduled and Real-time Alerts: Generates trading signal alerts based on preset strategies. Strategy optimization is primarily achieved through historical market data analysis and engineering optimization using ChatGPT, Claude, and Gemini.

• Price Alerts: Triggers real-time alerts when prices break take-profit/stop-loss levels.
• MACD Alerts: Monitors MACD golden/death crosses at multiple time intervals (1 day, 4 hours, 1 hour, 15 minutes, 5 minutes) and generates alerts.
• KDJ Alerts: Monitors KDJ golden/death crosses at multiple time intervals and generates alerts.
• Strategy Signal Alerts: Provides real-time buy/sell signal alerts.

• Moving Averages: EMA indicators with values of 12 and 26.
• MACD Values: DEA, DIF, and MACD trend analysis.
• KDJ Values: KDJ trend and crossover analysis.
• Trading Volume: Inflow/outflow volume analysis over 4-hour and 1-hour periods.
• Bollinger Bands: Calculates upper and lower bands for resistance and support levels.

Ensure the system has the following dependencies installed:

• Python 3.8+
• RabbitMQ
• Redis
• MySQL

pip install -r requirements.txt

CREATEDATABASEamf DEFAULT CHARACTERSET utf8mb4 COLLATE utf8mb4_unicode_ci;CREATEUSER 'myuser'@'localhost' IDENTIFIED BY'mypass';CREATEUSER 'myuser'@'%' IDENTIFIED BY'mypass';GRANT ALLON amf.* TO'myuser'@'localhost';GRANT ALLON amf.* TO'myuser'@'%';FLUSH PRIVILEGES;

rabbitmqctl add_user username passwordrabbitmqctl authenticate_user username password

python run.pypython runscheduler.pypython runconsumer.py