TRDR - Trading Framework

TRDR is a framework for algorithmic trading in Python. It features a custom Domain-Specific Language (DSL) for expressing trading strategies in a clear, concise manner.

🌟 Features

• Custom DSL: Define trading strategies with a readable, declarative syntax
• Modular Architecture: Easily swap components like brokers and data providers
• Async First: Built from the ground up with Python's async/await pattern
• Mock Trading: Test strategies with a mock broker before using real money
• Telemetry Integration: Optional OpenTelemetry support for performance monitoring
• Pattern Day Trading Controls: Built-in PDT rule compliance strategies (NunStrategy, WiggleStrategy, YoloStrategy)

📦 Installation

# Basic installation
pip install trdr

# Development installation (with testing tools)
pip install -e ".[dev]"

🚀 Quick Start

1. Define Your Strategy

Create a file my-strategy.trdr with your trading strategy:

STRATEGY
    NAME "Moving Average Crossover"
    DESCRIPTION "Basic MA crossover strategy with risk management"
    ENTRY
        ALL_OF
            MA5 CROSSED_ABOVE MA20
            MA20 > MA50
            CURRENT_PRICE > 100
    EXIT
        ANY_OF
            CURRENT_PRICE > (AVERAGE_COST * 1.06)  # 6% profit target
            CURRENT_PRICE < (AVERAGE_COST * 0.98)  # 2% stop loss
    SIZING
        RULE
            CONDITION
                ALL_OF
                    ACCOUNT_EXPOSURE < 0.5
                    NUMBER_OF_OPEN_POSITIONS < 3
            DOLLAR_AMOUNT 
                (AVAILABLE_CASH * 0.20)

2. Run Your Strategy

import asyncio
from trdr.core.bar_provider.yf_bar_provider.yf_bar_provider import YFBarProvider
from trdr.core.security_provider.security_provider import SecurityProvider
from trdr.core.broker.mock_broker.mock_broker import MockBroker
from trdr.core.trading_engine.trading_engine import TradingEngine
from trdr.core.trading_context.trading_context import TradingContext
from trdr.core.broker.pdt.nun_strategy import NunStrategy

async def main():
    try:
        pdt_strategy = NunStrategy.create()
        async with await MockBroker.create(pdt_strategy=pdt_strategy) as broker:
            bar_provider = await YFBarProvider.create(["TSLA"])
            security_provider = await SecurityProvider.create(bar_provider)
            context = await TradingContext.create(security_provider, broker)
            engine = await TradingEngine.create("my-strategy", context)
            await engine.execute()
    except Exception as e:
        print(e)

if __name__ == "__main__":
    asyncio.run(main())

🛠️ Architecture

TRDR is built with a modular, component-based architecture:

• Bar Provider: Supplies price/volume data (Yahoo Finance implementation included)
• Security Provider: Manages available securities for trading
• Broker: Handles order execution
  • Mock Broker - Local simulation for testing
  • Alpaca Broker - Real trading with Alpaca API
• Trading Context: Coordinates components and maintains state
• Trading Engine: Executes strategies using the DSL parser
• PDT Strategies: Enforces Pattern Day Trading rules with multiple compliance strategies

📊 DSL Reference

The TRDR Domain Specific Language provides a clean (I hope) syntax for expressing trading logic:

Strategy Structure

STRATEGY
    NAME "Strategy Name"
    DESCRIPTION "Strategy Description"
    ENTRY
        # Entry conditions
    EXIT
        # Exit conditions
    SIZING
        # Position sizing rules

Logical Operators

ALL_OF          # All conditions must be true
ANY_OF          # Any condition can be true

Technical Indicators

MA{period}      # Moving average (e.g., MA5, MA20, MA50, MA100, MA200)
AV{period}      # Average volume (e.g., AV5, AV20, AV50, AV100, AV200)

Comparison Operators

>               # Greater than
<               # Less than
>=              # Greater than or equal to
<=              # Less than or equal to
==              # Equal to
CROSSED_ABOVE   # Indicator crossed above another
CROSSED_BELOW   # Indicator crossed below another

Price Metrics

CURRENT_PRICE   # Current price of the security
CURRENT_VOLUME  # Current volume of the security

Account Metrics

ACCOUNT_EXPOSURE         # Percentage of account exposed to market
AVAILABLE_CASH           # Available cash for trading
AVERAGE_COST             # Average cost of current position
NUMBER_OF_OPEN_POSITIONS # Number of currently open positions

Mathematical Operators

+               # Addition
-               # Subtraction
*               # Multiplication
/               # Division
(expression)    # Parentheses for grouping expressions

📚 Examples

Check the examples/ directory for complete examples:

• No Telemetry Example: Basic usage without OpenTelemetry
• With Telemetry Example: Using OpenTelemetry for monitoring
• Strategy Examples: Sample trading strategies

🧪 Testing

# Run all tests
pytest

# Run specific test file
pytest src/trdr/path/to/test_file.py

# Run specific test
pytest src/trdr/path/to/test_file.py::TestClass::test_method

📝 License

MIT License

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.