fraq-nettrade-abstractions 0.1.2

SDK for developing trading strategies in Python for FraQ NetTrade

FraQ NetTrade Python Abstractions

SDK for developing trading strategies in Python for the FraQ NetTrade platform.

Installation

pip install fraq-nettrade-abstractions

Quick Start

from fraq_nettrade_abstractions import Strategy

class MyStrategy(Strategy):
    def on_start(self, context):
        """Initialize your strategy"""
        self.sma_fast = context['indicators'].sma(period=10)
        self.sma_slow = context['indicators'].sma(period=20)
    
    def on_bar(self, symbol, index):
        """Trading logic - called on each bar"""
        if self.sma_fast[index] > self.sma_slow[index]:
            return {'action': 'buy', 'volume': 1.0}
        elif self.sma_fast[index] < self.sma_slow[index]:
            return {'action': 'sell', 'volume': 1.0}
        return None

Running Your Strategy

1. Save your strategy to a .py file
2. Open FraQ application
3. Load your Python strategy file
4. Run backtest

Debugging

from fraq_nettrade_abstractions import Strategy, enable_debugger

class MyStrategy(Strategy):
    def on_start(self, context):
        enable_debugger()  # Wait for VS Code debugger
        # Your strategy code with breakpoints

Debug workflow:

1. Start FraQ with --debug flag
2. Attach VS Code to port 5678
3. Set breakpoints in your strategy
4. Press Enter in FraQ console

API Reference

Strategy Class

Base class for all trading strategies.

Methods to implement:

• on_start(context) - Called once when backtest starts
• on_bar(symbol, index) - Called on each bar (required)
• on_tick(symbol) - Called on each tick (optional)
• on_stop() - Called when backtest ends (optional)

Context Object

Passed to on_start():

{
    'account': {
        'balance': float,
        'equity': float,
        'margin_used': float,
        'margin_available': float
    },
    'symbols': [
        {
            'name': str,
            'bid': float,
            'ask': float,
        }
    ],
    'indicators': IndicatorFactory
}

Symbol Object

Passed to on_bar() and on_tick():

{
    'name': 'EURUSD',
    'bid': 1.0850,
    'ask': 1.0852,
    'spread': 0.0002,
    'close': 1.0851,
    'bars': [
        {
            'open': 1.0840,
            'high': 1.0855,
            'low': 1.0835,
            'close': 1.0850,
            'volume': 1000.0,
            'time': '2024-01-01T00:00:00'
        }
    ]
}

Trade Signals

Return from on_bar() or on_tick():

# Buy signal
{'action': 'buy', 'volume': 1.0}

# Sell signal
{'action': 'sell', 'volume': 1.0}

# Close all positions
{'action': 'close', 'volume': 0}

# No action
None

Built-in Indicators

Access via context['indicators'] in on_start():

• sma(period) - Simple Moving Average
• ema(period) - Exponential Moving Average
• rsi(period) - Relative Strength Index
• macd(fast, slow, signal) - MACD
• bollinger(period, stddev) - Bollinger Bands

Examples

See the examples directory for complete strategy examples.

License

MIT License - see LICENSE file for details

Support

• GitHub: https://github.com/FraQLabs/FraQ-NetTrade
• Issues: https://github.com/FraQLabs/FraQ-NetTrade/issues