Local changes: Updated model training, removed debug instrumentation, and configuration improvements

tests/fixtures/__init__.py

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+"""Test fixtures and mocks."""
+

tests/fixtures/mock_exchange.py

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+"""Mock exchange adapter for testing."""
+
+from unittest.mock import Mock, AsyncMock
+from src.exchanges.base import BaseExchange
+
+
+class MockExchange(BaseExchange):
+    """Mock exchange adapter for testing."""
+    
+    def __init__(self, name: str = "mock_exchange", **kwargs):
+        super().__init__(name, "mock_key", "mock_secret")
+        self.is_connected = True
+        self._mock_responses = {}
+    
+    async def connect(self):
+        """Mock connection."""
+        self.is_connected = True
+    
+    async def disconnect(self):
+        """Mock disconnection."""
+        self.is_connected = False
+    
+    async def fetch_balance(self):
+        """Mock balance fetch."""
+        return self._mock_responses.get('balance', {
+            'USD': {'free': 1000.0, 'used': 0.0, 'total': 1000.0}
+        })
+    
+    async def place_order(self, symbol, side, order_type, amount, price=None, params=None):
+        """Mock order placement."""
+        return self._mock_responses.get('order', {
+            'id': 'mock_order_123',
+            'status': 'filled',
+            'filled': amount,
+            'price': price or 50000.0
+        })
+    
+    async def cancel_order(self, order_id, symbol=None):
+        """Mock order cancellation."""
+        return {'id': order_id, 'status': 'canceled'}
+    
+    async def fetch_order_status(self, order_id, symbol=None):
+        """Mock order status fetch."""
+        return self._mock_responses.get('order_status', {
+            'id': order_id,
+            'status': 'filled'
+        })
+    
+    async def fetch_ohlcv(self, symbol, timeframe, since=None, limit=None):
+        """Mock OHLCV fetch."""
+        return self._mock_responses.get('ohlcv', [])
+    
+    async def subscribe_ohlcv(self, symbol, timeframe, callback):
+        """Mock OHLCV subscription."""
+        pass
+    
+    async def subscribe_trades(self, symbol, callback):
+        """Mock trades subscription."""
+        pass
+    
+    async def subscribe_order_book(self, symbol, callback):
+        """Mock order book subscription."""
+        pass
+    
+    async def fetch_open_orders(self, symbol=None):
+        """Mock open orders fetch."""
+        return self._mock_responses.get('open_orders', [])
+    
+    async def fetch_positions(self, symbol=None):
+        """Mock positions fetch."""
+        return self._mock_responses.get('positions', [])
+    
+    async def fetch_markets(self):
+        """Mock markets fetch."""
+        return self._mock_responses.get('markets', [])
+

tests/fixtures/sample_data.py

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+"""Sample data generators for testing."""
+
+import pandas as pd
+import numpy as np
+from datetime import datetime, timedelta
+from faker import Faker
+
+fake = Faker()
+
+
+def generate_ohlcv_data(
+    symbol: str = "BTC/USD",
+    periods: int = 100,
+    start_price: float = 50000.0,
+    timeframe: str = "1h"
+) -> pd.DataFrame:
+    """Generate sample OHLCV data.
+    
+    Args:
+        symbol: Trading pair
+        periods: Number of periods
+        start_price: Starting price
+        timeframe: Data timeframe
+        
+    Returns:
+        DataFrame with OHLCV data
+    """
+    dates = pd.date_range(
+        start=datetime.now() - timedelta(hours=periods),
+        periods=periods,
+        freq=timeframe
+    )
+    
+    # Generate realistic price movement
+    prices = [start_price]
+    for i in range(1, periods):
+        change = np.random.randn() * 0.02  # 2% volatility
+        prices.append(prices[-1] * (1 + change))
+    
+    return pd.DataFrame({
+        'timestamp': dates,
+        'open': prices,
+        'high': [p * 1.01 for p in prices],
+        'low': [p * 0.99 for p in prices],
+        'close': prices,
+        'volume': [1000.0 + np.random.randn() * 100 for _ in range(periods)]
+    })
+
+
+def generate_trade_data(
+    symbol: str = "BTC/USD",
+    count: int = 10
+) -> list:
+    """Generate sample trade data.
+    
+    Args:
+        symbol: Trading pair
+        count: Number of trades
+        
+    Returns:
+        List of trade dictionaries
+    """
+    trades = []
+    base_price = 50000.0
+    
+    for i in range(count):
+        trades.append({
+            'order_id': f'trade_{i}',
+            'symbol': symbol,
+            'side': 'buy' if i % 2 == 0 else 'sell',
+            'type': 'market',
+            'price': base_price + np.random.randn() * 100,
+            'amount': 0.01,
+            'cost': 500.0,
+            'fee': 0.5,
+            'status': 'filled',
+            'timestamp': datetime.now() - timedelta(hours=count-i)
+        })
+    
+    return trades
+