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

tests/fixtures/sample_data.py

@@ -0,0 +1,81 @@
+"""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
+