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import pandas as pd
import numpy as np
from typing import Dict, List, Optional, Tuple
from datetime import datetime, timedelta
import logging

class DataAnalyzer:
    """Analyzes sales data and generates insights."""
    
    def __init__(self, data_path: str):
        self.logger = logging.getLogger(__name__)
        self.data_path = data_path
        self.df: Optional[pd.DataFrame] = None
        self._load_data()
    
    def _load_data(self) -> None:
        """Load sales data from CSV file."""
        try:
            self.df = pd.read_csv(self.data_path)
            self.df['date'] = pd.to_datetime(self.df['date'])
            self.logger.info(f"Loaded {len(self.df)} records")
        except Exception as e:
            self.logger.error(f"Failed to load data: {e}")
            raise
    
    def calculate_revenue_metrics(self) -> Dict[str, float]:
        """Calculate key revenue metrics."""
        if self.df is None:
            raise ValueError("No data loaded")
        
        metrics = {
            'total_revenue': self.df['revenue'].sum(),
            'average_order_value': self.df['revenue'].mean(),
            'revenue_std': self.df['revenue'].std(),
            'top_percentile_95': self.df['revenue'].quantile(0.95)
        }
        
        return metrics

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