business_analyzer.py

from typing import Dict, Optional
import logging
from datetime import datetime, timedelta

logger = logging.getLogger(__name__)

class BusinessAnalyzer:
    """
    Analyzes market data and identifies business opportunities.
    Implements machine learning models for predictive insights.
    """

    def __init__(self):
        # Initialize any required ML models here
        pass

    def analyze_trends(self, data: Dict) -> Dict:
        """
        Analyzes trends in the provided market data.
        
        Args:
            data (Dict): Market data to analyze.
            
        Returns:
            Dict: Analysis results including identified opportunities.
        """
        analysis = {}
        try:
            # Example trend analysis
            current_trend = self._detect_trend(data)
            if current_trend == 'upward':
                analysis['opportunity'] = 'Buy signal detected'
            elif current_trend == 'downward':
                analysis['opportunity'] = 'Sell signal detected'
            else:
                analysis['opportunity'] = 'No clear trend'

            # Add more detailed analysis as needed
            return analysis
        except Exception as e:
            logger.error(f"Analysis failed: {str(e)}")
            return {}

    def _detect_trend(self, data: Dict) -> str:
        """
        Internal method to detect the current market trend.
        
        Args:
            data (Dict): Market data for a specific symbol.
            
        Returns:
            str: 'upward', 'downward', or 'flat'
        """
        if not data:
            return 'flat'
        
        # Simplified trend detection
        prices = [d['price'] for d in data.get('prices', [])]
        if len(prices) < 2:
            return 'flat'
        
        last_price = prices[-1]
        previous_price = prices[0]
        if last_price > previous_price * 1.05:
            return 'upward'
        elif last_price < previous_price * 0.95:
            return 'downward'
        else:
            return 'flat'

    def generate_insights(self, analysis: Dict) -> Dict:
        """
        Generates actionable insights from the analysis.
        
        Args:
            analysis (Dict): The result of trend analysis.
            
        Returns