first commit

monitor/services/analyzer.py

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+import logging
+from datetime import timedelta
+from django.utils import timezone
+from django.db.models import Avg, Min, Max
+from decimal import Decimal
+
+from monitor.models import BitcoinPrice, MarketAnalysis
+
+logger = logging.getLogger(__name__)
+
+
+class MarketAnalyzer:
+    """Service for analyzing Bitcoin market data."""
+    
+    def __init__(self, threshold_percent=15.0):
+        self.threshold_percent = Decimal(str(threshold_percent))
+    
+    def analyze_market(self, period='hourly'):
+        """Analyze the Bitcoin market for a given period."""
+        try:
+            # Get data for the period
+            time_filter = self._get_time_filter(period)
+            prices = BitcoinPrice.objects.filter(timestamp__gte=time_filter)
+            
+            if not prices.exists():
+                logger.warning(f"No price data available for {period} analysis")
+                return None
+            
+            # Get latest price
+            latest_price = prices.latest('timestamp')
+            
+            # Calculate statistics
+            stats = prices.aggregate(
+                avg=Avg('price_usd'),
+                min=Min('price_usd'),
+                max=Max('price_usd'),
+            )
+            
+            avg_price = stats['avg'] or latest_price.price_usd
+            min_price = stats['min'] or latest_price.price_usd
+            max_price = stats['max'] or latest_price.price_usd
+            
+            # Calculate thresholds
+            lower_threshold = avg_price * (1 - self.threshold_percent / 100)
+            upper_threshold = avg_price * (1 + self.threshold_percent / 100)
+            
+            # Determine status
+            current_price = latest_price.price_usd
+            
+            if current_price < lower_threshold:
+                status = 'dip'
+                is_event = True
+                event_type = 'dip_below'
+            elif current_price > upper_threshold:
+                status = 'peak'
+                is_event = True
+                event_type = 'rise_above'
+            else:
+                status = 'neutral'
+                is_event = False
+                event_type = ''
+            
+            # Save analysis
+            analysis = MarketAnalysis.objects.create(
+                period=period,
+                current_price=current_price,
+                average_price=avg_price,
+                min_price=min_price,
+                max_price=max_price,
+                status=status,
+                threshold_percent=self.threshold_percent,
+                lower_threshold=lower_threshold,
+                upper_threshold=upper_threshold,
+                is_event=is_event,
+                event_type=event_type,
+            )
+            
+            logger.info(f"Market analysis saved: {status} at ${current_price}")
+            return analysis
+            
+        except BitcoinPrice.DoesNotExist:
+            logger.error("No Bitcoin price data found")
+            return None
+        except Exception as e:
+            logger.error(f"Error analyzing market: {e}")
+            return None
+    
+    def _get_time_filter(self, period):
+        """Get datetime filter based on period."""
+        now = timezone.now()
+        
+        if period == 'hourly':
+            return now - timedelta(hours=1)
+        elif period == 'daily':
+            return now - timedelta(days=1)
+        elif period == 'weekly':
+            return now - timedelta(weeks=1)
+        elif period == 'yearly':
+            return now - timedelta(days=365)
+        else:
+            return now - timedelta(days=1)  # Default to daily
+    
+    def get_latest_analysis(self, period='hourly'):
+        """Get the latest analysis for a period."""
+        try:
+            return MarketAnalysis.objects.filter(period=period).latest('timestamp')
+        except MarketAnalysis.DoesNotExist:
+            return None
+    def get_analysis_summary(self):
+        """Get summary of all analyses."""
+        summary = {}
+        
+        for period in ['hourly', 'daily', 'weekly', 'yearly']:
+            analysis = self.get_latest_analysis(period)
+            if analysis:
+                summary[period] = {
+                    'status': analysis.status,
+                    'current_price': float(analysis.current_price),
+                    'average_price': float(analysis.average_price),
+                    'threshold_percent': float(analysis.threshold_percent),
+                    'is_event': analysis.is_event,
+                }
+        
+        return summary