pipeline issues fix

services/calendar_service/models.py

@@ -1,77 +1,83 @@
-from sqlalchemy import Column, String, Integer, Date, Text, Boolean, ForeignKey
-from sqlalchemy.dialects.postgresql import UUID
-from shared.database import BaseModel
 import uuid
 
+from sqlalchemy import Boolean, Column, Date, ForeignKey, Integer, String, Text
+from sqlalchemy.dialects.postgresql import UUID
+
+from shared.database import BaseModel
+
 
 class CalendarEntry(BaseModel):
     __tablename__ = "calendar_entries"
-    
+
     uuid = Column(UUID(as_uuid=True), default=uuid.uuid4, unique=True, index=True)
     user_id = Column(Integer, ForeignKey("users.id"), nullable=False, index=True)
-    
+
     entry_date = Column(Date, nullable=False, index=True)
-    entry_type = Column(String(50), nullable=False)  # period, ovulation, symptoms, medication, etc.
-    
+    entry_type = Column(
+        String(50), nullable=False
+    )  # period, ovulation, symptoms, medication, etc.
+
     # Period tracking
     flow_intensity = Column(String(20))  # light, medium, heavy
     period_symptoms = Column(Text)  # cramps, headache, mood, etc.
-    
+
     # General health
     mood = Column(String(20))  # happy, sad, anxious, irritated, etc.
     energy_level = Column(Integer)  # 1-5 scale
     sleep_hours = Column(Integer)
-    
+
     # Symptoms and notes
     symptoms = Column(Text)  # Any symptoms experienced
     medications = Column(Text)  # Medications taken
     notes = Column(Text)  # Personal notes
-    
+
     # Predictions and calculations
     is_predicted = Column(Boolean, default=False)  # If this is a predicted entry
     confidence_score = Column(Integer)  # Prediction confidence 1-100
-    
+
     def __repr__(self):
         return f"<CalendarEntry user_id={self.user_id} date={self.entry_date} type={self.entry_type}>"
 
 
 class CycleData(BaseModel):
     __tablename__ = "cycle_data"
-    
+
     user_id = Column(Integer, ForeignKey("users.id"), nullable=False, index=True)
     cycle_start_date = Column(Date, nullable=False)
     cycle_length = Column(Integer)  # Length of this cycle
     period_length = Column(Integer)  # Length of period in this cycle
-    
+
     # Calculated fields
     ovulation_date = Column(Date)
     fertile_window_start = Column(Date)
     fertile_window_end = Column(Date)
     next_period_predicted = Column(Date)
-    
+
     # Cycle characteristics
     cycle_regularity_score = Column(Integer)  # 1-100, how regular is this cycle
     avg_cycle_length = Column(Integer)  # Rolling average
     avg_period_length = Column(Integer)  # Rolling average
-    
+
     def __repr__(self):
         return f"<CycleData user_id={self.user_id} start={self.cycle_start_date}>"
 
 
 class HealthInsights(BaseModel):
     __tablename__ = "health_insights"
-    
+
     user_id = Column(Integer, ForeignKey("users.id"), nullable=False, index=True)
-    insight_type = Column(String(50), nullable=False)  # cycle_pattern, symptom_pattern, etc.
-    
+    insight_type = Column(
+        String(50), nullable=False
+    )  # cycle_pattern, symptom_pattern, etc.
+
     title = Column(String(200), nullable=False)
     description = Column(Text, nullable=False)
     recommendation = Column(Text)
-    
+
     # Metadata
     confidence_level = Column(String(20))  # high, medium, low
     data_points_used = Column(Integer)  # How many data points were used
     is_dismissed = Column(Boolean, default=False)
-    
+
     def __repr__(self):
-        return f"<HealthInsights user_id={self.user_id} type={self.insight_type}>"
+        return f"<HealthInsights user_id={self.user_id} type={self.insight_type}>"