Files
ALwrity/backend/models/oauth_token_monitoring_models.py

103 lines
3.6 KiB
Python

"""
OAuth Token Monitoring Models
Database models for tracking OAuth token status and monitoring tasks.
"""
from sqlalchemy import Column, Integer, String, Text, DateTime, Boolean, JSON, Index, ForeignKey
from sqlalchemy.orm import relationship
from datetime import datetime
# Import the same Base from enhanced_strategy_models
from models.enhanced_strategy_models import Base
class OAuthTokenMonitoringTask(Base):
"""
Model for storing OAuth token monitoring tasks.
Tracks per-user, per-platform token monitoring with weekly checks.
"""
__tablename__ = "oauth_token_monitoring_tasks"
id = Column(Integer, primary_key=True, index=True)
# User and Platform Identification
user_id = Column(String(255), nullable=False, index=True) # Clerk user ID (string)
platform = Column(String(50), nullable=False) # 'gsc', 'bing', 'wordpress', 'wix'
# Task Status
status = Column(String(50), default='active') # 'active', 'failed', 'paused', 'needs_intervention'
# Execution Tracking
last_check = Column(DateTime, nullable=True)
last_success = Column(DateTime, nullable=True)
last_failure = Column(DateTime, nullable=True)
failure_reason = Column(Text, nullable=True)
# Failure Pattern Tracking
consecutive_failures = Column(Integer, default=0) # Count of consecutive failures
failure_pattern = Column(JSON, nullable=True) # JSON storing failure analysis
# Scheduling
next_check = Column(DateTime, nullable=True, index=True) # Next scheduled check time
# Metadata
created_at = Column(DateTime, default=datetime.utcnow)
updated_at = Column(DateTime, default=datetime.utcnow, onupdate=datetime.utcnow)
# Execution Logs Relationship
execution_logs = relationship(
"OAuthTokenExecutionLog",
back_populates="task",
cascade="all, delete-orphan"
)
# Indexes for efficient queries
__table_args__ = (
Index('idx_user_platform', 'user_id', 'platform'),
Index('idx_next_check', 'next_check'),
Index('idx_status', 'status'),
)
def __repr__(self):
return f"<OAuthTokenMonitoringTask(id={self.id}, user_id={self.user_id}, platform={self.platform}, status={self.status})>"
class OAuthTokenExecutionLog(Base):
"""
Model for storing OAuth token monitoring execution logs.
Tracks individual execution attempts with results and error details.
"""
__tablename__ = "oauth_token_execution_logs"
id = Column(Integer, primary_key=True, index=True)
# Task Reference
task_id = Column(Integer, ForeignKey("oauth_token_monitoring_tasks.id"), nullable=False, index=True)
# Execution Details
execution_date = Column(DateTime, default=datetime.utcnow, nullable=False)
status = Column(String(50), nullable=False) # 'success', 'failed', 'skipped'
# Results
result_data = Column(JSON, nullable=True) # Token status, expiration info, etc.
error_message = Column(Text, nullable=True)
execution_time_ms = Column(Integer, nullable=True)
# Metadata
created_at = Column(DateTime, default=datetime.utcnow)
# Relationship to task
task = relationship("OAuthTokenMonitoringTask", back_populates="execution_logs")
# Indexes for efficient queries
__table_args__ = (
Index('idx_task_execution_date', 'task_id', 'execution_date'),
Index('idx_status', 'status'),
)
def __repr__(self):
return f"<OAuthTokenExecutionLog(id={self.id}, task_id={self.task_id}, status={self.status}, execution_date={self.execution_date})>"