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infrastructure/repositories/rate_limit_repository.py
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252
infrastructure/repositories/rate_limit_repository.py
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"""
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Rate Limit Repository - Persistierung von Rate Limit Events und Policies
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"""
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import json
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import sqlite3
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from typing import List, Optional, Dict, Any
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from datetime import datetime, timedelta
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from collections import defaultdict
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from infrastructure.repositories.base_repository import BaseRepository
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from domain.entities.rate_limit_policy import RateLimitPolicy
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from domain.value_objects.action_timing import ActionTiming, ActionType
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class RateLimitRepository(BaseRepository):
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"""Repository für Rate Limit Daten"""
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def save_timing(self, timing: ActionTiming) -> None:
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"""Speichert ein Action Timing Event"""
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query = """
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INSERT INTO rate_limit_events (
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timestamp, action_type, duration_ms, success, response_code,
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session_id, url, element_selector, error_message, retry_count, metadata
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) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
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"""
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params = (
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timing.timestamp,
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timing.action_type.value,
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int(timing.duration_ms),
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timing.success,
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timing.metadata.get('response_code') if timing.metadata else None,
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timing.metadata.get('session_id') if timing.metadata else None,
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timing.url,
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timing.element_selector,
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timing.error_message,
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timing.retry_count,
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self._serialize_json(timing.metadata) if timing.metadata else None
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)
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self._execute_insert(query, params)
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def get_recent_timings(self, action_type: Optional[ActionType] = None,
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hours: int = 1) -> List[ActionTiming]:
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"""Holt kürzliche Timing-Events"""
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query = """
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SELECT * FROM rate_limit_events
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WHERE timestamp > datetime('now', '-' || ? || ' hours')
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"""
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params = [hours]
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if action_type:
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query += " AND action_type = ?"
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params.append(action_type.value)
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query += " ORDER BY timestamp DESC"
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rows = self._execute_query(query, tuple(params))
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timings = []
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for row in rows:
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timing = ActionTiming(
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action_type=ActionType(row['action_type']),
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timestamp=self._parse_datetime(row['timestamp']),
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duration=row['duration_ms'] / 1000.0,
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success=bool(row['success']),
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url=row['url'],
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element_selector=row['element_selector'],
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error_message=row['error_message'],
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retry_count=row['retry_count'],
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metadata=self._deserialize_json(row['metadata'])
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)
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timings.append(timing)
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return timings
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def save_policy(self, action_type: ActionType, policy: RateLimitPolicy) -> None:
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"""Speichert oder aktualisiert eine Rate Limit Policy"""
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query = """
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INSERT OR REPLACE INTO rate_limit_policies (
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action_type, min_delay, max_delay, adaptive,
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backoff_multiplier, max_retries, updated_at
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) VALUES (?, ?, ?, ?, ?, ?, ?)
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"""
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params = (
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action_type.value,
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policy.min_delay,
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policy.max_delay,
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policy.adaptive,
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policy.backoff_multiplier,
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policy.max_retries,
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datetime.now()
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)
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self._execute_insert(query, params)
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def get_policy(self, action_type: ActionType) -> Optional[RateLimitPolicy]:
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"""Holt eine Rate Limit Policy"""
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query = "SELECT * FROM rate_limit_policies WHERE action_type = ?"
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rows = self._execute_query(query, (action_type.value,))
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if not rows:
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return None
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row = rows[0]
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return RateLimitPolicy(
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min_delay=row['min_delay'],
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max_delay=row['max_delay'],
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adaptive=bool(row['adaptive']),
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backoff_multiplier=row['backoff_multiplier'],
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max_retries=row['max_retries']
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)
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def get_all_policies(self) -> Dict[ActionType, RateLimitPolicy]:
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"""Holt alle gespeicherten Policies"""
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query = "SELECT * FROM rate_limit_policies"
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rows = self._execute_query(query)
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policies = {}
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for row in rows:
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try:
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action_type = ActionType(row['action_type'])
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policy = RateLimitPolicy(
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min_delay=row['min_delay'],
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max_delay=row['max_delay'],
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adaptive=bool(row['adaptive']),
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backoff_multiplier=row['backoff_multiplier'],
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max_retries=row['max_retries']
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)
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policies[action_type] = policy
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except ValueError:
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# Unbekannter ActionType
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pass
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return policies
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def get_statistics(self, action_type: Optional[ActionType] = None,
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timeframe: Optional[timedelta] = None) -> Dict[str, Any]:
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"""Berechnet Statistiken über Rate Limiting"""
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query = """
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SELECT
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action_type,
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COUNT(*) as total_actions,
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AVG(duration_ms) as avg_duration_ms,
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MIN(duration_ms) as min_duration_ms,
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MAX(duration_ms) as max_duration_ms,
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SUM(CASE WHEN success = 1 THEN 1 ELSE 0 END) as successful_actions,
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SUM(CASE WHEN success = 0 THEN 1 ELSE 0 END) as failed_actions,
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AVG(retry_count) as avg_retry_count,
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MAX(retry_count) as max_retry_count
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FROM rate_limit_events
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WHERE 1=1
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"""
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params = []
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if timeframe:
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query += " AND timestamp > datetime('now', '-' || ? || ' seconds')"
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params.append(int(timeframe.total_seconds()))
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if action_type:
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query += " AND action_type = ?"
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params.append(action_type.value)
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query += " GROUP BY action_type"
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else:
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query += " GROUP BY action_type"
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rows = self._execute_query(query, tuple(params))
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if action_type and rows:
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# Einzelne Action Type Statistik
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row = rows[0]
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return {
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'action_type': row['action_type'],
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'total_actions': row['total_actions'],
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'avg_duration_ms': row['avg_duration_ms'],
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'min_duration_ms': row['min_duration_ms'],
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'max_duration_ms': row['max_duration_ms'],
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'success_rate': row['successful_actions'] / row['total_actions'] if row['total_actions'] > 0 else 0,
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'failed_actions': row['failed_actions'],
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'avg_retry_count': row['avg_retry_count'],
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'max_retry_count': row['max_retry_count']
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}
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else:
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# Statistiken für alle Action Types
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stats = {}
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for row in rows:
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stats[row['action_type']] = {
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'total_actions': row['total_actions'],
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'avg_duration_ms': row['avg_duration_ms'],
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'min_duration_ms': row['min_duration_ms'],
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'max_duration_ms': row['max_duration_ms'],
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'success_rate': row['successful_actions'] / row['total_actions'] if row['total_actions'] > 0 else 0,
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'failed_actions': row['failed_actions'],
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'avg_retry_count': row['avg_retry_count'],
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'max_retry_count': row['max_retry_count']
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}
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return stats
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def detect_anomalies(self, action_type: ActionType,
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threshold_multiplier: float = 2.0) -> List[Dict[str, Any]]:
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"""Erkennt Anomalien in den Timing-Daten"""
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# Berechne Durchschnitt und Standardabweichung
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query = """
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SELECT
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AVG(duration_ms) as avg_duration,
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AVG(duration_ms * duration_ms) - AVG(duration_ms) * AVG(duration_ms) as variance
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FROM rate_limit_events
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WHERE action_type = ?
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AND timestamp > datetime('now', '-1 hour')
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AND success = 1
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"""
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row = self._execute_query(query, (action_type.value,))[0]
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if not row['avg_duration']:
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return []
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avg_duration = row['avg_duration']
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std_dev = (row['variance'] ** 0.5) if row['variance'] > 0 else 0
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threshold = avg_duration + (std_dev * threshold_multiplier)
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# Finde Anomalien
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query = """
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SELECT * FROM rate_limit_events
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WHERE action_type = ?
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AND timestamp > datetime('now', '-1 hour')
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AND duration_ms > ?
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ORDER BY duration_ms DESC
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LIMIT 10
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"""
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rows = self._execute_query(query, (action_type.value, threshold))
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anomalies = []
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for row in rows:
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anomalies.append({
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'timestamp': row['timestamp'],
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'duration_ms': row['duration_ms'],
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'deviation': (row['duration_ms'] - avg_duration) / std_dev if std_dev > 0 else 0,
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'success': bool(row['success']),
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'url': row['url'],
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'error_message': row['error_message']
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})
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return anomalies
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def cleanup_old_events(self, older_than: datetime) -> int:
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"""Bereinigt alte Rate Limit Events"""
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query = "DELETE FROM rate_limit_events WHERE timestamp < ?"
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return self._execute_delete(query, (older_than,))
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