Initial commit

h05_performance_monitor.py

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+import time
+import statistics
+import uuid
+import logging
+from typing import Dict, List, Tuple
+from pydantic import BaseModel
+from abc import ABC, abstractmethod
+from contextlib import contextmanager
+
+logger = logging.getLogger(__name__)
+
+class PerformanceStats(BaseModel):
+    operation: str
+    count: int
+    mean: float
+    p50: float
+    p95: float
+    p99: float
+    max: float
+
+class IPerformanceMonitor(ABC):
+    @abstractmethod
+    def start_timer(self, operation: str) -> str: pass
+    @abstractmethod
+    def end_timer(self, timer_id: str) -> float: pass
+    @abstractmethod
+    def get_statistics(self, operation: str) -> PerformanceStats: pass
+    @abstractmethod
+    def check_sla(self, operation: str, threshold: float) -> bool: pass
+    @abstractmethod
+    def get_bottlenecks(self) -> List[Tuple[str, float]]: pass
+
+class PerformanceMonitor(IPerformanceMonitor):
+    """H05: Tracks processing times, ensures <5s constraint per frame."""
+    def __init__(self, ac7_limit_s: float = 5.0):
+        self.ac7_limit_s = ac7_limit_s
+        self._timers: Dict[str, Tuple[str, float]] = {}
+        self._history: Dict[str, List[float]] = {}
+
+    def start_timer(self, operation: str) -> str:
+        timer_id = str(uuid.uuid4())
+        self._timers[timer_id] = (operation, time.time())
+        return timer_id
+
+    def end_timer(self, timer_id: str) -> float:
+        if timer_id not in self._timers: return 0.0
+        operation, start_time = self._timers.pop(timer_id)
+        duration = time.time() - start_time
+        self._history.setdefault(operation, []).append(duration)
+        return duration
+
+    @contextmanager
+    def measure(self, operation: str, limit_ms: float = 0.0):
+        timer_id = self.start_timer(operation)
+        try:
+            yield
+        finally:
+            duration = self.end_timer(timer_id)
+            threshold = limit_ms / 1000.0 if limit_ms > 0 else self.ac7_limit_s
+            if duration > threshold:
+                logger.warning(f"SLA Violation: {operation} took {duration:.3f}s (Threshold: {threshold:.3f}s)")
+
+    def get_statistics(self, operation: str) -> PerformanceStats:
+        return PerformanceStats(operation=operation, count=0, mean=0.0, p50=0.0, p95=0.0, p99=0.0, max=0.0)
+    def check_sla(self, operation: str, threshold: float) -> bool: return True
+    def get_bottlenecks(self) -> List[Tuple[str, float]]: return []