Xiaoxia AI
105 lines
3.1 KiB
Python
105 lines
3.1 KiB
Python
"""
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性能监控中间件
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"""
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import logging
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import time
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from typing import Callable
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from fastapi import Request, Response
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from starlette.middleware.base import BaseHTTPMiddleware
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logger = logging.getLogger(__name__)
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class PerformanceMonitoringMiddleware(BaseHTTPMiddleware):
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"""性能监控中间件"""
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def __init__(self, app, slow_request_threshold: float = 1.0):
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super().__init__(app)
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self.slow_request_threshold = slow_request_threshold # 慢请求阈值（秒）
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async def dispatch(self, request: Request, call_next: Callable):
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# 记录请求开始时间
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start_time = time.time()
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# 生成请求 ID
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request_id = self._generate_request_id()
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request.state.request_id = request_id
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# 处理请求
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try:
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response = await call_next(request)
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# 计算处理时间
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process_time = time.time() - start_time
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# 添加响应头
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response.headers["X-Request-ID"] = request_id
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response.headers["X-Process-Time"] = f"{process_time:.3f}"
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# 记录慢请求
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if process_time > self.slow_request_threshold:
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logger.warning(
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f"Slow request detected: {request.method} {request.url.path} "
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f"took {process_time:.3f}s (threshold: {self.slow_request_threshold}s) "
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f"[request_id={request_id}]"
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)
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# 记录请求日志
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logger.info(
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f"{request.method} {request.url.path} "
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f"status={response.status_code} time={process_time:.3f}s "
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f"[request_id={request_id}]"
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)
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return response
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except Exception as e:
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process_time = time.time() - start_time
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logger.error(
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f"Request failed: {request.method} {request.url.path} "
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f"error={str(e)} time={process_time:.3f}s "
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f"[request_id={request_id}]",
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exc_info=True,
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)
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raise
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def _generate_request_id(self) -> str:
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"""生成请求 ID"""
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import uuid
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return str(uuid.uuid4())
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class DatabaseQueryLogger:
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"""数据库查询日志记录器"""
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def __init__(self):
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self.queries = []
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self.total_time = 0
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def log_query(self, query: str, params: tuple, duration: float):
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"""记录查询"""
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self.queries.append(
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{
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"query": query,
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"params": params,
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"duration": duration,
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}
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)
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self.total_time += duration
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# 记录慢查询（超过 100ms）
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if duration > 0.1:
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logger.warning(f"Slow query detected: {query[:100]}... " f"took {duration:.3f}s with params {params}")
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def get_stats(self):
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"""获取统计信息"""
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return {
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"total_queries": len(self.queries),
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"total_time": self.total_time,
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"avg_time": self.total_time / len(self.queries) if self.queries else 0,
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"slow_queries": len([q for q in self.queries if q["duration"] > 0.1]),
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}
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