mirror of
https://github.com/jxxghp/MoviePilot.git
synced 2026-04-13 17:52:28 +08:00
remove monitoring
This commit is contained in:
jxxghp
@@ -2,7 +2,7 @@ from fastapi import APIRouter
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from app.api.endpoints import login, user, webhook, message, site, subscribe, \
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media, douban, search, plugin, tmdb, history, system, download, dashboard, \
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transfer, mediaserver, bangumi, storage, discover, recommend, workflow, torrent, monitoring
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transfer, mediaserver, bangumi, storage, discover, recommend, workflow, torrent
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api_router = APIRouter()
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api_router.include_router(login.router, prefix="/login", tags=["login"])
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@@ -28,4 +28,3 @@ api_router.include_router(discover.router, prefix="/discover", tags=["discover"]
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api_router.include_router(recommend.router, prefix="/recommend", tags=["recommend"])
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api_router.include_router(workflow.router, prefix="/workflow", tags=["workflow"])
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api_router.include_router(torrent.router, prefix="/torrent", tags=["torrent"])
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api_router.include_router(monitoring.router, prefix="/monitoring", tags=["monitoring"])
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@@ -1,409 +0,0 @@
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from typing import Any, List
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from fastapi import APIRouter, Depends, Query
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from fastapi.responses import HTMLResponse
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from app import schemas
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from app.core.security import verify_apitoken
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from app.monitoring import monitor, get_metrics_response
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from app.schemas.monitoring import (
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PerformanceSnapshot,
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EndpointStats,
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ErrorRequest,
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MonitoringOverview
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)
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router = APIRouter()
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@router.get("/overview", summary="获取监控概览", response_model=schemas.MonitoringOverview)
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def get_overview(_: str = Depends(verify_apitoken)) -> Any:
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"""
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获取完整的监控概览信息
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"""
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# 获取性能快照
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performance = monitor.get_performance_snapshot()
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# 获取最活跃端点
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top_endpoints = monitor.get_top_endpoints(limit=10)
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# 获取最近错误
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recent_errors = monitor.get_recent_errors(limit=20)
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# 检查告警
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alerts = monitor.check_alerts()
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return MonitoringOverview(
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performance=PerformanceSnapshot(
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timestamp=performance.timestamp,
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cpu_usage=performance.cpu_usage,
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memory_usage=performance.memory_usage,
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active_requests=performance.active_requests,
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request_rate=performance.request_rate,
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avg_response_time=performance.avg_response_time,
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error_rate=performance.error_rate,
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slow_requests=performance.slow_requests
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),
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top_endpoints=[EndpointStats(**endpoint) for endpoint in top_endpoints],
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recent_errors=[ErrorRequest(**error) for error in recent_errors],
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alerts=alerts
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)
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@router.get("/performance", summary="获取性能快照", response_model=schemas.PerformanceSnapshot)
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def get_performance(_: str = Depends(verify_apitoken)) -> Any:
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"""
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获取当前性能快照
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"""
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snapshot = monitor.get_performance_snapshot()
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return PerformanceSnapshot(
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timestamp=snapshot.timestamp,
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cpu_usage=snapshot.cpu_usage,
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memory_usage=snapshot.memory_usage,
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active_requests=snapshot.active_requests,
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request_rate=snapshot.request_rate,
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avg_response_time=snapshot.avg_response_time,
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error_rate=snapshot.error_rate,
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slow_requests=snapshot.slow_requests
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)
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@router.get("/endpoints", summary="获取端点统计", response_model=List[schemas.EndpointStats])
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def get_endpoints(
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limit: int = Query(10, ge=1, le=50, description="返回的端点数量"),
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_: str = Depends(verify_apitoken)
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) -> Any:
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"""
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获取最活跃的API端点统计
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"""
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endpoints = monitor.get_top_endpoints(limit=limit)
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return [EndpointStats(**endpoint) for endpoint in endpoints]
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@router.get("/errors", summary="获取错误请求", response_model=List[schemas.ErrorRequest])
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def get_errors(
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limit: int = Query(20, ge=1, le=100, description="返回的错误数量"),
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_: str = Depends(verify_apitoken)
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) -> Any:
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"""
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获取最近的错误请求记录
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"""
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errors = monitor.get_recent_errors(limit=limit)
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return [ErrorRequest(**error) for error in errors]
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@router.get("/alerts", summary="获取告警信息", response_model=List[str])
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def get_alerts(_: str = Depends(verify_apitoken)) -> Any:
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"""
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获取当前告警信息
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"""
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return monitor.check_alerts()
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@router.get("/metrics", summary="Prometheus指标")
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def get_prometheus_metrics(_: str = Depends(verify_apitoken)) -> Any:
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"""
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获取Prometheus格式的监控指标
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"""
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return get_metrics_response()
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@router.get("/dashboard", summary="监控仪表板", response_class=HTMLResponse)
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def get_dashboard(_: str = Depends(verify_apitoken)) -> Any:
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"""
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获取实时监控仪表板HTML页面
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"""
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return HTMLResponse(content="""
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<!DOCTYPE html>
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<html lang="zh-CN">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>MoviePilot 性能监控仪表板</title>
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<script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
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<style>
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body {
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font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
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margin: 0;
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padding: 20px;
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background-color: #f5f5f5;
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}
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.container {
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max-width: 1200px;
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margin: 0 auto;
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}
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.header {
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text-align: center;
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margin-bottom: 30px;
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color: #333;
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}
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.metrics-grid {
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display: grid;
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grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));
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gap: 20px;
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margin-bottom: 30px;
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}
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.metric-card {
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background: white;
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padding: 20px;
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border-radius: 10px;
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box-shadow: 0 2px 10px rgba(0,0,0,0.1);
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text-align: center;
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}
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.metric-value {
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font-size: 2em;
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font-weight: bold;
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color: #2196F3;
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}
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.metric-label {
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color: #666;
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margin-top: 5px;
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}
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.chart-container {
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background: white;
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padding: 20px;
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border-radius: 10px;
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box-shadow: 0 2px 10px rgba(0,0,0,0.1);
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margin-bottom: 20px;
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}
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.alerts {
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background: #fff3cd;
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border: 1px solid #ffeaa7;
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border-radius: 5px;
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padding: 15px;
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margin-bottom: 20px;
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}
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.alert-item {
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color: #856404;
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margin: 5px 0;
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}
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.refresh-btn {
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background: #2196F3;
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color: white;
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border: none;
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padding: 10px 20px;
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border-radius: 5px;
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cursor: pointer;
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margin-bottom: 20px;
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}
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.refresh-btn:hover {
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background: #1976D2;
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}
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</style>
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</head>
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<body>
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<div class="container">
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<div class="header">
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<h1>🎬 MoviePilot 性能监控仪表板</h1>
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<button class="refresh-btn" onclick="refreshData()">刷新数据</button>
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</div>
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<div id="alerts" class="alerts" style="display: none;">
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<h3>⚠️ 告警信息</h3>
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<div id="alerts-list"></div>
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</div>
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<div class="metrics-grid">
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<div class="metric-card">
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<div class="metric-value" id="cpu-usage">--</div>
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<div class="metric-label">CPU使用率 (%)</div>
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</div>
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<div class="metric-card">
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<div class="metric-value" id="memory-usage">--</div>
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<div class="metric-label">内存使用率 (%)</div>
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</div>
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<div class="metric-card">
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<div class="metric-value" id="active-requests">--</div>
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<div class="metric-label">活跃请求数</div>
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</div>
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<div class="metric-card">
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<div class="metric-value" id="request-rate">--</div>
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<div class="metric-label">请求率 (req/min)</div>
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</div>
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<div class="metric-card">
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<div class="metric-value" id="avg-response-time">--</div>
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<div class="metric-label">平均响应时间 (s)</div>
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</div>
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<div class="metric-card">
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<div class="metric-value" id="error-rate">--</div>
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<div class="metric-label">错误率 (%)</div>
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</div>
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</div>
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<div class="chart-container">
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<h3>📊 性能趋势</h3>
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<canvas id="performanceChart" width="400" height="200"></canvas>
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</div>
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<div class="chart-container">
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<h3>🔥 最活跃端点</h3>
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<canvas id="endpointsChart" width="400" height="200"></canvas>
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</div>
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</div>
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<script>
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let performanceChart, endpointsChart;
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let performanceData = {
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labels: [],
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cpu: [],
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memory: [],
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requests: []
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};
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// 初始化图表
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function initCharts() {
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const ctx1 = document.getElementById('performanceChart').getContext('2d');
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performanceChart = new Chart(ctx1, {
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type: 'line',
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data: {
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labels: performanceData.labels,
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datasets: [{
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label: 'CPU使用率 (%)',
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data: performanceData.cpu,
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borderColor: '#2196F3',
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backgroundColor: 'rgba(33, 150, 243, 0.1)',
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tension: 0.4
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}, {
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label: '内存使用率 (%)',
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data: performanceData.memory,
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borderColor: '#4CAF50',
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backgroundColor: 'rgba(76, 175, 80, 0.1)',
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tension: 0.4
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}, {
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label: '活跃请求数',
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data: performanceData.requests,
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borderColor: '#FF9800',
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backgroundColor: 'rgba(255, 152, 0, 0.1)',
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tension: 0.4
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}]
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},
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options: {
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responsive: true,
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scales: {
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y: {
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beginAtZero: true
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}
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}
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}
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});
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const ctx2 = document.getElementById('endpointsChart').getContext('2d');
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endpointsChart = new Chart(ctx2, {
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type: 'bar',
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data: {
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labels: [],
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datasets: [{
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label: '请求数',
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data: [],
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backgroundColor: 'rgba(33, 150, 243, 0.8)'
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}]
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},
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options: {
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responsive: true,
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scales: {
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y: {
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beginAtZero: true
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}
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}
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}
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});
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}
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// 更新性能数据
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function updatePerformanceData(data) {
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const now = new Date().toLocaleTimeString();
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performanceData.labels.push(now);
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performanceData.cpu.push(data.performance.cpu_usage);
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performanceData.memory.push(data.performance.memory_usage);
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performanceData.requests.push(data.performance.active_requests);
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// 保持最近20个数据点
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if (performanceData.labels.length > 20) {
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performanceData.labels.shift();
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performanceData.cpu.shift();
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performanceData.memory.shift();
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performanceData.requests.shift();
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}
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// 更新图表
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performanceChart.data.labels = performanceData.labels;
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performanceChart.data.datasets[0].data = performanceData.cpu;
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performanceChart.data.datasets[1].data = performanceData.memory;
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performanceChart.data.datasets[2].data = performanceData.requests;
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performanceChart.update();
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// 更新端点图表
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const endpointLabels = data.top_endpoints.map(e => e.endpoint.substring(0, 20));
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const endpointData = data.top_endpoints.map(e => e.count);
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endpointsChart.data.labels = endpointLabels;
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endpointsChart.data.datasets[0].data = endpointData;
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endpointsChart.update();
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}
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// 更新指标显示
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function updateMetrics(data) {
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document.getElementById('cpu-usage').textContent = data.performance.cpu_usage.toFixed(1);
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document.getElementById('memory-usage').textContent = data.performance.memory_usage.toFixed(1);
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document.getElementById('active-requests').textContent = data.performance.active_requests;
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document.getElementById('request-rate').textContent = data.performance.request_rate.toFixed(0);
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document.getElementById('avg-response-time').textContent = data.performance.avg_response_time.toFixed(3);
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document.getElementById('error-rate').textContent = (data.performance.error_rate * 100).toFixed(2);
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}
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// 更新告警
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function updateAlerts(alerts) {
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const alertsDiv = document.getElementById('alerts');
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const alertsList = document.getElementById('alerts-list');
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if (alerts.length > 0) {
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alertsDiv.style.display = 'block';
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alertsList.innerHTML = alerts.map(alert =>
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`<div class="alert-item">⚠️ ${alert}</div>`
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).join('');
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} else {
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alertsDiv.style.display = 'none';
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}
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}
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// 获取URL中的token参数
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function getTokenFromUrl() {
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const urlParams = new URLSearchParams(window.location.search);
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return urlParams.get('token');
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}
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// 刷新数据
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async function refreshData() {
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try {
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const token = getTokenFromUrl();
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if (!token) {
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console.error('未找到token参数');
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return;
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}
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const response = await fetch(`/api/v1/monitoring/overview?token=${token}`);
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if (response.ok) {
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const data = await response.json();
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updateMetrics(data);
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updatePerformanceData(data);
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updateAlerts(data.alerts);
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}
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} catch (error) {
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console.error('获取监控数据失败:', error);
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}
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}
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// 页面加载完成后初始化
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document.addEventListener('DOMContentLoaded', function() {
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initCharts();
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refreshData();
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// 每5秒自动刷新
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setInterval(refreshData, 5000);
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});
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</script>
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</body>
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</html>
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""")
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@@ -360,8 +360,6 @@ class ConfigModel(BaseModel):
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# ==================== 性能配置 ====================
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# 大内存模式
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BIG_MEMORY_MODE: bool = False
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# FastApi性能监控
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PERFORMANCE_MONITOR_ENABLE: bool = False
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# 是否启用编码探测的性能模式
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ENCODING_DETECTION_PERFORMANCE_MODE: bool = True
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# 编码探测的最低置信度阈值
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@@ -21,7 +21,7 @@ from app.core.config import settings
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from app.core.event import eventmanager, Event
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from app.db.plugindata_oper import PluginDataOper
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from app.db.systemconfig_oper import SystemConfigOper
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from app.helper.plugin import PluginHelper, PluginMemoryMonitor
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from app.helper.plugin import PluginHelper
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from app.helper.sites import SitesHelper # noqa
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from app.log import logger
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from app.schemas.types import EventType, SystemConfigKey
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@@ -98,8 +98,6 @@ class PluginManager(metaclass=Singleton):
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self._config_key: str = "plugin.%s"
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# 监听器
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self._observer: Observer = None
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# 内存监控器
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self._memory_monitor = PluginMemoryMonitor()
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# 开发者模式监测插件修改
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if settings.DEV or settings.PLUGIN_AUTO_RELOAD:
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self.__start_monitor()
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@@ -865,28 +863,6 @@ class PluginManager(metaclass=Singleton):
|
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"""
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return list(self._running_plugins.keys())
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def get_plugin_memory_stats(self, pid: Optional[str] = None) -> List[Dict[str, Any]]:
|
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"""
|
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获取插件内存统计信息
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||||
:param pid: 插件ID，为空则获取所有插件
|
||||
:return: 内存统计信息列表
|
||||
"""
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if pid:
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plugin_instance = self._running_plugins.get(pid)
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if plugin_instance:
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return [self._memory_monitor.get_plugin_memory_usage(pid, plugin_instance)]
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else:
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return []
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else:
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return self._memory_monitor.get_all_plugins_memory_usage(self._running_plugins)
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|
||||
def clear_plugin_memory_cache(self, pid: Optional[str] = None):
|
||||
"""
|
||||
清除插件内存统计缓存
|
||||
:param pid: 插件ID，为空则清除所有缓存
|
||||
"""
|
||||
self._memory_monitor.clear_cache(pid)
|
||||
|
||||
def get_online_plugins(self, force: bool = False) -> List[schemas.Plugin]:
|
||||
"""
|
||||
获取所有在线插件信息
|
||||
|
||||
@@ -3,7 +3,6 @@ from fastapi.middleware.cors import CORSMiddleware
|
||||
from fastapi.responses import ORJSONResponse
|
||||
|
||||
from app.core.config import settings
|
||||
from app.monitoring import setup_prometheus_metrics
|
||||
from app.startup.lifecycle import lifespan
|
||||
|
||||
|
||||
@@ -27,9 +26,6 @@ def create_app() -> FastAPI:
|
||||
allow_headers=["*"],
|
||||
)
|
||||
|
||||
# 设置性能监控
|
||||
setup_prometheus_metrics(_app)
|
||||
|
||||
return _app
|
||||
|
||||
|
||||
|
||||
@@ -4,11 +4,10 @@ import json
|
||||
import shutil
|
||||
import site
|
||||
import sys
|
||||
import time
|
||||
import traceback
|
||||
import zipfile
|
||||
from pathlib import Path
|
||||
from typing import Dict, List, Optional, Tuple, Set, Callable, Awaitable, Any
|
||||
from typing import Dict, List, Optional, Tuple, Set, Callable, Awaitable
|
||||
|
||||
import aiofiles
|
||||
import aioshutil
|
||||
@@ -25,7 +24,6 @@ from app.db.systemconfig_oper import SystemConfigOper
|
||||
from app.log import logger
|
||||
from app.schemas.types import SystemConfigKey
|
||||
from app.utils.http import RequestUtils, AsyncRequestUtils
|
||||
from app.utils.memory import MemoryCalculator
|
||||
from app.utils.singleton import WeakSingleton
|
||||
from app.utils.system import SystemUtils
|
||||
from app.utils.url import UrlUtils
|
||||
@@ -1593,87 +1591,3 @@ class PluginHelper(metaclass=WeakSingleton):
|
||||
except Exception as e:
|
||||
logger.error(f"解压 Release 压缩包失败：{e}")
|
||||
return False, f"解压 Release 压缩包失败：{e}"
|
||||
|
||||
|
||||
class PluginMemoryMonitor:
|
||||
"""
|
||||
插件内存监控器
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
self._calculator = MemoryCalculator()
|
||||
self._cache = {}
|
||||
self._cache_ttl = 300 # 缓存5分钟
|
||||
|
||||
def get_plugin_memory_usage(self, plugin_id: str, plugin_instance: Any) -> Dict[str, Any]:
|
||||
"""
|
||||
获取插件内存使用情况
|
||||
:param plugin_id: 插件ID
|
||||
:param plugin_instance: 插件实例
|
||||
:return: 内存使用信息
|
||||
"""
|
||||
# 检查缓存
|
||||
if self._is_cache_valid(plugin_id):
|
||||
return self._cache[plugin_id]
|
||||
|
||||
# 计算内存使用
|
||||
memory_info = self._calculator.calculate_object_memory(plugin_instance)
|
||||
|
||||
# 添加插件信息
|
||||
result = {
|
||||
'plugin_id': plugin_id,
|
||||
'plugin_name': getattr(plugin_instance, 'plugin_name', 'Unknown'),
|
||||
'plugin_version': getattr(plugin_instance, 'plugin_version', 'Unknown'),
|
||||
'timestamp': time.time(),
|
||||
**memory_info
|
||||
}
|
||||
|
||||
# 更新缓存
|
||||
self._cache[plugin_id] = result
|
||||
return result
|
||||
|
||||
def get_all_plugins_memory_usage(self, plugins: Dict[str, Any]) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
获取所有插件的内存使用情况
|
||||
:param plugins: 插件实例字典
|
||||
:return: 内存使用信息列表
|
||||
"""
|
||||
results = []
|
||||
for plugin_id, plugin_instance in plugins.items():
|
||||
if plugin_instance:
|
||||
try:
|
||||
memory_info = self.get_plugin_memory_usage(plugin_id, plugin_instance)
|
||||
results.append(memory_info)
|
||||
except Exception as e:
|
||||
logger.error(f"获取插件 {plugin_id} 内存使用情况失败：{str(e)}")
|
||||
results.append({
|
||||
'plugin_id': plugin_id,
|
||||
'plugin_name': getattr(plugin_instance, 'plugin_name', 'Unknown'),
|
||||
'error': str(e),
|
||||
'total_memory_bytes': 0,
|
||||
'total_memory_mb': 0,
|
||||
'object_count': 0,
|
||||
'calculation_time_ms': 0
|
||||
})
|
||||
|
||||
# 按内存使用量排序
|
||||
results.sort(key=lambda x: x.get('total_memory_bytes', 0), reverse=True)
|
||||
return results
|
||||
|
||||
def _is_cache_valid(self, plugin_id: str) -> bool:
|
||||
"""
|
||||
检查缓存是否有效
|
||||
"""
|
||||
if plugin_id not in self._cache:
|
||||
return False
|
||||
return time.time() - self._cache[plugin_id]['timestamp'] < self._cache_ttl
|
||||
|
||||
def clear_cache(self, plugin_id: Optional[str] = None):
|
||||
"""
|
||||
清除缓存
|
||||
:param plugin_id: 插件ID，为空则清除所有缓存
|
||||
"""
|
||||
if plugin_id:
|
||||
self._cache.pop(plugin_id, None)
|
||||
else:
|
||||
self._cache.clear()
|
||||
|
||||
@@ -1,338 +0,0 @@
|
||||
import threading
|
||||
import time
|
||||
from collections import defaultdict, deque
|
||||
from dataclasses import dataclass
|
||||
from datetime import datetime, timedelta
|
||||
from typing import Dict, List, Any
|
||||
|
||||
import psutil
|
||||
from fastapi import Request, Response
|
||||
from fastapi.responses import PlainTextResponse
|
||||
from prometheus_client import Counter, Histogram, Gauge, generate_latest, CONTENT_TYPE_LATEST
|
||||
from prometheus_fastapi_instrumentator import Instrumentator
|
||||
|
||||
from app.core.config import settings
|
||||
from app.log import logger
|
||||
|
||||
|
||||
@dataclass
|
||||
class RequestMetrics:
|
||||
"""
|
||||
请求指标数据类
|
||||
"""
|
||||
path: str
|
||||
method: str
|
||||
status_code: int
|
||||
response_time: float
|
||||
timestamp: datetime
|
||||
client_ip: str
|
||||
user_agent: str
|
||||
|
||||
|
||||
@dataclass
|
||||
class PerformanceSnapshot:
|
||||
"""
|
||||
性能快照数据类
|
||||
"""
|
||||
timestamp: datetime
|
||||
cpu_usage: float
|
||||
memory_usage: float
|
||||
active_requests: int
|
||||
request_rate: float
|
||||
avg_response_time: float
|
||||
error_rate: float
|
||||
slow_requests: int
|
||||
|
||||
|
||||
class FastAPIMonitor:
|
||||
"""
|
||||
FastAPI性能监控器
|
||||
"""
|
||||
|
||||
def __init__(self, max_history: int = 1000, window_size: int = 60):
|
||||
self.max_history = max_history
|
||||
self.window_size = window_size # 秒
|
||||
|
||||
# 请求历史记录
|
||||
self.request_history: deque = deque(maxlen=max_history)
|
||||
|
||||
# 实时统计
|
||||
self.active_requests = 0
|
||||
self.total_requests = 0
|
||||
self.error_requests = 0
|
||||
self.slow_requests = 0 # 响应时间超过1秒的请求
|
||||
|
||||
# 时间窗口统计
|
||||
self.window_requests: deque = deque(maxlen=window_size)
|
||||
self.window_response_times: deque = deque(maxlen=window_size)
|
||||
|
||||
# 线程锁
|
||||
self._lock = threading.Lock()
|
||||
|
||||
# 性能阈值
|
||||
self.slow_request_threshold = 1.0 # 1秒
|
||||
self.error_threshold = 0.05 # 5%
|
||||
self.cpu_threshold = 80.0 # 80%
|
||||
self.memory_threshold = 80.0 # 80%
|
||||
|
||||
# 告警状态
|
||||
self.alerts: List[str] = []
|
||||
|
||||
logger.debug("FastAPI性能监控器已初始化")
|
||||
|
||||
def record_request(self, request: Request, response: Response, response_time: float):
|
||||
"""
|
||||
记录请求指标
|
||||
"""
|
||||
with self._lock:
|
||||
# 创建请求指标
|
||||
metrics = RequestMetrics(
|
||||
path=str(request.url.path),
|
||||
method=request.method,
|
||||
status_code=response.status_code,
|
||||
response_time=response_time,
|
||||
timestamp=datetime.now(),
|
||||
client_ip=request.client.host if request.client else "unknown",
|
||||
user_agent=request.headers.get("user-agent", "unknown")
|
||||
)
|
||||
|
||||
# 添加到历史记录
|
||||
self.request_history.append(metrics)
|
||||
|
||||
# 更新统计
|
||||
self.total_requests += 1
|
||||
if response.status_code >= 400:
|
||||
self.error_requests += 1
|
||||
if response_time > self.slow_request_threshold:
|
||||
self.slow_requests += 1
|
||||
|
||||
# 添加到时间窗口
|
||||
self.window_requests.append(metrics)
|
||||
self.window_response_times.append(response_time)
|
||||
|
||||
def start_request(self):
|
||||
"""
|
||||
开始处理请求
|
||||
"""
|
||||
with self._lock:
|
||||
self.active_requests += 1
|
||||
|
||||
def end_request(self):
|
||||
"""
|
||||
结束处理请求
|
||||
"""
|
||||
with self._lock:
|
||||
self.active_requests = max(0, self.active_requests - 1)
|
||||
|
||||
def get_performance_snapshot(self) -> PerformanceSnapshot:
|
||||
"""
|
||||
获取性能快照
|
||||
"""
|
||||
with self._lock:
|
||||
now = datetime.now()
|
||||
|
||||
# 计算请求率（每分钟）
|
||||
recent_requests = [
|
||||
req for req in self.window_requests
|
||||
if now - req.timestamp < timedelta(seconds=self.window_size)
|
||||
]
|
||||
request_rate = len(recent_requests) / (self.window_size / 60)
|
||||
|
||||
# 计算平均响应时间
|
||||
recent_response_times = [
|
||||
rt for rt in self.window_response_times
|
||||
if len(self.window_response_times) > 0
|
||||
]
|
||||
avg_response_time = sum(recent_response_times) / len(recent_response_times) if recent_response_times else 0
|
||||
|
||||
# 计算错误率
|
||||
error_rate = self.error_requests / self.total_requests if self.total_requests > 0 else 0
|
||||
|
||||
# 系统资源使用率
|
||||
cpu_usage = psutil.cpu_percent(interval=0.1)
|
||||
memory_usage = psutil.virtual_memory().percent
|
||||
|
||||
return PerformanceSnapshot(
|
||||
timestamp=now,
|
||||
cpu_usage=cpu_usage,
|
||||
memory_usage=memory_usage,
|
||||
active_requests=self.active_requests,
|
||||
request_rate=request_rate,
|
||||
avg_response_time=avg_response_time,
|
||||
error_rate=error_rate,
|
||||
slow_requests=self.slow_requests
|
||||
)
|
||||
|
||||
def get_top_endpoints(self, limit: int = 10) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
获取最活跃的端点
|
||||
"""
|
||||
with self._lock:
|
||||
endpoint_stats = defaultdict(lambda: {
|
||||
'count': 0,
|
||||
'total_time': 0,
|
||||
'errors': 0,
|
||||
'avg_time': 0.0
|
||||
})
|
||||
|
||||
for req in self.request_history:
|
||||
key = f"{req.method} {req.path}"
|
||||
endpoint_stats[key]['count'] += 1
|
||||
endpoint_stats[key]['total_time'] += req.response_time
|
||||
if req.status_code >= 400:
|
||||
endpoint_stats[key]['errors'] += 1
|
||||
|
||||
# 计算平均时间
|
||||
for stats in endpoint_stats.values():
|
||||
if stats['count'] > 0:
|
||||
stats['avg_time'] = stats['total_time'] / stats['count']
|
||||
|
||||
# 按请求数量排序
|
||||
sorted_endpoints = sorted(
|
||||
[{'endpoint': k, **v} for k, v in endpoint_stats.items()],
|
||||
key=lambda x: x['count'],
|
||||
reverse=True
|
||||
)
|
||||
|
||||
return sorted_endpoints[:limit]
|
||||
|
||||
def get_recent_errors(self, limit: int = 20) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
获取最近的错误请求
|
||||
"""
|
||||
with self._lock:
|
||||
errors = [
|
||||
{
|
||||
'timestamp': req.timestamp.isoformat(),
|
||||
'method': req.method,
|
||||
'path': req.path,
|
||||
'status_code': req.status_code,
|
||||
'response_time': req.response_time,
|
||||
'client_ip': req.client_ip
|
||||
}
|
||||
for req in self.request_history
|
||||
if req.status_code >= 400
|
||||
]
|
||||
return errors[-limit:]
|
||||
|
||||
def check_alerts(self) -> List[str]:
|
||||
"""
|
||||
检查告警条件
|
||||
"""
|
||||
snapshot = self.get_performance_snapshot()
|
||||
alerts = []
|
||||
|
||||
if snapshot.error_rate > self.error_threshold:
|
||||
alerts.append(f"错误率过高: {snapshot.error_rate:.2%}")
|
||||
|
||||
if snapshot.cpu_usage > self.cpu_threshold:
|
||||
alerts.append(f"CPU使用率过高: {snapshot.cpu_usage:.1f}%")
|
||||
|
||||
if snapshot.memory_usage > self.memory_threshold:
|
||||
alerts.append(f"内存使用率过高: {snapshot.memory_usage:.1f}%")
|
||||
|
||||
if snapshot.avg_response_time > self.slow_request_threshold:
|
||||
alerts.append(f"平均响应时间过长: {snapshot.avg_response_time:.2f}s")
|
||||
|
||||
if snapshot.request_rate > 1000: # 每分钟1000请求
|
||||
alerts.append(f"请求率过高: {snapshot.request_rate:.0f} req/min")
|
||||
|
||||
self.alerts = alerts
|
||||
return alerts
|
||||
|
||||
|
||||
# 全局监控实例
|
||||
monitor = FastAPIMonitor()
|
||||
|
||||
|
||||
def setup_prometheus_metrics(app):
|
||||
"""
|
||||
设置Prometheus指标
|
||||
"""
|
||||
|
||||
if not settings.PERFORMANCE_MONITOR_ENABLE:
|
||||
return
|
||||
|
||||
# 创建Prometheus指标
|
||||
request_counter = Counter(
|
||||
"http_requests_total",
|
||||
"Total number of HTTP requests",
|
||||
["method", "endpoint", "status"]
|
||||
)
|
||||
|
||||
request_duration = Histogram(
|
||||
"http_request_duration_seconds",
|
||||
"HTTP request duration in seconds",
|
||||
["method", "endpoint"]
|
||||
)
|
||||
|
||||
active_requests = Gauge(
|
||||
"http_active_requests",
|
||||
"Number of active HTTP requests"
|
||||
)
|
||||
|
||||
# 自定义指标收集函数
|
||||
def custom_metrics(request: Request, response: Response, response_time: float):
|
||||
request_counter.labels(
|
||||
method=request.method,
|
||||
endpoint=request.url.path,
|
||||
status=response.status_code
|
||||
).inc()
|
||||
|
||||
request_duration.labels(
|
||||
method=request.method,
|
||||
endpoint=request.url.path
|
||||
).observe(response_time)
|
||||
|
||||
active_requests.set(monitor.active_requests)
|
||||
|
||||
# 设置Prometheus监控
|
||||
Instrumentator().instrument(app).expose(app, include_in_schema=False, should_gzip=True)
|
||||
|
||||
# 添加自定义指标
|
||||
@app.middleware("http")
|
||||
async def monitor_middleware(request: Request, call_next):
|
||||
start_time = time.time()
|
||||
|
||||
# 开始请求
|
||||
monitor.start_request()
|
||||
|
||||
try:
|
||||
response = await call_next(request)
|
||||
response_time = time.time() - start_time
|
||||
|
||||
# 记录请求指标
|
||||
monitor.record_request(request, response, response_time)
|
||||
|
||||
# 更新Prometheus指标
|
||||
custom_metrics(request, response, response_time)
|
||||
|
||||
return response
|
||||
except Exception as e:
|
||||
response_time = time.time() - start_time
|
||||
logger.error(f"请求处理异常: {e}")
|
||||
|
||||
# 创建错误响应
|
||||
response = Response(
|
||||
content=str(e),
|
||||
status_code=500,
|
||||
media_type="text/plain"
|
||||
)
|
||||
|
||||
# 记录错误请求
|
||||
monitor.record_request(request, response, response_time)
|
||||
|
||||
return response
|
||||
finally:
|
||||
# 结束请求
|
||||
monitor.end_request()
|
||||
|
||||
|
||||
def get_metrics_response():
|
||||
"""
|
||||
获取Prometheus指标响应
|
||||
"""
|
||||
return PlainTextResponse(
|
||||
generate_latest(),
|
||||
media_type=CONTENT_TYPE_LATEST
|
||||
)
|
||||
@@ -1,178 +0,0 @@
|
||||
import sys
|
||||
import time
|
||||
from collections import deque
|
||||
from typing import Any, Dict, Set
|
||||
|
||||
from app.log import logger
|
||||
|
||||
|
||||
class MemoryCalculator:
|
||||
"""
|
||||
内存计算器，用于递归计算对象的内存占用
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
# 缓存已计算的对象ID，避免重复计算
|
||||
self._calculated_ids: Set[int] = set()
|
||||
# 最大递归深度，防止无限递归
|
||||
self._max_depth = 10
|
||||
# 最大对象数量，防止计算过多对象
|
||||
self._max_objects = 10000
|
||||
|
||||
def calculate_object_memory(self, obj: Any, max_depth: int = None, max_objects: int = None) -> Dict[str, Any]:
|
||||
"""
|
||||
计算对象的内存占用
|
||||
:param obj: 要计算的对象
|
||||
:param max_depth: 最大递归深度
|
||||
:param max_objects: 最大对象数量
|
||||
:return: 内存统计信息
|
||||
"""
|
||||
if max_depth is None:
|
||||
max_depth = self._max_depth
|
||||
if max_objects is None:
|
||||
max_objects = self._max_objects
|
||||
|
||||
# 重置缓存
|
||||
self._calculated_ids.clear()
|
||||
|
||||
start_time = time.time()
|
||||
object_details = []
|
||||
|
||||
try:
|
||||
# 递归计算内存
|
||||
memory_info = self._calculate_recursive(obj, depth=0, max_depth=max_depth,
|
||||
max_objects=max_objects, object_count=0)
|
||||
total_memory = memory_info['total_memory']
|
||||
object_count = memory_info['object_count']
|
||||
object_details = memory_info['object_details']
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"计算对象内存时出错：{str(e)}")
|
||||
total_memory = 0
|
||||
object_count = 0
|
||||
|
||||
calculation_time = time.time() - start_time
|
||||
|
||||
return {
|
||||
'total_memory_bytes': total_memory,
|
||||
'total_memory_mb': round(total_memory / (1024 * 1024), 2),
|
||||
'object_count': object_count,
|
||||
'calculation_time_ms': round(calculation_time * 1000, 2),
|
||||
'object_details': object_details[:10] # 只返回前10个最大的对象
|
||||
}
|
||||
|
||||
def _calculate_recursive(self, obj: Any, depth: int, max_depth: int,
|
||||
max_objects: int, object_count: int) -> Dict[str, Any]:
|
||||
"""
|
||||
递归计算对象内存
|
||||
"""
|
||||
if depth > max_depth or object_count > max_objects:
|
||||
return {
|
||||
'total_memory': 0,
|
||||
'object_count': object_count,
|
||||
'object_details': []
|
||||
}
|
||||
|
||||
total_memory = 0
|
||||
object_details = []
|
||||
|
||||
# 获取对象ID，避免重复计算
|
||||
obj_id = id(obj)
|
||||
if obj_id in self._calculated_ids:
|
||||
return {
|
||||
'total_memory': 0,
|
||||
'object_count': object_count,
|
||||
'object_details': []
|
||||
}
|
||||
|
||||
self._calculated_ids.add(obj_id)
|
||||
object_count += 1
|
||||
|
||||
try:
|
||||
# 计算对象本身的内存
|
||||
obj_memory = sys.getsizeof(obj)
|
||||
total_memory += obj_memory
|
||||
|
||||
# 记录大对象
|
||||
if obj_memory > 1024: # 大于1KB的对象
|
||||
object_details.append({
|
||||
'type': type(obj).__name__,
|
||||
'memory_bytes': obj_memory,
|
||||
'memory_mb': round(obj_memory / (1024 * 1024), 2),
|
||||
'depth': depth
|
||||
})
|
||||
|
||||
# 递归计算容器对象的内容
|
||||
if depth < max_depth:
|
||||
container_memory = self._calculate_container_memory(
|
||||
obj, depth + 1, max_depth, max_objects, object_count
|
||||
)
|
||||
total_memory += container_memory['total_memory']
|
||||
object_count = container_memory['object_count']
|
||||
object_details.extend(container_memory['object_details'])
|
||||
|
||||
except Exception as e:
|
||||
logger.debug(f"计算对象 {type(obj).__name__} 内存时出错：{str(e)}")
|
||||
|
||||
return {
|
||||
'total_memory': total_memory,
|
||||
'object_count': object_count,
|
||||
'object_details': object_details
|
||||
}
|
||||
|
||||
def _calculate_container_memory(self, obj: Any, depth: int, max_depth: int,
|
||||
max_objects: int, object_count: int) -> Dict[str, Any]:
|
||||
"""
|
||||
计算容器对象的内存
|
||||
"""
|
||||
total_memory = 0
|
||||
object_details = []
|
||||
|
||||
try:
|
||||
# 处理不同类型的容器
|
||||
if isinstance(obj, (list, tuple, deque)):
|
||||
for item in obj:
|
||||
if object_count > max_objects:
|
||||
break
|
||||
item_memory = self._calculate_recursive(item, depth, max_depth, max_objects, object_count)
|
||||
total_memory += item_memory['total_memory']
|
||||
object_count = item_memory['object_count']
|
||||
object_details.extend(item_memory['object_details'])
|
||||
|
||||
elif isinstance(obj, dict):
|
||||
for key, value in obj.items():
|
||||
if object_count > max_objects:
|
||||
break
|
||||
# 计算key的内存
|
||||
key_memory = self._calculate_recursive(key, depth, max_depth, max_objects, object_count)
|
||||
total_memory += key_memory['total_memory']
|
||||
object_count = key_memory['object_count']
|
||||
object_details.extend(key_memory['object_details'])
|
||||
|
||||
# 计算value的内存
|
||||
value_memory = self._calculate_recursive(value, depth, max_depth, max_objects, object_count)
|
||||
total_memory += value_memory['total_memory']
|
||||
object_count = value_memory['object_count']
|
||||
object_details.extend(value_memory['object_details'])
|
||||
|
||||
elif hasattr(obj, '__dict__'):
|
||||
# 处理有__dict__属性的对象
|
||||
for attr_name, attr_value in obj.__dict__.items():
|
||||
if object_count > max_objects:
|
||||
break
|
||||
# 跳过一些特殊属性
|
||||
if attr_name.startswith('_') and attr_name not in ['_calculated_ids']:
|
||||
continue
|
||||
attr_memory = self._calculate_recursive(attr_value, depth, max_depth, max_objects, object_count)
|
||||
total_memory += attr_memory['total_memory']
|
||||
object_count = attr_memory['object_count']
|
||||
object_details.extend(attr_memory['object_details'])
|
||||
|
||||
except Exception as e:
|
||||
logger.debug(f"计算容器对象 {type(obj).__name__} 内存时出错：{str(e)}")
|
||||
|
||||
return {
|
||||
'total_memory': total_memory,
|
||||
'object_count': object_count,
|
||||
'object_details': object_details
|
||||
}
|
||||
@@ -77,6 +77,4 @@ pympler~=1.1
|
||||
smbprotocol~=1.15.0
|
||||
setproctitle~=1.3.6
|
||||
httpx[socks]~=0.28.1
|
||||
prometheus-client~=0.22.1
|
||||
prometheus-fastapi-instrumentator~=7.1.0
|
||||
orjson~=3.11.3
|
||||
Reference in New Issue
Block a user