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Python爬虫监控程序设计思路

news 2025/8/13 23:16:40

最近因为爬虫程序太多，想要为Python爬虫设计一个监控程序，主要功能包括一下几种：

1、监控爬虫的运行状态（是否在运行、运行时间等）

2、监控爬虫的性能（如请求频率、响应时间、错误率等）

3、资源使用情况（CPU、内存、网络等）

4、异常捕获与告警（当爬虫出现异常时能够及时通知）

在这里插入图片描述

要为Python爬虫创建一个监控程序，根据上面思路我们可以按照以下步骤实现，涵盖运行状态、性能指标、异常告警和可视化：

核心监控功能设计

运行状态监控
- 心跳检测：定期记录爬虫存活状态
- 进程检查：验证爬虫进程是否运行中
性能指标监控
- 请求统计：成功/失败请求计数
- 数据处理：已抓取/解析的项目数
- 资源使用：CPU/内存占用
- 时效指标：请求响应时间、运行时长
异常告警
- 错误捕获：网络异常、解析失败等
- 阈值告警：连续失败/资源超限
- 通知渠道：邮件/Slack/钉钉
数据持久化
- 存储日志：运行日志和错误日志
- 记录指标：时间序列数据库存储

实现方案代码示例

1. 基础监控类 (monitor.py)

import time
import logging
import psutil
from prometheus_client import start_http_server, Counter, Gauge, Histogramclass SpiderMonitor:def __init__(self, spider_name):self.spider_name = spider_nameself.start_time = time.time()# 初始化监控指标self.requests_total = Counter(f'{spider_name}_requests_total', 'Total requests')self.requests_failed = Counter(f'{spider_name}_requests_failed', 'Failed requests')self.items_scraped = Counter(f'{spider_name}_items_scraped', 'Items scraped')self.memory_usage = Gauge(f'{spider_name}_memory_usage', 'Memory usage (MB)')self.request_latency = Histogram(f'{spider_name}_request_latency', 'Request latency (seconds)')# 启动指标服务器start_http_server(8000)logging.basicConfig(filename=f'{spider_name}.log', level=logging.INFO)def record_request(self, success=True, latency=0):self.requests_total.inc()if not success:self.requests_failed.inc()if latency > 0:self.request_latency.observe(latency)def record_item(self, count=1):self.items_scraped.inc(count)def update_resources(self):process = psutil.Process()self.memory_usage.set(process.memory_info().rss / 1024 / 1024)  # MBdef log_error(self, error):logging.error(f"[{time.ctime()}] ERROR: {error}")def uptime(self):return time.time() - self.start_time

2. 爬虫集成示例 (my_spider.py)

import requests
from monitor import SpiderMonitorclass MySpider:def __init__(self):self.monitor = SpiderMonitor("my_spider")self.session = requests.Session()def crawl(self, url):start = time.time()try:response = self.session.get(url, timeout=10)response.raise_for_status()# 处理数据items = self.parse(response)self.monitor.record_item(len(items))self.monitor.record_request(success=True, latency=time.time()-start)return itemsexcept Exception as e:self.monitor.record_request(success=False)self.monitor.log_error(f"URL: {url} - Error: {str(e)}")return []def parse(self, response):# 解析逻辑return [{"data": "sample"}]def run(self):while True:self.crawl("https://example.com/data")self.monitor.update_resources()time.sleep(5)if __name__ == "__main__":spider = MySpider()spider.run()

3. 独立监控进程 (monitor_daemon.py)

import time
import subprocess
import smtplib
from email.mime.text import MIMETextdef check_heartbeat(spider_name):"""检查最近15分钟是否有活动日志"""try:with open(f"{spider_name}.log") as f:logs = f.readlines()[-100:]return any(time.time() - get_log_time(line) < 900 for line in logs)except FileNotFoundError:return Falsedef get_log_time(log_line):# 从日志行提取时间戳timestamp_str = log_line.split("]")[0][1:]return time.mktime(time.strptime(timestamp_str))def send_alert(subject, message):"""发送邮件告警"""msg = MIMEText(message)msg['Subject'] = f"[SPIDER ALERT] {subject}"msg['From'] = 'monitor@example.com'msg['To'] = 'admin@example.com'with smtplib.SMTP('smtp.example.com') as server:server.send_message(msg)def monitor_daemon():spider_name = "my_spider"consecutive_failures = 0while True:if not check_heartbeat(spider_name):consecutive_failures += 1if consecutive_failures >= 3:send_alert("Spider Down", f"{spider_name} has been inactive for 45+ minutes")else:consecutive_failures = 0time.sleep(300)  # 每5分钟检查一次if __name__ == "__main__":monitor_daemon()

监控系统部署方案

指标可视化
- 使用Prometheus收集指标（默认端口8000）
- 配置Grafana仪表盘展示：
  - 请求成功率 = (1 - requests_failed/requests_total) * 100
  - 内存使用趋势图
  - 最近1小时错误日志

告警配置

# Prometheus alert.rules
groups:
- name: spider_alertsrules:- alert: HighFailureRateexpr: rate(my_spider_requests_failed[5m]) / rate(my_spider_requests_total[5m]) > 0.1for: 10mlabels:severity: criticalannotations:description: "超过10%的请求失败"

进程管理

使用Supervisor管理进程：

[program:my_spider]
command=python /path/to/my_spider.py
autostart=true
autorestart=true
stderr_logfile=/var/log/spider.err.log

高级功能扩展

分布式监控

使用Redis共享监控数据：

import redis
r = redis.Redis()
r.incr('global_requests_count')

网页状态面板

# 添加Flask状态页
from flask import Flask
app = Flask(__name__   
@app.route('/status')
def status():return {"uptime": monitor.uptime(),"items": monitor.items_scraped._value.get()}