Python crawler thinking: exception handling and logging

As a professional crawler agent supplier, we often see various crawler anomalies. Problems such as network request timeouts, page structure changes, and anti-crawler mechanism interception often appear in the work of customers.
In this article, I will share with you some ways of thinking about exception handling and logging. Through reasonable exception handling and effective logging, we can better troubleshoot problems, reduce the probability of errors, and improve the efficiency and robustness of crawler development.

1. exception handling

In Python crawlers, exception handling is very critical. By handling exceptions, we can take corresponding measures when the program goes wrong to avoid program crashes. Here are some common exception handling techniques:

1.1 try-except statement: Use the try-except statement to catch and handle specific exceptions to prevent the program from being interrupted due to exceptions. By adding exception types in the except block, we can handle different types of exceptions in a targeted manner.

import requests

try:
    response = requests.get('http://www.example.com')
    # 对响应进行处理...
except requests.exceptions.RequestException as e:
    print('请求出错：', str(e))

1.2 finally statement: Sometimes we want to perform some specific cleanup operations, such as closing files or database connections, regardless of whether an exception occurs. At this time, you can use the finally statement block to achieve.

file = open('data.txt', 'w')
try:
    # 对文件进行操作...
except Exception as e:
    print('发生异常：', str(e))
finally:
    file.close()

2. logging

Logging is a non-negligible part of crawler development. Effective logging can help us track the running status of the program, locate problems, and analyze the cause of exceptions. Here are some suggestions for logging:

Using the logging module: The logging module in Python provides rich logging capabilities. We can set the logging level, output format and output location. Through reasonable configuration, we can record exception information, warning information and debugging information.

import logging

logging.basicConfig(level=logging.ERROR, filename='crawler.log', format='%(asctime)s - %(levelname)s - %(message)s')

try:
    # 爬虫操作...
except Exception as e:
    logging.exception('爬取过程中发生异常：')

.Differentiate log levels: Divide according to the level of the log, which can better manage the log information. Common log levels include DEBUG, INFO, WARNING, ERROR, and CRITICAL. We can choose the appropriate level according to the current development stage and program needs.

I hope the above thinking method will help you in exception handling and logging in Python crawler development. Reasonable handling of exceptions and effective logging will help us better troubleshoot problems and improve the robustness of crawlers.
If you have any questions or want to share your own experience, please leave a message in the comment area. Let's explore together how to meet challenges in the journey of crawling data, and maintain a good attitude and professional technology!