How Scrapy improves crawling stability and crawling efficiency

Scrapy is a powerful web crawler framework written in Python, which can help users quickly and efficiently crawl the required information from the Internet. However, in the process of using Scrapy to crawl, you often encounter some problems, such as crawling failure, incomplete data or slow crawling speed. These problems will affect the efficiency and stability of the crawler. Therefore, this article will explore how Scrapy improves crawling stability and crawling efficiency.

1. Set request headers and User-Agent

When crawling the web, if we do not provide any information, the website server may regard our request as unsafe or act maliciously and refuse to provide data. At this time, we can set the request header and User-Agent through the Scrapy framework to simulate a normal user request, thereby improving the stability of crawling.

You can set the request headers by defining the DEFAULT_REQUEST_HEADERS attribute in the settings.py file:

DEFAULT_REQUEST_HEADERS = {
    'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
    'Accept-Language': 'en',
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36 Edge/16.16299'
}

Two attributes, Accept-Language and User-Agent, are set here to simulate common request headers. information. Among them, the User-Agent field is the most important because it allows the server to know the browser and operating system information we are using. Different browsers and operating systems will have different User-Agent information, so we need to set it according to the actual situation.

2. Adjust the number of concurrency and delay time

In the Scrapy framework, we can adjust the number of concurrency and delay time of the crawler by setting the DOWNLOAD_DELAY and CONCURRENT_REQUESTS_PER_DOMAIN properties to achieve the best results. Excellent crawling efficiency.

DOWNLOAD_DELAY attribute is mainly used to control the interval between requests to avoid excessive burden on the server. It can also prevent websites from blocking our IP address. Generally speaking, the setting of DOWNLOAD_DELAY should be a reasonable time value to ensure that it does not put excessive pressure on the server and also ensures the integrity of the data.

CONCURRENT_REQUESTS_PER_DOMAIN attribute is used to control the number of requests made to the same domain name at the same time. The higher the value, the faster the crawling speed, but the greater the pressure on the server. Therefore, we need to adjust this value according to the actual situation to achieve the optimal crawling effect.

3. Use proxy IP

When crawling websites, some websites may restrict access from the same IP address, such as setting a verification code or directly banning the IP. address. At this time, we can use proxy IP to solve this problem.

The method to use the proxy IP is to set the DOWNLOADER_MIDDLEWARES attribute in the Scrapy framework, and then write a custom middleware to obtain an available proxy IP from the proxy pool before sending the request, and then send the request to the target website. In this way, you can effectively circumvent the website's IP blocking policy and improve the stability and efficiency of crawling.

4. Dealing with anti-crawler strategies

Many websites today will have anti-crawler strategies, such as setting verification codes, limiting access frequency, etc. These strategies cause a lot of trouble for our crawlers, so we need to take some effective measures to circumvent these strategies.

One solution is to use a random User-Agent and proxy IP to crawl so that the website cannot determine our true identity. Another method is to use automated tools for verification code recognition, such as Tesseract, Pillow and other libraries, to automatically analyze the verification code and enter the correct answer.

5. Use distributed crawling

When crawling large-scale websites, stand-alone crawlers often have some bottlenecks, such as performance bottlenecks, IP bans, etc. At this time, we can use distributed crawling technology to disperse the data to different crawler nodes for processing, thereby improving the efficiency and stability of crawling.

Scrapy also provides some distributed crawling plug-ins, such as Scrapy-Redis, Scrapy-Crawlera, etc., which can help users quickly build a reliable distributed crawler platform.

Summary

Through the above five methods, we can effectively improve the stability and crawling efficiency of Scrapy website crawling. Of course, these are just some basic strategies, and different sites and situations may require different approaches. Therefore, in practical applications, we need to choose the most appropriate measures according to the specific situation to make the crawler work more efficient and stable.

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