A web crawler, also known as a web spider, is actually an automated web robot that takes the place of a human to access information on the Web. The business and strategy of many enterprises need a lot of multidimensional data analysis, which makes crawler more and more popular.
Reptiles are a simple thing to say. But often simple things to achieve the best need to overcome a lot of difficulties. To do a good job of reptiles need to pay attention to a few points, let's take a look at ~.
1. Website management and scheduling.
If there are many addresses to access, a URL manager is set up to mark all urls that need to be processed. If the logic is not complex, data structures such as arrays can be used, and if the logic is more complex, databases can be used for storage. One advantage of the database is that when a program hangs unexpectedly, execution can continue based on the ID number it is working on, rather than having to start over and crawl back to a previously processed URL.
2. Data analysis: Data analysis refers to the extraction of the required data from the content returned by the server.
The initial approach was to use "regular expressions," a common technique that Python's BeautifulSoup and Requests-HTML are great for extracting content from tags.
3. Dealing with anti-crawler strategies.
There are many kinds of strategies for the server to contain crawlers. Every HTTP request has a large number of parameters, and the server can judge whether the request is a malicious crawler according to the parameters. For example, if the Cookie value is incorrect, the server needs values other than Referer and user-agent. At this point, we can check the browser to see what values the server accepts, and then modify the various parameters of the request header in the code to disguise normal access.
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