Is network python crawler difficult?

The arrival of the era of big data and artificial intelligence makes data more and more important to us. How to obtain valuable data information from the Internet is particularly important! The data on the Internet is growing explosively, and using Python crawlers we can obtain a large amount of valuable data:

1. Crawl data and conduct market research and business analysis

Crawling Zhihu’s high-quality answers and screening the best content under each topic; Crawling real estate website buying and selling information, analyzing housing price trends, and conducting housing price analysis in different regions; Crawling job information on recruitment websites, analyzing talent demand in various industries and Salary level.

2. As raw data for machine learning and data mining

For example, if you want to make a recommendation system, then you can crawl more dimensions of data and do Come up with better models.

3. Crawl high-quality resources: pictures, texts, videos

Crawl product (store) reviews and various picture websites to obtain picture resources and comment texts data.

It is actually very easy to master the correct method and be able to crawl data from mainstream websites in a short time.

But it is recommended that you have a specific goal from the beginning. Driven by the goal, your learning will be more accurate and efficient. Here is a smooth learning path for you to get started quickly with zero foundation:

1. Understand the basic principles and processes of crawlers

2.Requests Xpath implements general crawler routines

3. Understand the storage of unstructured data

4. Anti-crawler measures for special websites

5.Scrapy and MongoDB, advanced distribution Formula

Understand the basic principles and processes of crawlers

Most crawlers follow the steps of "Send a request - Obtain the page - Parse the page - Extract and store content" Carrying out such a process actually simulates the process of using a browser to obtain web page information.

Simply put, after we send a request to the server, we will get the returned page. After parsing the page, we can extract the part of the information we want and store it in the specified document or database.

In this part you can simply understand the basic knowledge of the HTTP protocol and web pages, such as POST\GET, HTML, CSS, and JS. A simple understanding is enough, and no systematic learning is required.

Learn Python packages and implement basic crawler processes

There are many crawler-related packages in Python: urllib, requests, bs4, scrapy, pyspider, etc. It is recommended that you start from requests Starting with Xpath, requests are responsible for connecting to the website and returning web pages. Xpath is used to parse web pages to facilitate data extraction.

If you have used BeautifulSoup, you will find that Xpath saves a lot of trouble, and the work of checking element codes layer by layer is omitted. After mastering it, you will find that the basic routines of crawlers are similar. General static websites are not a problem at all. You can basically get started with Xiaozhu, Douban, Embarrassing Encyclopedia, Tencent News, etc.

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