Practical crawler combat in Python: Toutiao crawler

Crawler practice in Python: Today's Toutiao crawler

In today's information age, the Internet contains massive amounts of data, and the demand for using this data for analysis and application is getting higher and higher. As one of the technical means to achieve data acquisition, crawlers have also become one of the popular areas of research. This article will mainly introduce the actual crawler in Python, and focus on how to use Python to write a crawler program for Toutiao.

1. Basic concepts of crawlers

Before we start to introduce the actual practice of crawlers in Python, we need to first understand the basic concepts of crawlers.

To put it simply, a crawler simulates the behavior of a browser through code and grabs the required data from the website. The specific process is:

1. Send request: Use the code to send an HTTP request to the target website.
2. Parse and obtain: Use the parsing library to parse web page data and analyze the required content.
3. Processing data: Save the obtained data locally or use it for other operations.
4. Commonly used libraries for Python crawlers

When developing Python crawlers, there are many commonly used libraries available. Some of the more commonly used libraries are as follows:

1. requests: Library for sending HTTP requests and processing response results.
2. BeautifulSoup4: Library for parsing documents such as HTML and XML.
3. re: Python's regular expression library for extracting data.
4. scrapy: A popular crawler framework in Python, providing very rich crawler functions.
5. Today’s Toutiao Crawler Practice

Today’s Toutiao is a very popular information website, which contains a large amount of news, entertainment, technology and other information content. We can get this content by writing a simple Python crawler program.

Before starting, you first need to install the requests and BeautifulSoup4 libraries. The installation method is as follows:

pip install requests pip install beautifulsoup4

Get the Toutiao homepage information:

We first need to get the HTML code of the Toutiao homepage.

import requests url = "https://www.toutiao.com/" # 发送HTTP GET请求 response = requests.get(url) # 打印响应结果 print(response.text)

After executing the program, you can see the HTML code of the Toutiao homepage.

Get the news list:

Next, we need to extract the news list information from the HTML code. We can use the BeautifulSoup library for parsing.

import requests from bs4 import BeautifulSoup url = "https://www.toutiao.com/" # 发送HTTP GET请求 response = requests.get(url) # 创建BeautifulSoup对象 soup = BeautifulSoup(response.text, "lxml") # 查找所有class属性为title的div标签，返回一个列表 title_divs = soup.find_all("div", attrs={"class": "title"}) # 遍历列表，输出每个div标签的文本内容和链接地址 for title_div in title_divs: title = title_div.find("a").text.strip() link = "https://www.toutiao.com" + title_div.find("a")["href"] print(title, link)

After executing the program, the news list of Today’s Toutiao homepage will be output, including the title and link address of each news.

Get news details:

Finally, we can get the detailed information of each news.

import requests from bs4 import BeautifulSoup url = "https://www.toutiao.com/a6931101094905454111/" # 发送HTTP GET请求 response = requests.get(url) # 创建BeautifulSoup对象 soup = BeautifulSoup(response.text, "lxml") # 获取新闻标题 title = soup.find("h1", attrs={"class": "article-title"}).text.strip() # 获取新闻正文 content_list = soup.find("div", attrs={"class": "article-content"}) # 将正文内容转换为一个字符串 content = "".join([str(x) for x in content_list.contents]) # 获取新闻的发布时间 time = soup.find("time").text.strip() # 打印新闻的标题、正文和时间信息 print(title) print(time) print(content)

After executing the program, the title, text and time information of the news will be output.

4. Summary

Through the introduction of this article, we have learned about the basic concepts of crawlers in Python, commonly used libraries, and how to use Python to write Toutiao crawler programs. Of course, crawler technology is a technology that needs continuous improvement and improvement. We need to continuously summarize and improve in practice how to ensure the stability of crawler programs and avoid anti-crawling methods.

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