Scrapy framework practice: crawling Jianshu website data

Scrapy framework practice: crawling Jianshu website data

Scrapy is an open source Python crawler framework that can be used to extract data from the World Wide Web. In this article, we will introduce the Scrapy framework and use it to crawl data from Jianshu websites.

1. Installing Scrapy

Scrapy can be installed using package managers such as pip or conda. Here, we use pip to install Scrapy. Enter the following command in the command line:

pip install scrapy

After the installation is complete, you can use the following command to check whether Scrapy has been successfully installed:

scrapy version

If you see something similar to "Scrapy x.x.x - no active project" output, Scrapy has been installed successfully.

2. Create Scrapy Project

Before we start using Scrapy, we need to create a Scrapy project. Enter the following command at the command line:

scrapy startproject jianshu

This will create a Scrapy project named "jianshu" in the current directory.

3. Creating a Scrapy crawler

In Scrapy, a crawler is a component that processes data extracted from a website. We use Scrapy Shell to analyze Jianshu website and create crawlers.

Enter the following command at the command line:

scrapy shell "https://www.jianshu.com"

This will launch the Scrapy Shell, where we can view the page source code and elements of the Jianshu website in order to create selectors for our crawler .

For example, we can use the following selector to extract the article title:

response.css('h1.title::text').extract_first()

We can use the following selector to extract the article author:

response.css('a.name::text').extract_first()

Tested in Scrapy Shell After selecting the selector, we can create a new Python file for our crawler. Enter the following command at the command line:

scrapy genspider jianshu_spider jianshu.com

This will create a Scrapy crawler named "jianshu_spider". We can add the selector we tested in Scrapy Shell to the crawler's .py file and specify the data to extract.

For example, the following code extracts the titles and authors of all articles on the home page of the Jianshu website:

import scrapy

class JianshuSpider(scrapy.Spider):
    name = 'jianshu_spider'
    allowed_domains = ['jianshu.com']
    start_urls = ['https://www.jianshu.com/']

    def parse(self, response):
        for article in response.css('li[data-note-id]'):
            yield {
                'title': article.css('a.title::text').extract_first(),
                'author': article.css('a.name::text').extract_first(),
            }

4. Run the Scrapy crawler and output the results

Now , we execute the Scrapy crawler in command line mode and output the results to a JSON file. Enter the following command at the command line:

scrapy crawl jianshu_spider -o articles.json

This command will run our crawler and save the output data to a JSON file called "articles.json".

5. Conclusion

In this article, we introduced the Scrapy framework and used it to crawl data from the Jianshu website. Extracting data from websites is easy using the Scrapy framework, and Scrapy can be scaled into large-scale data extraction applications due to its concurrency and scalability.

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