Scrapy asynchronous loading implementation method based on Ajax

Scrapy is an open source Python crawler framework that can quickly and efficiently obtain data from websites. However, many websites use Ajax asynchronous loading technology, making it impossible for Scrapy to obtain data directly. This article will introduce the Scrapy implementation method based on Ajax asynchronous loading.

1. Ajax asynchronous loading principle

Ajax asynchronous loading: In the traditional page loading method, after the browser sends a request to the server, it must wait for the server to return a response and load all the pages. Go to the next step. After using Ajax technology, the browser can asynchronously obtain data from the server and dynamically update the page content without refreshing the page, thus saving network bandwidth and improving user experience.

The basic principle of Ajax technology is to implement asynchronous communication through the XMLHttpRequest object. The client (browser) sends a request to the server and keeps the page from refreshing while waiting for a response. Then, after the server responds and returns data, it dynamically updates the page through JavaScript to achieve asynchronous loading.

2. Scrapy based on Ajax asynchronous loading implementation method

1. Analyze the Ajax request of the page

Before using Scrapy to crawl, we need to analyze the Ajax request of the target website . You can use the browser's developer tools under the Network tab to view and analyze the URL, request parameters, and return data format of the Ajax request.

2. Use Scrapy’s Request module to send Ajax requests

We can use Scrapy’s Request module to send Ajax requests, the code is as follows:

import scrapy

class AjaxSpider(scrapy.Spider):
    name = "ajax_spider"
    start_urls = ["http://www.example.com"]

    def start_requests(self):
        for url in self.start_urls:
            yield scrapy.Request(url=url, callback=self.parse)

    def parse(self, response):
        ajax_url = "http://www.example.com/ajax"
        ajax_headers = {'x-requested-with': 'XMLHttpRequest'}
        ajax_data = {'param': 'value'}
        yield scrapy.FormRequest(url=ajax_url, headers=ajax_headers, formdata=ajax_data, callback=self.parse_ajax)

    def parse_ajax(self, response):
        # 解析Ajax返回的数据
        pass

In this code, we First, use Scrapy's Request module to send the original request through the start_requests() method, parse the response content in the parse() method, and initiate an Ajax request. In the parse_ajax() method, parse the data returned by the Ajax request.

3. Process the data returned by Ajax

After we obtain the return data from the Ajax request, we can parse and process it. Normally, the data returned by Ajax is in JSON format, which can be parsed using Python's json module. For example:

import json

def parse_ajax(self, response):
    json_data = json.loads(response.body)
    for item in json_data['items']:
        # 对数据进行处理
        pass

4. Use Scrapy’s Item Pipeline for data persistence

The last step is to use Scrapy’s Item Pipeline for data persistence. We can store the parsed data in the database or save it to a local file, for example:

import json

class AjaxPipeline(object):
    def open_spider(self, spider):
        self.file = open('data.json', 'w')

    def close_spider(self, spider):
        self.file.close()

    def process_item(self, item, spider):
        line = json.dumps(dict(item)) + "
"
        self.file.write(line)
        return item

Summary:

This article introduces the Scrapy method based on Ajax asynchronous loading. First analyze the Ajax request of the page, use Scrapy's Request module to send the request, parse and process the data returned by Ajax, and finally use Scrapy's Item Pipeline for data persistence. Through the introduction of this article, you can better deal with crawling websites that need to use Ajax to load asynchronously.

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