PHP web crawler framework ScrapyPython + PHP implement web crawler

With the development of the Internet, network data is becoming increasingly abundant, and many companies need to crawl a large amount of data from the Internet to analyze and make business decisions. Web crawlers have become an important tool for enterprises to obtain data.

Among the many web crawler frameworks, Scrapy is a very popular one. Scrapy, as an open source web crawler framework written in Python, has efficient crawling speed, flexible architecture and strong scalability. At the same time, it also provides many excellent extensions, such as Scrapy-Redis, which can support multi-distributed crawling, making Scrapy shine in web crawler development.

However, some companies also use PHP language to develop their own Web services, and they may need to convert the development of the crawler part into Python code. At this time, you need to combine the code and use Python and PHP to implement a web crawler.

Next, we will introduce step by step how to use Scrapy and PHP to implement crawlers.

First, we need to install Scrapy, which can be installed using pip:

pip install scrapy

After completion, you can create a Scrapy project:

scrapy startproject tutorial

With the above command, Scrapy will be created A directory named tutorial contains a crawler project structure that can be started.

Next, we need to create a crawler to define which pages to crawl, how to identify the required information, and how to store the data. In Scrapy, each crawler is defined by a Spider class.

The following is a simple Spider class example:

import scrapy

class MySpider(scrapy.Spider):
    name = 'myspider'

    def start_requests(self):
        urls = [
            'http://www.example.com/1.html',
            'http://www.example.com/2.html',
            'http://www.example.com/3.html',
        ]
        for url in urls:
            yield scrapy.Request(url=url, callback=self.parse)

    def parse(self, response):
        page = response.url.split("/")[-2]
        filename = f'page-{page}.html'
        with open(filename, 'wb') as f:
            f.write(response.body)
        self.log(f'Saved file {filename}')

In this example, we define a Spider named myspider, define the URLs that need to be accessed in start_requests, and explain in parse How to process the crawled data. In this simple example, we save the downloaded web page to a file called "page-X.html".

Next, we need to define a PHP script to start the Spider and process the crawled data. Here we store Scrapy's log information in a file so that the PHP program can read it. Similarly, we can also store the data crawled by Scrapy into the database for subsequent analysis.

<?php
// 启动Spider
exec("scrapy crawl myspider -o data.json");

// 读取日志信息
$log = file_get_contents('scrapy.log');

// 解析JSON格式的数据
$data = json_decode(file_get_contents('data.json'), true);

// 在此处添加数据处理逻辑
// ...

// 输出数据，或者将数据存储到数据库
var_dump($data);
?>

Through the above code, we implement the process of starting the Scrapy crawler through PHP and store the data in JSON format. Finally, we can add appropriate data processing logic to the PHP program to obtain the data we need.

Summary:
This article introduces how to use the Scrapy framework in Python and the process of combining Python and PHP to implement a web crawler. It should be noted that throughout the process, we need to pay attention to how data is transferred between the two languages ​​and how to handle exceptions. Through this method, we can quickly and efficiently obtain large amounts of data on the Internet to provide support for enterprises' business intelligence decisions.

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