How to use Scrapy to build an efficient crawler system

With the development of the Internet, people's demand for information is getting stronger and stronger, but it is becoming more and more difficult to obtain and process this information. Therefore, crawler technology came into being. Crawler technology has been widely used in web search engines, data mining, social networks, finance and investment, e-commerce and other fields.

Scrapy is an efficient web crawler framework based on Python, which can help us quickly build an efficient crawler system. In this article, we will introduce how to use Scrapy to build an efficient crawler system.

1. Introduction to Scrapy

Scrapy is a Python-based web crawler framework with efficient processing capabilities and strong scalability. It provides a powerful data extraction mechanism, supports asynchronous processing, and has a powerful middleware and plug-in system. Scrapy can also easily implement proxy, user agent, anti-crawler and other functions through configuration files. Scrapy provides a powerful debugging and logging system that can help us locate crawler problems more easily.

2. Scrapy installation and environment configuration

1. Installing Scrapy

Installing Scrapy requires installing Python first. It is recommended to use Python2.7 or Python3.6 or above Version. Installation method:

pip install scrapy

2. Environment configuration

After installing Scrapy, we need to perform relevant environment configuration, mainly including:

(1) Setup request Headers

In Scrapy’s configuration file, we can set our request headers. This can help us disguise ourselves as a browser to access the target website and avoid being blocked by the website's anti-crawler mechanism. The code is as follows:

DEFAULT_REQUEST_HEADERS = {
    'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8',
    'Accept-Language': 'en',
    'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/49.0.2623.110 Safari/537.36'
}

(2) Set downloader middleware

Scrapy supports many downloader middleware, such as HttpErrorMiddleware, RetryMiddleware, UserAgentMiddleware, etc. These middleware can help us solve various download and network problems. We can set the downloader middleware in the configuration file and set the downloader middleware parameters as needed. The code example is as follows:

DOWNLOADER_MIDDLEWARES = {
     'scrapy.contrib.downloadermiddleware.httpproxy.HttpProxyMiddleware': 110,
     'scrapy.contrib.downloadermiddleware.useragent.UserAgentMiddleware' : None,
     'myproject.spiders.middlewares.RotateUserAgentMiddleware': 400,
     'scrapy.contrib.downloadermiddleware.retry.RetryMiddleware': 90,
}

3. Scrapy crawler development

1. Create a Scrapy project

Before using Scrapy, we need to create a Scrapy project. Using the command line, enter the following command:

scrapy startproject myproject

This will create a Scrapy project named myproject.

2. Writing crawler programs

The Scrapy framework has a very good architecture and is divided into five modules: engine, scheduler, downloader, crawler and pipeline. To develop a Scrapy crawler, you need to write the following programs:

(1) Crawler module

In Scrapy, the crawler is the most important part. You need to create a spider folder in the myproject directory and write a crawler file in it, such as myspider.py. The sample code is as follows:

import scrapy

class MySpider(scrapy.Spider):
    name = 'myspider'
    allowed_domains = ['www.example.com']
    start_urls = ['http://www.example.com']

    def parse(self, response):
        # 爬虫主逻辑

In the code, we need to define a Spider class, where the name attribute is the crawler name, the allowed_domains attribute is the domain name that is allowed to be crawled, and the start_urls attribute is the URL to start crawling. Commonly used crawler categories in Scrapy include: CrawlSpider, XMLFeedSpider, SitemapSpider, etc.

(2) Data extraction module

The data extraction module is responsible for extracting data from the HTML page returned by the crawler. Scrapy provides two methods for extracting data: XPath and CSS selectors.

XPath: Scrapy implements the XPath selector through the lxml library. The usage method is as follows:

selector.xpath('xpath-expression').extract()

CSS selector: Scrapy implements the CSS selector through the Sizzle library. The usage method is as follows:

selector.css('css-expression').extract()

(3) Pipeline module

In Scrapy, the pipeline module is responsible for processing the data extracted by the crawler. Create a pipelines.py file in the myproject directory and write the code for the pipeline module:

class MyProjectPipeline(object):
    def process_item(self, item, spider):
        # 处理item数据
        return item

3. Run the crawler program

Use the following command to start the crawler:

scrapy crawl myspider

4. Scrapy crawler scheduling and optimization

1. Set download delay

In order to avoid too many requests to the target website, we should set a download delay. The DOWNLOAD_DELAY attribute can be set in Scrapy's configuration file:

DOWNLOAD_DELAY = 2

2. Set request timeout

Sometimes the target website will return an error message or the request times out, in order to avoid falling into an infinite loop , we should set a request timeout. The DOWNLOAD_TIMEOUT attribute can be set in Scrapy's configuration file:

DOWNLOAD_TIMEOUT = 3

3. Set the number of concurrent threads and concurrent requests

Scrapy can set the number of concurrent threads and concurrent requests. The number of concurrent threads refers to the number of web pages downloaded at the same time, while the number of concurrent requests refers to the number of requests made to the target website at the same time. It can be set in the Scrapy configuration file:

CONCURRENT_REQUESTS = 100
CONCURRENT_REQUESTS_PER_DOMAIN = 16

4. Comply with Robots protocol

The target website may set the Robots protocol, which is used to restrict crawler access. We should comply with the Robots protocol and adjust our crawler code according to the robots.txt file of the target website.

5. Anti-crawler mechanism

Some websites will use anti-crawler technology to prevent our crawlers, such as forced login, IP blocking, verification code, JS rendering, etc. In order to avoid these limitations, we need to use technologies such as proxies, distributed crawlers, and automatic identification of verification codes to solve these problems.

In short, using Scrapy to build an efficient crawler system requires a certain amount of technical accumulation and experience summary. During the development process, we need to pay attention to the efficiency of network requests, the accuracy of data extraction, and the reliability of data storage. Only through continuous optimization and improvement can our crawler system achieve higher efficiency and quality.

The above is the detailed content of How to use Scrapy to build an efficient crawler system. For more information, please follow other related articles on the PHP Chinese website!