Using Scrapy: A Simple Guide to Web Scraping

‌Scrapy is a fast, high-level web crawling framework developed in Python, used to crawl web sites and extract structured data from pages. ‌It has a wide range of uses and can be used for data mining, monitoring and automated testing. ‌

Overview of Scrapy

The Scrapy framework consists of five major components: scheduler, downloader, crawler, entity pipeline and Scrapy engine. ‌
Among them, the scheduler determines the next URL to be crawled, the downloader is used to download network resources at high speed, the crawler is used to extract the required information from a specific web page, the entity pipeline processes the data extracted by the crawler, and the Scrapy engine controls the flow of data in all components of the system. ‌
The reason why Scrapy is often used is that it is a framework that anyone can easily modify according to their needs, and provides base classes for various types of web scraping.

Advantages of Scrapy for crawling web pages

The advantages of Scrapy for crawling web pages mainly include: ‌
1‌.High efficiency‌: Scrapy uses asynchronous processing and concurrent requests, which can efficiently handle large-scale crawling tasks and improve the efficiency of web crawling. ‌
2.Flexibility‌: Scrapy provides a rich set of components and plug-in mechanisms, and users can customize and expand them according to their needs to meet various web crawling needs.
3.Stability‌: Scrapy has good fault tolerance and stability, and can cope with complex and changing network environments. ‌
4.Rich functions‌: Scrapy supports parsing and processing of multiple data formats, including HTML, XML, JSON, etc., and provides functions such as automated processing, data extraction, and data storage. ‌
‌5.Strong scalability‌: Scrapy supports distributed crawling, which can crawl and process data simultaneously through multiple crawler nodes to improve crawling efficiency.

Basic steps for scraping web pages with scrapy

Scrapy is a fast and advanced web crawling and web scraping framework, used to crawl websites and extract structured data from pages. ‌Here are the basic steps to use Scrapy for web scraping:‌

1.‌Install Scrapy‌

First, make sure Scrapy is installed. ‌If it is not installed yet, you can install it through pip:‌
pip install scrapy

2. Create a Scrapy project

Use the scrapy startproject command to create a new Scrapy project. For example, create a project named myproject:
scrapy startproject myproject

3. Define Item

Define Item in the project to store crawled data. For example, define an Item in myproject/myproject/items.py:

import scrapy

class MyprojectItem(scrapy.Item):
    title = scrapy.Field()
    link = scrapy.Field()
    desc = scrapy.Field()

4. Write a Spider

Create a Spider in your project to define the website to be crawled and how to crawl it. For example, create a Spider file named example.py in the myproject/myproject/spiders directory:

import scrapy
from myproject.items import MyprojectItem

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

    def parse(self, response):
        items = []
        for sel in response.xpath('//ul/li'):
            item = MyprojectItem()
            item['title'] = sel.xpath('a/text()').get()
            item['link'] = sel.xpath('a/@href').get()
            item['desc'] = sel.xpath('text()').get()
            items.append(item)
        return items

5. Run the Spider

Use the scrapy crawl command to run the Spider. For example, run the example Spider created above:
scrapy crawl example

6. Save data

You can process the crawled data by defining Item Pipeline, such as saving it to a file or database.

7. Further configuration

You can further configure the Scrapy project as needed, such as setting up middleware, downloader, log, etc.

These are the basic steps for crawling websites with Scrapy. Depending on your specific needs, you may need to perform some additional configuration and optimization.

How to set up Scrapy to use dynamic User-Agent?

Dynamic User-Agent is an effective strategy to prevent crawlers from being identified by websites. ‌ In Scrapy, dynamic User-Agent can be set in a variety of ways: ‌ ‌

• Add a custom_settings attribute in the Spider class: ‌ This attribute is a dictionary used to set custom Scrapy configuration. ‌ Add the 'USER_AGENT' key in the custom_settings dictionary and set the corresponding User-Agent value. ‌ ‌ ‌

• Use the fake_useragent library: ‌ This library has a large number of built-in User-Agents that can be randomly replaced. ‌ After installing the fake_useragent package, import and use the library in Scrapy's settings configuration file to generate a random User-Agent. ‌ ‌ ‌

• Implement random User-Agent middleware: ‌ Create a middleware that uses the fake_useragent library to assign a different User-Agent to each request. ‌ ‌ ‌
  Through these methods, you can effectively simulate normal user behavior and reduce the risk of being identified as a crawler by the website. ‌ ‌

Why do you need to set up a proxy when using Scrapy for web crawling?

When using the Scrapy framework for web scraping, it is very necessary to set up a proxy. The main reasons are as follows:

• Avoid IP blocking: When the crawler accesses the website, if the original IP address is used directly, it is easy to be identified and blocked by the website. Using a proxy can hide the real IP address, thereby avoiding being blocked and protecting the identity of the crawler. ‌

• Break through access restrictions: Some websites will set access restrictions. Using a proxy can break through these restrictions and freely obtain data on the target website. ‌

• Improve crawler efficiency: In some scenarios where a large amount of crawling data is required, using a proxy can effectively avoid IP addresses from being blocked, thereby ensuring the normal operation of the crawler program and improving crawler efficiency. ‌
  In summary, in order to better collect data in the Scrapy framework, it is very important to set up a proxy.

How to set up a proxy server in Scrapy?

Setting a proxy in Scrapy can be achieved by modifying the project's settings.py file. ‌The specific steps are as follows:‌

1. Prepare the proxy server:‌First,‌you need to get the IP from a reliable proxy service provider and‌save it in a file‌or use the proxy's API. ‌

2. Enable the proxy‌:‌Set PROXY_ENABLED = True in the settings.py file to enable the proxy. ‌

3. Set the proxy IP and port‌:‌You can specify the proxy and port by setting the PROXY variable,‌for example, PROXY = 'http://your_proxy_ip:port'. ‌

4. Configure the downloader middleware‌:‌To ensure that the proxy settings take effect,‌you need to add or modify the proxy-related middleware settings in the DOWNLOADER_MIDDLEWARES configuration in the settings.py file. ‌

By understanding this article, you can learn to use Scrapy to crawl web pages, and try to avoid problems encountered during web crawling by dynamically setting User-Agent and agents.