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Often when programming we use available APIs that provide us with the data we need for our application. For example, building an app that will show us the current weather, we need to get this data from somewhere, and most often we use the available APIs on the market, but what if we can't find the API we are interested in? That's when it's worth considering, page scraping. In this article I will just introduce a tool that will help us scrape pages.

scrapy

What is page scraping?

Page scraping is nothing more than extracting some content from a page and saving this data for use in your application, for example. Page scraping is used by sites such as ceneo, google, or portals that collect job listings from other portals. Keep in mind that what we do later with such data can sometimes be illegal.

 

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What is Scrapy?

Scrapy is a Python language framework and it is the most popular and powerful tool for scraping websites. Scrapy provides all the necessary tools you need to efficiently extract data from pages, process it and store it in your preferred structure and format. Scrapy is easy to use, has support for asynchronous requests, and automatically adjusts indexing speed with an "Auto-throttling" mechanism.

 

Scrapy Spider

The most important part in Scrapy are the Spider classes. Scrapy uses them to collect information from the website. They define how our Spider should extract data from the page.

 

An example of a Spider class that extracts quotes from a page.

import scrapy
class QuotesSpider(scrapy.Spider):
    name = 'quotes'
    start_urls = [
        'https://quotes.toscrape.com/tag/humor/',
    ]
    def parse(self, response):
        for quote in response.css('div.quote'):
            yield {
                'author': quote.xpath('span/small/text()').get(),
                'text': quote.css('span.text::text').get(),
            }
        next_page = response.css('li.next a::attr("href")').get()
        if next_page is not None:
            yield response.follow(next_page, self.parse)

 

We write such code to the file "quotes_spider.py" and start our scraping bot with the command:

scrapy runspider quotes_spider.py -o quotes.jl

 

When our bot finishes its work we should get a file "quotes.jl", which will contain a list of quotes saved in json format.

{"author": "Jane Austen", "text": "\u201cThe person, be it gentleman or lady, who has not pleasure in a good novel, must be intolerably stupid.\u201d"}
{"author": "Steve Martin", "text": "\u201cA day without sunshine is like, you know, night.\u201d"}
{"author": "Garrison Keillor", "text": "\u201cAnyone who thinks sitting in church can make you a Christian must also think that sitting in a garage can make you a car.\u201d"}
...

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