Scrapy – Building Spiders For Scraping Websites With Scrapy

Scrapy is a web crawling and scraping framework written in Python. It is a powerful and beginner-friendly tool that allows you to build efficient and robust spiders for scraping websites. It has a built-in mechanism called selectors for extracting data from the web. It also has the ability to control crawling speed using an auto-throttle mechanism.

It is an open-source and free-to-use framework that can be used for large-scale web crawling and scraping in a very short time frame. It is used by thousands of developers around the world to scrape data from websites in production applications.

The main goal of this tutorial is to help you learn how to build a scraper https://scrapy.ca/en/location/sell-your-car-laval/ that can crawl and extract data from any website. You will use XPath to navigate through an XML document and CSS selectors to get data from HTML documents.

To start with, we will write a simple script that scrapes the data from an Amazon website. This will use XPath and CSS selectors to get the information we want, and it will output it as a string.

Once we have the data, we need to store it. This is easily done with an object called Items, which is like a Python dictionaries and can be used to store all your scraped data in a structured format.

Item containers will automatically be created when you create your scraper. You can then use them to save your scraped data for temporary storage. Once you have stored the scraped data, it is possible to export it into a feed URI for use in other parts of your application.

Besides the Item container, Scrapy also includes a scheduler that is used to manage requests and responses. You can use this to schedule your scraper to make a series of requests and have it register a callback method to handle the data extraction process for each request.

When a request is received, it will be processed by the parse() method and a response will be returned to the user. If the response is not available, bytes will be returned instead of the data. If the response is available, it will be passed to the items() method to store it in a container for later use.

Once this is complete, the scraper will schedule a new request for the next page. The request will be made using the urljoin() method and the results of the previous request will be used as input for the parse() method to get the scraped data from.

This is a very simple way to build a scraper and it is the core architecture of all scrapy based web scrapers. You can think of it as a web robot with two wheels, one for requesting and the other to extract the data from the website.

You can add more functionality to your scraper by writing generators that generate either requests with callback methods or results that will be saved in item containers. You can also store the extracted data in a CSV, JSON, or XML file and store that in databases as well.