Web Scraping With Scrapy and MongoDB :

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August 28, 2024
Web Scraping With Scrapy and MongoDB
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Scrapy is a robust Python web scraping framework that can manage requests asynchronously, follow links, and parse site content. To store scraped data, you can use MongoDB, a scalable NoSQL database, that stores data in a JSON-like format. Combining Scrapy with MongoDB offers a powerful solution for web scraping projects, leveraging Scrapy’s efficiency and MongoDB’s flexible data storage.

In this tutorial, you’ll learn how to:

  • Set up and configure a Scrapy project
  • Build a functional web scraper with Scrapy
  • Extract data from websites using selectors
  • Store scraped data in a MongoDB database
  • Test and debug your Scrapy web scraper

If you’re new to web scraping and you’re looking for flexible and scalable tooling, then this is the right tutorial for you. You’ll also benefit from learning this tool kit if you’ve scraped sites before, but the complexity of your project has outgrown using Beautiful Soup and Requests.

To get the most out of this tutorial, you should have basic Python programming knowledge, understand object-oriented programming, comfortably work with third-party packages, and be familiar with HTML and CSS.

By the end, you’ll know how to get, parse, and store static data from the Internet, and you’ll be familiar with several useful tools that allow you to go much deeper.

Take the Quiz: Test your knowledge with our interactive “Web Scraping With Scrapy and MongoDB” quiz. You’ll receive a score upon completion to help you track your learning progress:

Web Scraping With Scrapy and MongoDB

Interactive Quiz

Web Scraping With Scrapy and MongoDB

In this quiz, you'll test your understanding of web scraping with Scrapy and MongoDB. You'll revisit how to set up a Scrapy project, build a functional web scraper, extract data from websites, store scraped data in MongoDB, and test and debug your Scrapy web scraper.

Prepare the Scraper Scaffolding

You’ll start by setting up the necessary tools and creating a basic project structure that will serve as the backbone for your scraping tasks.

While working through the tutorial, you’ll build a complete web scraping project, approaching it as an ETL (Extract, Transform, Load) process:

  • Extract data from the website using a Scrapy spider as your web crawler.
  • Transform this data, for example by cleaning or validating it, using an item pipeline.
  • Load the transformed data into a storage system like MongoDB with an item pipeline.

Scrapy provides scaffolding for all of these processes, and you’ll tap into that scaffolding to learn web scraping following the robust structure that Scrapy provides and that numerous enterprise-scale web scraping projects rely on.

First, you’ll install Scrapy and create a new Scrapy project, then explore the auto-generated project structure to ensure that you’re well-equipped to proceed with building a performant web scraper.

Install the Scrapy Package

To get started with Scrapy, you first need to install it using pip. Create and activate a virtual environment to keep the installation separate from your global Python installation. Then, you can install Scrapy:

Shell 
(venv) $ python -m pip install scrapy

After the installation is complete, you can verify it by running the scrapy command and viewing the output:

Shell 
(venv) $ scrapy
Scrapy 2.11.2 - no active project

Usage:
  scrapy <command> [options] [args]

Available commands:
  bench         Run quick benchmark test
  fetch         Fetch a URL using the Scrapy downloader
  genspider     Generate new spider using pre-defined templates
  runspider     Run a self-contained spider (without creating a project)
  settings      Get settings values
  shell         Interactive scraping console
  startproject  Create new project
  version       Print Scrapy version
  view          Open URL in browser, as seen by Scrapy

  [ more ]      More commands available when run from project directory

Use "scrapy <command> -h" to see more info about a command

The command-line (CLI) program should display the help text of Scrapy. This confirms that you installed the package correctly. You’ll next run the highlighted startproject command to create a project.

Create a Scrapy Project

Scrapy is built around projects. Generally, you’ll create a new project for each web scraping project that you’re working on. In this tutorial, you’ll work on scraping a website called Books to Scrape, so you can call your project books.

As you may have already identified in the help text, the framework provides a command to create a new project:

Shell 
(venv) $ scrapy startproject books

Read the full article at https://realpython.com/web-scraping-with-scrapy-and-mongodb/ »

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August 28, 2024 at 07:30PM
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