Introduction to Web Scraping

Do you require data to kickstart a new project? Discover the power of web scraping!

Data is crucial in today’s world. Whether you're a data scientist, data analyst, or a software developer, data plays an integral role in daily operations. It empowers you to make informed choices, solve problems, generate reports, and tailor communications with clients. This is why even those without a programming background should consider mastering web scraping.

Web scraping is a method for gathering data from websites. Automated bots, known as web scrapers, can extract vast amounts of information from the internet, saving you hours of manual data collection, allowing you to concentrate on more essential tasks. For a comprehensive overview of web scraping, check out my YouTube video below.

This article will provide you with free resources to learn web scraping effectively. Over the next 12 weeks, we will explore popular Python libraries such as Beautiful Soup, Selenium, and Scrapy. If you’re new to Python, a complete crash course video is available at the end of this article, which is highly recommended before diving into web scraping.

Week 1: HTML Basics

• Introduction to HTML Elements and Tags
• Understanding Headers, Paragraphs, Images, and Links
• Working with Unordered and Ordered Lists
• Exploring the Div Element
• Learning about the Footer, Head Section, and Website Title

Along with HTML, grasping basic Python concepts is also necessary. If you're unfamiliar with Python, a crash course is linked at the end of this article.

Beautiful Soup

The first library you should explore is Beautiful Soup, known for its user-friendly approach to web scraping. It simplifies the extraction of data from websites, requiring minimal memorization of methods compared to other libraries. However, it has limitations, particularly with JavaScript-driven websites and speed. Thus, it is advisable to start your web scraping journey with Beautiful Soup and gradually progress to more advanced tools.

You can expect to spend 1 to 2 weeks learning the fundamentals of Beautiful Soup, depending on your availability.

Week 2: Getting Started with Beautiful Soup

• How to Retrieve HTML from a Website
• Scraping a Single Page
• Exporting Data to a Text File
• Scraping Multiple Links on One Page
• Navigating Multiple Pages with Beautiful Soup

Selenium

Selenium surpasses Beautiful Soup in several areas, including the ability to scrape JavaScript-driven pages and create explicit waits. Before you start with Selenium, it's important to understand XPath, the XML Path Language, which allows for selecting nodes in an XML document. While you can locate elements without XPath, mastering it becomes crucial when dealing with complex HTML structures.

Week 3: XPath Fundamentals

• Understanding XPath Syntax
• Utilizing XPath Functions and Operators
• Navigating Special Characters in XPath

All necessary materials for week 3 can be found in the article below.

Week 4–5: Introduction to Selenium

• Creating a Selenium Driver
• Clicking Buttons with Selenium
• Extracting Data from Tables
• Exporting Data to CSV Files using Pandas
• Selecting Elements from Dropdowns using Selenium

Week 6–7: Advanced Selenium Techniques

After grasping the basics of Selenium in week 5, you'll want to delve into more complex techniques for scraping intricate websites. Here are tasks you can tackle with Selenium:

• Handling Pagination
• Implementing Waits (Implicit vs. Explicit)
• Logging into Websites
• Managing Infinite Scrolling
• Exploring the Options Class (headless mode, window size, etc.)

Learning all of this may seem daunting, so I recommend working on projects that focus on one or two of these tasks.

#### Example Projects:

• Scraping a Betting Site with Selenium (Implicit waits)
• Building a Betting Tool with Selenium and Pandas (Explicit waits, pagination, Options class)

Scrapy

To elevate your web scraping skills, learning Scrapy is essential. As the most powerful web scraping framework in Python, Scrapy can efficiently scrape JavaScript-driven sites and manage large-scale projects while offering data export options to MongoDB, SQLite, and more.

To use Scrapy effectively, familiarity with XPath is necessary. Once you master XPath, you’re set to learn Scrapy.

Week 8–9: Getting Started with Scrapy

Scrapy can be more challenging than Beautiful Soup and Selenium, so take your time. Begin by properly setting up your project and familiarizing yourself with the commands and templates used in Scrapy.

• Scrapy Commands
• Creating Your First Project and Spider
• Utilizing Scrapy Templates and Finding Elements
• Working with Scrapy's Shell Command
• Building Your Spider
• Exporting Data to CSV or JSON Files

Week 10–12: Advanced Scrapy Techniques

• Building Crawlers with Scrapy
• Exporting Data to Databases (MongoDB and SQLite)
• Managing Proxies
• Scraping APIs
• Logging into Websites

The amount of information can be overwhelming, so just like with Selenium, consider projects that concentrate on one or two tasks.

#### Sample Projects:

• Web Scraping Amazon
• Scraping Data from 10 Online Shops