Python Web Scraping: A Step-by-Step Guide for Beginners

Web scraping is a valuable skill that allows you to collect and analyze large amounts of data from web pages with almost no manual effort. In this article, we will provide a step-by-step guide on how to perform web scraping using Python on an Ubuntu VPS. We will cover the prerequisites, setting up the environment, making requests, extracting data with Beautiful Soup, parsing HTML, handling dynamic data, error handling and logging, creating a web scraper application, and more.

Prerequisites

An Ubuntu VPS with Python, pip, and venv module installed
Secure Shell (SSH) access to the VPS
Basic knowledge of how to run commands on a terminal

While it is possible to write Python code for web scraping without using a VPS, we recommend using one for better stability and performance, especially for large-scale tasks.

Setting up your environment for Python web scraping

To set up your environment for Python web scraping, you need to log in to your VPS via SSH. Once logged in, you can create a new virtual environment for Python, activate the virtual environment, and install the required libraries like Beautiful Soup and requests.

Making your first request

In Python, you can use the requests library to send HTTP requests and retrieve the HTML response. We will show you how to make your first request and print the HTML content of the page.

Extracting data with Beautiful Soup

Beautiful Soup is a popular Python library for parsing HTML content. We will demonstrate how to use Beautiful Soup to extract specific data from the HTML response we obtained in the previous step.

Parsing HTML and navigating the DOM tree

The Document Object Model (DOM) represents an HTML document as a tree structure. We will explain how to navigate this tree using Beautiful Soup and locate specific elements or data points.

Handling dynamic content and Ajax calls

Some websites load content dynamically via Ajax calls or JavaScript. We will explore different techniques for handling dynamic data, including using Selenium and analyzing network requests.

Error handling and logging

We will discuss the importance of error handling and logging in web scraping scripts. Proper error handling ensures that your script gracefully handles exceptions and prevents it from crashing. We will show you how to implement error handling and logging techniques in your Python web scraping code.

Creating a simple web scraper application

We will walk you through the process of creating a simple web scraper application in Python. This application will prompt the user for a keyword and a URL, count the occurrences of the keyword in the page text, and display all the internal links present in the text.

Conclusion

Web scraping is a powerful technique for collecting and analyzing data from websites. In this article, we covered the basics of Python web scraping, including setting up the environment, making requests, extracting data with Beautiful Soup, handling dynamic content, error handling and logging, and creating a web scraper application. We hope this guide has provided you with a solid foundation to start your web scraping journey.

Python web scraping FAQ

Which Python libraries are commonly used for web scraping?

The most commonly used Python libraries for web scraping are Beautiful Soup, requests, and Scrapy.

Is it possible to scrape websites that require login credentials using Python?

It is technically possible to scrape websites that require login credentials using Python web scraping. However, replicating the login process can be complex, especially if there are CAPTCHAs or multi-factor authentication involved. Make sure to review the website’s terms of service before proceeding with web scraping.

Can I extract images or media files with Python web scraping?

Yes, Python web scraping can be used to extract images or media files from websites. You can use tools like Beautiful Soup to locate the appropriate HTML tags (e.g., ) and retrieve the URLs of the images or media files. Then, you can use the requests library to download the files.

Web scraping vs. API: which is better?

The choice between web scraping and API depends on your specific needs. If an API is available and provides the data you need in a structured format, it is generally the preferred option due to its ease of use and standardization. However, if the website does not offer an API or you need to scrape specific data that is not available through the API, web scraping may be the only option.

👉
Start your website with Hostinger – get fast, secure hosting here 👈

🔗 Read more from MinimaDesk:

🎁 Download free premium WordPress tools from our Starter Tools page.