How to Scrape Multiple Pages Using Beautiful Soup in Python
на канале: vlogize
Learn to modify your Python web scraping code to efficiently scrape data from multiple pages with Beautiful Soup and Pandas.
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This video is based on the question https://stackoverflow.com/q/69071299/ asked by the user 'Arslan Aziz' ( https://stackoverflow.com/u/16671552/ ) and on the answer https://stackoverflow.com/a/69071492/ provided by the user 'Ram' ( https://stackoverflow.com/u/2773206/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.
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Scraping Multiple Pages with Beautiful Soup in Python
Web scraping can be an excellent way to gather data from multiple pages of a website. However, many enthusiasts run into a common problem: their scraping code only returns data from a single page. In this guide, we’ll guide you through modifying your existing Beautiful Soup code to effectively scrape data from multiple pages.
Understanding the Problem
You might have tried running your web scraping code and found that it only scrapes data from one page. This happens often due to how variables and loops are structured in the code. Let's dive into the key issues that prevent it from scraping multiple pages successfully:
List Initialization: The lists used to store data (like titles, brands, etc.) might be re-initialized with each loop iteration, meaning only the data from the last page is stored.
Data Extraction Placement: The loops that extract data are positioned in a way that they only grab results from the last page processed.
Solution Overview
To correct these issues, we need to:
Move the initialization of lists outside of the loop.
Ensure that data collection properly accumulates results from all pages during each iteration.
Let’s take a closer look at the modified code that accomplishes this.
Modified Code
Here's the revised version of your web scraping code that will allow data collection from multiple pages:
[[See Video to Reveal this Text or Code Snippet]]
Key Changes Explained
Single Initialization of Lists: Moving the list initializations outside the for page loop prevents them from resetting with each page iteration. This is crucial for accumulating values across multiple pages.
Cleaner URL Formatting: Using an f-string for better readability and efficiency when creating the URL.
Consolidated Data Collection: The extraction and appending of values happen outside of nested loops dedicated to retrieving links.
Final Thoughts
By adopting these changes, you can successfully scrape data from multiple pages and consolidate it into a structured format using Pandas. Experimenting with web scraping not only improves your coding skills but also helps you gather valuable data efficiently. Happy scraping!
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