How to Effectively Scrape Multiple Pages with Python BeautifulSoup and requests
Learn how to scrape multiple pages of data from eBay using Python's `BeautifulSoup` and `requests`. This guide will help you gather comprehensive data from all desired pages, ensuring robust web scraping practices.
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This video is based on the question https://stackoverflow.com/q/68805102/ asked by the user 'Arslan Aziz' ( https://stackoverflow.com/u/16671552/ ) and on the answer https://stackoverflow.com/a/68808354/ provided by the user 'Md. Fazlul Hoque' ( https://stackoverflow.com/u/12848411/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.
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Understanding the Problem: Why is the Code Scraping Only One Page?
If you've ventured into web scraping using Python, you might have encountered a scenario where your code only returns data from a single page. This is a common issue, especially for beginners. In this post, we'll explore why your scraping code might not be functioning as expected and how you can enhance it to scrape data from multiple pages efficiently.
The Basic Scraping Logic
The initial code you provided intends to scrape sneaker listings from eBay. However, if it's only scraping one page, it could be due to:
Incorrect URL Formatting: The URL for subsequent pages may not be generated correctly.
Improperly Defined Loops: The loop that iterates through pages may not correctly fetch the desired content.
Enhancing Your Code for Multi-Page Scraping
A Working Example
To address the issue of only scraping one page, let's take a look at a refined version of the code that successfully retrieves data from multiple pages. Here’s how to implement this effectively:
[[See Video to Reveal this Text or Code Snippet]]
Code Breakdown
1. Setup
We import necessary libraries (requests, BeautifulSoup, and pandas).
Lists Title and Price are initialized to store the scraped data.
2. Headers
Custom headers are included to mimic a real browser and reduce the risk of being blocked by the server.
3. Pagination Loop
A for loop runs from 0 to 9, fetching data from ten pages.
The URL includes the page variable dynamically to point to different pages.
4. Data Extraction
Using BeautifulSoup, we parse the HTML to locate the items' titles and prices.
We append each title and price to their respective lists.
5. Data Presentation
Finally, we create a pandas DataFrame to neatly present the collected data.
Conclusion
With the corrected code and approach, you'll now be able to scrape data from multiple eBay pages efficiently. Be sure to enhance your skills further by experimenting with different websites and expanding your scraping logic. Happy coding!
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