Python – BeautifulSoup returning none when element definitely exists

I’m relatively new to web scraping and have been using BeautifulSoup to extract daily mortgage rates from various servicer websites.

However, I’m encountering an issue where many of the websites I’m trying to scrape return either ‘None’ or an empty list when I attempt to extract specific tags.

I’ve double-checked that the tags I’m trying to scrape do exist in the HTML structure, but I’m still puzzled as to why I’m getting these empty results.

Here’s an example of the code I’m using:

from urllib.request import urlopen
from bs4 import BeautifulSoup

html = urlopen('')
bsObj = BeautifulSoup(html, 'html.parser')
rate = bsObj.find('span', {'class': 'text-md text-popular-medium-blue'}).div

Can anyone help me understand why I might be getting ‘None’ or empty results when scraping this particular website?


Sure, I’d be happy to provide a detailed explanation for the issue you’re facing with web scraping using BeautifulSoup.

Understanding the Problem

First, let’s break down the problem you’re encountering:

  1. You are new to web scraping and using BeautifulSoup to extract information from websites.
  2. Specifically, you are trying to scrape daily mortgage rates from various servicer websites.
  3. Some of the websites you are attempting to scrape return ‘None’ or an empty list when you try to extract specific HTML tags.
  4. You’ve confirmed that the tags you are trying to scrape do exist in the HTML structure.

Now, let’s delve into why you might be facing this issue:

Potential Reasons for ‘None’ or Empty Results

There are several reasons why you might be getting ‘None’ or empty results when scraping a website:

1. Page Load Timing

Web scraping relies on parsing the HTML content of a web page. If the content you are trying to scrape is loaded dynamically via JavaScript after the initial page load, BeautifulSoup, which operates on static HTML, may not capture the data.

To check if this is the case, you can inspect the page’s source code (right-click and select “View Page Source”) and compare it with what you see in your browser’s developer tools (right-click and select “Inspect”).

2. HTML Structure Changes

Websites frequently update their structure, including class names, IDs, or tag hierarchy.

If the website you are scraping changes its HTML structure, your code may no longer be able to locate the desired elements. This can result in ‘None’ or empty results.

To address this, you should periodically inspect the website’s HTML structure and update your code accordingly.

3. Data Loading via AJAX Requests

Some websites load data via AJAX requests, which means the data you are interested in might not be present in the initial HTML response but is fetched separately.

In such cases, you may need to inspect the network requests made by the page and determine how to retrieve the data from these requests.

4. Server-side Rendering (SSR)

If a website uses server-side rendering (SSR) or a technology like JavaScript frameworks (e.g., React, Angular, Vue.js), it can complicate the scraping process. SSR generates HTML dynamically on the server, which can be challenging to scrape.

In such cases, you may need to use tools like Puppeteer to control a headless browser for scraping.

5. Bot Detection and CAPTCHA

Websites often employ bot detection mechanisms to prevent automated scraping.

If a website detects your scraping activity as suspicious, it may return ‘None’ or empty results or even block your IP address.

You can try setting headers in your requests to mimic a real browser and avoid aggressive scraping to mitigate this issue.

Troubleshooting Steps

To address these potential issues and improve the success of your web scraping efforts, consider the following steps:

  1. Check for Dynamic Loading: Verify if the data you want is loaded dynamically using JavaScript. If so, you may need to use a tool like Selenium to interact with the page as a user would.
  2. Inspect HTML Structure: Regularly inspect the website’s HTML structure to ensure it hasn’t changed. Update your code accordingly if you notice any changes.
  3. Examine Network Requests: Use your browser’s developer tools to monitor network requests and identify where the data you need is being fetched from.
  4. Handle SSR and JavaScript Frameworks: For websites with SSR or complex JavaScript frameworks, consider using headless browsers like Puppeteer to scrape data effectively.
  5. Respect Robots.txt: Always check a website’s robots.txt file to see if it permits scraping and adhere to any specified rules.
  6. User-Agent Headers: Set a user-agent header in your requests to simulate a real browser.
  7. Rate Limiting: Avoid aggressive scraping, which can trigger bot detection mechanisms. Implement rate limiting in your scraping code.

In summary, web scraping can be complex, and various factors can lead to ‘None’ or empty results.

By understanding these potential issues and following best practices, you can enhance the reliability and success of your web scraping projects.

Remember to stay informed about web scraping legality and ethical considerations when scraping websites.

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