How to Solve BeautifulSoup HTMLParser Fail

When working with HTML data, one common task is parsing and removing HTML tags to extract the plain text. If you’ve ever tried to do this with Python’s built-in HTMLParser library, you may have encountered an error that left you scratching your head. I’ll walk you through the issue I faced when using HTMLParser to strip HTML tags and how I solved it by switching to a more robust solution, BeautifulSoup.

Understanding the Code

To start, here’s the code I used that originally worked well in many cases. The idea is to strip the HTML tags from a string using Python’s built-in HTMLParser:

from HTMLParser import HTMLParser

class MLStripper(HTMLParser):
    def __init__(self):
        self.reset()  # Resets the parser
        self.fed = []  # List to store parsed data

    def handle_data(self, d):
        self.fed.append(d)  # Adds parsed text to the list

    def get_data(self):
        return ''.join(self.fed)  # Joins the list into a single string

def strip_tags(html):
    s = MLStripper()  # Creates a new instance of the parser
    s.feed(html)  # Feeds the HTML content to the parser
    return s.get_data()  # Returns the cleaned text without HTML tags

What Does This Code Do?

1. MLStripper Class: This class inherits from HTMLParser. It overrides the handle_data method to capture the text content between HTML tags.
2. strip_tags Function: This function creates an instance of MLStripper and feeds the provided HTML into it. The get_data() method then returns the cleaned text without the HTML tags.

Code Error

Everything worked fine until I tried parsing a specific file (0001005214-12-000007.txt). The error I encountered was:

HTMLParser.HTMLParseError: unknown status keyword 't\n' in marked section, at line 35210, column 58

This error happened because the HTMLParser encountered a part of the HTML that it couldn’t process, specifically an unknown keyword (‘t\n’) within an HTML comment or declaration. The HTMLParser was not able to handle this particular situation, causing it to fail.

Why Does This Happen?

The HTMLParser library, although useful for basic HTML parsing, is relatively old and not very robust when it comes to handling modern or malformed HTML. It cannot process complex or non-standard HTML declarations, comments, or malformed tags. In my case, it encountered a keyword in a comment that it didn’t recognize, leading to the error.

Switching to BeautifulSoup

To avoid this error and make the HTML parsing more flexible and robust, I decided to switch to BeautifulSoup. BeautifulSoup is a more powerful and user-friendly HTML parser that can handle a variety of edge cases and malformed HTML without throwing errors.

Installing BeautifulSoup

If you don’t already have BeautifulSoup installed, you can install it using pip:

pip install beautifulsoup4

Modified Code with BeautifulSoup

from bs4 import BeautifulSoup

def strip_tags(html):
    soup = BeautifulSoup(html, 'html.parser')
    return soup.get_text()

# Usage
with open('0001005214-12-000007.txt', 'r') as fdir:
    text = fdir.read()
    clean_text = strip_tags(text)
    print(clean_text)

Explanation of Changes

1. BeautifulSoup: This is a more flexible HTML parser that can handle all kinds of HTML, even malformed ones. It’s much better at managing unexpected tags, comments, or strange encodings.
2. get_text(): This method retrieves all the text from the HTML, leaving out the tags.
3. File Handling: I used the with open statement, which ensures that the file is automatically closed once it’s no longer needed.

Additional Practice Functionality

To make the parsing more versatile, I added a few enhancements to the functionality:

Strip Specific Tags

Sometimes you may want to keep the text but remove specific HTML tags like <style> or <script>. You can do this by passing a list of tags to remove.

strip_tags_custom(html, tags_to_remove):
    soup = BeautifulSoup(html, 'html.parser')
    for tag in tags_to_remove:
        for match in soup.findAll(tag):
            match.extract()  # Removes the tag but keeps the content
    return soup.get_text()

# Example Usage
with open('0001005214-12-000007.txt', 'r') as fdir:
    text = fdir.read()
    clean_text = strip_tags_custom(text, ['style', 'script'])
    print(clean_text)

Handling Nested Tags

You can also unwrap nested tags while keeping their content intact:

strip_tags_nested(html):
    soup = BeautifulSoup(html, 'html.parser')
    for tag in soup.findAll(True):  # Find all tags
        tag.unwrap()  # Removes the tag but keeps its content
    return soup.get_text()

# Example Usage
with open('0001005214-12-000007.txt', 'r') as fdir:
    text = fdir.read()
    clean_text = strip_tags_nested(text)
    print(clean_text)

In this case, unwrap() is used to remove the tags but keep their content.

Handling Encoding Issues

If you’re working with files that might have encoding issues, you can ensure the text is properly decoded.

open('0001005214-12-000007.txt', 'r', encoding='utf-8', errors='ignore') as fdir:
    text = fdir.read()
    clean_text = strip_tags(text)
    print(clean_text)

Here, encoding='utf-8' ensures the file is read with the correct encoding, and errors='ignore' skips any invalid characters instead of causing errors.

Final Thought

Switching to BeautifulSoup significantly improved the reliability and flexibility of my HTML parsing, especially when handling malformed or complex HTML files. Unlike HTMLParser, which is limited in its capabilities, BeautifulSoup can handle edge cases like unknown status keywords or malformed tags, making it a far better choice for modern HTML parsing in Python.