Parsing HTML Tables with BeautifulSoup in Python - Handling Inconsistent Row Structures
I'm refactoring my project and I'm trying to parse a series of HTML tables from a webpage using BeautifulSoup (version 4.10.0). The challenge I'm facing is that the tables have inconsistent row structures; some rows contain a different number of columns than others, and some cells have nested elements that I need to extract. My goal is to extract the text from each cell while ignoring any nested tags. Here's a snippet of the HTML I'm working with: ```html <table> <tr> <td>Row 1 Col 1</td> <td>Row 1 Col 2</td> </tr> <tr> <td>Row 2 Col 1</td> <td><span>Row 2 Col 2 Nested</span></td> <td>Row 2 Col 3</td> </tr> <tr> <td>Row 3 Col 1</td> <td>Row 3 Col 2</td> </tr> </table> ``` I’ve tried the following code: ```python from bs4 import BeautifulSoup html = '''<table>...</table>''' # The HTML snippet goes here soup = BeautifulSoup(html, 'html.parser') table = soup.find('table') rows = table.find_all('tr') for row in rows: cols = row.find_all('td') col_data = [col.get_text(strip=True) for col in cols] print(col_data) ``` However, I noticed that this approach leads to inconsistent lists being printed, and I'm getting empty strings for rows that don't have columns due to missing data. Ideally, I want my output to look like this: ``` ['Row 1 Col 1', 'Row 1 Col 2'] ['Row 2 Col 1', 'Row 2 Col 2 Nested', 'Row 2 Col 3'] ['Row 3 Col 1', 'Row 3 Col 2'] ``` But the code outputs lists of varying lengths, which makes it hard to process further. Is there a way to handle these inconsistencies in row structures more gracefully? Also, how can I ensure I only extract the visible text and not any nested HTML elements? I recently upgraded to Python stable.