如何用Python的BeautifulSoup遍历XML中的表格区块？

Got it, let's walk through exactly how to parse and iterate through that TV guide table structure using BeautifulSoup. Here's a practical, step-by-step approach:

Step 1: Setup and Initialize BeautifulSoup #

First, make sure you've imported BeautifulSoup and have your target HTML/XML content ready (whether scraped from a URL or stored as a string).

from bs4 import BeautifulSoup

# Example content matching your structure (expand with full content as needed)
content = """
<h2>Fri 4 May</h2>
<table cellspacing="0" cellpadding="12"> 
  <tr> 
    <td class="time ">6:00am</td> 
    <td class="other-details "> 
      <a class="prog-link" href="http://www.tvguide.co.uk/m-detail/157702075/137913159/breakfast" id="308829348" > 
        <div class="title" style="border-left:4px solid #CE3D32"> Breakfast </div> 
        <div class="detail"> A round-up of national and interna...</div>
      </a>
    </td>
  </tr>
  <!-- Add more rows from your actual content here -->
</table>
"""

# Initialize parser: use 'html.parser' for HTML-like content, 'lxml-xml' for strict XML
soup = BeautifulSoup(content, 'html.parser')

Step 2: Locate the Target Table #

Since the table is tied to a specific date (<h2>Fri 4 May</h2>), we can link the two to ensure we're parsing the correct table (critical if there are multiple tables on the page):

# Find the date heading first
date_heading = soup.find('h2', string='Fri 4 May')
# Grab the immediately following table
target_table = date_heading.find_next('table', {'cellspacing': '0', 'cellpadding': '12'})

# Alternative: If there's only one table matching those attributes, skip the heading step:
# target_table = soup.find('table', {'cellspacing': '0', 'cellpadding': '12'})

Step 3: Iterate Through Rows and Extract Data #

Loop through each <tr> in the table to pull out time, title, details, and link for each program:

for row in target_table.find_all('tr'):
    # Extract show time
    time_cell = row.find('td', class_='time')
    show_time = time_cell.get_text(strip=True) if time_cell else "No time listed"
    
    # Extract program details cell
    details_cell = row.find('td', class_='other-details')
    if details_cell:
        # Get program link
        prog_link = details_cell.find('a', class_='prog-link')
        link_url = prog_link['href'] if prog_link else "No link available"
        
        # Get program title
        title_div = prog_link.find('div', class_='title')
        show_title = title_div.get_text(strip=True) if title_div else "No title listed"
        
        # Get program description
        detail_div = prog_link.find('div', class_='detail')
        show_description = detail_div.get_text(strip=True) if detail_div else "No description available"
        
        # Output or process the data (adjust as needed)
        print(f"📅 {date_heading.get_text(strip=True)}")
        print(f"⏰ {show_time}")
        print(f"🎬 {show_title}")
        print(f"ℹ️ {show_description}")
        print(f"🔗 {link_url}")
        print("---")

Key Notes for Robustness #

• Handle missing elements: Use conditional checks (like if time_cell) to avoid AttributeError if a cell or tag is missing in some rows.
• Clean text: get_text(strip=True) removes extra whitespace, newlines, and tabs from the extracted text.
• Parser choice: If you're working with strict XML instead of HTML, swap 'html.parser' with 'lxml-xml' (you'll need the lxml library installed for this).

内容的提问来源于stack exchange，提问作者gdogg371