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How to Find HTML Elements by Tag, Class, ID, CSS Selector, and Attribute in BeautifulSoup
Parse an HTML string with BeautifulSoup and demonstrate five distinct ways to locate elements: by tag name, by class, by ID, by CSS selector, and by attribute.
from bs4 import BeautifulSoup
html_content = """
<html><body>
<h1 id="title" class="heading">Hello World</h1>
<p class="content">First paragraph</p>
<p class="content special">Second paragraph</p>
<a href="https://example.com" class="link">Click here</a>
<div id="footer">
<p>© 2024</p>
…
How to Scrape Headlines from a News Website Using Beautiful Soup in Python
Scrape headline text from a news website using requests and Beautiful Soup with a CSS selector.
import requests
from bs4 import BeautifulSoup
def scrape_headlines(url: str, selector: str) -> list:
"""
Scrape headlines from a news website using Beautiful Soup.
Args:
url: The URL of the news website.
selector: CSS selector for headline elements.
Returns:
List of h…
Build a Complete Web Scraper with Requests and BeautifulSoup in Python
Scrape multiple paginated pages from a website using Requests and BeautifulSoup, with retry logic, error handling, and CSV export.
import requests
from bs4 import BeautifulSoup
import csv
import time
from typing import List, Dict, Optional
class WebScraper:
def __init__(self, base_url: str, output_file: str = "scraped_data.csv"):
self.base_url = base_url
self.output_file = output_file
self.session = requests.Session()…
Convert HTML Tables to Excel Reports in Python
Convert HTML tables into formatted Excel reports using BeautifulSoup and Pandas with auto-adjusted column widths.
import pandas as pd
from bs4 import BeautifulSoup
from pathlib import Path
def html_table_to_excel(html_file: str, excel_file: str) -> None:
"""Convert HTML table to formatted Excel report."""
with open(html_file, 'r', encoding='utf-8') as f:
html_content = f.read()
soup = BeautifulSoup(html_…
Discover RSS Feeds From Any Website in Python
Scrape a website's HTML to automatically find all linked RSS or Atom feed URLs using requests, BeautifulSoup, and regex.
import requests
import re
from urllib.parse import urljoin, urlparse
from bs4 import BeautifulSoup
def discover_rss_feeds(url):
"""Discover all RSS/Atom feeds linked from a given website."""
try:
headers = {'User-Agent': 'Mozilla/5.0 (compatible; RSSDiscovery/1.0)'}
response = requests.get(url…
Download Images from a Web Page Automatically in Python
Scrape all images from a webpage, filter by extension, and save them to a local folder using requests and BeautifulSoup.
import requests
from bs4 import BeautifulSoup
from urllib.parse import urljoin
import os
def download_images(url, output_folder="downloaded_images"):
"""Download all images from a given URL."""
os.makedirs(output_folder, exist_ok=True)
response = requests.get(url)
response.raise_for_status()
…
Find Broken Image References Across a Website in Python
Crawl internal pages of a website, collect all image source URLs, then check each with HEAD requests to report any that return HTTP 4xx or connection errors.
import requests
from urllib.parse import urljoin, urlparse
from bs4 import BeautifulSoup
from concurrent.futures import ThreadPoolExecutor, as_completed
def find_all_links(base_url, max_pages=50):
visited, to_visit = set(), {base_url}
while to_visit and len(visited) < max_pages:
url = to_visit.pop()
…
How to Create a Link Graph Visualization for Any Website in Python
A Python script that crawls a website's internal links, builds a directed graph of parent-child URL relationships, and prints the graph to the console.
import requests
from bs4 import BeautifulSoup
from collections import defaultdict
from urllib.parse import urljoin, urlparse
import sys
def get_links(url, max_links=20):
try:
response = requests.get(url, timeout=5)
soup = BeautifulSoup(response.text, 'html.parser')
base_url = f"{urlparse(u…
Extract Schema.org Structured Data from Any Website in Python
A Python tool that fetches a webpage and extracts all JSON-LD structured data (Schema.org) embedded in <script> tags with type="application/ld+json".
import requests
from bs4 import BeautifulSoup
import json
def extract_schema_org(url):
"""Extract structured data (Schema.org) from a website."""
try:
response = requests.get(url, timeout=10)
response.raise_for_status()
except requests.exceptions.RequestException as e:
return {"err…
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