Web Scraping: Tips & Techniques for Data Harvesting in Python

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Web scraping is a technique used in data science to extract data from websites. Here’s a comprehensive list of tools, libraries, and techniques commonly used in web scraping:

1. Libraries for Web Scraping:

i. Beautiful Soup:

• A library for pulling data out of HTML and XML files. It provides Pythonic idioms for iterating, searching, and modifying the parse tree.
• Documentation: Beautiful Soup Documentation

ii. Requests:

• A simple HTTP library for making web requests in Python. It’s often used to fetch web pages before parsing them with Beautiful Soup.
• Documentation: Requests Documentation

import requests
from bs4 import BeautifulSoup

# Make a request to the website
url = "https://example.com"
response = requests.get(url)

# Parse the HTML content with Beautiful Soup
soup = BeautifulSoup(response.content, 'html.parser')

# Extract data from the parsed HTML
title = soup.title.text
print(f"Title: {title}")

iii. Selenium:

• A browser automation tool often used for dynamic web scraping. It can interact with websites like a user and is useful for pages with JavaScript-based…