Web scraping involves extracting data from websites. When sites are static, the Python library BeautifulSoup can parse the HTML and extract information easily. However, many modern sites use JavaScript to load content dynamically. In these cases, Selenium may be necessary to automate a browser and render the full page before scraping.
When to Use BeautifulSoup
BeautifulSoup is a very popular Python library for web scraping. It allows you to parse a website's HTML and extract the data you need through various search and traversal methods.
Some key advantages of BeautifulSoup:
If the content you want exists in the initial HTML, BeautifulSoup is a great choice:
from bs4 import BeautifulSoup
soup = BeautifulSoup(requests.get("http://example.com").text, 'html.parser')
print(soup.find("h1").text)
When Selenium is Necessary
However, many websites today rely on JavaScript to dynamically load content. This content won't exist until the JavaScript executes in a browser. In these cases, Selenium can automate a browser like Chrome and load the full JavaScript-rendered page before parsing:
from selenium import webdriver
from bs4 import BeautifulSoup
driver = webdriver.Chrome()
driver.get("http://example.com")
soup = BeautifulSoup(driver.page_source, 'html.parser')
Selenium introduces more complexity with browser automation but enables scraping dynamic SPAs and sites relying on JS.
Bottom Line
Prefer BeautifulSoup when possible for its speed and ease-of-use. But when sites load content dynamically through JavaScript, Selenium + BeautifulSoup together are effective for rendering pages fully before scraping.