Two popular Python libraries used for web scraping are Scrapy and BeautifulSoup. But which one is faster for scraping data? Here's an in-depth comparison.
What is Scrapy?
Scrapy is a dedicated web crawling and scraping framework for Python. Key features:
For example:
import scrapy
class BookSpider(scrapy.Spider):
name = 'books'
def start_requests(self):
urls = [
'http://books.toscrape.com/catalogue/page-1.html',
'http://books.toscrape.com/catalogue/page-2.html',
]
for url in urls:
yield scrapy.Request(url=url, callback=self.parse)
def parse(self, response):
for book in response.css('article.product_pod'):
yield {
'title': book.xpath('./h3/a/@title').get(),
'price': book.css('p.price_color::text').get(),
} This spider crawls multiple pages and scrapes book titles and prices.
What is BeautifulSoup?
BeautifulSoup is a popular Python library used to parse HTML and XML documents. Key features:
For example:
from bs4 import BeautifulSoup
import requests
url = 'http://books.toscrape.com/catalogue/page-1.html'
response = requests.get(url)
soup = BeautifulSoup(response.text, 'html.parser')
titles = soup.find_all(class_='product_pod')
for title in titles:
print(title.h3.a['title'])
print(title.find(class_='price_color').get_text())This scrapes book titles and prices from a single page.
Verdict: Scrapy is Faster
While both libraries can scrape data, Scrapy is faster for large scale web scraping because:
BeautifulSoup parses single pages well but lacks Scrapy's performance optimizations for large crawls.
In summary, Scrapy is a faster dedicated web scraping framework while BeautifulSoup excels at parsing HTML/XML.