Web scraping is a database extraction/scraping technique. This technique focuses mostly on turning unstructured data (HTML format) into structured data on the Internet.
There are hundreds of web scraping packages out there, but you need only a handful to scrap nearly any site. This guide is an opinionated one. We have decided to feature the most famous web scraping Python libraries that we like the most. We cover all the important bases together, and they are well-documented.
Do I Need to Learn From Any of the Libraries Below?
No, but everybody is going to need requests because that is how you communicate with websites. The rest of the cases depend on your use.
- You should learn at least one thing about Beautiful Soup or lxml. Choose which one is more intuitive for you (more on this below).
- Learn Selenium if you need Java Script-hidden data scraping sites.
- Learn Scrapy if you need to build a real spider or web-crawler, instead of just scraping a couple of pages here and there.
Below Are Some Famous Python Libraries Used for Web Scraping
- The Restaurant: Selenium
- The Chef: Scrapy
- The Stew: Beautiful soup 4
- The Salad: lxml
The Restaurant: Selenium
You may need to go to a restaurant to eat certain dishes. The farm is great, but you cannot find everything out there.
Other sites can allow you to click through forms before displaying their contents. Alternatively, choose the options from a dropdown. Alternatively, do a tribal rain dance… you’re going to need something more powerful for these sites. You are going to need Selenium (which can accommodate everything except tribal rain dancing).
Selenium is a browser-automated tool, also known as a web-driver. You can open a Google Chrome window, visit a site, and click on a link. Pretty cool, huh?
It also comes with Python bindings to manage it right from your application. This makes it easy to integrate with your chosen parsing library.
- Python selenium – Documentation for Python selenium bindings.
- Selenium web scraping – Excellent, in-depth 3
- part tutorial on the scraping of Selenium websites.
- Scraping hotel prices – Script snippet for scraping hotel prices using Selenium and lxml.
The Chef: Scrapy
What if you need a total spider that can systematically crawl through websites?
Introducing: Scrapy! Technically, scrapy is not even a library… it is a complete framework for web scraping. This means that you can use it to manage requests, preserve user sessions, follow redirects, and manage output pipelines.
It also means that you can swap out individual modules with other Python web scraping libraries. For example, if you need to insert Selenium to scrape dynamic web pages, you can do that.
If you need your crawler to be reused, scale it up, manage complex data pipelines or cook some other sophisticated spider, then Scrapy was made for you.
The Stew: Beautiful Soup 4
Beautiful Soup (BS4) is a library for parsing, which can use various parsers. A parser is simply a program capable of extracting data from both HTML and XML documents.
The default parser for Beautiful Soup comes from a standard library for Python. It is flexible and forgiving, but somewhat slow. The good news is that if you need the speed, you can swap its parser to a faster one.
One advantage of BS4 is its ability to detect encoding automatically. This enables it to handle HTML documents gracefully with special characters.
BS4 can also help you navigate a parsed document, and find out what you need. That makes building common applications quick and painless. For example, if you wanted to find all the links on the web page that we pulled down earlier, that is just a few lines.
from bs4 import BeautifulSoup soup = BeautifulSoup(contents, 'html.parser') soup.find_all('a')
This wonderful simplicity has made it one of the most popular web scraping libraries on Python!
The Salad: lxml
lxml is an HTML and XML parsing library of high performance, output standard. We call it The Salad, because you can rely on it to be healthy for you, regardless of which diet you adopt.
We enjoyed using lxml the most among all the Python web scraping libraries. It is clear, fast, and rich in features.
Even so, if you have experience with either XPaths or CSS, it is quite easy to pick up. The raw speed and power have led to its widespread adoption in the industry.
Beautiful soup Vs Lxml
- If you need acceleration, go for lxml.
- Choose Beautiful Soup, if you need to manage messy papers.
However, that distinction does not hold anymore. Beautiful Soup now uses the lxml parser to support it, and vice versa. It is also pretty easy to learn others once you have mastered this.
So to begin with, we suggest that you try both and pick the one that feels more comfortable for you.
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