This section provides an overview of what web-scraping is, and why a developer might want to use it.
It should also mention any large subjects within web-scraping, and link out to the related topics. Since the Documentation for web-scraping is new, you may need to create initial versions of those related topics.
When performing data science tasks, it’s common to want to use data found on the internet. You’ll usually be able to access this data via an Application Programming Interface(API) or in other formats. However, there are times when the data you want can only be accessed as part of a web page. In cases like this, a technique called web scraping comes into picture.
To apply this technique to get data from web-pages, we need to have basic knowledge about web-page structure and tags used in web-page development(i.e,
<div> etc.,). If you are new to web development you can learn it here.
So to start with web scrapping, we'll use a simple website. We'll use
requests module to get the web-page content OR source code.
import requests page = requests.get("http://dataquestio.github.io/web-scraping-pages/simple.html") print (page.content) ## shows the source code
Now we'll use bs4 module to scrap the content to get the useful data.
from bs4 import BeautifulSoup soup = BeautifulSoup(page.content, 'html.parser') print(soup.prettify()) ##shows source in html format
You can find the required tags using
inspect element tool in your browser.Now let's say you want to get all the data that is stored with
<li> tag.Then you can find it with the script
soup.find_all('li') # you can also find all the list items with class='ABC' # soup.find_all('p', class_='ABC') # OR all elements with class='ABC' # soup.find_all(class_="ABC") # OR all the elements with class='ABC' # soup.find_all(id="XYZ")
Then you can get the text in the tag using
for i in range(len(soup.find_all('li'))): print (soup.find_all('li')[i].get_text())
The whole script is small and pretty simple.
import requests from bs4 import BeautifulSoup page = requests.get("http://dataquestio.github.io/web-scraping-pages/simple.html") #get the page soup = BeautifulSoup(page.content, 'html.parser') # parse according to html soup.find_all('li') #find required tags for i in range(len(soup.find_all('li'))): print (soup.find_all('li')[i].get_text())