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Introduction to Python BeautifulSoup

Web development, programming languages, Software testing & others

Installation of Python BeautifulSoup

Explanation on Installing python beautifulsoup is given below:

pip install beautifulsoup4 pip install lxml sudo pip install lxml pip install future sudo pip install future

Note: It becomes easier if you already have Python installers such as pip.

Accessing of the HTML Through a Webpage import requests r = requests.get(URL) print(r.content)

Let me elaborate on every piece of code for you:

Import the library requests.

Scraping the webpage of your desire by specifying the URL.

To the specified URL, send an HTTP request and save the response. The response object is called r.

r.content print is to be done later, which is the webpage’s raw HTML content and is not of ‘ string ’ type.

Parsing of the Content HTML import requests from bs4 import BeautifulSoup r = requests.get(URL) soup = BeautifulSoup(r.content, 'html5lib' ) print = (soup.prettify())

BeautifulSoup library has a really nice thing: HTML parsing libraries like html.parser, lxml, html5lib, and others can be built.

Understanding the Python BeautifulSoup with Examples

Example of python beautifulsoup better are given below:

All that is done here is to create a regex that matches phone numbers for the data that I found in the file and matches just a really basic email format. It is not a great regex. To grab HTML from a webpage, let us write code. Let us see how to parse through it. The below code sends a request of GET to the desired webpage and creates a beautifulsoup object with HTML.

import requests from bs4 import BeautifulSoup html_text = requests.get(vgm_url).text soup = BeautifulSoup(html_text,'html.parser')

Before writing the code for a parse, we will look into the HTML that the browser is being rendered. Pattern recognition and experimentation are required for a little web scraping as every webpage is different on its own. Let us download a bunch of MIDI files. Writing a code through a webpage to parse it usually helps through developer tools available in modern browsers. Inspecting HTML will help you figure out if you can access the data programmatically.

We are going to use findall() method for going through the links using regular expressions cause our goal is to get only the links containing MIDI files by filtering out and texts of such with no parenthesis. This allows us to exclude all the remixes and duplicates.

import re import requests from bs4 import BeautifulSoup html_text = requests.get(vgm_url).text soup = BeautifulSoup(html_text,’html.parser’) if __name__ == '__main__': attrs = { } count = 0 for track in tracks: print(track) count += 1 print(len(tracks))

The same, we need to look into iterating all the MIDI files and just understand how to download them by giving in a code. Adding a little donwload_track and calling the function to the above helps us to download the files through iterating all the MIDI files.

import re import requests from bs4 import BeautifulSoup html_text = requests.get(vgm_url).text soup = BeautifulSoup(html_text, 'html.parser') def download_track(count, track_element): #Get the title of the track from the HTML element track_title = track_element.text.strip().replace('/','-') download_url = '{}{}'.format(vgm_url, track_element['href']) file_name = '{}_{}.mid'.format(count,track_title) #Download the track r = requests.get(download_url,allow_redirects=True) with open(file_name, 'wb') as f: f.write(r.content) #Print to the console to keep track of how the scraping is coming along. print('Downloaded: {}'.format(track_title, download_url)) if __name__ == '__main__': attrs = { } count = 0 for track in tracks: print(track) count += 1 print(len(tracks))

Passing the object of BeautifulSoup, which represents HTML and linking to a MIDI file with a unique number along and using the filename and overcoming possible naming collisions.

Conclusion

If you want to get some data out of any webpage, BeautifulSoup is here for you. It helps you overcome the code hurdles of web scraping. A Python library that helps to get out the data from markup languages such as XML and HTML. Content parsing from the data is simply created using an object of BeautifulSoup.