May 7th, 2020
Copy of Scraping Reddit with Python and Beautiful Soup

Today we are going to see how we can scrape Reddit posts using Python and BeautifulSoup is a simple and elegant manner.

This article aims to get you started on a real-world problem solving while keeping it super simple, so you get familiar and get practical results as fast as possible.

So the first thing we need is to make sure we have Python 3 installed. If not, you can just get Python 3 and get it installed before you proceed.

Then you can install beautiful soup.

pip3 install beautifulsoup4

We will also need the library's requests, lxml, and soupsieve to fetch data, break it down to XML, and to use CSS selectors. Install them using.

pip3 install requests soupsieve lxml

Once installed, open an editor and type in.

# -*- coding: utf-8 -*-
from bs4 import BeautifulSoup
import requests

Now let's go to the programming subreddit and inspect the data we can get.

This is how it looks.

Back to our code now. Let's try and get this data by pretending we are a browser like this.

# -*- coding: utf-8 -*-
from bs4 import BeautifulSoup
import requests

headers = {'User-Agent':'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_2) AppleWebKit/601.3.9 (KHTML, like Gecko) Version/9.0.2 Safari/601.3.9'}
url = 'https://www.reddit.com/r/programming/'

response=requests.get(url,headers=headers)
print(response.text())

Save this as reddit_bs.py.

If you run it

python3 reddit_bs.py

You will see the whole HTML page.

Now, let's use CSS selectors to get to the data we want. To do that, let's go back to Chrome and open the inspect tool. You can see that all the post title elements have a class called review-title in them.

Let's use CSS selectors to get this data like so.

# -*- coding: utf-8 -*-
from bs4 import BeautifulSoup
import requests

headers = {'User-Agent':'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_2) AppleWebKit/601.3.9 (KHTML, like Gecko) Version/9.0.2 Safari/601.3.9'}
url = 'https://www.reddit.com/r/programming/'

response=requests.get(url,headers=headers)


soup=BeautifulSoup(response.content,'lxml')

print(soup.select('._eYtD2XCVieq6emjKBH3m')[0].get_text())

This will print the title of the first post's title. We now need to get to all the posts. We notice that the

with the class 'Post' (amongst others) holds all the individual data together.

To get to them individually, we run through them like this and try and get to the post title from 'inside' the 'Post.'

# -*- coding: utf-8 -*-
from bs4 import BeautifulSoup
import requests

headers = {'User-Agent':'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_2) AppleWebKit/601.3.9 (KHTML, like Gecko) Version/9.0.2 Safari/601.3.9'}
url='https://www.reddit.com/r/programming/'
response=requests.get(url,headers=headers)


soup=BeautifulSoup(response.content,'lxml')

#print(soup.select('.Post')[0].get_text())

for item in soup.select('.Post'):
	try:
		print('----------------------------------------')
		print(item.select('._1rZYMD_4xY3gRcSS3p8ODO')[0].get_text())


	except Exception as e:
		#raise e
		print('')

And when you run it, you get.

Bingo!! We got the post titles.

Now with the same process, we get the class names of all the other data like post votes, the number of comments, link to it, etc.

# -*- coding: utf-8 -*-
from bs4 import BeautifulSoup
import requests

headers = {'User-Agent':'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_2) AppleWebKit/601.3.9 (KHTML, like Gecko) Version/9.0.2 Safari/601.3.9'}
url='https://www.reddit.com/r/programming/'
response=requests.get(url,headers=headers)


soup=BeautifulSoup(response.content,'lxml')

#print(soup.select('.Post')[0].get_text())

for item in soup.select('.Post'):
	try:
		print('----------------------------------------')
		print(item.select('._1rZYMD_4xY3gRcSS3p8ODO')[0].get_text())
		print(item.select('._eYtD2XCVieq6emjKBH3m')[0].get_text())
		print(item.select('.FHCV02u6Cp2zYL0fhQPsO')[0].get_text())
 		print(item.select('._2INHSNB8V5eaWp4P0rY_mE a[href]')[0]['href'])

	except Exception as e:
		#raise e
		print('')

That, when run, should print everything we need from each post like this.

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