find_all() in BeautifulSoup returns empty ResultSet - python-3.x

Question

I am trying to scrape data from a website for practicing web scraping.But the findall() returns empty set. How can I resolve this issue?
#importing required modules
import requests,bs4
#sending request to the server
req = requests.get("https://www.udemy.com/courses/search/?q=python")
# checking the status on the request
print(req.status_code)
req.raise_for_status()
#converting using BeautifulSoup
soup = bs4.BeautifulSoup(req.text,'html.parser')
#Trying to scrape the particular div with the class but returning 0
container = soup.find_all('div',class_='popover--popover--t3rNO popover--popover-hover--14ngr')
#trying to print the number of container returned.
print(len(container))
Output :
200
0

Answer 1

See my comment about it being entirely javascript driven content. Modern websites often will use javascript to invoke HTTP requests to the server to grab data on demand when needed. Here if you disable javascript which you can easily do in chrome by going to more settings when you inspect the page. You will see that NO text is available on this website. Which is probably much different to imdb as you pointed out. If you check the beautifulsoup parsed html, you'll see you don't have any of the actual page source derived with javascript.
There are two ways to get data from a javascript rendered website
Mimic the HTTP request to the server
Browser automation package like selenium
The first option is better and more efficient, as the second option is more brittle and not great for larger data sets.
Fortunately udemy is getting the data you want from an API endpoint which it uses javascript to make HTTP requests to and the response back gets fed to the browser.
Code Example
import requests
cookies = {
'__udmy_2_v57r': '4f711b308da548b49394854a189d3179',
'ud_firstvisit': '2020-05-29T13:48:56.584511+00:00:1jefNY:9F1BJVEUJpv7gmNPgYNini76UaE',
'existing_user': 'true',
'optimizelyEndUserId': 'oeu1590760136407r0.2130390415126655',
'EUCookieMessageShown': 'true',
'_ga': 'GA1.2.1359933509.1590760142',
'_pxvid': '26d89ed1-a1b3-11ea-9179-cb750fa4136b',
'_ym_uid': '1585144165890161851',
'_ym_d': '1590760145',
'__ssid': 'd191bc02a1063fd2c75fbab525ededc',
'stc111655': 'env:1592304425%7C20200717104705%7C20200616111705%7C1%7C1014616:20210616104705|uid:1590760145861.374775813.04725504.111655.1839745362:20210616104705|srchist:1069270%3A1%3A20200629134905%7C1014624%3A1592252104%3A20200716201504%7C1014616%3A1592304425%3A20200717104705:20210616104705|tsa:0:20200616111705',
'ki_t': '1590760146239%3B1592304425954%3B1592304425954%3B3%3B5',
'ki_r': 'aHR0cHM6Ly93d3cuZ29vZ2xlLmNvbS8%3D',
'IR_PI': '00aea1e6-9da9-11ea-af3a-42010a24660a%7C1592390825988',
'_gac_UA-12366301-1': '1.1592304441.CjwKCAjw26H3BRB2EiwAy32zhfcltNEr_HHFK5JRaJar5qxUn4ifG9FVFctWyTUXigNZvKeOCz7PgxoCAfAQAvD_BwE',
'csrftoken': 'pPOdtdbH0HPaHvDfAZMzEOdvWqKZuQWufu8dUrEeXuy5mOOrnFRbWZ9vq8Dfd2ts',
'__cfruid': 'f1963d736e3891a2e307ebc9f918c89065ffe40f-1596962093',
'__cfduid': 'df4d951c87bc195c73b2f12b5e29568381597085850',
'ud_cache_price_country': 'GB',
'ud_cache_device': 'desktop',
'ud_cache_language': 'en',
'ud_cache_logged_in': '0',
'ud_cache_release': '0804b40d37e001f97dfa',
'ud_cache_modern_browser': '1',
'ud_cache_marketplace_country': 'GB',
'ud_cache_brand': 'GBen_US',
'ud_cache_version': '1',
'ud_cache_user': '',
'seen': '1',
'eventing_session_id': '66otW5O9TQWd5BYq1_etrA-1597087737933',
'ud_cache_campaign_code': '',
'exaff': '%7B%22start_date%22%3A%222020-08-09T08%3A52%3A04.083577Z%22%2C%22code%22%3A%22_7fFXpljNdk-m3_OJPaWBwAQc5gVKutaSg%22%2C%22merchant_id%22%3A39197%2C%22aff_type%22%3A%22LS%22%2C%22aff_id%22%3A60680%7D:1k5D3W:2PemPLTm4xaHixBYRvRyBaAukL4',
'evi': 'SlFfLh4RBzwTSVBjXFdHehNJUGMYQE99HVFdIExYQ3gARVY8QkAWIEEDCXsVQEd0BEsJexVAA24LQgdjGANXdgZBG3ETH1luRBdHKBoHV3ZKURl5XVBXdkpRXWNUU1luRxIJe1lTQXhMDgdjHRAFbgsICXNWVk1uCwgJN0xYRGATBUpjVFVEdAEOB2NcWkR+E0lQYxhAT30dUV0gTFhCfAhDVm1MUEJ0B1EROkwUV3YAXwk3D0BPewFAHzxCQEd0BUcJexVAA24LQgdjGANXdgZCHHETTld+BkUdY1QZVzoTSRptTBQUbgtFEnleHwhgEwBcY1QZV34HShtjVBlXOhNJE21MFBRuC0UceV4fWW4DSxh3TFgObkdREXBCQAMtE0kccFtUCGATQR54VkBPNxMFCXtfTlc6UFERd1tUTTEdURlzX1JXdkpRXWNUU1luRxIJe1tXQnpMXwlzVldDbgsICTdMWEdgEwVKY1RVRHUJDgdjXFdCdBNJUGMYQE99HVFdIExYQ3kCQ1Y8Ew==',
'ud_rule_vars': 'eJyFjkuOwyAQBa9isZ04agyYz1ksIYxxjOIRGmhPFlHuHvKVRrPItvWqus4EXT4EDJP9jSViyobPktKRgZqc4GrkmmmuBHdU6YlRqY1P6RgDMQ05D2SOueCDtZPDMNT7QDrooAXRdrqhzHBlRL8XUjPgXwAGYCC7ulpdRX3acglPA8bvPwbVgm6g4p0Bvqeyhsh_BkybXyxmN8_R21J9vvpcjm5cn7ZDTidc7G2xxnvlm87hZwvlU7wE2VP1en0hlyuoG10j:1k5D3W:nxRv-tyLU7lxhsF2jRYvkJA53uM',
}
headers = {
'authority': 'www.udemy.com',
'x-udemy-cache-release': '0804b40d37e001f97dfa',
'x-udemy-cache-language': 'en',
'x-udemy-cache-user': '',
'x-udemy-cache-modern-browser': '1',
'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/84.0.4147.105 Safari/537.36',
'accept': 'application/json, text/plain, */*',
'x-udemy-cache-brand': 'GBen_US',
'x-udemy-cache-version': '1',
'x-requested-with': 'XMLHttpRequest',
'x-udemy-cache-logged-in': '0',
'x-udemy-cache-price-country': 'GB',
'x-udemy-cache-device': 'desktop',
'x-udemy-cache-marketplace-country': 'GB',
'x-udemy-cache-campaign-code': '',
'sec-fetch-site': 'same-origin',
'sec-fetch-mode': 'cors',
'sec-fetch-dest': 'empty',
'referer': 'https://www.udemy.com/courses/search/?q=python',
'accept-language': 'en-US,en;q=0.9',
}
params = (
('q', 'python'),
('skip_price', 'false'),
)
response = requests.get('https://www.udemy.com/api-2.0/search-courses/', headers=headers, params=params, cookies=cookies)
ids = []
titles = []
durations = []
ratings = []
for a in response.json()['courses']:
title = a['title']
duration =int(a['estimated_content_length']) / 60
rating = a['rating']
id = str(a['id'])
titles.append(title)
ids.append(id)
durations.append(duration)
ratings.append(rating)
clean_ids = ','.join(ids)
params2 = (
('course_ids', clean_ids),
('fields/[pricing_result/]', 'price,discount_price,list_price,price_detail,price_serve_tracking_id'),
)
response = requests.get('https://www.udemy.com/api-2.0/pricing/', params=params2)
data = response.json()['courses']
prices = []
for a in ids:
price = response.json()['courses'][a]['price']['amount']
prices.append(price)
data = zip(titles, durations,ratings, prices)
for a in data:
print(a)
Output
('Learn Python Programming Masterclass', 56.53333333333333, 4.54487, 14.99)
('The Python Mega Course: Build 10 Real World Applications', 25.3, 4.51476, 16.99)
('Python for Beginners: Learn Python Programming (Python 3)', 2.8833333333333333, 4.4391, 17.99)
('The Python Bible™ | Everything You Need to Program in Python', 9.15, 4.64238, 17.99)
('Python for Absolute Beginners', 3.066666666666667, 4.42209, 14.99)
('The Modern Python 3 Bootcamp', 30.3, 4.64714, 16.99)
('Python for Finance: Investment Fundamentals & Data Analytics', 8.25, 4.52908, 12.99)
('The Complete Python Course | Learn Python by Doing', 35.31666666666667, 4.58885, 17.99)
('REST APIs with Flask and Python', 17.033333333333335, 4.61233, 12.99)
('Python for Financial Analysis and Algorithmic Trading', 16.916666666666668, 4.53173, 12.99)
('Python for Beginners with Examples', 4.25, 4.27316, 12.99)
('Python OOP : Four Pillars of OOP in Python 3 for Beginners', 2.6166666666666667, 4.46451, 12.99)
('Python Bootcamp 2020 Build 15 working Applications and Games', 32.13333333333333, 4.2519, 14.99)
('The Complete Python Masterclass: Learn Python From Scratch', 32.36666666666667, 4.39151, 16.99)
('Learn Python MADE EASY : A Concise Python Course in Python 3', 2.1166666666666667, 4.76601, 12.99)
('Complete Python Web Course: Build 8 Python Web Apps', 15.65, 4.37577, 13.99)
('Python for Excel: Use xlwings for Data Science and Finance', 16.116666666666667, 4.92293, 12.99)
('Python 3 Network Programming - Build 5 Network Applications', 12.216666666666667, 4.66143, 12.99)
('The Complete Python & PostgreSQL Developer Course', 21.833333333333332, 4.5664, 12.99)
('The Complete Python Programmer Bootcamp 2020', 13.233333333333333, 4.63859, 12.99)
Explanation
There are two ways to do this, here is re-engineering the requests which is the more efficient solution. To get the necessary information, you'll need to inspect the page and look at which HTTP requests give which information. You can do this through the network tools --> XHR when you inspect the page. You can see there are two requests that give you information. My suggestion would be look at the previews of the responses on the right hand side when you select the request. The first gives you the title, duration, price, ratings and the second request you need the id's of the courses to get the prices of the courses.
I usually copy the CURL of the HTTP requests the javascript invokes into curl.trillworks.com and this converts the necessary headers, parameters and cookies to python format.
In the first request, headers, cookies and parameters are required. THe second request, only requires the parameters.
The response you get is a json object. response.json() converts this into a python dictionary. You have to do abit of digging in this dictionary to get what you want. But for each item in response.json()['courses'] all the necessary data for each 'card' on the website is there. So we do a for loop around where the data sits in the dictionary we've created. I would play around the with response.json() till you get a feel for what the object gives you to understand the code.
The duration comes in minutes therefore I've done a quick convert to hours here. Also the id's need to be a string because in the second request we use them as parameters to get the necessary prices for the courses. We convert ids into a string and feed this as a parameter.
The second request then gives us the necessary prices, again you have to go digging in the dictionary object and I suggest you do this yourself to confirm that nested in that is the price.
The data we zip up to combine all the lists of data and then I've done a for loop to print it all. You could feed this into pandas if you wanted etc...

Answer 2

To get required data you need to send requests to appropriate API. For that you need to create Session:
import requests
s = requests.Session()
cookies = s.get('https://www.udemy.com').cookies
headers={"Referer": "https://www.udemy.com/courses/search/?q=python&skip_price=false"}
for page_counter in range(1, 500):
data = s.get('https://www.udemy.com/api-2.0/search-courses/?p={}&q=python&skip_price=false'.format(page_counter), cookies=cookies, headers=headers).json()
for course in data['courses']:
params = {'course_ids': [str(course['id']),],
'fields/[pricing_result/]': ['price',]}
title = course['title']
price = s.get('https://www.udemy.com/api-2.0/pricing/', params=params, cookies=cookies).json()['courses'][str(course['id'])]['price']['amount']
print({'title': title, 'price': price})