Following Links in Python: The program will use urllib to read the HTML from the data files below, extract the href= vaues from the anchor tags, scan for a tag that is in a particular position relative to the first name in the list, follow that link and repeat the process a number of times and report the last name you find.

py4e_ex_12_02

from bs4 import BeautifulSoup
import urllib.request, urllib.parse, urllib.error
import ssl
import re

ctx = ssl.create_default_context()
ctx.check_hostname = False
ctx.verify_mode = ssl.CERT_NONE
url = "http://py4e-data.dr-chuck.net/known_by_Bryce.html"

#to repeat 7 times#
for i in range(7):
    html = urllib.request.urlopen(url, context=ctx).read()
    soup = BeautifulSoup(html, 'html.parser')
    tags = soup('a')
    count = 0
    for tag in tags:
        count = count +1
   
        #make it stop at position 3#
        if count>18:
            break
        url = tag.get('href', None)

print(url)

In case of some people if the above code does not work, try the following

import urllib.request, urllib.parse, urllib.error
from bs4 import BeautifulSoup

url = input('Enter URL - ')
html = urllib.request.urlopen(url).read()
soup = BeautifulSoup(html, 'html.parser')

Find all the tags with class="comments"

span_tags = soup.find_all('span', class_='comments')

count = 0
total_sum = 0

for span in span_tags:
# Extract the text content of the span tag and convert to an integer
count += 1
total_sum += int(span.contents[0])

print("Count", count)
print("Sum", total_sum)

Here's how the code works:

It takes the URL as input from the user.
It retrieves the HTML content from the specified URL using urllib.request.urlopen.
It uses BeautifulSoup to parse the HTML and find all the tags with the class "comments" using soup.find_all.
It initializes two variables count and total_sum to keep track of the number of comments and the sum of the comments, respectively.
It iterates through each tag, converts the text content of the tag to an integer using int(span.contents[0]), and adds it to the total_sum.
Finally, it prints the total count and sum of the comments.
When you run the script, it will prompt you to enter the URL (e.g., http://py4e-data.dr-chuck.net/comments_42.html) and then display the count and sum of the comments in the given URL.