Section 14.6 Write Code Questions - Parsons for Select

Activity 14.6.1.

Create a function called cur_stud_link(soup) that takes a soup object and returns the URL that links to Current Students in the Navigation Bar. The soup object is created from the file UMich-8-16-2026.html which is a saved version of “https://umich.edu/” from 2026. Click on the following link to view the source:link. For example, cur_stud_link(soup) should return 'https://umich.edu/web/20260808043645/https://umich.edu/current-students/'.

import requests
from bs4 import BeautifulSoup
---
def cur_stud_link(soup):
---
    text = soup.find('a', string="Current Students")
---
    text = soup.find_all('a', string="Current Students")   #paired
---
    info = text.get('href')
---
    info = text.get(href)  #paired
---
    all_info = "https://umich.edu" + info
---
    return all_info

Activity 14.6.2.

Create a function called headings(soup) that takes a soup object and returns a list of the text from all h2 tags in the soup. The soup object is created from the file MOOC-Wikipedia-8-20-2026.html which is a saved version of “https://en.wikipedia.org/wiki/Massive_open_online_course” from 2026. Click on the following link to view the source: link For example, headings(soup) should return a list of 14 headings starting with ['Contents', 'History', 'Equity and access', ...].

import requests
from bs4 import BeautifulSoup
---
def headings(soup):
    out_list = []
---
    h_list = soup.find_all("h2")
---
    h_list = soup.find("h2")    #paired
---
    for h_tag in h_list:
---
        out_list.append(h_tag.text)
---
        out_list.append(h_tag)  #paired
---
    return out_list

Activity 14.6.3.

Create a function called coursera_dict(soup) that takes a soup object and returns a dictionary with Country as keys and Percentage as values. The soup object is created from the file ’WikipediaMOOC-Jan-12-2018.html’ which is a saved version of “https://en.wikipedia.org/wiki/Massive_open_online_course” from 2018. Click on the following link to view the source: link For example, coursera_dict(soup) should return a dictionary like: {'United States': '27.7%', 'India': '8.8%', 'Brazil': '5.1%', ...}.

from bs4 import BeautifulSoup
import requests
---
def coursera_dict(soup):
    coursera_enrollees = {}
---
    tables = soup.find_all('table', class_='wikitable')
---
    tables = soup.find('table', class_='wikitable')  #paired
---
    rows = tables[1].find_all('tr')
---
    for row in rows[1:]:
---
          both_columns = row.find_all("td")
---
          key = both_columns[0].text
          value = both_columns[1].text.rstrip("\n")
---
          coursera_enrollees[key] = value
---
    return coursera_enrollees

Activity 14.6.4.

Create a function called keywords(soup) that takes a soup object and returns a list of Python keywords. The soup object is created from the file PythonKeywords.html which is a saved version of “https://www.w3schools.com/python/python_ref_keywords.asp” from 2026. Click on the following link to view the source: link. For example, keywords(soup) should return a list that starts with: ['and', 'as', ...].

import requests
from bs4 import BeautifulSoup
---
def keywords(soup):
    keywords = []
---
    table = soup.find('table', class_="ws-table-all")
---
    table = soup.find(table) #paired
---
    rows = table.find_all('tr')
---
    for row in rows[1:]:
---
    for row in rows:  #paired
---
        data = row.find("td")
---
        keyword = data.find('a').text
---
        keywords.append(keyword)
---
    return keywords

Activity 14.6.5.

Create a function called movies(soup) that takes a soup object and returns a list of the top box office movies. The soup object is created from the file top-box-office-8-2026.html which is a saved version of “https://www.imdb.com/chart/boxoffice/” from Aug 7-9th 2026. Click on the following link to view the source: link. For example, movies(soup) should return a list that starts with: ['Spider-Man: Brand New Day', 'The Odyssey', 'One Night Only', ...].

from bs4 import BeautifulSoup
import requests
---
def movies(soup):
    movies = []
---
    head_list = soup.find_all("h4", class_="ipc-title__text")
---
    head_list = soup.find('h4', class_="ipc-title__text")  #paired
---
    for header in head_list:
---
        movies.append(header.text.strip())
---
    return movies

Activity 14.6.6.

Write a function called bsi_list(soup) that takes in a parameter soup and returns a list of the section names and subsection names under Programs-Bachelor of Science in Information. The soup object is created from the file BSI-Aug-3-2023.html which is a saved version of “https://www.si.umich.edu/programs/bachelor-science-information” from Aug 3rd 2023. Click on the following link to view the source: link. For example, bsi_list(soup) should return a list that starts with: ['How do I apply?', 'Current U-M students', 'Transfer students', ...].

import requests
from bs4 import BeautifulSoup
---
def bsi_list(soup):
    list1 = []
---
    url = re.compile("/programs/bachelor-science-information/")
    sections = soup.find_all('a', href=url)
---
    for section in sections[:-2]:
---
        list1.append(section.text.strip("\n").strip())
---
        list1.append(section.strip("\n").strip())  #paired
---
    return list1

Activity 14.6.7.

Create a function called bsi_dict(soup) that takes in a parameter soup and returns a list of the section names and subsection names under Programs-Bachelor of Science in Information. The soup object is created from the file BSI-Aug-3-2023.html which is a saved version of “https://www.si.umich.edu/programs/bachelor-science-information” from Aug 3rd 2023. Click on the following link to view the source: link. For example, bsi_list(soup) should return a dictionary that starts with: [.

from bs4 import BeautifulSoup
import requests
import re
---
def bsi_dict(soup):
    bsi_dict = {}
---
    url = re.compile("/programs/bachelor-science-information/")
    sections = soup.find_all('a', href=url)
---
    for section in sections[:-2]:
---
        key = section.text.strip()
        value = section.get('href')
---
        bsi_dict[bsi_list[key] = value
---
    return bsi_dict

Activity 14.6.8.

Create a function called envelope_address that takes in a parameter url and uses BeautifulSoup to web scrape and return the address text in the footer as a list. For example, envelope_address('https://www.si.umich.edu/programs/bachelor-science-information') should return a list like: ['School of Information', 'University of Michigan', ...]. Since we are scraping a live site the results may be different.

import requests
from bs4 import BeautifulSoup
---
def envelope_address(url):
    out_list = []
---
    address = soup.find('div', class_ = 'footer--address').text.strip()
---
    address = soup.find('div', class = 'footer--address').text.strip()  #paired
---
    add_list = address.split("\n")
---
    add_list = address.split()  #paired
---
    for add_line in add_list:
---
        out_list.append(add_line.strip())
---
        add_list.append(add_line.strip())  #paired
---
    return out_list

Activity 14.6.9.

Create a function called names(soup) that takes in a parameter soup, and returns a list with the faculty names. The soup object is created from the file FacultyUMSI-7-30-2025.html which is a saved version of “https://www.si.umich.edu/people/directory/faculty/e” from July 30th 2025. Click on the following link to view the source: link. For example, names(souop) should return ['Paul Edwards', 'Ron Eglash', ...].

from bs4 import BeautifulSoup
import requests
---
import re  #paired
---
def names(soup):
    name_list = []
---
    names = soup.find_all(class_="research-person-profile__name")
---
    names = soup.find_all(class="research-person-profile__name")  #paired
---
    for name in names:
---
        name = name.text.strip("\n ")
        name_list.append(name)
---
    return name_list

Activity 14.6.10.

Create a function called program_email that takes in a parameter url, uses BeautifulSoup to web scrape the program names under Email Addresses and Admissions (BSI program, MSI program, etc.) and their associated email addresses, and returns a dictionary with the program names as keys and the email addresses as values. For example, program_email('https://www.si.umich.edu/about-umsi/contact-us') should return something like {'BSI program': '[email protected]', 'MSI program': '[email protected]', ...}. Since we are scraping a live site the results may be different.

import requests
from bs4 import BeautifulSoup
---
def program_email(soup):
    program_email_dict = {}
---
    programs_section = soup.find("ul", dir="ltr")
---
    programs = programs_section.find_all("li")
---
    programs = programs_section.find("li")  #paired
---
    for program in programs:
---
        split_name_email = program.text.split(":")
---
        program_name = split_name_email[0]
---
        program_email = split_name_email[1].replace("\xa0", "")
---
        program_email = split_name_email[0].replace("\xa0", "")  #paired
---
        program_email_dict[program_name] = program_email
---
    return program_email_dict

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