INTRODUCTION – Regular Expressions

PRACTICE QUIZ: REGULAR EXPRESSIONS

1. When using regular expressions, which of the following expressions uses a reserved character that can represent any single character?

2. Which of the following is NOT a function of the Python regex module?

3. The circumflex [^] and the dollar sign [$] are anchor characters. What do these anchor characters do in regex?

4. When using regex, some characters represent particular types of characters. Some examples are the dollar sign, the circumflex, and the dot wildcard. What are these characters collectively known as?

5. What is grep?

6. Which of the following demonstrates how regex (regular expressions) might be used?

7. Rather than using the index() function of the string module, we can use regular expressions, which are more flexible. After importing the regular expression module re, what regex function might be used instead of standard methods?

8. Using the terminal, which of the following commands will correctly use grep to find the words “sling” and “sting” (assuming they are in our file, file.txt)?

PRACTICE QUIZ: BASIC REGULAR EXPRESSIONS 

1. The check_web_address function checks if the text passed qualifies as a top-level web address, meaning that it contains alphanumeric characters (which includes letters, numbers, and underscores), as well as periods, dashes, and a plus sign, followed by a period and a character-only top-level domain such as “.com”, “.info”, “.edu”, etc. Fill in the regular expression to do that, using escape characters, wildcards, repetition qualifiers, beginning and end-of-line characters, and character classes.

import re


def check_web_address(text):
    pattern = r"^[a-zA-Z0-9_.+-]+(?:\.[a-zA-Z0-9-]+)*\.[a-zA-Z]{2,}$"
    result = re.search(pattern, text)
    return result is not None


print(check_web_address("gmail.com"))             # True
print(check_web_address("www@google"))            # False
print(check_web_address("www.Coursera.org"))       # True
print(check_web_address("web-address.com/homepage"))  # False
print(check_web_address("My_Favorite-Blog.US"))    # True

2. The check_time function checks for the time format of a 12-hour clock, as follows: the hour is between 1 and 12, with no leading zero, followed by a colon, then minutes between 00 and 59, then an optional space, and then AM or PM, in upper or lower case. Fill in the regular expression to do that. How many of the concepts that you just learned can you use here?

import re
def check_time(text):
    pattern = r"^(1[0-2]|0?[1-9]):[0-5][0-9]\s?(am|pm|AM|PM)$"
    result = re.search(pattern, text)
    return result is not None


print(check_time("12:45pm"))    # True
print(check_time("9:59 AM"))    # True
print(check_time("6:60am"))      # False
print(check_time("five o'clock"))  # False

3 What does the “r” before the pattern string in re.search(r”Py.*n”, sample.txt) indicate?

4. What does the plus character [+] do in regex?

5. Fill in the code to check if the text passed contains the vowels a, e and i, with exactly one occurrence of any other character in between.

import re


def check_aei(text):
    result = re.search(r"a.e.i", text)
    return result is not None


print(check_aei("academia"))    # True
print(check_aei("aerial"))       # False
print(check_aei("paramedic"))    # True

6. Fill in the code to check if the text passed contains punctuation symbols: commas, periods, colons, semicolons, question marks, and exclamation points.

import re
def check_punctuation(text):
    result = re.search(r"[,.;:?!]+", text)
    return result is not None


print(check_punctuation("This is a sentence that ends with a period."))  # True
print(check_punctuation("This is a sentence fragment without a period"))  # False
print(check_punctuation("Aren't regular expressions awesome?"))  # True
print(check_punctuation("Wow! We're really picking up some steam now!"))  # True
print(check_punctuation("End of the line"))  # False

7. The repeating_letter_a function checks if the text passed includes the letter “a” (lowercase or uppercase) at least twice. For example, repeating_letter_a(“banana”) is True, while repeating_letter_a(“pineapple”) is False. Fill in the code to make this work.

import re
def repeating_letter_a(text):
    result = re.search(r"[Aa].*[Aa]", text)
    return result is not None


print(repeating_letter_a("banana"))          # True
print(repeating_letter_a("pineapple"))        # False
print(repeating_letter_a("Animal Kingdom"))   # True
print(repeating_letter_a("A is for apple"))   # True

8. Fill in the code to check if the text passed has at least 2 groups of alphanumeric characters (including letters, numbers, and underscores) separated by one or more whitespace characters.

import re
def check_character_groups(text):
    result = re.search(r"\w+\s+\w+", text)
    return result is not None


print(check_character_groups("One")) # False
print(check_character_groups("123  Ready Set GO")) # True
print(check_character_groups("username user_01")) # True
print(check_character_groups("shopping_list: milk, bread, eggs.")) # False

9. Fill in the code to check if the text passed looks like a standard sentence, meaning that it starts with an uppercase letter, followed by at least some lowercase letters or a space, and ends with a period, question mark, or exclamation point.

import re
def check_sentence(text):
    result = re.search(r"^[A-Z][a-z\s]+[.!?]$", text)
    return result is not None


print(check_sentence("Is this is a sentence?")) # True
print(check_sentence("is this is a sentence?")) # False
print(check_sentence("Hello")) # False
print(check_sentence("1-2-3-GO!")) # False
print(check_sentence("A star is born.")) # True

PRACTICE QUIZ: ADVANCED REGULAR EXPRESSIONS

1. We’re working with a CSV file, which contains employee information. Each record has a name field, followed by a phone number field, and a role field. The phone number field contains U.S. phone numbers, and needs to be modified to the international format, with “+1-” in front of the phone number. Fill in the regular expression, using groups, to use the transform_record function to do that.

import re
def transform_record(record):
  new_record = re.sub(r"(\d{3}-\d{3}-\d{4})", r"+1-\1",record)
  return new_record


print(transform_record("Sabrina Green,802-867-5309,System Administrator")) 
# Sabrina Green,+1-802-867-5309,System Administrator


print(transform_record("Eli Jones,684-3481127,IT specialist")) 
# Eli Jones,+1-684-3481127,IT specialist


print(transform_record("Melody Daniels,846-687-7436,Programmer")) 
# Melody Daniels,+1-846-687-7436,Programmer


print(transform_record("Charlie Rivera,698-746-3357,Web Developer")) 
# Charlie Rivera,+1-698-746-3357,Web Developer

2. The multi_vowel_words function returns all words with 3 or more consecutive vowels (a, e, i, o, u). Fill in the regular expression to do that.

import re
def multi_vowel_words(text):
    pattern = r'\b\w*[aeiouAEIOU]{3,}\w*\b'
    result = re.findall(pattern, text)
    return result


print(multi_vowel_words("Life is beautiful")) 
# ['beautiful']


print(multi_vowel_words("Obviously, the queen is courageous and gracious.")) 
# ['Obviously', 'queen', 'courageous', 'gracious']


print(multi_vowel_words("The rambunctious children had to sit quietly and await their delicious dinner.")) 
# ['rambunctious', 'quietly', 'delicious']


print(multi_vowel_words("The order of a data queue is First In First Out (FIFO)")) 
# ['queue']


print(multi_vowel_words("Hello world!")) 
# []

3. When capturing regex groups, what datatype does the groups method return?

4. The transform_comments function converts comments in a Python script into those usable by a C compiler. This means looking for text that begins with a hash mark (#) and replacing it with double slashes (//), which is the C single-line comment indicator. For the purpose of this exercise, we’ll ignore the possibility of a hash mark embedded inside of a Python command, and assume that it’s only used to indicate a comment. We also want to treat repetitive hash marks (##), (###), etc., as a single comment indicator, to be replaced with just (//) and not (#//) or (//#). Fill in the parameters of the substitution method to complete this function:

import re
def transform_comments(line_of_code):
  result = re.sub((r"\s*#+\s*"),"// ", line_of_code)
  return result


print(transform_comments("### Start of program")) 
# Should be "// Start of program"
print(transform_comments("  number = 0   ## Initialize the variable")) 
# Should be "  number = 0   // Initialize the variable"
print(transform_comments("  number += 1   # Increment the variable")) 
# Should be "  number += 1   // Increment the variable"
print(transform_comments("  return(number)")) 
# Should be "  return(number)"

5. The convert_phone_number function checks for a U.S. phone number format: XXX-XXX-XXXX (3 digits followed by a dash, 3 more digits followed by a dash, and 4 digits), and converts it to a more formal format that looks like this: (XXX) XXX-XXXX. Fill in the regular expression to complete this function.

import re
def convert_phone_number(phone):
  result = re.sub(r"\b(\d{3})-(\d{3})-(\d{4})\b",r"(\1) \2-\3", phone)
  return result


print(convert_phone_number("My number is 212-345-9999.")) # My number is (212) 345-9999.
print(convert_phone_number("Please call 888-555-1234")) # Please call (888) 555-1234
print(convert_phone_number("123-123-12345")) # 123-123-12345
print(convert_phone_number("Phone number of Buckingham Palace is +44 303 123 7300")) # Phone number of Buckingham Palace is +44 303 123 7300

6. Fix the regular expression used in the rearrange_name function so that it can match middle names, middle initials, as well as double surnames.

import re
def rearrange_name(name):
    result = re.search(r"^(\w+),\s*(\w+(?:\s+[A-Z]\.)?)$", name)
    if result is None:
        return name
    return "{} {}".format(result[2], result[1])


name=rearrange_name("Kennedy, John F.")
print(name)

7. The long_words function returns all words that are at least 7 characters. Fill in the regular expression to complete this function.

import re
def long_words(text):
    pattern = r'\b\w{7,}\b'
    result = re.findall(pattern, text)
    return result


print(long_words("I like to drink coffee in the morning.")) # ['morning']
print(long_words("I also have a taste for hot chocolate in the afternoon.")) # ['chocolate', 'afternoon']
print(long_words("I never drink tea late at night.")) # []

8. Add to the regular expression used in the extract_pid function, to return the uppercase message in parenthesis, after the process id.

import re
def extract_pid(log_line):
    regex = r"\[(\d+)\]:\s+([A-Z]+)"
    result = re.search(regex, log_line)
    if result is None:
        return None
    return "{} ({})".format(result.group(1), result.group(2))


print(extract_pid("July 31 07:51:48 mycomputer bad_process[12345]: ERROR Performing package upgrade")) # 12345 (ERROR)
print(extract_pid("99 elephants in a [cage]")) # None
print(extract_pid("A string that also has numbers [34567] but no uppercase message")) # None
print(extract_pid("July 31 08:08:08 mycomputer new_process[67890]: RUNNING Performing backup")) # 67890 (RUNNING)

9. We want to split a piece of text by either the word “a” or “the”, as implemented in the following code. What is the resulting split list?

re.split(r"the|a", "One sentence. Another one? And the last one!")

re.split(r"the|a", "One sentence. Another one? And the last one!")

WRITING FILE PATHS

1. There are two types of file paths: relative and absolute. What is an absolute file path?

2. As a Python programmer, you will probably choose to use relative file paths more often than absolute file paths. What are the advantages of relative file paths over absolute file paths? Select all that apply. 

3. When writing file paths in Python, it’s a best practice to use only forward slashes (/ )to separate the directories. Why is that? 

4. Many Python programmers use the command os.path to wrap directories. What is that specific command designed to do? 

5. You can call a file with a relative file path using the file name, provided you also use the CWD: What does CWD stand for?

WORK WITH REGULAR EXPRESSIONS

1. Which of the following tasks can be accomplished using regular expressions? Select all that apply.

2. What is a characteristic of a CSV file? 

3. What does the variable old_domain_pattern store in the lab’s first set of codes?

4. Which of the following statements are correct regarding the re.sub() function? Select all that apply.

5. You have been tasked with initializing two lists: old_domain_email_list and new_domain_email_list. The goal is to populate old_domain_email_list with email addresses that contain the old domain name and meet the criteria defined in the contains_domain function. How would you achieve this in Python based on the content in your lab?

6. What is a key benefit of using Python for creating reports and employing regular expressions?

7. What are headers in the context of a CSV file?

8. In the process of updating email domains in a CSV file using Python, how do the contains_domain and replace_domain functions work together?

9. What is a regular expression? 

10. Which method from the csv module is used to write rows of data into a CSV file? 

11. In the provided code snippet, what is the purpose of the replace_domain function?

def replace_domain(address, old_domain, new_domain):
 old_domain_pattern = r'' + old_domain + '$'
 address = re.sub(old_domain_pattern, new_domain, address)
 return address

12. In regular expressions, what does the re.split() function do? 

13. What is the significance of the variables csv_file_location and report_file in the code snippet from the lab?

csv_file_location = '<csv-file-location>'
 report_file = '<data-directory>' + '/updated_user_emails.csv

14. What is the next step after declaring the output file variable report_file at the beginning of the script?

Questions15. What is the second step in the process of replacing old domain names with new ones in a CSV file using Python?

16. Which function is used to match a regular expression pattern in Python?

17. Why is it important to write the list to an output file in a Python script, as specified by the variable report_file?

18. Which Python libraries or modules are commonly employed to perform updates to domain names to a new specified domain and saving all the modified domain names to a separate file?

19. Which Python function would you use to open a CSV file? 

20. In the Python script for processing user_emails.csv, what is the purpose of the contains_domain function?

21. What is the purpose of initializing the old_domain_email_list in the code from the lab?

22. What is the purpose of the replace_domain function in the process of replacing old domain names with new ones in a CSV file using Python?

23. You have been tasked with replacing old domain names with new ones in a CSV file using Python, based on the lab. What is the correct sequence of steps to accomplish this task?

24. Why is it important to define headers for the output file when replacing old domain names with new ones in a CSV file using Python, as described in the lab?

CONCLUSION – Regular Expressions