Python Regular Expressions Exercises

Python’s regular expressions (regex) provide a powerful way to search, match, and manipulate text based on specific patterns. Regex is widely used in tasks such as validating input formats, searching within strings, or extracting data from text files and web pages.

Python offers the built-in `re` module to work with regular expressions. Common functions include `re.search()`, `re.match()`, and `re.findall()` which allow you to locate patterns in strings efficiently.

Consider the following code snippet:

import re

text = "Contact us at support@example.com or sales@example.org."
emails = re.findall(r"\b[\w.-]+@[\w.-]+\.\w{2,4}\b", text)
print(emails)

What will this code output, and what does it demonstrate about Python’s regex capabilities?

It prints a list of email addresses found in the text, showing how re.findall() extracts all matches for the given pattern.

It raises a syntax error because the pattern string is invalid.

It prints the input text unchanged because re.findall() does not work with email patterns.

It prints an empty list because regex cannot find patterns in strings.

The re.findall() function searches the string for all non-overlapping matches of the regex pattern and returns them as a list.

The pattern r"\b[\w.-]+@[\w.-]+\.\w{2,4}\b" is designed to match email addresses by looking for:

A word boundary \b.
One or more word characters, dots, or hyphens before the @.
The @ symbol.
One or more word characters, dots, or hyphens after the @.
A dot . followed by 2 to 4 word characters (typical domain suffix).
Another word boundary.

Given the example text, the output will be:

['support@example.com', 'sales@example.org']

This example highlights how regex can extract structured information from unstructured text, making it a vital tool for data cleaning, validation, and parsing tasks.

What is the purpose of the `re.findall()` function in Python?

Find the first match only

Find all matches and return them as a list

Replace all matches in a string

Compile a regex into pattern object

The re.findall() function returns all non-overlapping matches of a pattern in a string, as a list of strings. It scans the string from left to right and finds every match of the pattern. It is useful when you want to collect all instances instead of stopping at the first match.

Which regex pattern matches a string that starts with 'cat'?

cat$

^cat

.cat

cat*

The caret symbol ^ anchors the match at the start of the string. So ^cat matches any string that begins with "cat". This is useful when validating prefixes or checking for patterns at the beginning of lines.

Which regex pattern matches a single digit?

\d

\w

\D

\s

The \d pattern matches a single digit character, equivalent to [0-9]. In contrast, \w matches alphanumeric characters, \D matches non-digits, and \s matches whitespace. Thus, \d is the correct pattern for matching a single digit.

What will this code print?

import re
text = "apple banana cherry"
words = re.findall(r"\b\w+\b", text)
print(words)

['a', 'b', 'c']

['apple banana cherry']

['apple', 'banana', 'cherry']

['apple', 'banana cherry']

The pattern \b\w+\b matches complete words using word boundaries. \w+ matches one or more alphanumeric characters, and \b ensures those matches start and end at word boundaries. Hence, it returns all separate words as list items.

What does the following code print?

import re
text = "123abc456def"
print(re.findall(r"[a-z]+", text))

['abc456def']

['abc', 'def']

['123', '456']

[]

The pattern [a-z]+ matches one or more lowercase letters. It does not include digits, so the result only includes the alphabetic substrings 'abc' and 'def'. The findall() function returns both matches as a list.

Which regex pattern would match both 'color' and 'colour'?

colou?r

colou+r

colo*r

col[o|u]r

The pattern colou?r uses ? to make the letter 'u' optional. This matches both 'color' and 'colour' by allowing 0 or 1 occurrences of 'u'. It is a common approach to handle such spelling variations in regex.

What is the output of the following code?

import re
text = "Python 3.10 is better than 2.7"
print(re.findall(r"\d+\.\d+", text))

['3.10', '2.7']

['310', '27']

['3', '10', '2', '7']

[]

The pattern \d+\.\d+ matches numbers with a decimal point. \d+ matches one or more digits, and \. matches the dot literally. So it finds '3.10' and '2.7' in the text and returns them in a list.

What does this code do?

import re
text = "hello123world"
print(re.sub(r"\d+", "-", text))

Replaces numbers with hyphens

Extracts only letters

Removes all letters

Removes all whitespace

The re.sub() function replaces all matches of a pattern with a given replacement string. In this case, \d+ matches the numeric part '123', and it's replaced with a hyphen. The final output is 'hello-world'.

What will this code output?

import re
text = "test1 TEST2 test3 TEST4"
print(re.findall(r"test\d", text, re.IGNORECASE))

['test1', 'test3']

['TEST2', 'TEST4']

['test1', 'TEST2', 'test3', 'TEST4']

[]

The pattern test\d matches the word 'test' followed by a digit. With re.IGNORECASE, the match becomes case-insensitive, so it matches both lowercase and uppercase forms. As a result, it returns all 4 matches from the text in a list.

What will the following code return?

import re
text = "user@example.com and admin@mail.co.uk"
emails = re.findall(r"\b[\w.-]+@[\w.-]+\.\w+\b", text)
print(emails)

['example.com', 'mail.co.uk']

['user@example.com', 'admin@mail.co.uk']

['user@', 'admin@']

['user@example', 'admin@mail']

The pattern [\w.-]+@[\w.-]+\.\w+ matches typical email addresses. It captures the username, the '@' symbol, and the domain. The function re.findall() returns all email matches from the string. The result is a list of complete emails found in the text.

Which pattern correctly matches a U.S. phone number format like 123-456-7890?

\d{3}-\d{3}-\d{4}

\d\d\d-\d\d\d-\d\d\d\d

\d+-\d+-\d+

\d{10}

The pattern \d{3}-\d{3}-\d{4} uses quantifiers to match exactly 3 digits, then 3 digits, then 4 digits, with hyphens in between. It's the most precise and standard way to match phone numbers formatted as 123-456-7890.

What does the following code output?

import re
text = "file_001.txt file_002.csv image_003.png"
result = re.findall(r"file_\d+\.(txt|csv)", text)
print(result)

['file_001.txt', 'file_002.csv']

['txt', 'csv']

['001.txt', '002.csv']

['txt', 'csv', 'png']

When using capturing groups like (txt|csv) with re.findall(), the function returns only the matched groups, not the full match. So instead of full filenames, it returns just the extensions 'txt' and 'csv'. To get full matches, a non-capturing group (?:...) should be used.

Which pattern matches the string 'abc123xyz' but not 'abcxyz'?

abc\d+xyz

abc[0-9]*xyz

abc[0-9]+xyz

abc.*xyz

The pattern abc[0-9]+xyz requires at least one digit between 'abc' and 'xyz'. The + ensures that the digit part is not optional. So, 'abc123xyz' matches, but 'abcxyz' does not. This is a stricter match compared to using * or .*.

Which regex pattern matches a string that contains only lowercase letters and has exactly 5 characters?

[a-z]*

[a-z]{5}

^[a-z]+$

^[a-z]{5}$

The pattern ^[a-z]{5}$ ensures the string is exactly 5 lowercase letters long. The ^ and $ anchors ensure the entire string must match this pattern — no more, no less. Without anchors, the pattern could match just part of the string.

What does the following code print?

import re
text = "apple, banana, cherry"
result = re.findall(r"\b[a-zA-Z]+\b", text)
print(result)

['apple', 'banana', 'cherry']

['apple', 'banana']

['banana', 'cherry']

['apple', 'banana', 'cherry', '']

The pattern \b[a-zA-Z]+\b matches words composed of alphabetic characters, bounded by word boundaries. It correctly captures 'apple', 'banana', and 'cherry', ignoring commas and spaces. Word boundaries \b ensure only whole words are matched.

What is the output of the following code?

import re
text = "cat hat rat"
result = re.sub(r"(\w)(\w)", r"\2\1", text)
print(result)

act hta tar

tac hat tar

cat hat tar

cat at rat

The pattern (\w)(\w) captures pairs of adjacent characters (two words) in the string. In the substitution \2\1, the two captured groups are swapped. As a result, 'cat' becomes 'tac', 'hat' remains 'hat', and 'rat' becomes 'tar'.

Which regex pattern matches strings that contain '123' anywhere in the text?

.*123.*

123

\d+123\d+

^123$

The pattern \d+123\d+ ensures that '123' is surrounded by digits, which means it will match '123' in any numeric string or as part of a number. This is more restrictive compared to .*123.*, which can match '123' anywhere in the string.

What does this code output?

import re
text = "Hello 123, world!"
result = re.sub(r"(\d+)([a-zA-Z]+)", r"\2\1", text)
print(result)

Hello world123,!

Hello world123, Hello world123!

Hello world123123,!

Hello world,123!

The pattern (\d+)([a-zA-Z]+) captures a number followed by a word. In the substitution \2\1, it swaps them, resulting in 'world123' instead of '123world'. The result will be 'Hello world123,!' after replacing '123' and 'world'.

Which regex pattern matches strings that have either 'cat' or 'dog' as a whole word?

\b(cat|dog)\b

(cat|dog)

cat|dog

^(cat|dog)$

The pattern ^(cat|dog)$ matches the exact string 'cat' or 'dog', but not any other variations or parts of words. The caret ^ and dollar sign $ ensure that only 'cat' or 'dog' will be matched in its entirety, with no additional characters before or after.

Python Regular Expressions Exercises

Python’s regular expressions (regex) provide a powerful way to search, match, and manipulate text based on specific patterns. Regex is widely used in tasks such as validating input formats, searching within strings, or extracting data from text files and web pages.

Python offers the built-in re module to work with regular expressions. Common functions include re.search(), re.match(), and re.findall() which allow you to locate patterns in strings efficiently.

Consider the following code snippet:

What will this code output, and what does it demonstrate about Python’s regex capabilities?

What is the purpose of the re.findall() function in Python?

Which regex pattern matches a string that starts with 'cat'?

Which regex pattern matches a single digit?

What will this code print?

What does the following code print?

Which regex pattern would match both 'color' and 'colour'?

What is the output of the following code?

What does this code do?

What will this code output?

What will the following code return?

Which pattern correctly matches a U.S. phone number format like 123-456-7890?

What does the following code output?

Which pattern matches the string 'abc123xyz' but not 'abcxyz'?

Which regex pattern matches a string that contains only lowercase letters and has exactly 5 characters?

What does the following code print?

What is the output of the following code?

Which regex pattern matches strings that contain '123' anywhere in the text?

What does this code output?

Which regex pattern matches strings that have either 'cat' or 'dog' as a whole word?

About This Exercise: Python – Regular Expressions

Python offers the built-in `re` module to work with regular expressions. Common functions include `re.search()`, `re.match()`, and `re.findall()` which allow you to locate patterns in strings efficiently.

What is the purpose of the `re.findall()` function in Python?