sorted("elvis") == sorted("lives") # True
Why Learning about Python Anagrams?
A popular question in programming interviews is to create an anagram checker.
The interviewer wants to test your knowledge about the basic terminology in computer science, and how good you are at developing your own simple algorithms to solve the problems you are facing. In this article, you’ll learn about a simple algorithm to find anagrams in Python.
Most students who have pursued an academic education in computer science, know exactly what to do here. When posed in a coding interview, this question serves as a test that immediately reveals whether you are part of this community. So let’s prepare!
What are anagrams? Two words are anagrams if they consist of the same characters.
? “An anagram is a word or phrase formed by rearranging the letters of a different word or phrase, typically using all the original letters exactly once.” (Wikipedia)
Here are a few examples:
- “listen” → “silent”
- “funeral” → “real fun”
- “elvis” → “lives”
Challenge: Create a Python program that checks for two words
x1 is an anagram of
x2. More precisely: Given are two strings
x2. Write a function
is_anagram which returns
True if string
x2 an anagram of string
Ok, now you know exactly what to do, right? So, let’s start coding.
The following one-liner solution (from my book Python One-Liners) solves this problem easily and in a very concise way too.
## Python Anagram One-Liner is_anagram = lambda x1, x2: sorted(x1) == sorted(x2)
If you don’t like one-liners, you can also create the same anagram checker function
is_anagram() in two lines:
def is_anagram(x1, x2): return sorted(x1) == sorted(x2)
? The function
is_anagram(x1, x2) simply returns the result of the expression
sorted(x1) == sorted(x2) which is
True if the sorted character sequences consist of the same characters.
The one-liner solves the problem efficiently and correctly. Two strings are anagrams if they have the same sorted character sequence. It’s that easy. There is no need for external dependencies – we simply create a function
is_anagram in a single line of code by using the lambda function definition with two arguments
Here’s the output of the two sorted character sequences:
print(sorted("elvis")) # ['e', 'i', 'l', 's', 'v'] print(sorted("lives")) # ['e', 'i', 'l', 's', 'v']
"lives" consist of the same characters, so the sorted list representation is the same. Thus, the result of the three
print() statements in the one-liner code snippet is the following:
## Results print(is_anagram("elvis", "lives")) # True print(is_anagram("elvise", "livees")) # True print(is_anagram("elvis", "dead")) # False
To learn more about the
sorted() function, check out my in-depth tutorial on the Finxter blog or watch the following video:
Where to Go From Here?
This article gave you the simplest way of finding anagrams in Python. There is no easier way — guaranteed.
If you feel like you need to become better in Python but you don’t know how and have little time, check out my daily “Coffee Break Python” email series with free Python cheat sheets. It’s fun!
Python One-Liners Book: Master the Single Line First!
Python programmers will improve their computer science skills with these useful one-liners.
Python One-Liners will teach you how to read and write “one-liners”: concise statements of useful functionality packed into a single line of code. You’ll learn how to systematically unpack and understand any line of Python code, and write eloquent, powerfully compressed Python like an expert.
The book’s five chapters cover (1) tips and tricks, (2) regular expressions, (3) machine learning, (4) core data science topics, and (5) useful algorithms.
Detailed explanations of one-liners introduce key computer science concepts and boost your coding and analytical skills. You’ll learn about advanced Python features such as list comprehension, slicing, lambda functions, regular expressions, map and reduce functions, and slice assignments.
You’ll also learn how to:
- Leverage data structures to solve real-world problems, like using Boolean indexing to find cities with above-average pollution
- Use NumPy basics such as array, shape, axis, type, broadcasting, advanced indexing, slicing, sorting, searching, aggregating, and statistics
- Calculate basic statistics of multidimensional data arrays and the K-Means algorithms for unsupervised learning
- Create more advanced regular expressions using grouping and named groups, negative lookaheads, escaped characters, whitespaces, character sets (and negative characters sets), and greedy/nongreedy operators
- Understand a wide range of computer science topics, including anagrams, palindromes, supersets, permutations, factorials, prime numbers, Fibonacci numbers, obfuscation, searching, and algorithmic sorting
By the end of the book, you’ll know how to write Python at its most refined, and create concise, beautiful pieces of “Python art” in merely a single line.
While working as a researcher in distributed systems, Dr. Christian Mayer found his love for teaching computer science students.
To help students reach higher levels of Python success, he founded the programming education website Finxter.com. He’s author of the popular programming book Python One-Liners (NoStarch 2020), coauthor of the Coffee Break Python series of self-published books, computer science enthusiast, freelancer, and owner of one of the top 10 largest Python blogs worldwide.
His passions are writing, reading, and coding. But his greatest passion is to serve aspiring coders through Finxter and help them to boost their skills. You can join his free email academy here.