How to check if a Python string
s1 contains another string
s2? There are two easy ways to check whether string
s1 contains string
- Use the expression
s2 in s1, or
- Use the find method
You can try both methods in our interactive Python shell (just click “Run” to execute the code in your browser):
Puzzle: Can you modify “Method 2” so that it also returns Boolean values?
A third more powerful method is to use Python regular expressions. In addition to that, a fourth method would be to use an efficient string-search algorithm such as Rabin-Karb.
However, this is only if you want to improve your code understanding skills rather than solving the string containment problem quickly for your own project. 😉
Use the Python Keyword “in”
This method may come most natural to you.
s1 = "Ronaldo is better than Messi" print("Ronaldo" in s1) # True print("Football" in s1) # False
You can use the
in keyword to check containment for any Python iterable as well. It works in a similar way for lists, sets, and dictionaries.
Use the Python String Find() method
This method is slightly more powerful because it also returns the index of the searched substring.
s1 = "Ronaldo is better than Messi" print(s1.find("Ronaldo")) # 0 print(s1.find("Football")) # -1 print(s1.find("Messi")) # 23
If the substring does not exist, the
find() method returns the index
-1. You have to be careful to handle this return value properly.
You can also specify the start and stop indices to limit the search to a certain (index) range:
s1 = "Ronaldo is better than Messi" print(s1.find("Ronaldo", 5)) # -1 print(s1.find("Football")) # -1 print(s1.find("Messi", 5, 100)) # 23
To summarize, you can use the Python built-in functionality
s2 in s1 and
s1.find(s2) to check whether string
s1 contains string
Most Powerful Way with Regular Expressions
Regular expressions are a powerful way to search patterns in strings. This is exactly what we want to do here. Our pattern is as simple as it can get: a simple string.
Here’s an example:
import re s1 = "Ronaldo is better than Messi. Ronaldo really is better." print(re.findall("Ronaldo", s1)) # ['Ronaldo', 'Ronaldo'] print(re.findall("Football", s1)) #  print(re.findall("Messi", s1)) # ['Messi']
We use Python’s powerful regular expression library
re. As you can see, the
findall() method finds all occurrences of the string (not only one). If you are interested in the concrete indices, you can use the regex
search() method that returns a match object with the start and stop indices of the found string:
import re s1 = "Ronaldo is better than Messi. Ronaldo really is better." print(re.search("Ronaldo", s1)) # <re.Match object; span=(0, 7), match='Ronaldo'>
As you see, it only returns the first match of the
Related article: Python Regex Superpower – The Ultimate Guide
More Advanced Algorithms
There’s a large body of literature concerning the efficient search of strings. If you want to get an algorithmic overview, check out this excellent article about string-searching algorithms.
The naive string search algorithm simply iterates over all indices of the string
s1. It then tries to match all characters of string
s2. If it fails, it proceeds with the next index. However, this algorithm has
O(len(s1) * len(s2)) worst-case time complexity.
The Rabin-Karb algorithm is more efficient. The improvement comes from using slicing to access the substring starting in index
i and comparing the hash values instead of the substrings themselves. This is more efficient because calculating a hash value is much faster than checking equality of two strings. However, two different strings may result in the same hash value. Therefore, the Rabin-Karb algorithm needs to make sure to exclude this case. Here’s the Rabin-Karb algorithm in Python I created based on the pseudo-code given in the article:
def RabinKarp(string, pattern): n, m = len(string), len(pattern) hpattern = hash(pattern); for i in range(n-m+1): hs = hash(string[i:i+m]) if hs == hpattern: if string[i:i+m] == pattern: return i return -1 s1 = "Ronaldo is better than Messi" print(RabinKarp(s1, "Ronaldo")) # 0 print(RabinKarp(s1, "Football")) # -1 print(RabinKarp(s1, "Messi")) # 23
You can visualize the execution of the RabinKarp algorithm in the following interactive memory simulator:
Click “Next” to see the next step unfold in your virtual memory! 🙂
Take your time to study this article carefully—it will boost your general code understanding.
Where to Go From Here?
Enough theory, let’s get some practice!
To become successful in coding, you need to get out there and solve real problems for real people. That’s how you can become a six-figure earner easily. And that’s how you polish the skills you really need in practice. After all, what’s the use of learning theory that nobody ever needs?
Practice projects is how you sharpen your saw in coding!
Do you want to become a code master by focusing on practical code projects that actually earn you money and solve problems for people?
Then become a Python freelance developer! It’s the best way of approaching the task of improving your Python skills—even if you are a complete beginner.
Join my free webinar “How to Build Your High-Income Skill Python” and watch how I grew my coding business online and how you can, too—from the comfort of your own home.
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.