5 Best Ways to Count How Many Times “Pizza” Appears in a Given String in Python

Rate this post

πŸ’‘ Problem Formulation: This article explores various Python methods to count the occurences of the word “pizza” within any given string. For example, given the input string “I love pizza, because pizza is the best food. Pizza!”, we aim to find that the output is 3, as the word “pizza” appears thrice.

Method 1: Using the count() Method

This method involves the use of the built-in count() method in Python, which returns the number of times a specified value appears in the string. It’s straightforward, case-sensitive, and doesn’t require importing any libraries. If case-insensitivity is needed, the string and search term should be converted to the same case using lower() or upper() beforehand.

Here’s an example:

input_string = "Pizza is good. I love pizza, specially when the pizza is free!"
count = input_string.lower().count('pizza')
print(count)

Output:

3

This code snippet counts occurrences of the lowercase ‘pizza’ in the input_string, which it first converts to lowercase to ensure case insensitivity. It prints out the number of times ‘pizza’ was found in the string.

Method 2: Using Regular Expressions

The re.findall() function from the re (regular expressions) module is useful when you need more control over the search, such as considering word boundaries. It returns a list of all matches, and the length of this list represents the count.

Here’s an example:

import re

input_string = "pizzapizza pizza? Pizza; napoletana pizza!"
matches = re.findall(r'\bpizza\b', input_string, re.IGNORECASE)
print(len(matches))

Output:

4

This snippet searches for the word ‘pizza’ as a whole word (using the word boundary marker \b) regardless of case (using re.IGNORECASE), and then prints the number of matching occurrences.

Method 3: Using a Loop and Slicing

A more manual approach can be taken by iterating over the string with a loop and slice. For each position in the string, check if the subsequent characters form the word “pizza”. This method doesn’t depend on any libraries and gives an understanding of basic string manipulation.

Here’s an example:

input_string = "Pizzapizzapizzapizza!"
count = 0
search_term = 'pizza'
for i in range(len(input_string) - len(search_term) + 1):
    if input_string[i:i+len(search_term)].lower() == search_term:
        count += 1
print(count)

Output:

4

We loop through the input string, checking for ‘pizza’ at every possible position, while converting sliced parts of input_string to lowercase for case-insensitive comparison. The counter increases with each discovery.

Method 4: Using the split() Method

The split() method can be used to split the string into a list based on a separator and then the number of occurrences can be deduced from the length of the resulting list minus one. This method is effective but can give incorrect results if the separator occurs at the start or end of the string.

Here’s an example:

input_string = "pizza, only pizza; because: pizza!"
count = len(input_string.lower().split('pizza')) - 1
print(count)

Output:

3

By splitting the converted lowercase string at each ‘pizza’, we end up with a list where the number of split parts is one more than the number of ‘pizza’ occurrences. Thus, we subtract one to get the correct count.

Bonus One-Liner Method 5: Using List Comprehension and the in Operator

A compact one-liner using list comprehension and the in operator can also achieve this. This method checks for ‘pizza’ in sliced sections of the string for each position. It’s concise but can be less readable for those unfamiliar with list comprehensions.

Here’s an example:

input_string = "Do you like pizza? Because pizza is great!"
count = sum('pizza' in input_string[i:i+5].lower() for i in range(len(input_string)))
print(count)

Output:

2

This one-liner loops through each position, checks if ‘pizza’ is in the sliced substring, converts it to lowercase, and sums up the Boolean values (True is converted to 1, False is converted to 0).

Summary/Discussion

  • Method 1: count() Method. Simple and straightforward. May not be suitable for complex pattern matching or case-insensitive counting without additional steps.
  • Method 2: Regular Expressions. Offers powerful and flexible search capabilities, which is useful for complex string matching requirements. However, it can be slower and has a steeper learning curve.
  • Method 3: Loop and Slicing. Provides a basic and educational approach to understanding string manipulation. It may be less efficient for very long strings and is more verbose.
  • Method 4: split() Method. Quick and usually efficient, but can give incorrect results with edge cases. Also, note that it’s not a direct way to count occurrences and might be confusing.
  • Method 5: List Comprehension. Pythonic and elegant but sacrifices some readability for brevity and may not be the most intuitive for new programmers.