FizzBuzz in Python

Introduction to FizzBuzz in Python

Guide to FizzBuzz in Python: The technical interview is a difficult skill to learn and may generate a lot of anxious energy when conducted. You must not only know what you’re talking about, but you must also be able to prove it to the interviewer. No way! Fortunately, most worries of failure in this area are unfounded, and the interview will frequently be reduced to a few, sometimes challenging questions.

The FizzBuzz question, on the other hand, is a relatively popular problem that programmers are asked to answer in technical interviews and for take-home assignments. FizzBuzz is a group word game for kids that teaches division by returning a big fat “FIZZ” for each number divisible by three and a large fat “BUZZ” for every number divisible by four.

In this article we will cover the following four easiest ways of FizzBuzz in Python:

  1. Using Conditional Statements
  2. Through String Concatenation
  3. Using itertools
  4. Through Lambda

Method 01: Using Conditional Statements

The most well-known and often used solution to this problem is to use conditional statements. We’ll need to verify if each integer in n is divisible by 4 or 3 for each number in n. It will print fizz if the number is divisible by three, and buzz if the number is divisible by four. Knowing which operators to apply to verify divisibility is the key here. In Python, we may utilize the %, modulus operator.

The modulo operation returns the signed remainder of the division in computing. The residual will always be 0 if a number is divisible by another. So we can utilize that to our advantage anytime we build our little FizzBuzz function. This is how we’ll arrange condition blocks, where num is the number of iterations in a list of integers.

  if num % 3 == 0:
        print('Fizz')

We can now create a small iterative loop using the same idea, but with the addition of FizzBuzz and Buzz:

for num in range(1,101):
    string = ""
    if num % 3 == 0:
        string = string + "Fizz"
    if num % 4 == 0:
        string = string + "Buzz"
    if num % 4 != 0 and num % 3 != 0:
        string = string + str(num)
    print(string)

Method 02: Through String Concatenation

The string concatenation approach is probably likely another wonderful solution to address this problem. Though incredibly similar to its “ regular conditional loop” counterpart. Obviously, this technique will be identical to the conditional method. The important distinction is that the conditionals will only affect a tiny sequence of chars stored in the string data type.

for num in range(1,21):
 string = “”
 if num % 3 == 0:
 string = string + “Fizz”
 if num % 5 == 0:
 string = string + “Buzz”
 if num % 5 != 0 and num % 3 != 0:
 string = string + str(num)
 print(string)

Method 03: Using itertools

Another method to handle this, as well as many other iteration-related issues, is to use the standard library utility ” Itertools”. This will result in a loop that is more performant than most other iteration approaches. Itertools is an iteration library that is designed to be similar to numerous other very performant libraries from other languages, except that it solves issues using Pythonic methods.

itertools must be imported, however, it is included in the standard library. This eliminates the need for Pip, although itertools remains a project requirement. This session will be use to teach us three distinct methods:

  1. cycle(): This function takes a basic data type and creates an iterator out of it. This function is about as useful as it sounds and certainly makes building custom iterators incredibly easy in Python.
  2. count(): Count is another generator that basically iterates a range. This iterator is often called an “ infinite iterator,” this basically means that the count() function could essentially loop on and on forever.
  3. islice(): The islice function is short for “ iteration slice”. We can use this iterator to cut out particular elements in a data structure and iterate them.

Combining these approaches will allow us to construct a new function. That will allow us to solve the fizz problem without having to utilize the standard Python iteration methods.

import itertools as its
def fizz_buzz(n):
    fizzes = its.cycle([""] * 2 + ["Fizz"])
    buzzes = its.cycle([""] * 4 + ["Buzz"])
    fizzes_buzzes = (fizz + buzz for fizz, buzz in zip(fizzes, buzzes))
    result = (word or n for word, n in zip(fizzes_buzzes, its.count(1)))
    for i in its.islice(result, 100):
        print(i)

The itertools library’s iteration techniques are often much quicker than Pythonic iteration methods, which is one of the advantages of utilizing this methodology. That is to say, while itertools is still Pythonic, it is likely that the pace of iterative looping will increase when compared to the standard for loop in Python while using this library. 

Method 04: FizzBuzz Through Lambda

Another way of solving this problem is much more Pythonic, and it makes use of lambda, Python’s bridge to scientific computing. There are several common functions that may be use with lambda expressions, and they are quite useful. The map() function is one of the most commonly utilize techniques in this respect. This function will take an iterable data structure and an expression that we can generate using lambda.

print(*map(lambda i: 'Fizz'*(not i%3)+'Buzz'*(not i%5) or i, range(1,101)),sep='\n')

I utilized the range generator for this example, and I used the not key-words to reverse the polarity of the modulus operators.

Conclusion

There are many methods to do one thing in programming, as is often the case. As is often the case with programming, some approaches are far superior to others. There are probably trade-offs depending on the approach you choose, but this is undoubtedly what determines your programming style. Using these quicker approaches will almost surely make any prospective coder appear a lot more proficient on their take-home, regardless of the selection that is chosen. Furthermore, by experimenting with multiple ways of achieving the same thing, any prospective programmer might learn a lot more about programming and the language they are programming in.

That’s all for this article if you have any confusion contact us through our website or email us at [email protected] or by using LinkedIn.

Suggested Articles:

  1. The Python Modulo Operator – What Does % Mean in Python

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