Oct 07, 2023 8 mins

Python loops

Python loops Python loops

Python loops are a fundamental concept that every programmer must be good at. This guide will dive deep into the practical uses of `for` and `while` loops showing you how to manage loop control statements. At the end, the article shares some best practices to enhance your coding efficiency.

Understanding Python Loops

Loops in Python offer a way to execute a block of code repeatedly, which is crucial when you need to process items in a collection or repeat actions until a condition changes. The two primary types of loops in Python are for loops and while loops.

Python For Loops Explained

A Python for loop is a control structure which allows you to repeat a block of code. This loop iterates over items in a sequence, such as a list or a string. Each item in the sequence is assigned to a variable, which you can use in the loop. A for loop in Python is often used to perform tasks on each item in a collection, which makes it useful for tasks like summing numbers or modifying elements.

You can also use a for loop with the range function, which generates a sequence of numbers. This is helpful for running a loop a specific number of times, which makes it easy to control how many iterations occur. In Python, for loops are clear and easy to write, which makes them a popular choice among developers.

Here are a few examples to illustrate the description of a Python for loop.

Iterating over a list

fruits = ["apple", "banana", "cherry"]
for fruit in fruits:

This loop iterates over each item in the list called fruits, which contains “apple”, “banana”, and “cherry”. Each item is printed to the screen.

Using a for loop with the range function

for i in range(5):

This loop uses the range function, which generates a sequence of numbers from 0 to 4. Each number is printed to the screen.

Summing numbers in a list

numbers = [1, 2, 3, 4, 5]
total = 0
for number in numbers:
    total += number

This loop iterates over each number in the list called numbers, which contains 1, 2, 3, 4, and 5. Each number is added to the variable total, which is then printed to show the sum.

Modifying elements in a list

numbers = [1, 2, 3, 4, 5]
for i in range(len(numbers)):
    numbers[i] *= 2

This loop uses the range function to generate a sequence of indices for the list called numbers. Each element in the list is doubled, which modifies the original list.

Python While Loops

A Python while loop keeps running as long as the condition is True. You use it when you want to repeat an action multiple times. The loop checks the condition before every iteration. If the condition is False, the loop stops.

You can use the while loop with any condition that evaluates to True or False, like x < 5. This loop is useful for tasks that involve repeatedly performing an action until a certain condition is met. You can also combine it with other control flow statements like if and else to create more complex behavior.

When you use a while loop, you should be careful to avoid infinite loops, which are loops that never stop because the condition always remains True. These can cause your program to become unresponsive and may require you to forcibly terminate it. So, it’s important to ensure that the condition in a while loop eventually becomes False to prevent such issues.

Counting with a while loop

count = 0
while count < 5:
    print("Count:", count)
    count += 1

This code will print numbers from 0 to 4 because the loop stops when count becomes 5.

User input validation

user_input = ""
while user_input != "quit":
    user_input = input("Enter 'quit' to exit: ")
    if user_input != "quit":
        print("You typed:", user_input)

This loop keeps asking the user for input until they type “quit”.

Searching for an element in a list

numbers = [1, 2, 3, 4, 5]
search_value = 3
found = False
index = 0
while index < len(numbers) and not found:
    if numbers[index] == search_value:
        found = True
        index += 1
if found:
    print("Found", search_value, "at index", index)
    print(search_value, "not found in the list.")

This loop iterates through a list to find a specific value (search_value). If found, it prints the index where it’s located; otherwise, it indicates that the value is not in the list.

Python Do-While Loops

A Python do-while loop is similar to a while loop, but it runs the code block at least once before checking the condition. This loop is useful when you need to execute a block of code at least once, regardless of whether the condition is true or false.

In Python, there isn’t a built-in do-while loop like in some other programming languages. Instead, you can achieve similar functionality using a while loop combined with a control variable. Here’s how it works.

You set up the initial conditions before entering the loop, then you execute the code block inside the loop. Afterward, you check the condition using a while loop, which determines whether to continue executing the code block. If the condition is true, the loop continues. If it’s false, the loop stops. This setup ensures that the code block executes at least once before the condition is evaluated, making it suitable for scenarios where you want to perform an action before checking a condition.

Let’s say you want to prompt the user to enter a positive number, and you want to keep asking until they actually enter one. Here’s how you could do it in Python using a while loop

number = 0

while number <= 0:
    number = int(input("Enter a positive number: "))

print("You entered:", number)

Let’s say you want to prompt the user to enter a positive number, and you want to keep asking until they actually enter one. Here’s how you could do it in Python using a while loop:

number = 0

while number <= 0:
    number = int(input("Enter a positive number: "))

print("You entered:", number)

In this example, the code block inside the while loop asks the user to input a number. The loop continues as long as the entered number is not positive (less than or equal to zero). Once the user enters a positive number, the condition number <= 0 becomes false, and the loop stops. This way, the code block inside the loop runs at least once, ensuring that the user is prompted to enter a number before checking if it’s positive.

Python nested loops

Python nested loops are loops inside other loops. This means you have a loop inside another loop. The outer loop controls the inner loop. Each time the outer loop runs, the inner loop can run several times. The inner loop will run for each time the outer loop runs.

This creates a pattern of repeating actions. You use nested loops when you need to work with every combination of items in two or more lists or sequences. This is helpful for tasks like processing grid-based data or performing operations on matrices.

For example, you might have a list of people, and for each person, you want to check their list of hobbies. You would use nested loops to go through each person and then go through each hobby of that person. It’s like a loop within a loop, looping over whom you need to do something with and what you need to do with them.

people = ["Alice", "Bob", "Charlie"]
hobbies = {
    "Alice": ["reading", "painting"],
    "Bob": ["gaming", "cooking"],
    "Charlie": ["gardening", "photography"]

for person in people:
    print(f"{person}'s hobbies are:")
    for hobby in hobbies[person]:
        print(f"- {hobby}")

Using Loop Control Statements

Loop control statements are used in programming to control the flow of loops. They include “break,” “continue,” and “pass.” Break stops the loop altogether when a condition is met. Continue skips the rest of the current iteration and moves to the next one. Pass is used to do nothing, acting as a placeholder in situations where syntax requires a statement but no action is needed. These statements help programmers manage loops more efficiently, making their code clearer and more concise.

for number in range(10):
    if number == 5:
        break  # stops the loop
    if number % 2 == 0:
        continue  # skips even numbers

For each number in the given range, the program checks if the number is equal to 5. If it is, the program uses the “break” statement to stop the loop completely. This means that if the number is 5, the loop will end early, and the program will move on to the next part of the code after the loop.

If the number is not equal to 5, the program then checks if the number is even by using the modulo operator (%) to see if the number divided by 2 leaves a remainder of 0. If the number is even, the program uses the “continue” statement to skip the rest of the code inside the loop for that iteration and move on to the next iteration of the loop.

If the number is odd (not even) and not equal to 5, the program prints the number. So, the code will print all odd numbers from 0 to 9, excluding the number 5.

Efficiency Tips for Python Loops

When dealing with large data sets or complex looping, efficiency becomes key. Here are some tips.
- Use list comprehensions instead of loops when possible to make your code more concise and faster.
- Avoid using heavy operations within loops, such as I/O operations.
- Minimize the loop’s work by handling as much as you can outside of the loop.


Python loops are powerful tools that can solve a range of programming problems effectively and efficiently. By understanding and using the different types of loops and control statements discussed in this guide, you can enhance your Python coding skills significantly.


Q: When should I use a for loop instead of a while loop?
A: Use a for loop when you know the number of iterations in advance, such as looping through items in a list. Use a while loop when the number of iterations is not known before the loop starts, and you are looping based on a condition being met.

Q: How can I avoid infinite loops?
A: Always ensure that the condition in a while loop will eventually become false. Also, be careful with the conditions and make sure they change as expected within the loop.

Q: Are there any alternatives to traditional loops in Python?
A: Yes, Python provides several built-in functions like map() and filter() that can often replace loops and are faster and more efficient. Additionally, list comprehensions provide a concise way to create lists.


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