logologo
  • Dashboard
  • Features
  • AI Tools
  • FAQs
  • Jobs
logologo

We source, screen & deliver pre-vetted developers—so you only interview high-signal candidates matched to your criteria.

Useful Links

  • Contact Us
  • Privacy Policy
  • Terms & Conditions
  • Refund & Cancellation
  • About Us

Resources

  • Certifications
  • Topics
  • Collections
  • Articles
  • Services

AI Tools

  • AI Interviewer
  • Xperto AI
  • Pre-Vetted Top Developers

Procodebase © 2025. All rights reserved.

Level Up Your Skills with Xperto-AI

A multi-AI agent platform that helps you level up your development skills and ace your interview preparation to secure your dream job.

Launch Xperto-AI

Understanding Loops in Python

author
Generated by
Abhishek Goyan

21/09/2024

Python

Sign in to read full article

Loops are fundamental constructs in virtually every programming language, including Python. They allow us to execute a block of code repeatedly, which is incredibly useful when we want to perform the same operation multiple times without needing to write the same lines of code over and over again. In Python, the two primary types of loops are for loops and while loops. Let’s take a closer look at each.

The for Loop

The for loop in Python is used to iterate over a sequence (that could be a list, tuple, dictionary, set, or string) and execute a block of code multiple times. This loop is particularly useful when the number of iterations is known ahead of time.

Syntax:

for variable in sequence: # code block to execute

Example:

Let’s consider a simple example where we want to print each number in a list:

numbers = [1, 2, 3, 4, 5] for number in numbers: print(number)

In this example, the for loop iterates through each item in the numbers list. The variable number takes on the value of each item in the list during each iteration, and the print(number) statement is executed for each one, resulting in:

1
2
3
4
5

Using range() with For Loop:

The range() function can be very handy when you want to execute a loop a specific number of times.

for i in range(5): print(i)

This will print:

0
1
2
3
4

The while Loop

The while loop is another type of loop in Python. Unlike the for loop, the while loop continues to execute as long as a certain condition is True. This means that the number of iterations may not be known beforehand.

Syntax:

while condition: # code block to execute

Example:

Here’s an example of a while loop that continues to prompt the user until they enter the correct password:

password = "" correct_password = "1234" while password != correct_password: password = input("Enter the password: ") print("Access granted!")

In this example, the code block inside the while loop will keep asking the user to enter the password until they type in "1234". Once the password is correct, the loop will exit, and "Access granted!" will be printed.

Combining Loops with Control Statements

Both for and while loops can be combined with control statements such as break and continue to enhance their functionality.

  • break Statement: This is used to exit the loop prematurely.
  • continue Statement: This can skip the current iteration and proceed to the next one.

Using break:

Here’s an example that uses the break statement:

for i in range(10): if i == 5: break print(i)

This will print:

0
1
2
3
4

The loop terminates as soon as the value of i reaches 5.

Using continue:

Now, let’s look at continue:

for i in range(5): if i == 2: continue print(i)

This will print:

0
1
3
4

When i equals 2, the loop skips the print(i) statement for that iteration, hence it is not printed.

With these crucial concepts of for and while loops, you should now feel more confident in using them effectively in your Python programming tasks.

By mastering loops, you’ll unlock a powerful tool that will make your code more efficient, readable, and concise. Happy coding!

Popular Tags

Pythonprogrammingloops

Share now!

Like & Bookmark!

Related Collections

  • Mastering LangGraph: Stateful, Orchestration Framework

    17/11/2024 | Python

  • Mastering Scikit-learn from Basics to Advanced

    15/11/2024 | Python

  • LlamaIndex: Data Framework for LLM Apps

    05/11/2024 | Python

  • Seaborn: Data Visualization from Basics to Advanced

    06/10/2024 | Python

  • Mastering Pandas: From Foundations to Advanced Data Engineering

    25/09/2024 | Python

Related Articles

  • Named Entity Recognition with NLTK in Python

    22/11/2024 | Python

  • Working with MongoDB Queries and Aggregation in Python

    08/11/2024 | Python

  • Testing Automation Workflows in Python

    08/12/2024 | Python

  • Crafting Custom Named Entity Recognizers in spaCy

    22/11/2024 | Python

  • Multiprocessing for Parallel Computing in Python

    13/01/2025 | Python

  • CRUD Operations in MongoDB with Python

    08/11/2024 | Python

  • Working with APIs for Automation in Python

    08/12/2024 | Python

Popular Category

  • Python
  • Generative AI
  • Machine Learning
  • ReactJS
  • System Design