Skip to main content

Break and Continue Statement in Python

 

Learning Sections     show

Break and Continue Statements in Python

In Python, the break and continue statements are used to control the flow of loops. They provide greater control over how and when the loop should terminate or skip an iteration.

The Break Statement

The break statement is used to exit a loop prematurely when a certain condition is met. It stops the execution of the loop and moves to the code that follows the loop.


# Using break in a loop
for i in range(10):
    if i == 5:
        break
    print(i)
    

In this example, the loop will print numbers from 0 to 4 and then terminate when i equals 5.

The Continue Statement

The continue statement is used to skip the current iteration of a loop and continue with the next iteration. It effectively skips the rest of the code inside the loop for the current iteration only.


# Using continue in a loop
for i in range(10):
    if i == 5:
        continue
    print(i)
    

In this example, the loop will print numbers from 0 to 9, except for 5, which is skipped.

Using Break and Continue in While Loops

The break and continue statements can also be used in while loops to provide additional control over loop execution.


# Using break in a while loop
count = 0

while count < 10:
    print(count)
    count += 1
    if count == 5:
        break
    

In this example, the loop will print numbers from 0 to 4 and then terminate when count equals 5.


# Using continue in a while loop
count = 0

while count < 10:
    count += 1
    if count == 5:
        continue
    print(count)
    

In this example, the loop will print numbers from 1 to 10, except for 5, which is skipped.

Popular posts from this blog

Generators in Python

  Learning Sections          show Generators in Python Generators are a special type of iterator in Python that allow you to iterate over a sequence of items without storing them all in memory at once. They are useful for generating large sequences of data on-the-fly, or for processing data in a memory-efficient manner. Creating Generators In Python, generators are created using generator functions or generator expressions: # Generator function def my_generator ( n ): for i in range ( n ): yield i # Generator expression my_generator = ( i for i in range ( 10 )) A generator function uses the yield keyword to yield values one at a time, while a generator expression creates an anonymous generator. Iterating Over Generators You can iterate over the values produced by a generator using a for loop: for value in my_generator ( 5 ): print ( value ) This w...

Walrus Operator in Python

  Learning Sections          show Walrus Operator in Python The walrus operator ( := ) is a new assignment operator introduced in Python 3.8. It allows you to assign values to variables as part of an expression, making certain constructs more concise. Basic Usage The basic syntax for the walrus operator is: variable_name := expression Here, variable_name is assigned the value of expression , and the result of the expression is also returned. Example: Simplifying Code Consider the following example where we find and print the length of a list if it's greater than 3: # Without walrus operator my_list = [ 1 , 2 , 3 , 4 ] if len ( my_list ) > 3 : length = len ( my_list ) print ( length ) # With walrus operator my_list = [ 1 , 2 , 3 , 4 ] if ( length := len ( my_list )) > 3 : print ( length ) In the second example, the walrus operator assigns the result of len(my...

Inheritance in Python

  Learning Sections          show Inheritance in Python Inheritance is a fundamental concept in object-oriented programming (OOP) that allows a class to inherit attributes and methods from another class. The class that inherits is called the child class or subclass, and the class being inherited from is called the parent class or superclass. Basic Inheritance In Python, a child class inherits from a parent class by specifying the parent class in parentheses after the child class name. Example: class Animal : def __init__ ( self , name ): self . name = name def speak ( self ): raise NotImplementedError ( "Subclass must implement this method" ) class Dog ( Animal ): def speak ( self ): return "Woof!" class Cat ( Animal ): def speak ( self ): return "Meow!" # Create instances of Dog and Cat dog = Dog ( "Buddy" ) cat = Cat ( "Whiskers" ...