Skip to main content

For Loop with else in Python

 

Learning Sections          show

For Loop with Else in Python

In Python, a `for` loop can have an `else` clause that executes when the loop completes normally (i.e., not interrupted by a `break` statement). Here are some examples:

1. Basic Example

In this example, the `else` block executes because the loop completes without encountering a `break` statement.


# A list of numbers
numbers = [1, 2, 3, 4, 5]

# Iterate through the list
for number in numbers:
    print(number)
else:
    print("Loop completed without break")

# Output:
# 1
# 2
# 3
# 4
# 5
# Loop completed without break
    

2. With Break

In this example, the `else` block does not execute because the loop is terminated by a `break` statement.


# A list of numbers
numbers = [1, 2, 3, 4, 5]

# Iterate through the list
for number in numbers:
    if number == 3:
        break
    print(number)
else:
    print("Loop completed without break")

# Output:
# 1
# 2
    

3. Searching in a List

Using `else` with a `for` loop can be helpful for search operations where you need to know if an item was found or not.


# A list of fruits
fruits = ['apple', 'banana', 'cherry']

# Item to search for
search_item = 'banana'

# Iterate through the list
for fruit in fruits:
    if fruit == search_item:
        print(fruit, "found!")
        break
else:
    print(search_item, "not found!")

# Output:
# banana found!
    

4. No Break

When the item is not found, the `else` block executes because the loop completes normally.


# A list of fruits
fruits = ['apple', 'banana', 'cherry']

# Item to search for
search_item = 'orange'

# Iterate through the list
for fruit in fruits:
    if fruit == search_item:
        print(fruit, "found!")
        break
else:
    print(search_item, "not found!")

# Output:
# orange not found!
    

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...

Lambda Functions in Python

  Learning Sections          show Lambda Functions in Python Lambda functions, also known as anonymous functions, are small, unnamed functions defined with the lambda keyword. They can have any number of arguments but only one expression. Lambda functions are often used for short, throwaway functions that are not needed elsewhere in the code. 1. Basic Syntax The syntax for a lambda function is: lambda arguments : expression Example: add = lambda x , y : x + y print ( add ( 2 , 3 )) # Output: 5 2. Using Lambda with Built-in Functions Lambda functions are commonly used with built-in functions like map() , filter() , and sorted() . Example with map() : numbers = [ 1 , 2 , 3 , 4 , 5 ] squared = map ( lambda x : x ** 2 , numbers ) print ( list ( squared )) # Output: [1, 4, 9, 16, 25] Example with filter() : numbers = [ 1 , 2 , 3 , 4 , 5 ] even = filter ( lambd...