Python map() and lambda() Use Cases and Examples

 In Python, map() and lambda functions are often used together for functional programming. Here are some examples to illustrate how they work.

Python map and lambda top use cases

1. Using map() with lambda

The map() function applies a given function to all items in an iterable (like a list) and returns a map object (which can be converted to a list).

Example: Doubling Numbers

numbers = [1, 2, 3, 4, 5]
doubled = list(map(lambda x: x * 2, numbers))

print(doubled)  # Output: [2, 4, 6, 8, 10]

2. Using map() to Convert Data Types

Example: Converting Strings to Integers

string_numbers = ["1", "2", "3", "4", "5"]
integers = list(map(lambda x: int(x), string_numbers))

print(integers)  # Output: [1, 2, 3, 4, 5]

3. Using map() with Multiple Iterables

You can also use map() with more than one iterable. The lambda function can take multiple arguments.

Example: Adding Two Lists Element-wise

list1 = [1, 2, 3]
list2 = [4, 5, 6]
summed = list(map(lambda x, y: x + y, list1, list2))

print(summed)  # Output: [5, 7, 9]

4. Using map() with Custom Functions

You can define a regular function and use it with map().

Example: Squaring Numbers

def square(x):
    return x ** 2

numbers = [1, 2, 3, 4, 5]
squared = list(map(square, numbers))

print(squared)  # Output: [1, 4, 9, 16, 25]

5. Combining filter() and map()

You can combine filter() and map() to process data in a pipeline.

Example: Squaring Even Numbers

numbers = [1, 2, 3, 4, 5]
squared_evens = list(map(lambda x: x ** 2, filter(lambda x: x % 2 == 0, numbers)))

print(squared_evens)  # Output: [4, 16]

Summary

• map() applies a function to each item in an iterable.
• lambda allows you to define small, anonymous functions in line.
• They can be combined for concise and expressive transformations of data.