**Prerequisite :** Anonymous function

In the program below, we have used anonymous (lambda) function inside the map() built-in function to find the powers of 2. In Python, anonymous function is defined without a name.

While normal functions are defined using the def keyword, in Python anonymous functions are defined using the lambda keyword. Hence, anonymous functions are also called lambda functions.**Syntax:**

lambda arguments: expression

Lambda functions can have any number of arguments but only one expression. The expression is evaluated and returned**Example:**

Input : ('The total terms is:', 10) Output : ('2 raised to power', 0, 'is', 1) ('2 raised to power', 1, 'is', 2) ('2 raised to power', 2, 'is', 4) ('2 raised to power', 3, 'is', 8) ('2 raised to power', 4, 'is', 16) ('2 raised to power', 5, 'is', 32) ('2 raised to power', 6, 'is', 64) ('2 raised to power', 7, 'is', 128) ('2 raised to power', 8, 'is', 256) ('2 raised to power', 9, 'is', 512)

`# Python Program to display the powers ` `# of 2 using anonymous function` ` ` `# Change this value for a different result` `terms ` `=` `10` ` ` `# Uncomment to take number of terms from user` `# terms = int(input("How many terms? "))` ` ` `# use anonymous function` `result ` `=` `list` `(` `map` `(` `lambda` `x: ` `2` `*` `*` `x, ` `range` `(terms)))` ` ` `# display the result` `print` `(` `"The total terms is:"` `, terms)` `for` `i ` `in` `range` `(terms):` ` ` `print` `(` `"2 raised to power"` `, i, ` `"is"` `, result[i])` |

Output:

('The total terms is:', 10) ('2 raised to power', 0, 'is', 1) ('2 raised to power', 1, 'is', 2) ('2 raised to power', 2, 'is', 4) ('2 raised to power', 3, 'is', 8) ('2 raised to power', 4, 'is', 16) ('2 raised to power', 5, 'is', 32) ('2 raised to power', 6, 'is', 64) ('2 raised to power', 7, 'is', 128) ('2 raised to power', 8, 'is', 256) ('2 raised to power', 9, 'is', 512)

Attention geek! Strengthen your foundations with the **Python Programming Foundation** Course and learn the basics.

To begin with, your interview preparations Enhance your Data Structures concepts with the **Python DS** Course. And to begin with your Machine Learning Journey, join the **Machine Learning – Basic Level Course**