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Functional programming in Python is possible with the use of lambda map reduce and filter functions. This article briefly describe use of each these functions.

Lambda : Lambda specifies an anonymous function. It is used to declare a function with no name; When you want to use function only once. But why would you declare a function if you don’t want to reuse the code? Read on you’ll see. Syntax: lambda arg1, arg2 : expression

lambda x : x*x

This lambda expression with just one argument x which returns square of x.

Map : It takes two arguments, the first argument is name of a function and second argument is a sequence. map() applies function f to all elements in the sequence and returns a new sequence. Syntax: map (func, sequence)

list = [1, 2, 3]
map (lambda x : x*x, list)

#output: [1, 4, 9]

This code also demonstrates use of lambda. Instead writing a square function we substituted it with a lambda expression. map() applies it to all elements in the list and returns a new list with each element square of original element.

Reduce: reduce() continuously applies a function to a sequence and returns one value. In the following example we sum all elements in the original list. Syntax: reduce (func, sequence)

(lambda x,y : x+y, list)

#output: 6

Filter: It filters all values in a sequence for which given function returns True. Syntax: filter (booleanFunc, sequence)

filter (lambda x : x%2, list)
#output: [1, 3]

Above example returns all odd integers in the list. Remember 2%2=0 is treated as boolean value False.