What are anonymous functions in python?

The def keyword is used to define a function in Python, as we have seen in the previous chapter. The lambda keyword is used to define anonymous functions in Python. Usually, such a function is meant for one-time use.

lambda [arguments] : expression

The lambda function can have zero or more arguments after the : symbol. When this function is called, the expression after : is executed.

square = lambda x : x * x

Above, the lambda function starts with the lambda keyword followed by parameter x. An expression x * x after : returns the value of x * x to the caller. The whole lambda function lambda x : x * x is assigned to a variable square in order to call it like a named function. The variable name becomes the function name so that We can call it as a regular function, as shown below.

The above lambda function definition is the same as the following function:

def square(x):
    return x * x

The expression does not need to always return a value. The following lambda function does not return anything.

>>> greet = lambda name: print('Hello ', name) 
>>> greet('Steve')
Hello Steve

The lambda function can have only one expression. Obviously, it cannot substitute a function whose body may have conditionals, loops, etc.

The following lambda function contains multiple parameters:

>>> sum = lambda x, y, z : x + y + z 
>>> sum(5, 10, 15)
30

The following lambda function can take any number of parameters:

>>> sum = lambda *x: x[0]+x[1]+x[2]+x[3]  
>>> sum(5, 10, 15, 20)
50

Parameterless Lambda Function

The following is an example of the parameterless lambda function.

>>> greet = lambda : print('Hello World!')
>>> greet()
Hello World!

Anonymous Function

We can declare a lambda function and call it as an anonymous function, without assigning it to a variable.

>>> (lambda x: x*x)(5)
25

Above, lambda x: x*x defines an anonymous function and call it once by passing arguments in the parenthesis (lambda x: x*x)(5).

In Python, functions are the first-class citizens, which means that just as literals, functions can also be passed as arguments.

The lambda functions are useful when we want to give the function as one of the arguments to another function. We can pass the lambda function without assigning it to a variable, as an anonymous function as an argument to another function.

>>> def dosomething(fn):
	    print('Calling function argument:')
	    fn()
>>> dosomething(lambda : print('Hello World')) # passing anonymous function
Calling function argument:
Hello World
>>> myfn = lambda : print('Hello World') 
>>> dosomething(myfn) # passing lambda function

Above, the dosomething() function is defined with the fn parameter which is called as a function inside dosomething(). The dosomething(lambda : print('Hello World')) calls the dosomething() function with an anonymous lambda function as an argument.

Python has built-in functions that take other functions as arguments. The map(), filter() and reduce() functions are important functional programming tools. All of them take a function as their argument. The argument function can be a normal function or a lambda function.

>>> sqrList = map(lambda x: x*x, [1, 2, 3, 4]) # passing anonymous function
>>> next(sqrList)
1
>>> next(sqrList)
4
>>> next(sqrList)
9
>>> next(sqrList)
16
>>> next(sqrList)
25

Python Lambda Functions are anonymous function means that the function is without a name. As we already know that the def keyword is used to define a normal function in Python. Similarly, the lambda keyword is used to define an anonymous function in Python. 

Python Lambda Function Syntax

Syntax: lambda arguments: expression

  • This function can have any number of arguments but only one expression, which is evaluated and returned.
  • One is free to use lambda functions wherever function objects are required.
  • You need to keep in your knowledge that lambda functions are syntactically restricted to a single expression.
  • It has various uses in particular fields of programming, besides other types of expressions in functions.

Python Lambda Function Example

Python3

str1 = 'GeeksforGeeks'

rev_upper = lambda string: string.upper()[::-1]

print(rev_upper(str1))

Output:

SKEEGROFSKEEG

Explanation: In the above example, we defined a lambda function(rev_upper) to convert a string to it’s upper-case and reverse it.

Use of Lambda Function in Python

Example 1: Condition Checking Using Python lambda function

Python3

format_numeric = lambda num: f"{num:e}" if isinstance(num, int) else f"{num:,.2f}"

print("Int formatting:", format_numeric(1000000))

print("float formatting:", format_numeric(999999.789541235))

Output:

Int formatting: 1.000000e+06
float formatting: 999,999.79

Example 2: Difference Between Lambda functions and def defined function

Python3

def cube(y):

    return y*y*y

def lambda_cube(y): return y*y*y

print("Using function defined with `def` keyword, cube:", cube(5))

print("Using lambda function, cube:", lambda_cube(5))

Output:

Using function defined with `def` keyword, cube: 125
Using lambda function, cube: 125

As we can see in the above example, both the cube() function and lambda_cube() function behave the same and as intended. Let’s analyze the above example a bit more:

With lambda function Without lambda function
Supports single line statements that returns some value. Supports any number of lines inside a function block
Good for performing short operations/data manipulations. Good for any cases that require multiple lines of code.
Using lambda function can sometime reduce the readability of code. We can use comments and function descriptions for easy readability.

Practical Uses of Python lambda function

Example 1: Python Lambda Function with List Comprehension

In this example, we will use the lambda function with list comprehension.

Python3

is_even_list = [lambda arg=x: arg * 10 for x in range(1, 5)]

for item in is_even_list:

    print(item())

Output:

10
20
30
40

Explanation: On each iteration inside the list comprehension, we are creating a new lambda function with default argument of x (where x is the current item in the iteration). Later, inside the for loop, we are calling the same function object having the default argument using item() and getting the desired value. Thus, is_even_list stores the list of lambda function objects.

Example 2: Python Lambda Function with if-else

Here we are using Max lambda function to find the maximum of two integers.

Python3

Max = lambda a, b : a if(a > b) else b

print(Max(1, 2))

Output:

2

Example 3: Python Lambda with Multiple statements

Lambda functions does not allow multiple statements, however, we can create two lambda functions and then call the other lambda function as a parameter to the first function. Let’s try to find the second maximum element using lambda.

Python3

List = [[2,3,4],[1, 4, 16, 64],[3, 6, 9, 12]]

sortList = lambda x: (sorted(i) for i in x)

secondLargest = lambda x, f : [y[len(y)-2] for y in f(x)]

res = secondLargest(List, sortList)

print(res)

Output:

[3, 16, 9]

Explanation: In the above example, we have created a lambda function that sorts each sublist of the given list. Then this list is passed as the parameter to the second lambda function, which returns the n-2 element from the sorted list, where n is the length of the sublist.

Lambda functions can be used along with built-in functions like filter(), map() and reduce().

Using lambda() Function with filter()

The filter() function in Python takes in a function and a list as arguments. This offers an elegant way to filter out all the elements of a sequence “sequence”, for which the function returns True. Here is a small program that returns the odd numbers from an input list: 

Example 1: Filter out all odd numbers using filter() and lambda function

Here, lambda x: (x % 2 != 0) returns True or False if x is not even. Since filter() only keeps elements where it produces True, thus it removes all odd numbers that generated False.

Python

li = [5, 7, 22, 97, 54, 62, 77, 23, 73, 61]

final_list = list(filter(lambda x: (x % 2 != 0), li))

print(final_list)

Output:

[5, 7, 97, 77, 23, 73, 61]

Example 2: Filter all people having age more than 18, using lambda and filter() function

Python3

ages = [13, 90, 17, 59, 21, 60, 5]

adults = list(filter(lambda age: age > 18, ages))

print(adults)

Output:

[90, 59, 21, 60]

Using lambda() Function with map()

The map() function in Python takes in a function and a list as an argument. The function is called with a lambda function and a list and a new list is returned which contains all the lambda modified items returned by that function for each item. Example: 

Example 1: Multiply all elements of a list by 2 using lambda and map() function

Python

li = [5, 7, 22, 97, 54, 62, 77, 23, 73, 61]

final_list = list(map(lambda x: x*2, li))

print(final_list)

Output:

[10, 14, 44, 194, 108, 124, 154, 46, 146, 122]

Example 2: Transform all elements of a list to upper case using lambda and map() function

Python3

animals = ['dog', 'cat', 'parrot', 'rabbit']

uppered_animals = list(map(lambda animal: animal.upper(), animals))

print(uppered_animals)

Output:

['DOG', 'CAT', 'PARROT', 'RABBIT']

Using lambda() Function with reduce()

The reduce() function in Python takes in a function and a list as an argument. The function is called with a lambda function and an iterable and a new reduced result is returned. This performs a repetitive operation over the pairs of the iterable. The reduce() function belongs to the  functools module. 

Example 1: Sum of all elements in a list using lambda and reduce() function

Python

from functools import reduce

li = [5, 8, 10, 20, 50, 100]

sum = reduce((lambda x, y: x + y), li)

print(sum)

Output:

193

Here the results of the previous two elements are added to the next element and this goes on till the end of the list like (((((5+8)+10)+20)+50)+100).

Example 2: Find the maximum element in a list using lambda and reduce() function

Python3

import functools

lis = [1, 3, 5, 6, 2, ]

print("The maximum element of the list is : ", end="")

print(functools.reduce(lambda a, b: a if a > b else b, lis))

Output:

The maximum element of the list is : 6

What is anonymous function with example?

An anonymous function is a function that was declared without any named identifier to refer to it. As such, an anonymous function is usually not accessible after its initial creation. Normal function definition: function hello() { alert('Hello world'); } hello();

What are anonymous functions used for?

Anonymous functions are often arguments being passed to higher-order functions or used for constructing the result of a higher-order function that needs to return a function. If the function is only used once, or a limited number of times, an anonymous function may be syntactically lighter than using a named function.

Is lambda a anonymous function?

A lambda function is a small anonymous function. A lambda function can take any number of arguments, but can only have one expression.

What is difference between anonymous and lambda function?

A lambda expression is a short form for writing an anonymous class. By using a lambda expression, we can declare methods without any name. Whereas, Anonymous class is an inner class without a name, which means that we can declare and instantiate class at the same time.