Lambda- Anonymous Functions

Anonymous function means that a function is without a name. As we already know that def keyword is used to define the normal functions and the lambda keyword is used to create anonymous functions. It has the following 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.

Let’s look at this example and try to understand the difference between a normal def defined function and lambda function.

CODE

# Python program for implementation of Lambda 
  
# Python code to illustrate cube of a number  
# showing difference between def() and lambda(). 
def cube(y): 
    return y*y*y; 
  
g = lambda x: x*x*x 
print(g(7)) 
  
print(cube(5)) 

Output:           343
125

• Without using Lambda : Here, both of them returns the cube of a given number. But, while using def, we needed to define a function with a name cube and needed to pass a value to it. After execution, we also needed to return the result from where the function was called using the return keyword.
• Using Lambda : Lambda definition does not include a “return” statement, it always contains an expression which is returned. We can also put a lambda definition anywhere a function is expected, and we don’t have to assign it to a variable at all. This is the simplicity of lambda functions.

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

Use of lambda() with filter()

The map() function in Python takes in a function and a list as 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:

CODE

# Python code to illustrate 
# filter() with lambda() 
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]

Use of lambda() with map()

The map() function in Python takes in a function and a list as 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:filter_none

CODE

# Python code to illustrate  
# map() with lambda()  
# to get double of a list. 
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]

Use of lambda() with reduce()

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

CODE

# Python code to illustrate  
# reduce() with lambda() 
# to get sum of a list 
from functools import reduce
li = [5, 8, 10, 20, 50, 100] 
sum = reduce((lambda x, y: x + y), li) 
print (sum) 

Output:           193