Python lambda

Last Updated : 27 Dec, 2019

In Python, 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:

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.

Example #1:

# Python program to demonstrate 
# lambda functions 
  
  
string ='GeeksforGeeks'
  
# lambda returns a function object 
print(lambda string : string) 

Output

<function <lambda> at 0x7f268eb16f28>

In this above example, the lambda is not being called by the print function but simply returning the function object and the memory location where it is stored.

So, to make the print to print the string first we need to call the lambda so that the string will get pass the print.

Example #2:

# Python program to demonstrate 
# lambda functions 
  
  
x ="GeeksforGeeks"
  
# lambda gets pass to print  
(lambda x : print(x))(x) 

Output

GeeksforGeeks

Example #3: Difference between lambda and normal function call

# Python program 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

Example #4: The lambda function gets more helpful when used inside a function.

# Python program to demonstrate 
# lmabda functions 
  
  
def power(n): 
    return lambda a : a ** n 
  
# base = lambda a : a**2 get  
# returned to base 
base = power(2) 
  
print("Now power is set to 2") 
  
# when calling base it gets  
# executed with already set with 2 
print("8 powerof 2 = ", base(8)) 
  
# base = lambda a : a**5 get  
# returned to base 
base = power(5) 
print("Now power is set to 5") 
  
# when calling base it gets executed 
# with already set with newly 2 
print("8 powerof 5 = ", base(8)) 

Output

Now power is set to 2
8 powerof 2 =  64
Now power is set to 5
8 powerof 5 =  32768

We can also replace list comprehension with Lamba by using a map() method, not only it is a fast but efficient too and let’s also see how to use lambda in the filter().

Example #5: filter() and map()

# Python program to demonstrate 
# lambda functions inside map() 
# and filter() 
  
  
a = [100, 2, 8, 60, 5, 4, 3, 31, 10, 11] 
  
# in filter either we use assignment or  
# conditional operator, the pass actual  
# parameter will get return 
filtered = filter (lambda x: x % 2 == 0, a)  
print(list(filtered)) 
  
# in map either we use assignment or 
# conditional operator, the result of  
# the value will get returned 
maped = map (lambda x: x % 2 == 0, a)  
print(list(maped)) 

Output

[100, 2, 8, 60, 4, 10]
[True, True, True, True, False, True, False, False, True, False]

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