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Python Lambda


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What are Python Lambda Functions?

Python Lambda functions are functions that do not have any name. Hence they are also known as anonymous or nameless functions. The word ‘lambda’ is a keyword. The function that follows the ‘lambda’ keyword is anonymous.

Functions Vs Lambda functions:

  • To define normal functions in function in Python, we use the ‘def’ keyword. We use ‘lambda’ keyword to define anonymous functions.
  • The lambda function can have any number of arguments, but they can return only one value in the form of expression. The Python lambda functions are syntactically restricted to a single expression.

Why use Python Lambda Functions?

  • Lambda functions come into the picture when we need a function only once.
  • Python Lambda functions are often used with built-in functions like filter(), map(), reduce(), etc.,
  • Using Lambda functions reduces the number of lines of code compared to normal functions.

Syntax:

lambda arguments:expression

As mentioned already, a lambda function can take any number of arguments but a single expression. Hence the number of arguments ranges from 0 to any number.

Examples:

With a single argument:

Here is an example to print the square root of a number.

a=lambda x:x**(1/2)
print(a(225))
15.0

x – is the argument.

x**(1/2) – The expression that gets evaluated.

lambda x:x**(1/2) – anonymous function which returns a function object.

>>> print(lambda x: x**(1/2))
<function <lambda> at 0x048388A0>

With multiple arguments:

Below is an example of a python lambda function that accepts multiple parameters.

a=lambda a,b,c:a+b+c
print(a(3,10,12))
25

When we write the same example using normal functions, which will take more lines. For instance,

def func(a,b,c):
    return a+b+c

print(func(3,10,12))

You might get this question, when we say lambda as nameless functions, then why we need to assign lambda function to some variable and call the lambda function using a variable. In general, we use lambda functions with higher-order functions and built-in functions like filter, map, reduce, etc.,

READ  Python Variables

Lambda functions with normal functions:

def func(x):
    return lambda :x*x

a=func(4)
b=func(5)
print(a())
print(b())
16
25

In the above example, the function func() returns a lambda function. Whenever we call the func(), we make use of the lambda function.

lambda function with filter:

The filter function filters the iterable with the help of another function. The filter function takes the function to filter the iterable and iterable as an argument.

Syntax:

filter(function, iterable)

Example:

Let’s see an example to filter the even numbers from the list.

l=[7,4,9,2,3,8,5,12,10]
new_l=list(filter(lambda a:a%2==0,l))
print(new_l)
[4, 2, 8, 12, 10]

lambda function with map:

The map function applies a function to all the values in an iterable. The map function takes the function to be applied to the iterable and iterable as an argument.

Syntax:

map(function, iterable)

Example:

Get the even numbers from a list using the map function.

l=[12,14,3,9,15,25]
new_list = list(map(lambda x: (x%2 == 0), l))
print(new_list)
[True, True, False, False, False, False]

lambda function with reduce:

The reduce function applies a function to all the values of an iterable and returns a single number. The reduce function takes the function and iterable as an argument.

Syntax:

reduce(function, iterable)

Example:

Get the product of all the numbers in a list.

from functools import reduce

l=[12,14,3,9,15,25]
product=reduce((lambda x,y:x*y), l)
print(product)
1701000
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