Namaste Coders 👩💻
Before starting have a glance on the below article to know about functions in Python 👇
Built-in Functions User Defined Functions
In this article, we will discuss lambda functions in Python. These are one liner 😎 functions in Python.
What are Lambda Functions 🤔?
Lambda functions or anonymous functions provide a sugary syntax to write functions in one line in Python.
To define an anonymous function we use the keyword lambda in Python.
It can have any number of arguments/parameters but should contain only one expression which has to be returned.
In Lambda function there is no def or return keyword used.
Syntax
lambda parameter_list: expression
Example
#Find square of a number using anonymous function
square=lambda x: x*x
num=5
print("Square of number is: ",square(num))
#Area of a rectangle
area=lambda l,b: l*b
l=4
b=5
print("area of rectangle is : ",area(l,b))
#Square of number is: 25
#area of rectangle is : 20
Using Conditionals in Lambda
Syntax :
lambda parameter_list: if statement (if condition) else else statement
Example
max = lambda a,b : a if a>b else b
print(max(5,4))
#5
tables = [lambda x=x: x*10 for x in range(1, 11)]
for t in tables:
print(t() , end =" ")
#10 20 30 40 50 60 70 80 90 100
Higher Order Functions
Higher Order Functions (HOF) are the functions in which another function is passed as an argument. Lambda Functions are passed as an argument in these functions.
map function
map function computes certain operation on an iterable(list) and returns new list.
Syntax
map(lambda function , iterable)
#returns a list
#even nums square and odd nums cube
nums = [1,2,3,4,5,6]
nums_list = list(map(lambda x :x**2 if x%2==0 else x**3 , nums))
print(nums_list)
#[1, 4, 27, 16, 125, 36]
filter function
As the name suggests, it filters the element from the list on the basis of the condition specified in the function.
Syntax
filter(lambda function , iterable)
Example
nums = [1,2,3,4,5,6]
# Filters all the even nums
even = list(filter(lambda x : x%2==0 , nums))
print(even)
#[2, 4, 6]
reduce function
It accumulates all the values into a single value. Like performing addition or multiplication among all the elements in the list and returning one result.
Syntax
reduce(lambda function , iterable)
Example
nums = [1,2,3,4,5,6]
# importing to reduce function
from functools import reduce
# multiplying all the elements
mul = reduce(lambda a,b : a*b , nums)
print(mul)
#720
P.S. : Will continue with the functions and discuss more in upcoming articles. Stay tuned👧
The End
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