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What is the lambda function in Python and why do we need it?
What is the lambda function in Python and why do we need it?

In this article, we will learn about the lambda function in Python and why we need it, and see some practical examples of lambda functions.
What is the lambda function in Python?
Lambda functions are often called "anonymous functions" and are the same as ordinary Python functions except that they can be defined without a name. >def keyword is used to define ordinary functions, while lambda keyword is used to define anonymous functions. However, they are limited to single-line expressions. They, like regular functions, can accept multiple arguments.
grammar
lambda arguments: expression
This function accepts any number of inputs, but only evaluates and returns an expression.
Lambda functions can be used wherever a function object is required.
You must remember that lambda functions are syntactically limited to a single expression.
In addition to other types of expressions in functions, it has a variety of uses in specific programming areas.
Why do we need Lambda functions?
A lambda function requires fewer lines of code than a normal Python function written using the def keyword. However, this is not entirely true, as functions defined using def can be defined in one line. However, def functions are usually defined on more than one line.
They are typically used when a shorter (temporary) function is required, usually within another function (such as a filter, map, or reduce).
You can define a function and call it immediately at the end of the definition using a lambda function. This is not possible with def functions.
Simple example of Python Lambda function
Example
# input string inputString = 'TUTORIALSpoint' # converting the given input string to lowercase and reversing it # with the lambda function reverse_lower = lambda inputString: inputString.lower()[::-1] print(reverse_lower(inputString))
Output
When executed, the above program will generate the following output -
tniopslairotut
Using Lambda functions in condition checks
Example
# Formatting number to 2 decimal places using lambda function
formatNum = lambda n: f"{n:e}" if isinstance(n, int) else f"{n:,.2f}"
print("Int formatting:", formatNum(1000))
print("float formatting:", formatNum(5555.4895412))
Output
When executed, the above program will generate the following output -
Int formatting: 1.000000e+03 float formatting: 5,555.49
What is the difference between a Lambda function and a def defined function?
Example
# creating a function that returns the square root of
# the number passed to it
def square(x):
return x*x
# using lambda function that returns the square root of
# the number passed
lambda_square = lambda x: x*x
# printing the square root of the number by passing the
# random number to the above-defined square function with the def keyword
print("Square of the number using the function with 'def' keyword:", square(4))
# printing the square root of the number by passing the
# random number to the above lambda_square function with lambda keyword
print("Square of the number using the function with 'lambda' keyword:", lambda_square(4))
Output
When executed, the above program will generate the following output -
Square of the number using the function with 'def' keyword: 16 Square of the number using the function with 'lambda' keyword: 16
As shown in the previous example, the square() and lambda_square () functions work the same way and as expected. Let's take a closer look at this example and find out the difference between them -
| Use lambda function | Do not use lambda function |
|---|---|
| Supports single-line statements that return a certain value. | Allows any number of lines within a function block. |
| Ideal for small operations or data manipulation. | This is useful in situations where multiple lines of code are required. |
| Reduce code readability | We can improve readability by using comments and functional explanations. |
Practical uses of Python lambda function
Example
Using Lambda functions with list comprehensions
is_odd_list = [lambda arg=y: arg * 5 for y in range(1, 10)] # looping on each lambda function and calling the function # for getting the multiplied value for i in is_odd_list: print(i())
Output
When executed, the above program will generate the following output -
5 10 15 20 25 30 35 40 45
On each iteration of the list comprehension, a new lambda function is created with the default parameter y (where y is the current item in the iteration). Later, in the for loop, we use i() to call the same function object with default parameters and get the required value. Therefore, is_odd_list holds a list of lambda function objects.
Example
Using Lambda functions with if-else conditional statements
# using lambda function to find the maximum number among both the numbers find_maximum = lambda x, y : x if(x > y) else y print(find_maximum(6, 3))
Output
When executed, the above program will generate the following output -
6
Example
Using Lambda functions with multiple statements
inputList = [[5,2,8],[2, 9, 12],[10, 4, 2, 7]] # sorting the given each sublist using lambda function sorted_list = lambda k: (sorted(e) for e in k) # getting the second-largest element second_largest = lambda k, p : [x[len(x)-2] for x in p(k)] output = second_largest(inputList, sorted_list) # printing the second largest element print(output)
Output
When executed, the above program will generate the following output -
[5, 9, 7]
Python lambda function with filter()
Example
inputList = [3, 5, 10, 7, 24, 6, 1, 12, 8, 4]
# getting the even numbers from the input list
# using lambda and filter functions
evenList = list(filter(lambda n: (n % 2 == 0), inputList))
# priting the even numbers from the input list
print("Even numbers from the input list:", evenList)
Output
When executed, the above program will generate the following output -
Even numbers from the input list: [10, 24, 6, 12, 8, 4]
Python lambda function with map()
Python’s map() function accepts a function and a list as parameters. Called with a lambda function and a list, it returns a new list containing all the lambda-changed items that the function returns for each item.
Example
Use lambda and map() functions to convert all list elements to lowercase
# input list
inputList = ['HELLO', 'TUTORIALSpoint', 'PyTHoN', 'codeS']
# converting all the input list elements to lowercase using lower()
# with the lambda() and map() functions and returning the result list
lowercaseList = list(map(lambda animal: animal.lower(), inputList))
# printing the resultant list
print("Converting all the input list elements to lowercase:\n", lowercaseList)
Output
When executed, the above program will generate the following output -
Converting all the input list elements to lowercase: ['hello', 'tutorialspoint', 'python', 'codes']
in conclusion
In this tutorial, we took an in-depth look at the lambda function in Python with lots of examples. We also learned the difference between lambda functions and def functions.
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