def keyword is used to define ordinary functions, while the lambda keyword is used to define anonymous functions. However, they are limited to single-line expressions. They, like regular functions, can accept multiple arguments. Syntax lambdaarguments:expression This function accepts any number of inputs, but only evaluates and returns an expression. Lamb"/> def keyword is used to define ordinary functions, while the lambda keyword is used to define anonymous functions. However, they are limited to single-line expressions. They, like regular functions, can accept multiple arguments. Syntax lambdaarguments:expression This function accepts any number of inputs, but only evaluates and returns an expression. Lamb">
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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.
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.
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.
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.
# 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))
When executed, the above program will generate the following output -
tniopslairotut
# 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))
When executed, the above program will generate the following output -
Int formatting: 1.000000e+03 float formatting: 5,555.49
# 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))
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. |
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())
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.
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))
When executed, the above program will generate the following output -
6
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)
When executed, the above program will generate the following output -
[5, 9, 7]
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)
When executed, the above program will generate the following output -
Even numbers from the input list: [10, 24, 6, 12, 8, 4]
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.
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)
When executed, the above program will generate the following output -
Converting all the input list elements to lowercase: ['hello', 'tutorialspoint', 'python', 'codes']
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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