Lambda Function in Python – Example Syntax
Lambda functions are anonymous functions that can contain only one expression.
You may think that lambda functions are an intermediate or advanced feature, but here you will learn how you can easily start using them in your code.
In Python, functions are usually created like this:
def my_func(a): # function body
You declare them with the def keyword, give them a name, and then add the list of arguments surrounded by round parenthesis. There could be many lines of code, with as many statements and expressions as you need inside.
But sometimes you might need a function with only one expression inside, for example a function that doubles its argument:
def double(x): return x*2
This is a function that you can use, for example, with the map method.
def double(x): return x*2 my_list = [1, 2, 3, 4, 5, 6] new_list = list(map(double, my_list)) print(new_list) # [2, 4, 6, 8, 10, 12]
This would be a good place to use a lambda function, as it can be created exactly where you need to use it. This means using fewer lines of code and and you can avoid creating a named function that is only used once (and then has to be stored in memory).
You use lambda functions when you need a small function for a short time – for example as an argument of a higher order function like map or filter.
The syntax of a lambda function is lambda args: expression. You first write the word lambda, then a single space, then a comma separated list of all the arguments, followed by a colon, and then the expression that is the body of the function.
Note that you can’t give a name to lambda functions, as they are anonymous (without a name) by definition.
A lambda function can have as many arguments as you need to use, but the body must be one single expression.
For example, you could write a lambda function that doubles its argument: lambda x: x*2, and use it with the map function to double all elements in a list:
my_list = [1, 2, 3, 4, 5, 6] new_list = list(map(lambda x: x*2, my_list)) print(new_list) # [2, 4, 6, 8, 10, 12]
Notice the difference between this one and the function we wrote above with the double function. This one is more compact, and there is not an extra function occupying space in memory.
Or you could write a lambda function that checks if a number is positive, like lambda x: x > 0, and use it with filter to create a list of only positive numbers.
my_list = [18, -3, 5, 0, -1, 12] new_list = list(filter(lambda x: x > 0, my_list)) print(new_list) # [18, 5, 12]
The lambda function is defined where it is used, in this way there is not a named function in memory. If a function is used i only one place it makes sense to use a lambda function to avoid cluttering.
You can also return a lambda function from a function.
If you ever need to create multiple functions that multiply numbers, for example doubling or tripling and so on, lambda can help.
Instead of creating multiple functions, you could create a function multiplyBy as below, and then call this function multiple times with different arguments to create the functions that double, triple, and so on.
def muliplyBy (n): return lambda x: x*n double = multiplyBy(2) triple = muliplyBy(3) times10 = multiplyBy(10)
The lambda function takes the value n from the parent function, so that in double the value of n is 2, in triple it is 3 and in times10 it is 10. Now calling these functions with an argument will multiply that number.
double(6) > 12 triple(5) > 15 times10(12) > 120
If you weren’t using a lambda function here, you would need to define a different function inside multiplyBy, something like the below:
def muliplyBy (x): def temp (n): return x*n return temp
Using a lambda function uses half the lines and makes it more readable.
Lambda functions are a compact way to write functions if your function includes only one small expression. They are not usually something that beginner coders use, but here you have seen how you can easily use them at any level.