Lambda functions are a Pythonic way of writing simple functions in a single line.
They may be applied to a list using the map statement.
The function filter offers a concise way to filter out all the elements of a list based on the results of a function.
The function reduce continually applies a function to a sequence until a single value is returned.
Defining one-line lambda functions
Instead of defining the function with def, we define the function with lambda.
Here is a ’normal’ function:
# A named function that returns the power of a number: def f(x, y): result = x ** y return result print (f(4,3)) OUT: 64
Re-writing as a lambda function:
g = lambda x,y: x**y print (g(4,3)) OUT: 64
Applying a lambda function to a list with map
In the example below we define a lambda function to convert Celsius to Fahrenheit, and then apply it to a list.
We will first define lambda separately, and then map, before looking at how they can be combined a single line.
The map command generates a ’map object’. To return a list we need to convert that to a list as below
celsius = [0, 10, 20, 30] g = lambda x: (9/5)*x + 32 fahrenheit = list(map(g, celsius)) print (fahrenheit) OUT: [32.0, 50.0, 68.0, 86.0]
This may be compressed further into one line. But there is always a balance to be had between being as concise as possible, and being as clear for others as possible. It may, however, generally be assumed that other experienced Python coders will be familiar with a combined one-line lambda/map function.
celsius = [0, 10, 20, 30] fahrenheit = list(map(lambda x: (9/5)*x + 32, celsius)) print (fahrenheit) [32.0, 50.0, 68.0, 86.0]
Filtering a list with a lambda function
The function filter offers a concise way to filter out all the elements of a list, for which the function function returns True. The function filter(f,l) needs a function f as its first argument. f returns a Boolean value, i.e. either True or False.
This function will be applied to every element of the list l. Only if f returns True will the element of the list be included in the result list.
Here is an example where filter is used to return even numbers from a list. As with the map example above we will combine the filter and lambda function in a single line.
my_list = [0,1,2,3,4,5,6,7,8,9,10] result = list(filter(lambda x: x % 2 == 0, my_list)) print (result) OUT: [0, 2, 4, 6, 8, 10]
Reducing a list with a repeated lambda function call
The reduce function will continually apply a lambda function until only a single value is returned. Though it used to be in core python, it is now found in the functools module.
A simple example is to use reduce to multiply all values in a list. The reduce function replaces the first two elements of a list with the product of those two elements. It will continue until one value is left.
import functools my_list = [10,30,34,56,89] result = functools.reduce(lambda x,y: x*y, my_list) print (result) OUT: 50836800
Alternatives to map, filter and reduce
Most results from map/filter and reduce may also be obtained from using list comprehensions, as previously outlined. Some see list comprehensions as more Pythonic than map, filter and reduce.