- Lambda functions in Python are temporary processes for small tasks or calculations, reducing code space and processing time.
- These anonymous functions are created without names and can be assigned to a variable for use.
- Lambda functions are often used within higher-order functions like ‘map()’, ‘filter()’, and ‘reduce()’ to simplify code.
Are you working with higher-order functions and want to simplify your code? A lambda function in Python, otherwise known as an anonymous function, can be used in a pinch. This tool is a versatile stand-in for common tasks or calculations.
So if they’re so versatile, how do they work? In this article, we explain how lambda functions work and how to apply them. We even provide the basic syntax to give you a base to start on. So let’s get into it and shorten our codes.
What Is a Lambda Function in Python?
Do you have a one-off action that you need to use, but don’t want to spend waste code space writing the function out? A lambda function in Python acts as a temporary process that works for a small task or calculation. While you won’t use them for complicated tasks, they help cut down processing time.
A lambda function in Python creates small anonymous functions without having to name them. To do this, you’ll assign the object to a variable. Here’s what that will look like:
lambda arguments: expression
The lambda keyword signals the use of the lambda function. Alongside, you’ll specify which parameters to send it. After you set the arguments, you’ll define the logic. Finally, when the lambda function is defined, you can assign it to a variable for use.
How Do You Use These Functions?
Typically, you’ll use a lambda function in Python within a higher-order function. This helps simplify the code that already starts to feel convoluted. For example, you may use lambda functions with “map()”, “filter()”, or “reduce()”. Here’s what the syntax might look like in an example “map()” function:
numbers = [1, 2, 3, 4, 5] # Using a lambda function with map() to square each number squared_numbers = list(map(lambda x: x**2, numbers)) print(squared_numbers) # Output: [1, 4, 9, 16, 25]
While Lambda functions work well for small tasks within larger ones, they aren’t very useful for complicated ones. This shows the limitation of the tool, making it largely inflexible. And the deeper within an argument lambda functions find themselves, the harder it becomes to debug them when something goes wrong.
Because of their versatility and ease of use, lambda functions have several applications. You’ll often find them used in functional programming, data transformation, event handling, and more. Understanding how a lambda function in Python works can help you consider creative tasks for the tool.
The image featured at the top of this post is ©Casimiro PT/Shutterstock.com.