Lambda functions, also known as anonymous functions, are incredibly useful tools in Python. They are small, nameless functions that consist of a single expression as their body. In Python, lambda functions are defined using the lambda keyword:
lambda <arguments> : <expression>
It is important to note that the body of a lambda function must be a single expression, not a statement. The key distinction here is that an expression returns a value, while a statement does not.
Let’s start with a simple example of a lambda function that doubles the value of a number:
lambda num : num * 2
Lambda functions can also accept multiple arguments:
lambda a, b : a * b
Although lambda functions cannot be invoked directly, you can assign them to variables:
multiply = lambda a, b : a * b
print(multiply(2, 2)) # 4
The true power of lambda functions lies in their ability to be combined with other Python functionalities, such as map(), filter(), and reduce().
By leveraging lambda functions, you can simplify your code and make it more concise. Whether you are working on small projects or large-scale applications, lambda functions can be a valuable addition to your Python toolkit.