Understanding Lambda Functions
Lambda functions are defined using the lambda keyword, followed by a list of arguments and a single expression. The expression is the return value of the lambda function, and it is automatically returned when the lambda function is called. Here is an example of a simple lambda function that takes a single argument and returns its square:
Python3
# Lambda function to return# square of a numbersquare = lambda x: x ** 2# Printing the square of a number# using square lambda functionprint(square(5)) |
Output:
25
Lambda functions are often used as a shorthand for defining small, one-line functions. They are particularly useful when the function is only needed in a specific context, such as in a loop or as a callback function. Lambda functions can also accept multiple arguments, just like regular functions. For example:
Python3
# lambda function with expression# which takes two values as argumentadd = lambda x, y: x + y# Adding two values using lambda functionprint(add(3, 4)) |
Output:
7
In addition to accepting arguments, lambda functions can also capture the values of variables that are defined outside of their scope. This is known as “closing over” a variable. When a lambda function is defined, it captures the current value of any variables that are used within its body. These variables become part of the lambda function’s environment and are retained even when the lambda function is executed outside of the context in which it was defined.
Here is an example that demonstrates how lambda functions can close over variables:
Python3
# Declaring a variable with value 5x = 5# Creating a function which returns# a lambda functiondef create_lambda(): return lambda: x# copy a function in my_lambdamy_lambda = create_lambda()# printing using my_lambda print(my_lambda()) |
Explanation: In this example, the create_lambda function returns a lambda function that simply returns the value of the x variable. When the lambda function is executed, it returns the value of x, which is 5. This ability to close over variables can be useful in certain situations, but it can also lead to confusion and unexpected behavior when used in a loop.
Why do Python lambda defined in a loop with different values all return the same result?
In this article, we are going to learn why Python lambda defined in a loop with different values all return the same result.
In this article, we will explore the reasons behind this behavior and discuss how to avoid it. We will start by looking at how lambda functions are defined and executed, and how they capture the values of variables that are used within their body. We will then look at an example of how this can cause lambda functions defined in a loop to all return the same result, and finally, we will discuss how to avoid this issue by using default argument values instead of closing over variables.