As a seasoned Python developer with a decade of experience under my belt, I’ve had my fair share of encounters with lambda functions. While they can be powerful and concise tools for functional programming, I’ve learned that there are certain practices that are best avoided to maintain code readability and maintainability.

In this article, I’ll share ten things I’ve stopped doing in Python lambda functions over the years and provide code snippets to explain each one.

`# Before`

result = lambda x, y: x * (y + 2)# After

def multiply_with_constant(x, y):

constant = 2

return x * (y + constant)

Complex expressions within lambda functions can quickly become unreadable. Instead, I’ve started using regular functions when dealing with intricate calculations or operations. This approach enhances code clarity and makes it easier for others to understand my code.

`# Before`

sorted_list = sorted(my_list, key=lambda x: x.split()[1])# After

def get_second_element(x):

return x.split()[1]

sorted_list = sorted(my_list, key=get_second_element)

While lambda functions can be convenient, they are not always the best choice. For simple operations, using a regular function with a meaningful name can make your code more expressive and self-documenting.

`# Before`

sum_of_two = lambda x, y: x + y# After

def add(x, y):

return x + y

When dealing with multiple parameters, lambda functions can become unwieldy. I’ve found it better to define regular functions that clearly express their intent and parameters.

`# Before`

result = lambda x, y: x if x > y else y# After

def max_value(x, y):

return x if x > y else y

Lambda functions are meant for simple expressions. Complex logic is best handled by regular functions, making your code more maintainable and easier to understand.