Python supports multiple programming paradigms, including functional programming. It treats functions as First-Class Citizens, meaning functions can be passed as arguments, returned from other functions, and assigned to variables.

• Lambda Functions: Small anonymous functions defined with the lambda keyword.
• Decorators: A design pattern that allows you to modify the behavior of a function or class without permanently modifying it.
• Map, Filter, Reduce: Common higher-order functions used to process collections.
• List Comprehension: A concise way to create lists based on existing lists.

Decorators are often used for logging, access control, or timing functions.

python Standard
# Lambda
square = lambda x: x * x

# Decorator
def log_execution(func):
    def wrapper(*args, **kwargs):
        print(f"Executing {func.__name__}...")
        return func(*args, **kwargs)
    return wrapper

@log_execution
def say_hello():
    print("Hello!")

say_hello()

• Lambda complexity: Trying to cram too much logic into a lambda (use a named function if it's more than one line).
• Decorator closure: Forgetting to use functools.wraps to preserve the metadata (like __name__) of the original function.
• Overusing map: Using map and filter when a list comprehension would be more readable.