2.5. Function

2.5.1. Omit Else Clauses in a Python Function to Improve Code Readability

If you are using if statements to return different values, adding an else clause may introduce unnecessary complexity. Omitting the else clause for the last condition will make the code simpler and easier to read.

def get_discount(price):
    if price >= 100:
        return 20
    if price >= 50:
        return 10
    else: # not necessary
        return 5

def get_discount(price):
    if price >= 100:
        return 20
    if price >= 50:
        return 10
    return 5 # omit else

2.5.2. When to Use and Not to Use Lambda Functions

Lambda functions are helpful when defining a function that is used only once and does not require a name.

numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9]

# use lambda function because it is used only once
even_numbers = filter(lambda num: num % 2 == 0, numbers)

However, if you need to reuse a function in various parts of your code, use a named function to avoid repeating the same code.

# use named function because it is used multiple times
def is_even(num: int):
    return num % 2 == 0

even_numbers = filter(is_even, numbers)
any(is_even(num) for num in numbers)

True

2.5.3. How to Pass an Arbitrary Number of Arguments to a Python Function

If you want to create a function that takes an arbitrary number of arguments, use *args or **kwargs.

*args allows variable arguments as a set, while **kwargs allows variable keyword arguments as a dictionary.

def multiply(*nums):
    print(f"nums: {nums}")
    res = 1
    for num in nums:
        res *= num
    return res

multiply(1, 2, 3)

nums: (1, 2, 3)

6

def add_to_order(**new_order):
    print(f"new_order: {new_order}")
    cart = {'apple': 2, 'orange': 3}
    cart.update(new_order) 
    return cart  

add_to_order(kiwi=2, apple=1)

new_order: {'kiwi': 2, 'apple': 1}

{'apple': 1, 'orange': 3, 'kiwi': 2}

2.5.4. Decorator in Python

If you want to apply a common piece of functionality to multiple functions while keeping the code clean, use decorator. Decorator modifies the behavior of your Python functions without altering the code directly.

In the code below, time_func is a decorator that can be used to track the execution time of any function.

import time 

def time_func(func):
    def wrapper(*args, **kwargs):
        start = time.time()
        func(*args, **kwargs)
        end = time.time()
        print(f'Elapsed time: {(end - start) * 1000:.3f}ms')
    return wrapper

@time_func
def add(num1: int, num2: int):
    print(f"Add {num1} and {num2}")
    return num1 + num2

@time_func
def multiply(num1: int, num2: int):
    print(f"Multiply {num1} and {num2}")
    return num1 * num2

add(1, 2)
multiply(1, 2)

Add 1 and 2
Elapsed time: 1.006ms
Multiply 1 and 2
Elapsed time: 0.027ms