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Returning Values from a Python Function

The Python return Statement: Usage and Best Practices

The Python return statement is a fundamental component of functions and methods in Python. It allows you to send Python objects back to the caller code as the function’s return value. In this tutorial, we will explore how to effectively use the return statement in Python functions, how to return single or multiple values, and best practices for using return statements.

Getting Started With Python Functions

Before diving into the details of the return statement, let’s start by understanding what Python functions are. Most programming languages provide the ability to assign a name to a code block that performs a specific computation. These named code blocks are known as subroutines, routines, procedures, or functions. In Python, functions are defined using the def keyword followed by the function name and a set of parentheses that may contain parameters.

To call a function, you simply use the function name followed by parentheses, potentially passing arguments inside the parentheses. A function can have a return statement that sends back a value to the caller code.

Understanding the Python return Statement

The return statement is used to specify what value a function should return. It allows you to send back Python objects to the caller code, which can then be used for further computation. There are two types of return statements in Python: explicit and implicit.

Explicit return Statements

An explicit return statement explicitly specifies the value to be returned by the function. It uses the return keyword followed by the value or expression that should be returned.

def square(x):
return x ** 2

In the example above, the square function returns the square of the parameter x.

Implicit return Statements

An implicit return statement does not specify a value to be returned. Instead, it ends the function execution, implicitly returning None.

def greet(name):
if name:
print(f"Hello, {name}!")
print("Hello, World!")

In this example, the greet function prints a greeting message if a name is provided as an argument. If no name is provided, it prints a generic greeting and implicitly returns None.

Returning vs Printing

It’s important to differentiate between returning a value from a function and printing a value. When you use the return statement, the value can be saved in a variable and used for further computation. On the other hand, printing a value only displays it on the console, without making it available as a return value.

def add(x, y):
return x + y
result = add(3, 4)
print(result) # Prints 7
def greet(name):
print(f"Hello, {name}!")
greet("Alice") # Prints "Hello, Alice!"

In the example above, the add function returns the sum of its arguments, which is then printed. The greet function, on the other hand, only prints a greeting message without returning a value.

Returning Multiple Values

Python functions can also return multiple values using the return statement. This is often achieved by returning a tuple or a list.

def get_name_and_age():
name = "Alice"
age = 25
return name, age
person = get_name_and_age()
name, age = person
print(name) # Prints "Alice"
print(age) # Prints 25

In this example, the get_name_and_age function returns a tuple containing the name and age. The returned tuple is then unpacked into variables name and age, which can be used individually.

Using the Python return Statement: Best Practices

To use the return statement effectively, it’s important to follow some best practices. Here are some key considerations:

Returning None Explicitly

If a function does not have a specific value to return, it’s a good practice to explicitly return None. This makes the intent of the function clear and prevents confusion.

def do_nothing():
return None

In this example, the do_nothing function explicitly returns None to indicate that it does not have a meaningful return value.

Remembering the Return Value

When calling a function that returns a value, it’s important to store the return value in a variable or use it immediately. Forgetting to do so can lead to unintended behavior or loss of data.

def calculate_total(items):
total = sum(items)
return total
items = [1, 2, 3, 4, 5]
calculate_total(items) # Function call not used

In this example, the calculate_total function returns the sum of the items in a list. However, the return value is not stored or used, which makes the function call ineffective.

Avoiding Complex Expressions

It’s generally recommended to avoid using complex expressions or calculations inside the return statement. Instead, break down the logic into separate steps for improved readability.

def calculate_total(items):
return sum(items) * 1.1 # Complex expression
def calculate_total(items):
tax_rate = 1.1
total = sum(items)
return total * tax_rate # Separate variables

In the first example, the calculate_total function uses a complex expression to calculate the total with tax. In the second example, the logic is divided into separate steps, using variables for improved readability.

Returning Values vs Modifying Globals

It’s generally recommended to avoid modifying global variables inside a function and instead return values. Modifying global variables can lead to unexpected side effects and make the function less reusable or testable.

total = 0
def add_to_total(value):
global total
total += value
print(total) # Prints 5

In this example, the add_to_total function modifies the global variable total. While this may work in simple scenarios, it can lead to unexpected behavior when working with larger codebases or collaborating with other developers. Instead, it’s recommended to return the updated value and let the caller code handle the update.

Using return With Conditionals

The return statement can be used with conditionals to control the flow of execution. In some cases, it may be necessary to return early from a function based on certain conditions.

def is_even(number):
if number % 2 == 0:
return True
return False
result = is_even(4)
print(result) # Prints True

In this example, the is_even function returns True if the input number is even, and False otherwise. By using the return statement inside the conditional, the function can exit early if the condition is met.

Returning True or False

In many cases, it’s common to write functions that return a boolean value, indicating a certain condition or result. In such cases, it’s best to directly return True or False instead of using conditional statements.

def is_positive(number):
return number > 0
result = is_positive(-3)
print(result) # Prints False

In this example, the is_positive function directly returns True if the input number is positive, and False otherwise. This improves readability and reduces the risk of errors.

Short-Circuiting Loops

The return statement can be used to short-circuit loops when a certain condition is met. This can help improve performance and efficiency in some cases.

def has_duplicates(items):
seen = set()
for item in items:
if item in seen:
return True
return False
items = [1, 2, 3, 4, 5]
result = has_duplicates(items)
print(result) # Prints False

In this example, the has_duplicates function checks if a list contains any duplicate values. It uses the return statement to immediately exit the loop and return True as soon as a duplicate is found. If no duplicates are found, it returns False.

Recognizing Dead Code

Sometimes, certain parts of a function may become unreachable due to changes in the code over time. It’s important to recognize and remove such dead code to improve the readability and maintainability of your code.

def get_user_role(user):
if user.is_admin:
return "Admin"
elif user.is_guest:
return "Guest"
# Dead code
return "User"
user = User()
role = get_user_role(user)
print(role) # Prints "Admin" or "Guest"

In this example, the get_user_role function has a dead code block that will never be executed. It can be safely removed to improve code clarity.

Returning Multiple Named-Objects

Python functions can also return multiple named objects using dictionaries or namedtuples. This can improve code readability and make the returned values more self-explanatory.

from collections import namedtuple
def get_person():
Person = namedtuple("Person", ["name", "age"])
return Person(name="Alice", age=25)
person = get_person()
print( # Prints "Alice"
print(person.age) # Prints 25

In this example, the get_person function returns a Person object with the properties name and age. By using a named tuple, the returned object provides named attributes, making it easier to work with.


The Python return statement is a powerful tool that allows you to send Python objects back to the caller code. It’s important to use it effectively and follow best practices to write more readable, maintainable, and concise functions. In this tutorial, we learned about various aspects of the return statement, including returning single or multiple values, using conditionals, avoiding complex expressions, and more. By applying these techniques, you’ll be able to write Pythonic and robust functions that serve your programming needs.

Remember to practice using the return statement in your own code and explore more advanced topics related to functions and methods in Python. With continued practice and exploration, you’ll become more comfortable and proficient in utilizing the return statement in your projects.