The World of Python Programming

Null Checks in Python: Using None and Best Practices

Data Types & Structures
目次

1. Introduction

When writing programs in Python, “null checks” are essential for confirming that data does not exist or for handling errors. In Python, a special value corresponding to “null” in other languages, None, is provided and is used in various situations. This article explains how to perform “null checks” and how to use them effectively from Python’s perspective. It’s written to be easy to understand for beginners and aimed at providing content that can be applied in real development, so please use it as a reference.

2. What is “null” in Python?

Programming languages have a special value that represents the absence of data or an invalid state. For example, JavaScript and Java use “null”, and PHP uses “NULL”, but in Python this is called “None“.

Basic concepts of Python’s None

Python’s None corresponds to “null” in other languages and indicates that data is absent or has not been specifically set. In Python, all data is treated as objects, and None is no exception — it is an object of the special type NoneType. For example, by assigning None to a variable as shown below, you indicate that no data has been set.
x = None
This makes it explicit that the variable x has no value set.

3. Basic usage of None

In Python, None is used in many situations to explicitly indicate a particular state. Here we’ll introduce the basic usage of None.

Assigning None to a variable

Assigning None to a variable indicates that it “contains no value” or is “unset”. This is used for data that hasn’t been decided yet or for variables you want to temporarily leave empty.
name = None
age = None

Functions that return None

When a return value is not particularly needed in a function, or you want to indicate “returning nothing” under certain conditions, it’s common to return None. For example, in a function like the one below you can return None when the condition is not met.
def find_even_number(numbers):
    for num in numbers:
        if num % 2 == 0:
            return num
    return None
This function finds and returns an even number, but if none is found it returns None to indicate that no matching data exists.

4. How to determine None

In Python, a common way to check whether None is set is to use the is operator. In particular, the is operator is highly reliable for testing None and is recommended by the official Python style guide (PEP 8). The == operator can also be used, but since it behaves differently you should be careful. This section explains each method of testing.

How to check using the is operator

The is operator is the standard way in Python to check whether a variable is None. is checks object identity, so it is suitable for determining None. Let’s look at the following example.
x = None
if x is None:
    print("x is None")
In this code, if the variable x is None, it will print “x is None”. Using the is operator makes the code clearer and more readable, so it is recommended to use is for testing None in particular.

Differences and caveats when using the == operator

In Python, you can also use the == operator to test for None, but the == operator is meant to compare “value equality”. It will also work for testing None, but it can sometimes produce unexpected results, so it’s better to use is when testing None.
x = None
if x == None:  # Works, but not recommended
    print("x is None")

Checking for the negative case (is not)

If you want to confirm that a variable is not None, use the is not operator. is not is convenient for specifying what to do when a variable is not None.
x = 5
if x is not None:
    print("x is not None")
In this example, if x is not None, it will print “x is not None”. Using the is not operator like this makes it possible to explicitly test for conditions where something is not None.

5. Differences between None and other falsy values

In Python, there are several values besides None that are evaluated as “falsy”. These include the empty string '', numeric values 0, empty lists [], and so on. However, these values are different from None. Here we’ll deepen our understanding of the differences between None and other falsy values.

Overview of None and other falsy values

The primary values that evaluate as falsy in Python are:
  • None
  • empty string ''
  • number 0
  • empty list []
  • empty dictionary {}
All of these evaluate as False, but None, unlike them, represents the absence of a value.

Differences between None and the empty string ''

The empty string '' indicates that the data is empty while retaining its data type str. On the other hand, None is a special object that does not have a type. Let’s look at the following example.
text = ''
if text is None:
    print("text is None")
elif text == '':
    print("text is an empty string")
This code distinguishes whether text is an empty string or None and handles each case accordingly.

Differences from the number 0 and the empty list []

The number 0 and the empty list [] also evaluate as False, but these indicate that there is a numeric or list value whose contents are empty. None, lacking a type, means that nothing has been set. Let’s confirm with the following example.
data = 0
if data is None:
    print("data is None")
elif data == 0:
    print("data is 0")
Understanding the differences between None and other falsy values will allow for more accurate checks.

6. Practical examples of using None

Here we explain several concrete examples of how to effectively utilize None in Python programs. None is widely used for default arguments, handling data retrieved from databases, error handling, and more. Understanding these usage examples improves code maintainability and readability.

Using None as a function’s default argument

By setting None as a function’s default argument, flexible function design becomes possible. For example, if an argument is not passed to a function, you can use None to determine this and set default behavior according to conditions.
def greet(name=None):
    if name is None:
        print("Hello, Guest!")
    else:
        print(f"Hello, {name}!")
This function greet displays “Hello, Guest!” when the argument name is not provided, and when provided it greets using the specified name. By leveraging None in this way, you can easily create functions with flexible behavior.

Handling None when retrieving data from a database

When retrieving data from a database, None may be returned when data does not exist. For example, SQL’s NULL values are often treated directly as None, and you perform None checks to determine whether data is missing.
user_data = get_user_data(user_id)  # Function to retrieve user data
if user_data is None:
    print("No user data found")
else:
    print("Displaying user data")
Here, if the get_user_data function does not return user data, None is returned, and in that case “No user data found” is displayed. Performing such None checks makes database operations safer and more reliable.

Using None in error handling

None is also used as part of error handling. In particular, in situations that require exception handling or error checks, determining whether a result is None makes it easy to check for errors.
def divide(a, b):
    if b == 0:
        return None
    return a / b

result = divide(10, 0)
if result is None:
    print("Error: Division by zero occurred")
else:
    print(f"Result: {result}")
In this example, the divide function checks for division by zero and returns None in case of an error. This allows the caller to check None and display an appropriate error message.

7. Best practices for checking None

When checking None in Python, using the proper method can improve your code’s readability and reliability. Here are best practices for checking None.

Recommended approach for checking None based on PEP 8

PEP 8, Python’s official style guide, recommends using the is operator to check None. This makes the intended object identity clear and distinguishes None from other falsy values.
value = None
if value is None:
    print("value is None")
Using is to check None improves readability and clarifies intent, which helps prevent bugs.

Code examples to improve readability and maintainability

For readability and maintainability, it’s important to check None with simple, easy-to-understand code. Also, when None is expected, adding comments to clarify the purpose and intent of None is useful.
# When no value is set, None is expected
data = fetch_data()
if data is None:
    print("Could not retrieve data")
In this way, clarifying the meaning of None with comments makes future code maintenance easier.</final

8. Summary

In this article, we provided a detailed explanation of the role and usage of None, which corresponds to “null checks” in Python. By understanding None and using it appropriately, you can improve the safety and maintainability of your programs. Additionally, clearly distinguishing None from other “falsy” values can further increase the reliability of your code. Below are the key takeaways from this article:
  • The basic concept and role of None in Python.
  • How to determine None and how it differs from other “falsy” values.
  • Practical uses of None in function arguments, database operations, and error handling.
  • Best practices for None checks.
Use this information as a reference to apply None in real Python code and build high-quality programs.