Assertions and Defensive Programming (With Examples)

In the previous tutorial, we learn about Exception Handling in Python (With Examples). So, now we are going to discuss Assertions and Defensive Programming in python. We also learn about how to use assertions in python for defensive programming.

In Python, assertions are statements that help developers identify and catch bugs during the development process.

They are used to check that certain conditions are true and raise an error if they are not.

Defensive programming, on the other hand, is a coding style that aims to anticipate and handle potential errors or unexpected inputs to a program.

What is Assertion in Python:

To use assertions in Python, you can write an assert statement followed by a boolean expression that should evaluate to True.

Code:

# Set a variable to represent the number of items in a shopping cart
num_items = 10

# Assert that the number of items is greater than zero
assert num_items > 0, "The number of items must be greater than zero"

# Print a message indicating that the assertion passed
print("Assertion passed: the number of items is greater than zero")

Output:

Assertion passed: the number of items is greater than zero

In the above code, we set a variable num_items to 10 to represent the number of items in a shopping cart. We use an assertion to check if the number of items is greater than zero. If the assertion fails, an AssertionError is raised with the message “The number of items must be greater than zero”.

What is Defensive Programming in Python:

Defensive programming involves anticipating potential errors and handling them gracefully. For example, if you are going to check rather you are eligible for vote casting or not:

Code:

# Ask the user for their age
age = input("Please enter your age: ")

# Validate input: check if the age is a valid integer
if age.isdigit():
    age = int(age)
    # Handle potential errors: check if the age is within a valid range
    if age >= 18 and age <= 120:
        print("You are eligible to vote!")
    else:
        print("You are not eligible to vote.")
else:
    print("Invalid input: age must be a positive integer.")

Output:

Please enter your age: 20
You are eligible to vote!

In the above example, we ask the user to enter their age using the input() function.

We then validate the input by checking if the age is a valid integer using the isdigit() method. If it is a valid integer, we convert it to an integer using the int() function.

Now we check if it is within a valid range for voting (between 18 and 120 years old).

If it is, we print a message indicating that the user is eligible to vote.

If it is not, we print a message indicating that the user is not eligible to vote.

Now, we are going to discuss some additional topics related to assertions and defensive programming in Python, along with examples.

Assertion Error Messages:

When an assertion fails, you can provide a custom error message to help identify the source of the problem. For example:

Code:

x = 10
y = 20
assert x == y, "x and y should be equal but are not"

Output:

AssertionError: x and y should be equal but are not

This will raise an AssertionError with the message “x and y should be equal but are not”, which can help identify the source of the problem.

Defensive Programming with Try-Except:

You can use try-except blocks to handle potential errors that may arise in your code. For example:

Code:

x = [1, 2, 3]
try:
    print(x[3])
except IndexError:
    print("Index out of range")

Output:

Index out of range

This will print “Index out of range” instead of raising an IndexError when trying to access an index that doesn’t exist in the list.

Asserting Function Inputs and Outputs:

You can use assertions to check that inputs and outputs of functions meet certain requirements. For example:

Code:

def multiply(x, y):
    assert isinstance(x, int) and isinstance(y, int), "Inputs must be integers"
    result = x * y
    assert isinstance(result, int), "Output must be an integer"
    return result

This function checks that both inputs are integers and that the output is also an integer. If you don’t know about functions in python click here.

Defensive Programming with Default Values:

You can use default values to handle potential errors with missing inputs. For example:

Code:

def my_function(x=None):
    if x is None:
        x = []
# Rest of the function code goes here

This function sets the default value of x to an empty list if no input is provided, which can help prevent errors if the function is called without an argument.

FAQs About Assertions and Defensive Programming in Python:

What is the assertion in Python?

The assertion is a statement in Python that checks if a condition is true. It is used for debugging and defensive programming to ensure that assumptions about the program’s state are correct.

How do you use assertions in Python for defensive programming?

Assertions are used in Python for defensive programming by including them in code to check if certain conditions are met. If the assertion fails, an AssertionError is raised, indicating that there is a bug in the code.

What is the difference between assertion and exception handling?

Assertions are used to check if assumptions about the program’s state are correct. While on the other hand exception handling is used to handle errors that occur during program execution.

How can you ensure code robustness in Python using defensive programming techniques?

To ensure code robustness in Python, defensive programming techniques can be used, such as input validation, error handling, and testing.

What are some common errors that can occur in Python programs, and how can you prevent them using defensive programming?

Common errors that can occur in Python programs include syntax errors, logical errors, and runtime errors. These can be prevented using defensive programming techniques such as input validation, exception handling, and testing.

How can you validate input in Python using defensive programming techniques?

Input can be validated in Python using defensive programming techniques such as input sanitization, data type validation, and boundary checks.

What are some popular Python debugging tools that can be used for defensive programming?

Popular Python debugging tools include pdb, PyCharm, and IPython. These tools can be used to step through code, inspect variables, and identify errors.

How can you use tracebacks to identify and fix errors in Python code?

Tracebacks provide information about where an error occurred in Python code, making it easier to identify and fix the problem.

What are the benefits of using defensive programming techniques in Python?

Using defensive programming techniques in Python can improve code quality, reduce the number of bugs, and increase the robustness of the code.

So, assertions and defensive programming are important techniques for creating robust and reliable code. By checking inputs and outputs, handling potential errors, and providing helpful error messages. You can create code that is more resilient and less prone to unexpected errors.