How to Validate Function Arguments in Python

Shows how to manually check argument types and values in a Python function, raising clear TypeError and ValueError messages.

Easy Python 3.9+ Aug 9, 2026 Functions & basics 13 views 0 copies

validation function arguments type hints

Python code

26 lines

Python 3.9+

def calculate_area(length: float, width: float) -> float:
    """Calculate the area of a rectangle with manual type validation."""
    if not isinstance(length, (int, float)) or isinstance(length, bool):
        raise TypeError(f"length must be a number, got {type(length).__name__}")
    if not isinstance(width, (int, float)) or isinstance(width, bool):
        raise TypeError(f"width must be a number, got {type(width).__name__}")
    if length <= 0 or width <= 0:
        raise ValueError("length and width must be positive numbers")
    
    return length * width


if __name__ == "__main__":
    print(calculate_area(5.5, 3))
    try:
        calculate_area("5", 3)
    except TypeError as e:
        print(f"TypeError: {e}")
    try:
        calculate_area(0, 3)
    except ValueError as e:
        print(f"ValueError: {e}")
    try:
        calculate_area(True, 3)
    except TypeError as e:
        print(f"TypeError: {e}")

Output

stdout

16.5
TypeError: length must be a number, got str
ValueError: length and width must be positive numbers
TypeError: length must be a number, got bool

How it works

The function calculate_area uses isinstance to confirm each argument is an int or float, while explicitly excluding bool because bool is a subclass of int in Python. After type checks, value validation ensures positive inputs to prevent meaningless results. Raising TypeError for wrong types and ValueError for bad values follows Python's exception conventions and makes bugs obvious. The if __name__ == "__main__" guard lets the code run as a script while keeping the function importable. This manual approach works without third-party libraries and gives full control over error messages.

Common mistakes

Forgetting that `bool` is a subclass of `int` in Python, so it passes `isinstance(x, int)` unless explicitly excluded
Checking types but not values, allowing zero or negative numbers to pass through with confusing results
Using `type(x) == int` instead of `isinstance()` which fails for subclasses and is less flexible

Variations

Use `numbers.Number` from the numbers module to accept all numeric types, including Decimal and Fraction
Use type hints with a runtime validator like Pydantic for deeper validation in larger projects

Real-world use cases

Validating numeric inputs in a data processing script before performing calculations to avoid NaN or negative values.
Checking configuration values in a CLI tool where mistyped flags could crash the application.
Guarding a library's public API input arguments to fail fast and give clear errors to the caller.

How to Validate Function Arguments in Python

Python code

Output

How it works

Common mistakes

Variations

Real-world use cases

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Real-world use cases

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