The article discusses the absence of built-in unsigned integers in Python, leading to challenges in scenarios requiring strictly non-negative values, such as porting code from C/C++ or handling memory buffers. It presents methods to enforce unsigned integer behavior, highlighting the creation of a custom class called UnsignedInt for runtime safety. This class raises errors for negative values or non-integer types. Additionally, it suggests using static type checkers like mypy to catch type errors during development, ensuring adherence to unsigned constraints before execution.
class UnsignedInt: """A class to enforce unsigned integers (≥ 0)""" def __init__(self, value: int): if not isinstance(value, int): raise TypeError(f"Expected an integer, received {type(value).__name__}") if value < 0: raise ValueError("Only non-negative values are allowed") self.value = value def __repr__(self): return f"UnsignedInt({self.value})" # ✅ Valid usage x = UnsignedInt(100) print(x) # Output: UnsignedInt(100) # ❌ Throws an error for negative numbers y = UnsignedInt(-5) # ValueError: Only non-negative values are allowed # ❌ Throws an error for non-integer types z = UnsignedInt(10.5) # TypeError: Expected an integer, received float
Using mypy provides a way to catch type errors before running the code, ensuring that all integer assignments adhere to defined constraints, like being non-negative.
Collection
[
|
...
]