Numeric types

Numeric values can be an integer or a floating-point number. Handle them as numbers without assuming a particular runtime type.

from typing import assert_never

from frequenz.core.typing import FloatInt


def describe(value: FloatInt | None) -> str:
    match value:
        case float() | int():
            return f"next value: {value + 1}"
        case None:
            return "no value"
        case unexpected:
            assert_never(unexpected)


print(describe(1.5))  # next value: 2.5
print(describe(2))  # next value: 3
print(describe(None))  # no value

FloatInt is exactly float | int. PEP 484's numeric tower allows an int where a float is annotated, so a FloatInt value may be a real float or int at runtime. Arithmetic and comparisons work the same for both. Do not use isinstance(value, float) alone: it is False for an int.

You can encounter FloatInt in MetricSample.value and from MetricSample.as_single_value(). Bounds also uses it for lower and upper. When you need to dispatch on the concrete type, use the match form above so both number types are handled together.

bool is a subclass of int, so True and False also satisfy FloatInt. Handle them separately only when your application does not accept boolean values.