Assertions

An Assertion is a reusable predicate that tests a numeric metric value. Assertions are used throughout qualink to define pass/fail thresholds for constraints.

Creating Assertions

Assertions are created via static factory methods on the Assertion class:

from qualink.constraints import Assertion

Available Assertion Types

Assertion.greater_than(value)

Passes when metric > value.

Assertion.greater_than(0)       # metric > 0
Assertion.greater_than(100)     # metric > 100

Assertion.greater_than_or_equal(value)

Passes when metric ≥ value.

Assertion.greater_than_or_equal(0.95)   # metric >= 0.95

Assertion.less_than(value)

Passes when metric < value.

Assertion.less_than(100)        # metric < 100

Assertion.less_than_or_equal(value)

Passes when metric ≤ value.

Assertion.less_than_or_equal(120)   # metric <= 120

Assertion.equal_to(value)

Passes when metric == value.

Assertion.equal_to(1.0)         # metric == 1.0
Assertion.equal_to(100)         # metric == 100

Assertion.between(lower, upper)

Passes when lower ≤ metric ≤ upper.

Assertion.between(18, 65)       # 18 <= metric <= 65
Assertion.between(0.9, 1.0)    # 0.9 <= metric <= 1.0

Assertion.custom(fn, label)

Passes when the provided callable returns True.

Assertion.custom(lambda x: x % 2 == 0, "is_even")
Assertion.custom(lambda x: x in [1, 2, 3], "in_set")

Usage with Constraints

Assertions are passed to constraint methods on the CheckBuilder:

from qualink.checks import Check
from qualink.constraints import Assertion

check = (
    Check.builder("Example")
    .has_completeness("email", Assertion.greater_than_or_equal(0.95))
    .has_min("age", Assertion.greater_than_or_equal(0))
    .has_max("age", Assertion.less_than_or_equal(120))
    .has_mean("age", Assertion.between(20, 60))
    .has_size(Assertion.equal_to(1000))
    .build()
)

How It Works Internally

The Assertion.evaluate(metric) method uses Python's match statement to compare:

assertion = Assertion.greater_than_or_equal(0.95)
assertion.evaluate(0.97)  # True
assertion.evaluate(0.80)  # False

Summary Table