Deterministic operators

Assign

Recover labeled relationships between two Spaces with deterministic code.

Assign applies a trusted labeled relationship function to X and Y values.

Worked example

Assign(
    name="assign-orders-to-bands",
    input_spaces=("orders", "price-bands"),
    output_space="order-bands",
    primary_key="id",
    evidence=("total", "name", "minimum", "maximum"),
    labels=("low", "medium", "high"),
    fn=lambda order, band: (
        band["name"]
        if band["minimum"] <= order["total"] < band["maximum"]
        else None
    ),
    max_assignments_per_x=1,
)

Callable contract

fn(x_row, y_row) -> label | None. Returned labels must be declared.

Rows available to the callable

Each row argument contains the declared primary-key fields and the declared evidence fields available for that input role. If the callable reads a field that is not part of the primary key, declare it as evidence.

One primary-key shape identifies values independently on both sides, so every primary-key column must exist in every input Space. When the two roles use different names for their central values, first use deterministic transforms to copy them to a common alias.

Parameter	Default	Meaning
`input_spaces`	required	The Space or Spaces read by the task.
`output_space`	required	The Space that receives the task output.
`name`	required	A stable task name used in sessions, reviews, and metrics.
`primary_key`	id	The field, or tuple of fields, that identifies one task input. Duplicate primary-key values are evaluated once.
`evidence`	none	Optional fields made available to the callable in addition to the primary key.
`fn`	required	A deterministic callable that completely defines the operation's decision. Use an importable named function from your package, or PythonFunction(name=..., source=...) when authoring through the hosted API or node editor. Pairwise endomorphic functions may declare an exact indexed candidate_gate.
`function_parameters`	registered defaults	Typed values bound to parameters declared by the registered function. Finite candidate sets let reviewed evidence support parameter advice.

Parameter	Default	Meaning
`labels`	required	The complete allowed assignment vocabulary.
`max_assignments_per_x`	unlimited	Validate that each X has at most this many authoritative Y assignments.
`max_assignments_per_y`	unlimited	Validate that each Y has at most this many authoritative X assignments.
`exact_x`	false	Require every X to have exactly its declared maximum.
`exact_y`	false	Require every Y to have exactly its declared maximum.

Output

Labeled X-to-Y assignments.

Design guidance

Deterministic degree fields validate the complete labeled relation. A violation fails the task; Assign never discards a true label or fabricates a missing assignment.