Markitect schema-validation integration use case and fixture for Markdown proxy documents

src/kontextual_engine/core/__init__.py

@@ -20,6 +20,7 @@ from .metadata import (
     MetadataFieldDefinition,
     MetadataRecord,
     MetadataSchema,
+    MetadataSchemaAssignment,
     MetadataValidationIssue,
     MetadataValueType,
     Sensitivity,
@@ -64,6 +65,7 @@ __all__ = [
     "MetadataFieldDefinition",
     "MetadataRecord",
     "MetadataSchema",
+    "MetadataSchemaAssignment",
     "MetadataValidationIssue",
     "MetadataValueType",
     "NormalizedDocument",

src/kontextual_engine/core/metadata.py

@@ -290,6 +290,63 @@ class MetadataSchema:
         )
 
 
+@dataclass(frozen=True)
+class MetadataSchemaAssignment:
+    schema_id: str
+    asset_types: tuple[str, ...] = ()
+    sensitivities: tuple[Sensitivity | str, ...] = ()
+    lifecycle_states: tuple[LifecycleState | str, ...] = ()
+    policy_ref: str | None = None
+    priority: int = 100
+    metadata: dict[str, Any] = field(default_factory=dict)
+    assignment_id: str = field(default_factory=lambda: new_id("metadata_schema_assignment"))
+
+    def __post_init__(self) -> None:
+        object.__setattr__(self, "asset_types", tuple(self.asset_types))
+        object.__setattr__(self, "sensitivities", tuple(Sensitivity(item) for item in self.sensitivities))
+        object.__setattr__(
+            self,
+            "lifecycle_states",
+            tuple(LifecycleState(item) for item in self.lifecycle_states),
+        )
+
+    def applies_to(self, classification: "Classification") -> bool:
+        if self.asset_types and classification.asset_type not in self.asset_types:
+            return False
+        if self.sensitivities and classification.sensitivity not in self.sensitivities:
+            return False
+        if self.lifecycle_states and classification.lifecycle not in self.lifecycle_states:
+            return False
+        return True
+
+    def to_dict(self) -> dict[str, Any]:
+        return compact_dict(
+            {
+                "assignment_id": self.assignment_id,
+                "schema_id": self.schema_id,
+                "asset_types": list(self.asset_types),
+                "sensitivities": [item.value for item in self.sensitivities],
+                "lifecycle_states": [item.value for item in self.lifecycle_states],
+                "policy_ref": self.policy_ref,
+                "priority": self.priority,
+                "metadata": dict(self.metadata),
+            }
+        )
+
+    @classmethod
+    def from_dict(cls, data: dict[str, Any]) -> "MetadataSchemaAssignment":
+        return cls(
+            assignment_id=data["assignment_id"],
+            schema_id=data["schema_id"],
+            asset_types=tuple(data.get("asset_types", [])),
+            sensitivities=tuple(Sensitivity(item) for item in data.get("sensitivities", [])),
+            lifecycle_states=tuple(LifecycleState(item) for item in data.get("lifecycle_states", [])),
+            policy_ref=data.get("policy_ref"),
+            priority=int(data.get("priority", 100)),
+            metadata=dict(data.get("metadata", {})),
+        )
+
+
 @dataclass(frozen=True)
 class Classification:
     asset_type: str