[FEATURE] Implements OneOf #37
112
docs/source/usage.oneof.rst
Normal file
112
docs/source/usage.oneof.rst
Normal file
@@ -0,0 +1,112 @@
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OneOf Type
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=================
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The OneOf type is used to specify that an object must conform to exactly one of the specified schemas. Unlike AnyOf which allows matching multiple schemas, OneOf enforces that the data matches one and only one of the provided schemas.
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Examples
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-----------------
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1. **Overlapping String Example** - A field that accepts strings with overlapping constraints:
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.. code-block:: python
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from jambo import SchemaConverter
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schema = {
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"title": "SimpleExample",
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"type": "object",
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"properties": {
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"value": {
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"oneOf": [
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{"type": "string", "maxLength": 6},
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{"type": "string", "minLength": 4}
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]
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}
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},
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"required": ["value"]
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}
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Model = SchemaConverter.build(schema)
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# Valid: Short string (matches first schema only)
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obj1 = Model(value="hi")
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print(obj1.value) # Output: hi
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# Valid: Long string (matches second schema only)
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obj2 = Model(value="very long string")
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print(obj2.value) # Output: very long string
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# Invalid: Medium string (matches BOTH schemas - violates oneOf)
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try:
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obj3 = Model(value="hello") # 5 chars: matches maxLength=6 AND minLength=4
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except ValueError as e:
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print("Validation fails as expected:", e)
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2. **Discriminator Example** - Different shapes with a type field:
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.. code-block:: python
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from jambo import SchemaConverter
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schema = {
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"title": "Shape",
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"type": "object",
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"properties": {
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"shape": {
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"oneOf": [
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{
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"type": "object",
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"properties": {
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"type": {"const": "circle"},
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"radius": {"type": "number", "minimum": 0}
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},
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"required": ["type", "radius"]
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},
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{
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"type": "object",
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"properties": {
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"type": {"const": "rectangle"},
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"width": {"type": "number", "minimum": 0},
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"height": {"type": "number", "minimum": 0}
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},
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"required": ["type", "width", "height"]
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}
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],
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"discriminator": {
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"propertyName": "type"
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}
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}
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},
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"required": ["shape"]
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}
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Model = SchemaConverter.build(schema)
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# Valid: Circle
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circle = Model(shape={"type": "circle", "radius": 5.0})
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print(circle.shape.type) # Output: circle
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# Valid: Rectangle
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rectangle = Model(shape={"type": "rectangle", "width": 10, "height": 20})
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print(rectangle.shape.type) # Output: rectangle
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# Invalid: Wrong properties for the type
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try:
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invalid = Model(shape={"type": "circle", "width": 10})
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except ValueError as e:
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print("Validation fails as expected:", e)
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.. note::
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OneOf ensures exactly one schema matches. The discriminator helps Pydantic efficiently determine which schema to use based on a specific property value.
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.. warning::
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If your data could match multiple schemas in a oneOf, validation will fail. Ensure schemas are mutually exclusive.
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.. warning::
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The discriminator feature is not officially in the JSON Schema specification, it was introduced by OpenAI. Use it with caution and ensure it fits your use case.
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@@ -45,5 +45,6 @@ For more complex schemas and types see our documentation on
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usage.reference
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usage.allof
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usage.anyof
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usage.oneof
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usage.enum
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usage.const
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@@ -9,6 +9,7 @@ from .float_type_parser import FloatTypeParser
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from .int_type_parser import IntTypeParser
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from .null_type_parser import NullTypeParser
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from .object_type_parser import ObjectTypeParser
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from .oneof_type_parser import OneOfTypeParser
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from .ref_type_parser import RefTypeParser
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from .string_type_parser import StringTypeParser
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@@ -25,6 +26,7 @@ __all__ = [
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"IntTypeParser",
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"NullTypeParser",
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"ObjectTypeParser",
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"OneOfTypeParser",
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"StringTypeParser",
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"RefTypeParser",
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]
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91
jambo/parser/oneof_type_parser.py
Normal file
91
jambo/parser/oneof_type_parser.py
Normal file
@@ -0,0 +1,91 @@
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from jambo.parser._type_parser import GenericTypeParser
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from jambo.types.type_parser_options import TypeParserOptions
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from pydantic import BeforeValidator, Field, TypeAdapter, ValidationError
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from typing_extensions import Annotated, Any, Union, Unpack
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class OneOfTypeParser(GenericTypeParser):
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mapped_type = Union
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json_schema_type = "oneOf"
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def from_properties_impl(
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self, name, properties, **kwargs: Unpack[TypeParserOptions]
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):
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if "oneOf" not in properties:
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raise ValueError(f"Invalid JSON Schema: {properties}")
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if not isinstance(properties["oneOf"], list):
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raise ValueError(f"Invalid JSON Schema: {properties['oneOf']}")
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mapped_properties = self.mappings_properties_builder(properties, **kwargs)
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sub_properties = properties["oneOf"]
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sub_types = [
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GenericTypeParser.type_from_properties(name, subProperty, **kwargs)
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for subProperty in sub_properties
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]
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if not kwargs.get("required", False):
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mapped_properties["default"] = mapped_properties.get("default")
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subfield_types = [Annotated[t, Field(**v)] for t, v in sub_types]
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# Added with the understanding of discriminator are not in the JsonSchema Spec,
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# they were added by OpenAI and not all implementations may support them,
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# and they do not always generate a model one-to-one to the Pydantic model
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# TL;DR: Discriminators were added by OpenAI and not a Official JSON Schema feature
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discriminator = properties.get("discriminator")
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if discriminator is not None:
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validated_type = self._build_type_one_of_with_discriminator(
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subfield_types, discriminator
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)
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else:
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validated_type = self._build_type_one_of_with_func(subfield_types)
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return validated_type, mapped_properties
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@staticmethod
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def _build_type_one_of_with_discriminator(
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subfield_types: list[Annotated], discriminator_prop: dict
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) -> Annotated:
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"""
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Build a type with a discriminator.
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"""
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if not isinstance(discriminator_prop, dict):
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raise ValueError("Discriminator must be a dictionary")
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property_name = discriminator_prop.get("propertyName")
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if property_name is None or not isinstance(property_name, str):
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raise ValueError("Discriminator must have a 'propertyName' key")
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return Annotated[Union[(*subfield_types,)], Field(discriminator=property_name)]
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@staticmethod
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def _build_type_one_of_with_func(subfield_types: list[Annotated]) -> Annotated:
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"""
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Build a type with a validation function for the oneOf constraint.
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"""
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def validate_one_of(value: Any) -> Any:
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matched_count = 0
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for field_type in subfield_types:
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try:
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TypeAdapter(field_type).validate_python(value)
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matched_count += 1
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except ValidationError:
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continue
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if matched_count == 0:
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raise ValueError("Value does not match any of the oneOf schemas")
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elif matched_count > 1:
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raise ValueError(
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"Value matches multiple oneOf schemas, exactly one expected"
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)
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return value
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return Annotated[Union[(*subfield_types,)], BeforeValidator(validate_one_of)]
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496
tests/parser/test_oneof_type_parser.py
Normal file
496
tests/parser/test_oneof_type_parser.py
Normal file
@@ -0,0 +1,496 @@
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from jambo import SchemaConverter
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from jambo.parser.oneof_type_parser import OneOfTypeParser
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from unittest import TestCase
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class TestOneOfTypeParser(TestCase):
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def test_oneof_raises_on_invalid_property(self):
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with self.assertRaises(ValueError):
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OneOfTypeParser().from_properties_impl(
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"test_field",
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{
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# Invalid schema, should have property "oneOf"
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},
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required=True,
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context={},
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ref_cache={},
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)
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with self.assertRaises(ValueError):
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SchemaConverter.build(
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{
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"title": "Test",
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"type": "object",
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"properties": {
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"value": {
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"oneOf": [], # should throw because oneOf requires at least one schema
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}
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},
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}
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)
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def test_oneof_basic_integer_and_string(self):
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schema = {
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"title": "Person",
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"description": "A person with an ID that can be either an integer or a formatted string",
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"type": "object",
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"properties": {
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"id": {
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"oneOf": [
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{"type": "integer", "minimum": 1},
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{"type": "string", "pattern": "^[A-Z]{2}[0-9]{4}$"},
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]
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},
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},
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"required": ["id"],
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}
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Model = SchemaConverter.build(schema)
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obj1 = Model(id=123)
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self.assertEqual(obj1.id, 123)
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obj2 = Model(id="AB1234")
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self.assertEqual(obj2.id, "AB1234")
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def test_oneof_validation_failures(self):
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schema = {
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"title": "Person",
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"type": "object",
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"properties": {
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"id": {
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"oneOf": [
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{"type": "integer", "minimum": 1},
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{"type": "string", "pattern": "^[A-Z]{2}[0-9]{4}$"},
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]
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},
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},
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"required": ["id"],
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}
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Model = SchemaConverter.build(schema)
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with self.assertRaises(ValueError):
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Model(id=-5)
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with self.assertRaises(ValueError):
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Model(id="invalid")
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with self.assertRaises(ValueError):
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Model(id=123.45)
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def test_oneof_with_conflicting_schemas(self):
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schema = {
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"title": "Value",
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"type": "object",
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"properties": {
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"data": {
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"oneOf": [
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{"type": "number", "multipleOf": 2},
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{"type": "number", "multipleOf": 3},
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]
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},
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},
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"required": ["data"],
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}
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Model = SchemaConverter.build(schema)
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obj1 = Model(data=4)
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self.assertEqual(obj1.data, 4)
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obj2 = Model(data=9)
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self.assertEqual(obj2.data, 9)
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with self.assertRaises(ValueError) as cm:
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Model(data=6)
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self.assertIn("matches multiple oneOf schemas", str(cm.exception))
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with self.assertRaises(ValueError):
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Model(data=5)
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def test_oneof_with_objects(self):
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schema = {
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"title": "Contact",
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"type": "object",
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"properties": {
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"contact_info": {
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"oneOf": [
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{
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"type": "object",
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"properties": {
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"email": {"type": "string", "format": "email"}
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},
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"required": ["email"],
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"additionalProperties": False,
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},
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{
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"type": "object",
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"properties": {
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"phone": {"type": "string", "pattern": "^[0-9-]+$"}
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},
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"required": ["phone"],
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"additionalProperties": False,
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},
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]
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},
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},
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"required": ["contact_info"],
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}
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Model = SchemaConverter.build(schema)
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obj1 = Model(contact_info={"email": "user@example.com"})
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self.assertEqual(obj1.contact_info.email, "user@example.com")
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obj2 = Model(contact_info={"phone": "123-456-7890"})
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self.assertEqual(obj2.contact_info.phone, "123-456-7890")
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with self.assertRaises(ValueError):
|
||||
Model(contact_info={"email": "user@example.com", "phone": "123-456-7890"})
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||||
|
||||
def test_oneof_with_discriminator_basic(self):
|
||||
schema = {
|
||||
"title": "Pet",
|
||||
"type": "object",
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||||
"properties": {
|
||||
"pet": {
|
||||
"oneOf": [
|
||||
{
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"type": {"const": "cat"},
|
||||
"meows": {"type": "boolean"},
|
||||
},
|
||||
"required": ["type", "meows"],
|
||||
},
|
||||
{
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"type": {"const": "dog"},
|
||||
"barks": {"type": "boolean"},
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||||
},
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||||
"required": ["type", "barks"],
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||||
},
|
||||
],
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||||
"discriminator": {"propertyName": "type"},
|
||||
}
|
||||
},
|
||||
"required": ["pet"],
|
||||
}
|
||||
|
||||
Model = SchemaConverter.build(schema)
|
||||
|
||||
cat = Model(pet={"type": "cat", "meows": True})
|
||||
self.assertEqual(cat.pet.type, "cat")
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||||
self.assertEqual(cat.pet.meows, True)
|
||||
|
||||
dog = Model(pet={"type": "dog", "barks": False})
|
||||
self.assertEqual(dog.pet.type, "dog")
|
||||
self.assertEqual(dog.pet.barks, False)
|
||||
|
||||
with self.assertRaises(ValueError):
|
||||
Model(pet={"type": "cat", "barks": True})
|
||||
|
||||
with self.assertRaises(ValueError):
|
||||
Model(pet={"type": "bird", "flies": True})
|
||||
|
||||
def test_oneof_with_discriminator_mapping(self):
|
||||
schema = {
|
||||
"title": "Vehicle",
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"vehicle": {
|
||||
"oneOf": [
|
||||
{
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"vehicle_type": {"const": "car"},
|
||||
"doors": {
|
||||
"type": "integer",
|
||||
"minimum": 2,
|
||||
"maximum": 4,
|
||||
},
|
||||
},
|
||||
"required": ["vehicle_type", "doors"],
|
||||
},
|
||||
{
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"vehicle_type": {"const": "motorcycle"},
|
||||
"engine_size": {"type": "number", "minimum": 125},
|
||||
},
|
||||
"required": ["vehicle_type", "engine_size"],
|
||||
},
|
||||
],
|
||||
"discriminator": {
|
||||
"propertyName": "vehicle_type",
|
||||
"mapping": {
|
||||
"car": "#/properties/vehicle/oneOf/0",
|
||||
"motorcycle": "#/properties/vehicle/oneOf/1",
|
||||
},
|
||||
},
|
||||
}
|
||||
},
|
||||
"required": ["vehicle"],
|
||||
}
|
||||
|
||||
Model = SchemaConverter.build(schema)
|
||||
|
||||
car = Model(vehicle={"vehicle_type": "car", "doors": 4})
|
||||
self.assertEqual(car.vehicle.vehicle_type, "car")
|
||||
self.assertEqual(car.vehicle.doors, 4)
|
||||
|
||||
motorcycle = Model(vehicle={"vehicle_type": "motorcycle", "engine_size": 600.0})
|
||||
self.assertEqual(motorcycle.vehicle.vehicle_type, "motorcycle")
|
||||
self.assertEqual(motorcycle.vehicle.engine_size, 600.0)
|
||||
|
||||
def test_oneof_with_discriminator_invalid_values(self):
|
||||
schema = {
|
||||
"title": "Shape",
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"shape": {
|
||||
"oneOf": [
|
||||
{
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"type": {"const": "circle"},
|
||||
"radius": {"type": "number", "minimum": 0},
|
||||
},
|
||||
"required": ["type", "radius"],
|
||||
},
|
||||
{
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"type": {"const": "square"},
|
||||
"side": {"type": "number", "minimum": 0},
|
||||
},
|
||||
"required": ["type", "side"],
|
||||
},
|
||||
],
|
||||
"discriminator": {"propertyName": "type"},
|
||||
}
|
||||
},
|
||||
"required": ["shape"],
|
||||
}
|
||||
|
||||
Model = SchemaConverter.build(schema)
|
||||
|
||||
with self.assertRaises(ValueError):
|
||||
Model(shape={"type": "triangle", "base": 5, "height": 3})
|
||||
|
||||
with self.assertRaises(ValueError):
|
||||
Model(shape={"type": "circle", "side": 5})
|
||||
|
||||
with self.assertRaises(ValueError):
|
||||
Model(shape={"radius": 5})
|
||||
|
||||
def test_oneof_missing_properties(self):
|
||||
schema = {
|
||||
"title": "Test",
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"value": {
|
||||
"notOneOf": [
|
||||
{"type": "string"},
|
||||
{"type": "integer"},
|
||||
]
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
with self.assertRaises(ValueError):
|
||||
SchemaConverter.build(schema)
|
||||
|
||||
def test_oneof_invalid_properties(self):
|
||||
schema = {
|
||||
"title": "Test",
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"value": {"oneOf": None},
|
||||
},
|
||||
}
|
||||
|
||||
with self.assertRaises(ValueError):
|
||||
SchemaConverter.build(schema)
|
||||
|
||||
def test_oneof_with_default_value(self):
|
||||
schema = {
|
||||
"title": "Test",
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"value": {
|
||||
"oneOf": [
|
||||
{"type": "string"},
|
||||
{"type": "integer"},
|
||||
],
|
||||
"default": "test",
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
Model = SchemaConverter.build(schema)
|
||||
obj = Model()
|
||||
self.assertEqual(obj.value, "test")
|
||||
|
||||
def test_oneof_with_invalid_default_value(self):
|
||||
schema = {
|
||||
"title": "Test",
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"value": {
|
||||
"oneOf": [
|
||||
{"type": "string", "minLength": 5},
|
||||
{"type": "integer", "minimum": 10},
|
||||
],
|
||||
"default": "hi",
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
with self.assertRaises(ValueError):
|
||||
SchemaConverter.build(schema)
|
||||
|
||||
def test_oneof_discriminator_without_property_name(self):
|
||||
# Should throw because the spec determines propertyName is required for discriminator
|
||||
with self.assertRaises(ValueError):
|
||||
SchemaConverter.build(
|
||||
{
|
||||
"title": "Test",
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"value": {
|
||||
"oneOf": [
|
||||
{
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"type": {"const": "a"},
|
||||
"value": {"type": "string"},
|
||||
},
|
||||
},
|
||||
{
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"type": {"const": "b"},
|
||||
"value": {"type": "integer"},
|
||||
},
|
||||
},
|
||||
],
|
||||
"discriminator": {}, # discriminator without propertyName
|
||||
}
|
||||
},
|
||||
}
|
||||
)
|
||||
|
||||
def test_oneof_discriminator_with_invalid_discriminator(self):
|
||||
# Should throw because a valid discriminator is required
|
||||
with self.assertRaises(ValueError):
|
||||
SchemaConverter.build(
|
||||
{
|
||||
"title": "Test",
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"value": {
|
||||
"oneOf": [
|
||||
{
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"type": {"const": "a"},
|
||||
"value": {"type": "string"},
|
||||
},
|
||||
},
|
||||
{
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"type": {"const": "b"},
|
||||
"value": {"type": "integer"},
|
||||
},
|
||||
},
|
||||
],
|
||||
"discriminator": "invalid", # discriminator without propertyName
|
||||
}
|
||||
},
|
||||
}
|
||||
)
|
||||
|
||||
def test_oneof_overlapping_strings_from_docs(self):
|
||||
"""Test the overlapping strings example from documentation"""
|
||||
schema = {
|
||||
"title": "SimpleExample",
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"value": {
|
||||
"oneOf": [
|
||||
{"type": "string", "maxLength": 6},
|
||||
{"type": "string", "minLength": 4},
|
||||
]
|
||||
}
|
||||
},
|
||||
"required": ["value"],
|
||||
}
|
||||
|
||||
Model = SchemaConverter.build(schema)
|
||||
|
||||
# Valid: Short string (matches first schema only)
|
||||
obj1 = Model(value="hi")
|
||||
self.assertEqual(obj1.value, "hi")
|
||||
|
||||
# Valid: Long string (matches second schema only)
|
||||
obj2 = Model(value="very long string")
|
||||
self.assertEqual(obj2.value, "very long string")
|
||||
|
||||
# Invalid: Medium string (matches BOTH schemas - violates oneOf)
|
||||
with self.assertRaises(ValueError) as cm:
|
||||
Model(value="hello") # 5 chars: matches maxLength=6 AND minLength=4
|
||||
self.assertIn("matches multiple oneOf schemas", str(cm.exception))
|
||||
|
||||
def test_oneof_shapes_discriminator_from_docs(self):
|
||||
"""Test the shapes discriminator example from documentation"""
|
||||
schema = {
|
||||
"title": "Shape",
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"shape": {
|
||||
"oneOf": [
|
||||
{
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"type": {"const": "circle"},
|
||||
"radius": {"type": "number", "minimum": 0},
|
||||
},
|
||||
"required": ["type", "radius"],
|
||||
},
|
||||
{
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"type": {"const": "rectangle"},
|
||||
"width": {"type": "number", "minimum": 0},
|
||||
"height": {"type": "number", "minimum": 0},
|
||||
},
|
||||
"required": ["type", "width", "height"],
|
||||
},
|
||||
],
|
||||
"discriminator": {"propertyName": "type"},
|
||||
}
|
||||
},
|
||||
"required": ["shape"],
|
||||
}
|
||||
|
||||
Model = SchemaConverter.build(schema)
|
||||
|
||||
# Valid: Circle
|
||||
circle = Model(shape={"type": "circle", "radius": 5.0})
|
||||
self.assertEqual(circle.shape.type, "circle")
|
||||
self.assertEqual(circle.shape.radius, 5.0)
|
||||
|
||||
# Valid: Rectangle
|
||||
rectangle = Model(shape={"type": "rectangle", "width": 10, "height": 20})
|
||||
self.assertEqual(rectangle.shape.type, "rectangle")
|
||||
self.assertEqual(rectangle.shape.width, 10)
|
||||
self.assertEqual(rectangle.shape.height, 20)
|
||||
|
||||
# Invalid: Wrong properties for the type
|
||||
with self.assertRaises(ValueError):
|
||||
Model(shape={"type": "circle", "width": 10})
|
||||
Reference in New Issue
Block a user