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Lexicon JSON to Data Model Converter
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Provides bidirectional conversion between Lexicon JSON schemas and Python data models.
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from typing import Any, Dict, Type, Union, TypeVar
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from pydantic import BaseModel
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from .exceptions import ValidationError, SerializationError
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from .types.primitive import NullModel, BooleanModel, IntegerModel
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from .types.string import StringModel
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from .types.complex import ArrayModel, ObjectModel, ParamsModel
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from .types.reference import TokenModel, RefModel, UnionModel
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from .types.special import (
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UnknownModel, RecordModel, QueryModel,
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ProcedureModel, SubscriptionModel
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class LexiconConverter:
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Bidirectional converter between Lexicon JSON and Python data models.
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modelMap (Dict[str, Type[BaseModel]]): Mapping from Lexicon types to model classes
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"boolean": BooleanModel,
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"integer": IntegerModel,
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"string": StringModel,
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"array": ArrayModel,
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"object": ObjectModel,
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"params": ParamsModel,
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"token": TokenModel,
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"union": UnionModel,
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"unknown": UnknownModel,
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"record": RecordModel,
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"query": QueryModel,
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"procedure": ProcedureModel,
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"subscription": SubscriptionModel,
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def fromLexicon(cls, lexiconJson: Union[str, Dict[str, Any]]) -> BaseModel:
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Convert Lexicon JSON to Python data model instance.
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lexiconJson: Lexicon JSON string or dict
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Instance of appropriate Pydantic model
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ValidationError: If JSON is invalid or doesn't match schema
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SerializationError: If conversion fails
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if isinstance(lexiconJson, str):
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data = json.loads(lexiconJson)
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except json.JSONDecodeError as e:
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raise ValidationError("lexiconJson", f"Invalid JSON: {e}")
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if not isinstance(data, dict):
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raise ValidationError("lexiconJson", "Lexicon must be a JSON object")
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if "type" not in data:
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raise ValidationError("type", "Lexicon definition must have 'type' field")
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typeName = data["type"]
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if typeName not in cls.modelMap:
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raise ValidationError("type", f"Unknown Lexicon type: {typeName}")
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modelClass = cls.modelMap[typeName]
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return modelClass(**data)
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except Exception as e:
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raise SerializationError(typeName, f"Failed to create model: {e}")
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def toLexicon(cls, modelInstance: BaseModel) -> Dict[str, Any]:
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Convert Python model instance back to Lexicon JSON format.
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modelInstance: Instance of a Lexicon model
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Dictionary representing Lexicon JSON
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SerializationError: If conversion fails
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if not isinstance(modelInstance, BaseModel):
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raise SerializationError("modelInstance", "Input must be a Pydantic model")
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# Get the model's type name by reverse lookup
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for typeName, modelClass in cls.modelMap.items():
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if isinstance(modelInstance, modelClass):
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modelType = typeName
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if modelType is None:
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raise SerializationError("modelInstance", "Unknown model type")
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# Convert to dict and add type field
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result = modelInstance.model_dump(exclude_unset=True)
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result["type"] = modelType
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# Handle special cases
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if modelType == "record" and "type" in result:
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result["$type"] = result.pop("type")
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except Exception as e:
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raise SerializationError("toLexicon", f"Failed to serialize model: {e}")
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def validateLexicon(cls, lexiconJson: Union[str, Dict[str, Any]]) -> bool:
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Validate Lexicon JSON against schema definitions.
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lexiconJson: Lexicon JSON to validate
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True if valid, False otherwise
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cls.fromLexicon(lexiconJson)
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except (ValidationError, SerializationError):
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