common.libs.pydantic

DltConfig Objects

class DltConfig(TypedDict)

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dlt configuration that can be attached to Pydantic model

Example below removes nested field from the resulting dlt schema.

class ItemModel(BaseModel):
    b: bool
    nested: Dict[str, Any]
    dlt_config: ClassVar[DltConfig] = {"skip_nested_types": True}

skip_nested_types

If True, columns of complex types (dict, list, BaseModel) will be excluded from dlt schema generated from the model

skip_complex_types

deprecated

pydantic_to_table_schema_columns

def pydantic_to_table_schema_columns(
        model: Union[BaseModel, Type[BaseModel]]) -> TTableSchemaColumns

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Convert a pydantic model to a table schema columns dict

See also DltConfig for more control over how the schema is created

Arguments:

• model - The pydantic model to convert. Can be a class or an instance.

Returns:

• TTableSchemaColumns - table schema columns dict

apply_schema_contract_to_model

def apply_schema_contract_to_model(
        model: Type[_TPydanticModel],
        column_mode: TSchemaEvolutionMode,
        data_mode: TSchemaEvolutionMode = "freeze") -> Type[_TPydanticModel]

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Configures or re-creates model so it behaves according to column_mode and data_mode settings.

column_mode sets the model behavior when unknown field is found. data_mode sets model behavior when known field does not validate. currently evolve and freeze are supported here.

discard_row is implemented in validate_item.

create_list_model

def create_list_model(
    model: Type[_TPydanticModel],
    data_mode: TSchemaEvolutionMode = "freeze"
) -> Type[ListModel[_TPydanticModel]]

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Creates a model from model for validating list of items in batch according to data_mode

Currently only freeze is supported. See comments in the code

validate_and_filter_items

def validate_and_filter_items(
        table_name: str, list_model: Type[ListModel[_TPydanticModel]],
        items: List[TDataItem], column_mode: TSchemaEvolutionMode,
        data_mode: TSchemaEvolutionMode) -> List[_TPydanticModel]

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Validates list of item with list_model and returns parsed Pydantic models. If column_mode and data_mode are set this function will remove non validating items (discard_row) or raise on the first non-validating items (freeze). Note that the model itself may be configured to remove non validating or extra items as well.

list_model should be created with create_list_model and have items field which this function returns.

validate_and_filter_item

def validate_and_filter_item(
        table_name: str, model: Type[_TPydanticModel], item: TDataItems,
        column_mode: TSchemaEvolutionMode,
        data_mode: TSchemaEvolutionMode) -> Optional[_TPydanticModel]

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Validates item against model model and returns an instance of it. If column_mode and data_mode are set this function will return None (discard_row) or raise on non-validating items (freeze). Note that the model itself may be configured to remove non validating or extra items as well.