Module aws_lambda_powertools.utilities.parser.types

Generics and other shared types used across parser

Classes

class Json

A special type wrapper which loads JSON before parsing.

You can use the Json data type to make Pydantic first load a raw JSON string before validating the loaded data into the parametrized type:

from typing import Any, List

from pydantic import BaseModel, Json, ValidationError

class AnyJsonModel(BaseModel):
    json_obj: Json[Any]

class ConstrainedJsonModel(BaseModel):
    json_obj: Json[List[int]]

print(AnyJsonModel(json_obj='{"b": 1}'))
#> json_obj={'b': 1}
print(ConstrainedJsonModel(json_obj='[1, 2, 3]'))
#> json_obj=[1, 2, 3]

try:
    ConstrainedJsonModel(json_obj=12)
except ValidationError as e:
    print(e)
    '''
    1 validation error for ConstrainedJsonModel
    json_obj
      JSON input should be string, bytes or bytearray [type=json_type, input_value=12, input_type=int]
    '''

try:
    ConstrainedJsonModel(json_obj='[a, b]')
except ValidationError as e:
    print(e)
    '''
    1 validation error for ConstrainedJsonModel
    json_obj
      Invalid JSON: expected value at line 1 column 2 [type=json_invalid, input_value='[a, b]', input_type=str]
    '''

try:
    ConstrainedJsonModel(json_obj='["a", "b"]')
except ValidationError as e:
    print(e)
    '''
    2 validation errors for ConstrainedJsonModel
    json_obj.0
      Input should be a valid integer, unable to parse string as an integer [type=int_parsing, input_value='a', input_type=str]
    json_obj.1
      Input should be a valid integer, unable to parse string as an integer [type=int_parsing, input_value='b', input_type=str]
    '''

When you dump the model using model_dump or model_dump_json, the dumped value will be the result of validation, not the original JSON string. However, you can use the argument round_trip=True to get the original JSON string back:

from typing import List

from pydantic import BaseModel, Json

class ConstrainedJsonModel(BaseModel):
    json_obj: Json[List[int]]

print(ConstrainedJsonModel(json_obj='[1, 2, 3]').model_dump_json())
#> {"json_obj":[1,2,3]}
print(
    ConstrainedJsonModel(json_obj='[1, 2, 3]').model_dump_json(round_trip=True)
)
#> {"json_obj":"[1,2,3]"}

Expand source code

class Json:
    """A special type wrapper which loads JSON before parsing.

    You can use the `Json` data type to make Pydantic first load a raw JSON string before
    validating the loaded data into the parametrized type:

    ```py
    from typing import Any, List

    from pydantic import BaseModel, Json, ValidationError

    class AnyJsonModel(BaseModel):
        json_obj: Json[Any]

    class ConstrainedJsonModel(BaseModel):
        json_obj: Json[List[int]]

    print(AnyJsonModel(json_obj='{"b": 1}'))
    #> json_obj={'b': 1}
    print(ConstrainedJsonModel(json_obj='[1, 2, 3]'))
    #> json_obj=[1, 2, 3]

    try:
        ConstrainedJsonModel(json_obj=12)
    except ValidationError as e:
        print(e)
        '''
        1 validation error for ConstrainedJsonModel
        json_obj
          JSON input should be string, bytes or bytearray [type=json_type, input_value=12, input_type=int]
        '''

    try:
        ConstrainedJsonModel(json_obj='[a, b]')
    except ValidationError as e:
        print(e)
        '''
        1 validation error for ConstrainedJsonModel
        json_obj
          Invalid JSON: expected value at line 1 column 2 [type=json_invalid, input_value='[a, b]', input_type=str]
        '''

    try:
        ConstrainedJsonModel(json_obj='["a", "b"]')
    except ValidationError as e:
        print(e)
        '''
        2 validation errors for ConstrainedJsonModel
        json_obj.0
          Input should be a valid integer, unable to parse string as an integer [type=int_parsing, input_value='a', input_type=str]
        json_obj.1
          Input should be a valid integer, unable to parse string as an integer [type=int_parsing, input_value='b', input_type=str]
        '''
    ```

    When you dump the model using `model_dump` or `model_dump_json`, the dumped value will be the result of validation,
    not the original JSON string. However, you can use the argument `round_trip=True` to get the original JSON string back:

    ```py
    from typing import List

    from pydantic import BaseModel, Json

    class ConstrainedJsonModel(BaseModel):
        json_obj: Json[List[int]]

    print(ConstrainedJsonModel(json_obj='[1, 2, 3]').model_dump_json())
    #> {"json_obj":[1,2,3]}
    print(
        ConstrainedJsonModel(json_obj='[1, 2, 3]').model_dump_json(round_trip=True)
    )
    #> {"json_obj":"[1,2,3]"}
    ```
    """

    @classmethod
    def __class_getitem__(cls, item: AnyType) -> AnyType:
        return Annotated[item, cls()]

    @classmethod
    def __get_pydantic_core_schema__(cls, source: Any, handler: GetCoreSchemaHandler) -> core_schema.CoreSchema:
        if cls is source:
            return core_schema.json_schema(None)
        else:
            return core_schema.json_schema(handler(source))

    def __repr__(self) -> str:
        return 'Json'

    def __hash__(self) -> int:
        return hash(type(self))

    def __eq__(self, other: Any) -> bool:
        return type(other) is type(self)