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 group='json' 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 group='json'
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]"}