Question 276629 in Json Question posted in
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JSON dumping a dictionary where some values are PyDantic models

Assume a dictionary with an arbitrary structure, where some values are native Python objects and others are instances of PyDantic’s BaseModel subclasses

e.g.

my_dict = {"key1": "value1",
           "key2": {"key3": pydantic_object1, 
                    "key4": 4},
           "key5": pydantic_object2}

I want to dump this dictionary to a JSON file. The naive solution of using BaseModel.model_dump() to convert first all the PyDantic objects to dictionaries and then using json.dump doesn’t work, because some of the attributes of the PyDantic objects cannot be serialized by the native serializer, e.g. datetimess and other custom objects which their serializers are attached to the object’s implementation.

I also couldn’t figure out how to write a custom encoder that will user PyDantic’s built in JSON encoder.

How would you solve this (PyDantic v2 and above)

Tags:

2

Answers


  1. 0

    Only Using Pydantic V2

    Use model_dump_json() instead of model_dump(). I assume SomePydanticModel is pydantic model.

    my_dict = SomePydanticModel.model_dump_json()

    Ref: https://docs.pydantic.dev/latest/concepts/serialization/#modelmodel_dump_json

    Using with FastAPI

    If you are using pydantic with FastAPI, use jsonable_encoder

    from datetime import datetime

from fastapi import FastAPI
from fastapi.encoders import jsonable_encoder
from pydantic import BaseModel

fake_db = {}


class Item(BaseModel):
    title: str
    timestamp: datetime
    description: str | None = None


app = FastAPI()


@app.put("/items/{id}")
def update_item(id: str, item: Item):
    json_compatible_item_data = jsonable_encoder(item)
    fake_db[id] = json_compatible_item_data

    The above code is in JSON Compatible Encoder

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  2. 0

    My Answer

    You can use json.dumps(obj, default=serialize_function_if_raise>) to handle the serialization.

    My Example

    from pydantic import BaseModel, VERSION
import json

print(VERSION)
# > 2.4.2


class Model1(BaseModel):
    i: int = 1

    def model_dump(self):  # customize
        d = super().model_dump()
        for k, v in d.items():
            d[k] = f'{v} !'  # < example: add a `!`
        return d  # return a dict


class Model2(BaseModel):
    model1: Model1 = Model1()


pydantic_object1 = Model1()
pydantic_object2 = Model2()
my_dict = {
    "key1": "value1",
    "key2": {"key3": pydantic_object1, "key4": 4},
    "key5": pydantic_object2,
}


print(json.dumps(my_dict, default=lambda x: x.model_dump()))
# > {"key1": "value1", "key2": {"key3": {"i": "1 !"}, "key4": 4}, "key5": {"model1": {"i": 1}}}

    Follow Up

    import json
class ComplexEncoder(json.JSONEncoder):
    def default(self, obj):
        if isinstance(obj, complex):
            return [obj.real, obj.imag]
        # Let the base class default method raise the TypeError
        return json.JSONEncoder.default(self, obj)

json.dumps(2 + 1j, cls=ComplexEncoder)

ComplexEncoder().encode(2 + 1j)

list(ComplexEncoder().iterencode(2 + 1j))
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