在Pydantic中直接获取根模型的列表及字典表示的方法

Great question! You don't have to stick with the somewhat clunky __root__ access—there are cleaner ways to get your validated list and dict representations directly. Here are a few tailored approaches for your use case:

1. Use parse_obj_as (No Extra Model Needed) #

If you don't need a dedicated DeviceList model, Pydantic's parse_obj_as function lets you validate a list of objects directly, skipping the intermediate root model entirely:

from datetime import datetime
from typing import List
from pydantic import BaseModel, Field, parse_obj_as

my_devices = {
    "devices": [
        {
            "modifyTimestamp": "2022-01-17T13:35:58.597569Z",
            "vehicleId": "VINWVWZZZAUZLW9191234",
        }
    ],
    "modifyTimestamp": "2022-01-17T13:35:58.597569Z",
}

class Device(BaseModel):
    vehicle_id: str = Field(alias="vehicleId")
    modify_timestamp: datetime = Field(alias="modifyTimestamp")

# Validate directly as a list of Device instances
validated_data = parse_obj_as(List[Device], my_devices["devices"])

# Now validated_data is already a list—no __root__ required!
validated_data_list = [v.dict() for v in validated_data]

print(validated_data)
print(validated_data_list)

This returns exactly what you need with minimal boilerplate.

2. Make DeviceList Iterable (For Pydantic V1 or Custom Models) #

If you want to keep a dedicated DeviceList model, you can add sequence methods to it so you can iterate over the instance directly instead of always accessing __root__:

from datetime import datetime
from typing import List
from pydantic import BaseModel, Field
from collections.abc import Sequence

my_devices = {
    "devices": [
        {
            "modifyTimestamp": "2022-01-17T13:35:58.597569Z",
            "vehicleId": "VINWVWZZZAUZLW9191234",
        }
    ],
    "modifyTimestamp": "2022-01-17T13:35:58.597569Z",
}

class Device(BaseModel):
    vehicle_id: str = Field(alias="vehicleId")
    modify_timestamp: datetime = Field(alias="modifyTimestamp")

class DeviceList(BaseModel, Sequence):
    __root__: List[Device]

    # Delegate sequence operations to __root__
    def __getitem__(self, index):
        return self.__root__[index]
    
    def __len__(self):
        return len(self.__root__)

validated_data = DeviceList(__root__=my_devices["devices"])

# Now you can iterate directly over validated_data
validated_data_list = [v.dict() for v in validated_data]

print(validated_data)
print(validated_data_list)

With this setup, you can treat validated_data just like a regular list for iteration, indexing, and length checks.

3. Use RootModel (Pydantic V2+) #

If you're using Pydantic V2, the official recommended way to handle root-level lists is with RootModel, which is designed to simplify this exact scenario:

from datetime import datetime
from typing import List
from pydantic import BaseModel, Field, RootModel

my_devices = {
    "devices": [
        {
            "modifyTimestamp": "2022-01-17T13:35:58.597569Z",
            "vehicleId": "VINWVWZZZAUZLW9191234",
        }
    ],
    "modifyTimestamp": "2022-01-17T13:35:58.597569Z",
}

class Device(BaseModel):
    vehicle_id: str = Field(alias="vehicleId")
    modify_timestamp: datetime = Field(alias="modifyTimestamp")

class DeviceList(RootModel[List[Device]]):
    pass

# You can pass the list directly without the __root__ keyword argument
validated_data = DeviceList(my_devices["devices"])

# Access the root list with .root, or iterate directly
validated_data_list = [v.dict() for v in validated_data]

print(validated_data)
print(validated_data_list)

RootModel automatically implements sequence behavior, so you can iterate over it directly, and it also supports all standard Pydantic model features.

All these approaches eliminate the need to repeatedly reference __root__, making your code cleaner and more intuitive.

内容的提问来源于stack exchange，提问作者Cord Kaldemeyer