Question

我有一个工作模型，可以使用json来接收pydantic数据集。模型数据集如下所示：

data = {'thing_number': 123, 
        'thing_description': 'duck',
        'thing_amount': 4.56}

我想做的是将json个文件列表作为数据集，并能够对其进行验证。最终，该列表将转换为pandas中的记录以进行进一步处理。我的目标是验证json条目的任意长列表，看起来像这样：

bigger_data = [{'thing_number': 123, 
                'thing_description': 'duck',
                'thing_amount': 4.56}, 
               {'thing_number': 456, 
                'thing_description': 'cow',
                'thing_amount': 7.89}]

我现在拥有的基本设置如下。请注意，添加class ItemList是使任意长度起作用的一部分尝试。

from typing import List
from pydantic import BaseModel
from pydantic.schema import schema
import json

class Item(BaseModel):
    thing_number: int
    thing_description: str
    thing_amount: float

class ItemList(BaseModel):
    each_item: List[Item]

然后，基本代码将生成我想在包含Item个对象的数组对象中寻找的东西。

item_schema = schema([ItemList])
print(json.dumps(item_schema, indent=2)) 

    {
      "definitions": {
        "Item": {
          "title": "Item",
          "type": "object",
          "properties": {
            "thing_number": {
              "title": "Thing_Number",
              "type": "integer"
            },
            "thing_description": {
              "title": "Thing_Description",
              "type": "string"
            },
            "thing_amount": {
              "title": "Thing_Amount",
              "type": "number"
            }
          },
          "required": [
            "thing_number",
            "thing_description",
            "thing_amount"
          ]
        },
        "ItemList": {
          "title": "ItemList",
          "type": "object",
          "properties": {
            "each_item": {
              "title": "Each_Item",
              "type": "array",
              "items": {
                "$ref": "#/definitions/Item"
              }
            }
          },
          "required": [
            "each_item"
          ]
        }
      }
    }

该设置适用于传递的单个json项目：

item = Item(**data)                                                      

print(item)

Item thing_number=123 thing_description='duck' thing_amount=4.56

但是当我尝试将单个项目传递给ItemList模型时，它将返回错误：

item_list = ItemList(**data)

---------------------------------------------------------------------------
ValidationError                           Traceback (most recent call last)
<ipython-input-94-48efd56e7b6c> in <module>
----> 1 item_list = ItemList(**data)

/opt/conda/lib/python3.7/site-packages/pydantic/main.cpython-37m-x86_64-linux-gnu.so in pydantic.main.BaseModel.__init__()

/opt/conda/lib/python3.7/site-packages/pydantic/main.cpython-37m-x86_64-linux-gnu.so in pydantic.main.validate_model()

ValidationError: 1 validation error for ItemList
each_item
  field required (type=value_error.missing)

我还尝试过将bigger_data传递到数组中，认为它需要以列表开头。也会返回错误--虽然，至少我对词典错误有更好的了解，但我不知道如何解决。

item_list2 = ItemList(**data_big)

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-100-8fe9a5414bd6> in <module>
----> 1 item_list2 = ItemList(**data_big)

TypeError: MetaModel object argument after ** must be a mapping, not list

谢谢。

我尝试过的其他事情

我已经尝试过将数据传递到特定密钥中，但还有些运气（也许？）。

item_list2 = ItemList(each_item=data_big)

---------------------------------------------------------------------------
ValidationError                           Traceback (most recent call last)
<ipython-input-111-07e5c12bf8b4> in <module>
----> 1 item_list2 = ItemList(each_item=data_big)

/opt/conda/lib/python3.7/site-packages/pydantic/main.cpython-37m-x86_64-linux-gnu.so in pydantic.main.BaseModel.__init__()

/opt/conda/lib/python3.7/site-packages/pydantic/main.cpython-37m-x86_64-linux-gnu.so in pydantic.main.validate_model()

ValidationError: 6 validation errors for ItemList
each_item -> 0 -> thing_number
  field required (type=value_error.missing)
each_item -> 0 -> thing_description
  field required (type=value_error.missing)
each_item -> 0 -> thing_amount
  field required (type=value_error.missing)
each_item -> 1 -> thing_number
  field required (type=value_error.missing)
each_item -> 1 -> thing_description
  field required (type=value_error.missing)
each_item -> 1 -> thing_amount
  field required (type=value_error.missing)

Answer 1

from typing import List
from pydantic import BaseModel
import json


class Item(BaseModel):
    thing_number: int
    thing_description: str
    thing_amount: float


class ItemList(BaseModel):
    each_item: List[Item]

基于您的代码，其中each_item作为项目列表

a_duck = Item(thing_number=123, thing_description="duck", thing_amount=4.56)
print(a_duck.json())

a_list = ItemList(each_item=[a_duck])

print(a_list.json())

生成以下输出：

{"thing_number": 123, "thing_description": "duck", "thing_amount": 4.56}
{"each_item": [{"thing_number": 123, "thing_description": "duck", "thing_amount": 4.56}]}

将它们用作“ entry json”：

a_json_duck = {"thing_number": 123, "thing_description": "duck", "thing_amount": 4.56}
a_json_list = {
    "each_item": [
        {"thing_number": 123, "thing_description": "duck", "thing_amount": 4.56}
    ]
}

print(Item(**a_json_duck))
print(ItemList(**a_json_list))

工作正常，并生成：

Item thing_number=123 thing_description='duck' thing_amount=4.56
ItemList each_item=[<Item thing_number=123 thing_description='duck' thing_amount=4.56>]

我们只剩下唯一的数据了：

just_datas = [
    {"thing_number": 123, "thing_description": "duck", "thing_amount": 4.56},
    {"thing_number": 456, "thing_description": "cow", "thing_amount": 7.89},
]
item_list = ItemList(each_item=just_datas)
print(item_list)
print(type(item_list.each_item[1]))
print(item_list.each_item[1])

那些按预期方式工作：

ItemList each_item=[<Item thing_number=123 thing_description='duck'thing_amount=4.56>,<Item thin…
<class '__main__.Item'>
Item thing_number=456 thing_description='cow' thing_amount=7.89

因此，以防万一我遗漏了大杂烩的东西，按预期工作。

我的pydantic版本：0.30 python 3.7.4

从相似文件读取：

json_data_file = """[
{"thing_number": 123, "thing_description": "duck", "thing_amount": 4.56},
{"thing_number": 456, "thing_description": "cow", "thing_amount": 7.89}]"""

from io import StringIO
item_list2 = ItemList(each_item=json.load(StringIO(json_data_file)))

工作也很好。

Answer 2

为避免在{{1}中包含"each_item"，可以使用__root__ Pydantic关键字：

ItemList

要构建from typing import List from pydantic import BaseModel class Item(BaseModel): thing_number: int thing_description: str thing_amount: float class ItemList(BaseModel): __root__: List[Item] # ⯇-- __root__：

item_list

支持Pydantic的网络框架通常将just_data = [ {"thing_number": 123, "thing_description": "duck", "thing_amount": 4.56}, {"thing_number": 456, "thing_description": "cow", "thing_amount": 7.89}, ] item_list = ItemList(__root__=just_data) a_json_duck = {"thing_number": 123, "thing_description": "duck", "thing_amount": 4.56} item_list.__root__.append(a_json_duck) JSON化为JSON数组，而没有中间ItemList关键字。

Python / Pydantic-将列表与json对象一起使用

2 个答案: