app = FastAPI()


@app.get("/users/{user_id}/items/{item_id}")
async def read_user_item(
    user_id: int, item_id: str, q: str | None = None, short: bool = False
):
    item = {"item_id": item_id, "owner_id": user_id}
    if q:
        item.update({"q": q})
    if not short:
        item.update(
            {"description": "This is an amazing item that has a long description"}
        )

app = FastAPI()


@app.get("/users/{user_id}/items/{item_id}")
async def read_user_item(
    user_id: int, item_id: str, q: Union[str, None] = None, short: bool = False
):
    item = {"item_id": item_id, "owner_id": user_id}
    if q:
        item.update({"q": q})
    if not short:
        item.update(
            {"description": "This is an amazing item that has a long description"}
        )

def get_items(skip: int = 0, limit: int = 100):
    return list(models.Item.select().offset(skip).limit(limit))


def create_user_item(item: schemas.ItemCreate, user_id: int):
    db_item = models.Item(**item.dict(), owner_id=user_id)
    db_item.save()

        return res


class ItemBase(BaseModel):
    title: str
    description: Union[str, None] = None


class ItemCreate(ItemBase):
    pass


class Item(ItemBase):
    id: int
    owner_id: int

    class Config:
        orm_mode = True
        getter_dict = PeeweeGetterDict


class UserBase(BaseModel):
    email: str


class UserCreate(UserBase):
    password: str

		{Name: "OwnerID", DBName: "company_owner_id", BindNames: []string{"Base", "OwnerID"}, DataType: schema.Int, Size: 64, TagSettings: map[string]string{"EMBEDDED": "EMBEDDED", "EMBEDDEDPREFIX": "company_"}},
		{Name: "OwnerID", DBName: "owner_id", BindNames: []string{"CorpBase", "OwnerID"}, DataType: schema.String},
	}

	for _, f := range fields {

`item.dict()`

 & ⤴️ 👥 🚶‍♀️ `dict`'Ⓜ 🔑-💲 👫 🇨🇻 ❌ 🇸🇲 `Item`, ⏮️:

`Item(**item.dict())`

 & ⤴️ 👥 🚶‍♀️ ➕ 🇨🇻 ❌ `owner_id` 👈 🚫 🚚 Pydantic *🏷*, ⏮️:

`Item(**item.dict(), owner_id=user_id)`

///

## 👑 **FastAPI** 📱

& 🔜 📁 `sql_app/main.py` ➡️ 🛠️ & ⚙️ 🌐 🎏 🍕 👥 ✍ ⏭.

### ✍ 💽 🏓

📶 🙃 🌌 ✍ 💽 🏓:

这里不是将每个关键字参数传递给Item并从Pydantic模型中读取每个参数，而是先生成一个字典，其中包含Pydantic模型的数据：

`item.dict()`

然后我们将dict的键值对 作为关键字参数传递给 SQLAlchemy `Item`：

`Item(**item.dict())`

然后我们传递 Pydantic模型未提供的额外关键字参数`owner_id`：

`Item(**item.dict(), owner_id=user_id)`

///

## 主**FastAPI**应用程序

现在在`sql_app/main.py`文件中 让我们集成和使用我们之前创建的所有其他部分。

### 创建数据库表

以非常简单的方式创建数据库表：

//// tab | Python 3.9+

						FieldSchema: "Toy",
						Polymorphic: Polymorphic{ID: "owner_id", Type: "Type", Value: "users"},
						References: []Reference{
							{ForeignKey: "Type", ForeignSchema: "Toy", PrimaryValue: "users"},
						},
					},
				},
			},
		})
	})

	t.Run("has many", func(t *testing.T) {
		type Toy struct {
			ID        int
			Name      string
			OwnerID   int
			OwnerType string
		}

            "price": None,
            "owner_ids": None,
        },
        {
            "name": "bar",
            "date": datetime(2021, 7, 26).isoformat(),
            "price": 1.0,
            "owner_ids": None,
        },
        {
            "name": "baz",
            "date": datetime(2021, 7, 26).isoformat(),
            "price": 2.0,
            "owner_ids": [1, 2, 3],
        },
    ]

        "price": 1.0,
        "owner_ids": None,
    }


def test_validlist():
    response = client.get("/items/validlist")
    response.raise_for_status()
    assert response.json() == [
        {"aliased_name": "foo", "price": None, "owner_ids": None},
        {"aliased_name": "bar", "price": 1.0, "owner_ids": None},
        {"aliased_name": "baz", "price": 2.0, "owner_ids": [1, 2, 3]},
    ]