请求体 - 更新数据¶

用 `PUT` 更新数据¶

更新数据请用 HTTP PUT 操作。

把输入数据转换为以 JSON 格式存储的数据（比如，使用 NoSQL 数据库时），可以使用 jsonable_encoder。例如，把 datetime 转换为 str。

Python 3.8+

from typing import List, Union

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

app = FastAPI()


class Item(BaseModel):
    name: Union[str, None] = None
    description: Union[str, None] = None
    price: Union[float, None] = None
    tax: float = 10.5
    tags: List[str] = []


items = {
    "foo": {"name": "Foo", "price": 50.2},
    "bar": {"name": "Bar", "description": "The bartenders", "price": 62, "tax": 20.2},
    "baz": {"name": "Baz", "description": None, "price": 50.2, "tax": 10.5, "tags": []},
}


@app.get("/items/{item_id}", response_model=Item)
async def read_item(item_id: str):
    return items[item_id]


@app.put("/items/{item_id}", response_model=Item)
async def update_item(item_id: str, item: Item):
    update_item_encoded = jsonable_encoder(item)
    items[item_id] = update_item_encoded
    return update_item_encoded

🤓 Other versions and variants

Python 3.10+Python 3.9+

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

app = FastAPI()


class Item(BaseModel):
    name: str | None = None
    description: str | None = None
    price: float | None = None
    tax: float = 10.5
    tags: list[str] = []


items = {
    "foo": {"name": "Foo", "price": 50.2},
    "bar": {"name": "Bar", "description": "The bartenders", "price": 62, "tax": 20.2},
    "baz": {"name": "Baz", "description": None, "price": 50.2, "tax": 10.5, "tags": []},
}


@app.get("/items/{item_id}", response_model=Item)
async def read_item(item_id: str):
    return items[item_id]


@app.put("/items/{item_id}", response_model=Item)
async def update_item(item_id: str, item: Item):
    update_item_encoded = jsonable_encoder(item)
    items[item_id] = update_item_encoded
    return update_item_encoded

from typing import Union

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

app = FastAPI()


class Item(BaseModel):
    name: Union[str, None] = None
    description: Union[str, None] = None
    price: Union[float, None] = None
    tax: float = 10.5
    tags: list[str] = []


items = {
    "foo": {"name": "Foo", "price": 50.2},
    "bar": {"name": "Bar", "description": "The bartenders", "price": 62, "tax": 20.2},
    "baz": {"name": "Baz", "description": None, "price": 50.2, "tax": 10.5, "tags": []},
}


@app.get("/items/{item_id}", response_model=Item)
async def read_item(item_id: str):
    return items[item_id]


@app.put("/items/{item_id}", response_model=Item)
async def update_item(item_id: str, item: Item):
    update_item_encoded = jsonable_encoder(item)
    items[item_id] = update_item_encoded
    return update_item_encoded

PUT 用于接收替换现有数据的数据。

关于更新数据的警告¶

用 PUT 把数据项 bar 更新为以下内容时：

{
    "name": "Barz",
    "price": 3,
    "description": None,
}

因为上述数据未包含已存储的属性 "tax": 20.2，新的输入模型会把 "tax": 10.5 作为默认值。

因此，本次操作把 tax 的值「更新」为 10.5。

用 `PATCH` 进行部分更新¶

HTTP PATCH 操作用于更新部分数据。

即，只发送要更新的数据，其余数据保持不变。

笔记

PATCH 没有 PUT 知名，也怎么不常用。

很多人甚至只用 PUT 实现部分更新。

FastAPI 对此没有任何限制，可以随意互换使用这两种操作。

但本指南也会分别介绍这两种操作各自的用途。

使用 Pydantic 的 `exclude_unset` 参数¶

更新部分数据时，可以在 Pydantic 模型的 .dict() 中使用 exclude_unset 参数。

比如，item.dict(exclude_unset=True)。

这段代码生成的 dict 只包含创建 item 模型时显式设置的数据，而不包括默认值。

然后再用它生成一个只含已设置（在请求中所发送）数据，且省略了默认值的 dict：

Python 3.8+

from typing import List, Union

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

app = FastAPI()


class Item(BaseModel):
    name: Union[str, None] = None
    description: Union[str, None] = None
    price: Union[float, None] = None
    tax: float = 10.5
    tags: List[str] = []


items = {
    "foo": {"name": "Foo", "price": 50.2},
    "bar": {"name": "Bar", "description": "The bartenders", "price": 62, "tax": 20.2},
    "baz": {"name": "Baz", "description": None, "price": 50.2, "tax": 10.5, "tags": []},
}


@app.get("/items/{item_id}", response_model=Item)
async def read_item(item_id: str):
    return items[item_id]


@app.patch("/items/{item_id}", response_model=Item)
async def update_item(item_id: str, item: Item):
    stored_item_data = items[item_id]
    stored_item_model = Item(**stored_item_data)
    update_data = item.dict(exclude_unset=True)
    updated_item = stored_item_model.copy(update=update_data)
    items[item_id] = jsonable_encoder(updated_item)
    return updated_item

🤓 Other versions and variants

Python 3.10+Python 3.9+

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

app = FastAPI()


class Item(BaseModel):
    name: str | None = None
    description: str | None = None
    price: float | None = None
    tax: float = 10.5
    tags: list[str] = []


items = {
    "foo": {"name": "Foo", "price": 50.2},
    "bar": {"name": "Bar", "description": "The bartenders", "price": 62, "tax": 20.2},
    "baz": {"name": "Baz", "description": None, "price": 50.2, "tax": 10.5, "tags": []},
}


@app.get("/items/{item_id}", response_model=Item)
async def read_item(item_id: str):
    return items[item_id]


@app.patch("/items/{item_id}", response_model=Item)
async def update_item(item_id: str, item: Item):
    stored_item_data = items[item_id]
    stored_item_model = Item(**stored_item_data)
    update_data = item.dict(exclude_unset=True)
    updated_item = stored_item_model.copy(update=update_data)
    items[item_id] = jsonable_encoder(updated_item)
    return updated_item

from typing import Union

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

app = FastAPI()


class Item(BaseModel):
    name: Union[str, None] = None
    description: Union[str, None] = None
    price: Union[float, None] = None
    tax: float = 10.5
    tags: list[str] = []


items = {
    "foo": {"name": "Foo", "price": 50.2},
    "bar": {"name": "Bar", "description": "The bartenders", "price": 62, "tax": 20.2},
    "baz": {"name": "Baz", "description": None, "price": 50.2, "tax": 10.5, "tags": []},
}


@app.get("/items/{item_id}", response_model=Item)
async def read_item(item_id: str):
    return items[item_id]


@app.patch("/items/{item_id}", response_model=Item)
async def update_item(item_id: str, item: Item):
    stored_item_data = items[item_id]
    stored_item_model = Item(**stored_item_data)
    update_data = item.dict(exclude_unset=True)
    updated_item = stored_item_model.copy(update=update_data)
    items[item_id] = jsonable_encoder(updated_item)
    return updated_item

使用 Pydantic 的 `update` 参数¶

接下来，用 .copy() 为已有模型创建调用 update 参数的副本，该参数为包含更新数据的 dict。

例如，stored_item_model.copy(update=update_data)：

Python 3.8+

from typing import List, Union

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

app = FastAPI()


class Item(BaseModel):
    name: Union[str, None] = None
    description: Union[str, None] = None
    price: Union[float, None] = None
    tax: float = 10.5
    tags: List[str] = []


items = {
    "foo": {"name": "Foo", "price": 50.2},
    "bar": {"name": "Bar", "description": "The bartenders", "price": 62, "tax": 20.2},
    "baz": {"name": "Baz", "description": None, "price": 50.2, "tax": 10.5, "tags": []},
}


@app.get("/items/{item_id}", response_model=Item)
async def read_item(item_id: str):
    return items[item_id]


@app.patch("/items/{item_id}", response_model=Item)
async def update_item(item_id: str, item: Item):
    stored_item_data = items[item_id]
    stored_item_model = Item(**stored_item_data)
    update_data = item.dict(exclude_unset=True)
    updated_item = stored_item_model.copy(update=update_data)
    items[item_id] = jsonable_encoder(updated_item)
    return updated_item

🤓 Other versions and variants

Python 3.10+Python 3.9+

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

app = FastAPI()


class Item(BaseModel):
    name: str | None = None
    description: str | None = None
    price: float | None = None
    tax: float = 10.5
    tags: list[str] = []


items = {
    "foo": {"name": "Foo", "price": 50.2},
    "bar": {"name": "Bar", "description": "The bartenders", "price": 62, "tax": 20.2},
    "baz": {"name": "Baz", "description": None, "price": 50.2, "tax": 10.5, "tags": []},
}


@app.get("/items/{item_id}", response_model=Item)
async def read_item(item_id: str):
    return items[item_id]


@app.patch("/items/{item_id}", response_model=Item)
async def update_item(item_id: str, item: Item):
    stored_item_data = items[item_id]
    stored_item_model = Item(**stored_item_data)
    update_data = item.dict(exclude_unset=True)
    updated_item = stored_item_model.copy(update=update_data)
    items[item_id] = jsonable_encoder(updated_item)
    return updated_item

from typing import Union

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

app = FastAPI()


class Item(BaseModel):
    name: Union[str, None] = None
    description: Union[str, None] = None
    price: Union[float, None] = None
    tax: float = 10.5
    tags: list[str] = []


items = {
    "foo": {"name": "Foo", "price": 50.2},
    "bar": {"name": "Bar", "description": "The bartenders", "price": 62, "tax": 20.2},
    "baz": {"name": "Baz", "description": None, "price": 50.2, "tax": 10.5, "tags": []},
}


@app.get("/items/{item_id}", response_model=Item)
async def read_item(item_id: str):
    return items[item_id]


@app.patch("/items/{item_id}", response_model=Item)
async def update_item(item_id: str, item: Item):
    stored_item_data = items[item_id]
    stored_item_model = Item(**stored_item_data)
    update_data = item.dict(exclude_unset=True)
    updated_item = stored_item_model.copy(update=update_data)
    items[item_id] = jsonable_encoder(updated_item)
    return updated_item

更新部分数据小结¶

简而言之，更新部分数据应：

使用 PATCH 而不是 PUT （可选，也可以用 PUT）；
提取存储的数据；
把数据放入 Pydantic 模型；
生成不含输入模型默认值的 dict （使用 exclude_unset 参数）；
- 只更新用户设置过的值，不用模型中的默认值覆盖已存储过的值。
为已存储的模型创建副本，用接收的数据更新其属性（使用 update 参数）。
把模型副本转换为可存入数据库的形式（比如，使用 jsonable_encoder）。
- 这种方式与 Pydantic 模型的 .dict() 方法类似，但能确保把值转换为适配 JSON 的数据类型，例如，把 datetime 转换为 str 。
把数据保存至数据库；
返回更新后的模型。

Python 3.8+

from typing import List, Union

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

app = FastAPI()


class Item(BaseModel):
    name: Union[str, None] = None
    description: Union[str, None] = None
    price: Union[float, None] = None
    tax: float = 10.5
    tags: List[str] = []


items = {
    "foo": {"name": "Foo", "price": 50.2},
    "bar": {"name": "Bar", "description": "The bartenders", "price": 62, "tax": 20.2},
    "baz": {"name": "Baz", "description": None, "price": 50.2, "tax": 10.5, "tags": []},
}


@app.get("/items/{item_id}", response_model=Item)
async def read_item(item_id: str):
    return items[item_id]


@app.patch("/items/{item_id}", response_model=Item)
async def update_item(item_id: str, item: Item):
    stored_item_data = items[item_id]
    stored_item_model = Item(**stored_item_data)
    update_data = item.dict(exclude_unset=True)
    updated_item = stored_item_model.copy(update=update_data)
    items[item_id] = jsonable_encoder(updated_item)
    return updated_item

🤓 Other versions and variants

Python 3.10+Python 3.9+

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

app = FastAPI()


class Item(BaseModel):
    name: str | None = None
    description: str | None = None
    price: float | None = None
    tax: float = 10.5
    tags: list[str] = []


items = {
    "foo": {"name": "Foo", "price": 50.2},
    "bar": {"name": "Bar", "description": "The bartenders", "price": 62, "tax": 20.2},
    "baz": {"name": "Baz", "description": None, "price": 50.2, "tax": 10.5, "tags": []},
}


@app.get("/items/{item_id}", response_model=Item)
async def read_item(item_id: str):
    return items[item_id]


@app.patch("/items/{item_id}", response_model=Item)
async def update_item(item_id: str, item: Item):
    stored_item_data = items[item_id]
    stored_item_model = Item(**stored_item_data)
    update_data = item.dict(exclude_unset=True)
    updated_item = stored_item_model.copy(update=update_data)
    items[item_id] = jsonable_encoder(updated_item)
    return updated_item

from typing import Union

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

app = FastAPI()


class Item(BaseModel):
    name: Union[str, None] = None
    description: Union[str, None] = None
    price: Union[float, None] = None
    tax: float = 10.5
    tags: list[str] = []


items = {
    "foo": {"name": "Foo", "price": 50.2},
    "bar": {"name": "Bar", "description": "The bartenders", "price": 62, "tax": 20.2},
    "baz": {"name": "Baz", "description": None, "price": 50.2, "tax": 10.5, "tags": []},
}


@app.get("/items/{item_id}", response_model=Item)
async def read_item(item_id: str):
    return items[item_id]


@app.patch("/items/{item_id}", response_model=Item)
async def update_item(item_id: str, item: Item):
    stored_item_data = items[item_id]
    stored_item_model = Item(**stored_item_data)
    update_data = item.dict(exclude_unset=True)
    updated_item = stored_item_model.copy(update=update_data)
    items[item_id] = jsonable_encoder(updated_item)
    return updated_item

提示

实际上，HTTP PUT 也可以完成相同的操作。但本节以 PATCH 为例的原因是，该操作就是为了这种用例创建的。

笔记

注意，输入模型仍需验证。

因此，如果希望接收的部分更新数据可以省略其他所有属性，则要把模型中所有的属性标记为可选（使用默认值或 None）。

为了区分用于更新所有可选值的模型与用于创建包含必选值的模型，请参照更多模型一节中的思路。

请求体 - 更新数据¶

用 PUT 更新数据¶

关于更新数据的警告¶

用 PATCH 进行部分更新¶

使用 Pydantic 的 exclude_unset 参数¶

使用 Pydantic 的 update 参数¶

更新部分数据小结¶

用 `PUT` 更新数据¶

用 `PATCH` 进行部分更新¶

使用 Pydantic 的 `exclude_unset` 参数¶

使用 Pydantic 的 `update` 参数¶