请求体 - 更新¶
使用 PUT
进行替换更新¶
要更新项目,你可以使用 HTTP PUT
操作。
你可以使用 jsonable_encoder
将输入数据转换为可存储为 JSON 的数据(例如,在 NoSQL 数据库中)。例如,将 datetime
转换为 str
。
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
🤓 其他版本和变体
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
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
PUT
用于接收应替换现有数据的数据。
关于替换的警告¶
这意味着如果你想使用 PUT
更新项目 bar
,并且请求体包含
{
"name": "Barz",
"price": 3,
"description": None,
}
因为它不包含已存储的属性 "tax": 20.2
,所以输入模型将采用默认值 "tax": 10.5
。
数据将以这个“新”的 10.5
税值保存。
使用 PATCH
进行部分更新¶
你还可以使用 HTTP PATCH
操作来部分更新数据。
这意味着你只发送要更新的数据,其余数据保持不变。
注意
PATCH
的使用和知名度不如 PUT
。
许多团队甚至在进行部分更新时也只使用 PUT
。
你可以自由选择如何使用它们,FastAPI 不会施加任何限制。
但本指南或多或少地向你展示了它们的使用方式。
使用 Pydantic 的 exclude_unset
参数¶
如果你想接收部分更新,在 Pydantic 模型的 .model_dump()
中使用参数 exclude_unset
会非常有用。
例如 item.model_dump(exclude_unset=True)
。
信息
在 Pydantic v1 中,该方法名为 .dict()
,在 Pydantic v2 中被弃用(但仍受支持),并更名为 .model_dump()
。
这里的示例使用 .dict()
以兼容 Pydantic v1,但如果可以使用 Pydantic v2,则应改用 .model_dump()
。
这将生成一个 dict
,其中只包含创建 item
模型时设置的数据,不包括默认值。
然后你可以使用它来生成一个 dict
,其中只包含已设置(在请求中发送)的数据,省略默认值
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
🤓 其他版本和变体
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
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
使用 Pydantic 的 update
参数¶
现在,你可以使用 .model_copy()
创建现有模型的副本,并传入包含要更新数据的 dict
作为 update
参数。
信息
在 Pydantic v1 中,该方法名为 .copy()
,在 Pydantic v2 中被弃用(但仍受支持),并更名为 .model_copy()
。
这里的示例为了与 Pydantic v1 兼容而使用 .copy()
,但如果你可以使用 Pydantic v2,则应改用 .model_copy()
。
例如 stored_item_model.model_copy(update=update_data)
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
🤓 其他版本和变体
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
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
部分更新回顾¶
总而言之,要应用部分更新,你需要
- (可选)使用
PATCH
而不是PUT
。 - 检索已存储的数据。
- 将该数据放入 Pydantic 模型中。
- 从输入模型生成一个不包含默认值的
dict
(使用exclude_unset
)。- 这样,你就可以只更新用户实际设置的值,而不是用模型中的默认值覆盖已存储的值。
- 创建存储模型的副本,并使用收到的部分更新(使用
update
参数)更新其属性。 - 将复制的模型转换为可存储在数据库中的格式(例如,使用
jsonable_encoder
)。- 这类似于再次使用模型的
.model_dump()
方法,但它确保(并转换)值成为可以转换为 JSON 的数据类型,例如将datetime
转换为str
。
- 这类似于再次使用模型的
- 将数据保存到数据库中。
- 返回更新后的模型。
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
🤓 其他版本和变体
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
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
提示
实际上,你也可以将这种技术用于 HTTP PUT
操作。
但这里的示例使用 PATCH
,因为它就是为这些用例创建的。
注意
请注意,输入模型仍然会进行验证。
因此,如果你想接收可以省略所有属性的部分更新,你需要一个所有属性都标记为可选(带有默认值或 None
)的模型。
为了区分用于更新的包含所有可选值的模型和用于创建的包含必需值的模型,你可以使用额外模型中描述的思想。