My FastAPI call is not returning the data in correct Response
model format. It is returning data in database model format.
My database model:
class cat(DBConnect.Base):
__tablename__ = 'category'
__table_args__ = {"schema": SCHEMA}
cat_id = Column('cat_id',UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
cat_desc = Column('cat_desc', TEXT, nullable=True)
cat_h__l_name = Column('cat_h_l_name', TEXT, nullable=True)
My Pydantic Model:
class CamelModel(BaseModel):
class config:
alias_generator = to_camel
allow_population_by_field_name = True
class cat(CamelModel):
cat_id =Field(alais='CatID', readonly=True)
cat_description =Field(alias='CatDescription')
cat_h__l_name = Field(alias='CatName')
class config:
orm_mode= True
My API call:
@router.patch('/cat/{id}/', response_model = 'cat')
def update_cat(response= Response, params: updatecat = Depends(updatecat)):
response_obj = { resonse_code: status.HTTP_200_OK,
response_obj : {}
}
response_obj = session.query() # It is returning the correct data from the database
response.status_code = response_obj['response_code']
return JSONResponse(response_obj['response_obj'], status_code = response_obj['response_code'])
Getting Response in below format:
cat_id = 'some uuid'
cat_desc = 'desc'
cat_h__l_name = 'some h_l_name'
but I want the response to be in the below format:
CatID = 'some uuid'
CatDescription ='' some description'
CatName = 'Some cat name'
This code is not giving any errors (I have typed it, so might be some indentation or spelling mistake). The only issue is that the API doesn't return data in correct format. I have been stuck on it for a while.
To return a Pydantic model from an API endpoint using the Field
aliases instead of names, you could add response_model_by_alias=True
to the endpoint's decorator. This is mentioned in the documentation. Using response_model_by_alias=False
would have the opposite effect. The example below uses the Model's Config alias_generator
to automatically generate aliases for the fields.
from fastapi import FastAPI
from pydantic import BaseModel
app = FastAPI()
def to_pascal(string: str) -> str:
return ''.join(word.capitalize() for word in string.split('_'))
class Item(BaseModel):
name: str
language_code: str
class Config:
alias_generator = to_pascal
allow_population_by_field_name = True
fake_db = [
Item(Name='foo', LanguageCode='en'),
Item(Name='bar', LanguageCode='fr')
]
@app.get('/item/{item_id}', response_model=Item, response_model_by_alias=True)
def create_item(item_id: int):
return fake_db[item_id]
In Pydantic V2, the alias_generator
could be used in a ConfigDict
class, as shown in the documentation (along with response_model_by_alias=True
). Pydantic offers three built-in alias generators: to_pascal
, to_camel
, and to_snake
. Also, in v2.0, the allow_population_by_field_name
configuration setting was changed to populate_by_name
. This setting indicates whether an aliased field may be populated by its name as given by the model attribute, as well as the alias. Defaults to False
.
from pydantic import BaseModel, ConfigDict
from pydantic.alias_generators import to_pascal
class Item(BaseModel):
model_config = ConfigDict(alias_generator=to_pascal, populate_by_name=True)
name: str
language_code: str
If one would like to create a Field
alias without using an alias_generator
, they could achieve this as follows:
from pydantic import BaseModel, ConfigDict, Field
class Item(BaseModel):
model_config = ConfigDict(populate_by_name=True)
name: str = Field(..., alias='Name')
language_code: str = Field(..., alias='LanguageCode')
In case you used an alias_generator
, as well as specified an alias
on the Field
, the alias
will take precedence over the generated alias by default.
Also, as explained in Pydantic's documentation:
The
alias
parameter is used for both validation and serialization. If you want to use different aliases for validation and serialization respectively, you can use thevalidation_alias
andserialization_alias
parameters, which will apply only in their respective use cases.In case you use
alias
together withvalidation_alias
orserialization_alias
at the same time, thevalidation_alias
will have priority overalias
for validation, andserialization_alias
will have priority overalias
for serialization.You may also set
alias_priority
on a field to change this behavior.
JSONResponse
It should also be noted that you seem to be returning a JSONResponse
directly, instead of a Pydantic model from your API endpoint (which would be later wrapped into a JSONResponse
by FastAPI, behind the scenes, and returned to the client); hence, setting response_model_by_alias=True
in the endpoint's decorator would have no effect. Thus, in that case, you could convert the model to a dictionary, using Pydantic's model.dict(...)
(Note: in Pydantic V2, this method has been replaced by model.model_dump(...)
), and set the by_alias
argument to True
.
On a side note, you cannot put a Pydantic model in a JSONResponse
without first converting it to a dict
, if you have data types, such as datetime
, UUID
, etc., that cannot be serialized. For those cases, you can use the jsonable_encoder
to convert your data before passing it to a response. The jsonable_encoder
will ensure that objects that are not serializable will be converted to a str
. Have a look at this answer for more details.
from fastapi.responses import JSONResponse
from fastapi.encoders import jsonable_encoder
@app.get('/item/{item_id}')
def create_item(item_id: int):
return JSONResponse(jsonable_encoder(fake_db[item_id].model_dump(by_alias=True)), status_code=200)
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With