Read a body JSON list with FastAPI

user_127670 0
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The body of an HTTP PUT request is a JSON list - like this:

[item1, item2, item3, ...]

I can't change this. (If the root was a JSON object rather than a list there would be no problem.)

Using FastAPI I seem to be unable to access this content in the normal way:

@router.put('/data')
def set_data(data: DataModel): # This doesn't work; how do I even declare DataModel?

I found the following workaround, which seems like a very ugly hack:

class DataModel(BaseModel):
    __root__: List[str]


from fastAPI import Request

@router.put('/data')
async def set_data(request: Request): # Get the request object directly
    data = DataModel(__root__=await request.json())

This surely can't be the 'approved' way to achieve this. I've scoured the documentation both of FastAPI and pydantic. What am I missing?

pydantic fastapi python
1 Answers

Descending from the model perspective to primitives

In FastAPI, you derive from BaseModel to describe the data models you send and receive (i.e. FastAPI also parses for you from a body and translates to Python objects). Also, it relies on the modeling and processing from pydantic.

from typing import List
from pydantic import BaseModel

class Item(BaseModel):
    name: str

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

def process_item_list(items: ItemList):
    pass

This example would be able to parse JSON like

{"items": [{"name": "John"}, {"name": "Mary"}]}

In your case - depending on what shape your list entries have - you'd also go for proper type modeling, but you want to directly receive and process the list without the JSON dict wrapper around it. You could go for:

from typing import List
from pydantic import BaseModel

class Item(BaseModel):
    name: str

def process_item_list(items: List[Item]):
    pass

Which is now able to process JSON like:

[{"name": "John"}, {"name": "Mary"}]

This is probably what you're looking for and the last adaption to take is depending on the shape of your item* in the list you receive. If it's plain strings, you can also go for:

from typing import List

def process_item_list(items: List[str]):
    pass

Which could process JSON like

["John", "Mary"]

I outlined the path from models down to primitives in lists because I think it's worth knowing where this can go if one needs more complexity in the data models.

user_56776020
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