litestar How to combine query parameters with API documentation

Question

from dataclasses import dataclass

from litestar import Litestar, get


@dataclass
class User:
    id: int
    name: str


@get(path="/")
async def index(
        query: User,
) -> dict[str, str]:
    print(query)
    return {}

app = Litestar(route_handlers=[index])

explain: The User class may be used in multiple GET views, and I want a reusable way. This is the current example, but it has its drawbacks. The API documentation does not support querying parameter requests and errors may occur

This is a demo on how to make the API documentation support ID and name query parameters.

from dataclasses import dataclass

from litestar import Litestar, get

from typing import Optional


@dataclass
class User:
    id: int
    name: str


@get(path="/")
async def index(
        # query: User,
        id: Optional[str] = None,
        name: Optional[str] = None
        # more params
) -> dict[str, str]:
    # print(query)
    return {}


app = Litestar(route_handlers=[index])

I know this approach supports displaying in the API documentation, but it is too cumbersome and requires declaring each parameter in the view, and these parameters may be used in multiple views, resulting in low reusability. Is there any way to support it, or is there another better way

Answer 1

I think I've found the best way.

from dataclasses import dataclass
from typing import Any

from litestar import Litestar, get
from litestar.params import Parameter
from litestar.di import Provide


@dataclass
class User:
    id: int
    name: str


async def get_params(
        id: int | None = Parameter(default=None),
        name: str | None = Parameter(default=None),
) -> dict[str, Any]:
    res = {}
    if id:
        res["id"] = id
    if name:
        res["name"] = name
    return res


@get(path="/", dependencies={"params": Provide(get_params)})
async def index(params: dict[str, Any]) -> dict[str, Any]:
    print(params)
    return params


app = Litestar(route_handlers=[index])

Now, good scalability and API documentation support can be maintained.