from sqlmodel import Field, Session, SQLModel, create_engine

engine = create_engine("postgresql+psycopg://postgres:postgres@localhost/db")


class User(SQLModel, table=True):
    id: int | None = Field(default=None, primary_key=True)
    name: str


app = FastAPI()


def get_session():
    with Session(engine) as session:
        yield session

     * Gets the installation settings source.
     *
     * @return the installation settings source or {@code null} if none
     */
    @Nonnull
    Optional<Source> getInstallationSettingsSource();

    /**
     * Gets the project settings source.
     *
     * @return the project settings source or {@code null} if none
     */
    @Nonnull
    Optional<Source> getProjectSettingsSource();

    /**

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

fake_db = {}


class Item(BaseModel):
    title: str
    timestamp: datetime
    description: str | None = None


app = FastAPI()


@app.put("/items/{id}")
def update_item(id: str, item: Item):
    json_compatible_item_data = jsonable_encoder(item)

from typing import Annotated, Union

from fastapi import FastAPI
from fastapi.temp_pydantic_v1_params import Body
from pydantic.v1 import BaseModel


class Item(BaseModel):
    name: str
    description: Union[str, None] = None
    size: float


app = FastAPI()


@app.post("/items/")
async def create_item(item: Annotated[Item, Body(embed=True)]) -> Item:

from fastapi import FastAPI, Path, Query

app = FastAPI()


@app.get("/items/{item_id}")
async def read_items(
    item_id: int = Path(title="The ID of the item to get"),
    q: Union[str, None] = Query(default=None, alias="item-query"),
):
    results = {"item_id": item_id}
    if q:
        results.update({"q": q})

You would have **one single `engine` object** for all your code to connect to the same database.

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[14:18] hl[14:15,17:18] *}

Using `check_same_thread=False` allows FastAPI to use the same SQLite database in different threads. This is necessary as **one single request** could use **more than one thread** (for example in dependencies).

from typing import Annotated, Union

from fastapi import Depends, FastAPI

app = FastAPI()


async def common_parameters(
    q: Union[str, None] = None, skip: int = 0, limit: int = 100
):
    return {"q": q, "skip": skip, "limit": limit}


CommonsDep = Annotated[dict, Depends(common_parameters)]


@app.get("/items/")
async def read_items(commons: CommonsDep):
    return commons


@app.get("/users/")

from typing import Union

from fastapi import Depends, FastAPI

app = FastAPI()


async def common_parameters(
    q: Union[str, None] = None, skip: int = 0, limit: int = 100
):
    return {"q": q, "skip": skip, "limit": limit}


@app.get("/items/")
async def read_items(commons: dict = Depends(common_parameters)):
    return commons


@app.get("/users/")
async def read_users(commons: dict = Depends(common_parameters)):

app = FastAPI()


@app.get("/items/")
async def read_items(
    q: Annotated[
        str | None,
        Query(
            title="Query string",
            description="Query string for the items to search in the database that have a good match",
            min_length=3,
        ),
    ] = None,
):
    results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
    if q:
        results.update({"q": q})

from typing import Union

from pydantic.v1 import BaseModel


class Item(BaseModel):
    name: str
    description: Union[str, None] = None