from fastapi import FastAPI
from pydantic_settings import BaseSettings


class Settings(BaseSettings):
    app_name: str = "Awesome API"
    admin_email: str
    items_per_user: int = 50


settings = Settings()
app = FastAPI()


@app.get("/info")
async def info():
    return {
        "app_name": settings.app_name,
        "admin_email": settings.admin_email,
        "items_per_user": settings.items_per_user,

from typing import Union

from fastapi import FastAPI

app = FastAPI()


@app.get("/items/{item_id}")
async def read_user_item(
    item_id: str, needy: str, skip: int = 0, limit: Union[int, None] = None
):
    item = {"item_id": item_id, "needy": needy, "skip": skip, "limit": limit}

from fastapi import FastAPI
from pydantic import BaseModel, EmailStr

app = FastAPI()


class UserIn(BaseModel):
    username: str
    password: str
    email: EmailStr
    full_name: str | None = None


# Don't do this in production!
@app.post("/user/")
async def create_user(user: UserIn) -> UserIn:

## Example using Python API

### 1. Prerequisites

- Install MinIO Server from [here](https://min.io/docs/minio/linux/index.html#procedure).
- Familiarity with AWS S3 API.
- Familiarity with Python and installing dependencies.

### 2. Install boto3

Install `aws-sdk-python` from AWS SDK for Python official docs [here](https://aws.amazon.com/sdk-for-python/)

### 3. Example

from typing import Union

from fastapi import Cookie, FastAPI

app = FastAPI()


@app.get("/items/")
async def read_items(ads_id: Union[str, None] = Cookie(default=None)):

  // from suspension. It is represented in RFC3339 form and is in UTC.
  // +optional
  optional k8s.io.apimachinery.pkg.apis.meta.v1.Time startTime = 2;

  // Represents time when the job was completed. It is not guaranteed to
  // be set in happens-before order across separate operations.
  // It is represented in RFC3339 form and is in UTC.

from fastapi import FastAPI
from fastapi.responses import RedirectResponse

app = FastAPI()


@app.get("/teleport")
async def get_teleport() -> RedirectResponse:

from fastapi import FastAPI, Path
from typing_extensions import Annotated

app = FastAPI()


@app.get("/items/{item_id}")
async def read_items(
    q: str, item_id: Annotated[int, Path(title="The ID of the item to get")]
):
    results = {"item_id": item_id}
    if q:
        results.update({"q": q})

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Image(BaseModel):
    url: str
    name: str


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None
    tags: set[str] = set()
    image: Image | None = None


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item):

// a map (`tensorflow::eager::TensorTape`) from the wrapped tensor to the id of
// the op that produced it (or -1 if this tensor was watched using
// `GradientTape::Watch`.) The op_id is simply a unique index assigned to each
// op executed under the tape. A separate map (`tensorflow::eager::OpTape`)
// maintains the map from `op_id` to a `OpTapeEntry` which stores the `op_type`,