current_user: Annotated[User, Depends(get_current_user)],
):
    if current_user.disabled:
        raise HTTPException(status_code=400, detail="Inactive user")
    return current_user


@app.post("/token")
async def login_for_access_token(
    form_data: Annotated[OAuth2PasswordRequestForm, Depends()],
) -> Token:
    user = authenticate_user(fake_users_db, form_data.username, form_data.password)
    if not user:

# limitations under the License.
# ==============================================================================


# This Workflow updates tensorflow/tools/toolchains/remote_config/configs.bzl
# to reference the most recent versions of the SIG Build Docker images.
name: Update RBE Configs
on:
  workflow_dispatch:

permissions:
  contents: read

jobs:
  rbe:
    name: Update RBE Configs
    runs-on: ubuntu-latest

For example, you could identify a "car" or a "blog post".

Then you could add permissions about that entity, like "drive" (for the car) or "edit" (for the blog).

And then, you could give that JWT token to a user (or bot), and they could use it to perform those actions (drive the car, or edit the blog post) without even needing to have an account, just with the JWT token your API generated for that.

It brings the same **developer experience** of building apps with FastAPI to **deploying** them to the cloud. 🎉

It will also take care of most of the things you would need when deploying an app, like:

* HTTPS
* Replication, with autoscaling based on requests
* etc.

A central part of the Gradle architecture is the "build state model", which holds the state for each piece and coordinates state transitions and other mutations. 
Most source code in Gradle is arranged by which part(s) of the build state model it acts on.
This affects the lifecycle of the code and the set of services available for dependency injection.

* Додайте його як "middleware" у Ваш додаток **FastAPI**.


Також можна вказати, чи дозволяє Ваш бекенд:

* Облікові дані (заголовки авторизації, сookies, тощо).
* Конкретні HTTP-методи (`POST`, `PUT`) або всі за допомогою `"*"`
* Конкретні HTTP-заголовки або всі за допомогою `"*"`.


{* ../../docs_src/cors/tutorial001.py hl[2,6:11,13:19] *}

to be replicated will eventually be synced to the target cluster as the scanner schedules them. This may be slower depending on the load on the cluster, latency and size of the namespace.

In the rare event that target DR site is entirely lost and previously replicated objects to the DR cluster need to be re-replicated, `mc replicate resync start alias/bucket --remote-bucket <arn>` can be used to initiate a reset. This would initiate a re-sync between the two clusters by walking the bucket...

# 응답 모델

어떤 *경로 작동*이든 매개변수 `response_model`를 사용하여 응답을 위한 모델을 선언할 수 있습니다:

* `@app.get()`
* `@app.post()`
* `@app.put()`
* `@app.delete()`
* 기타.

{* ../../docs_src/response_model/tutorial001.py hl[17] *}

/// note | 참고

`response_model`은 "데코레이터" 메소드(`get`, `post`, 등)의 매개변수입니다. 모든 매개변수들과 본문(body)처럼 *경로 작동 함수*가 아닙니다.

///

Pydantic 모델 어트리뷰트를 선언한 것과 동일한 타입을 수신하므로 Pydantic 모델이 될 수 있지만, `List[Item]`과 같이 Pydantic 모델들의 `list`일 수도 있습니다.

        * So, the user will have to log in again at some point later.
        * And if the token is stolen, the risk is less. It is not like a permanent key that will work forever (in most of the cases).
* The frontend stores that token temporarily somewhere.
* The user clicks in the frontend to go to another section of the frontend web app.
* The frontend needs to fetch some more data from the API.

You could also use `from starlette.requests import Request` and `from starlette.responses import JSONResponse`.

**FastAPI** provides the same `starlette.responses` as `fastapi.responses` just as a convenience for you, the developer. But most of the available responses come directly from Starlette. The same with `Request`.

///

## Override the default exception handlers { #override-the-default-exception-handlers }