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.

Articles:
  English:
  - author: Kurtis Pykes - NVIDIA
    link: https://developer.nvidia.com/blog/building-a-machine-learning-microservice-with-fastapi/
    title: Building a Machine Learning Microservice with FastAPI
  - author: Ravgeet Dhillon - Twilio
    link: https://www.twilio.com/en-us/blog/booking-appointments-twilio-notion-fastapi
    title: Booking Appointments with Twilio, Notion, and FastAPI
  - author: Abhinav Tripathi - Microsoft Blogs

Sie könnten beispielsweise ein „Auto“ oder einen „Blog-Beitrag“ identifizieren.

Anschließend könnten Sie Berechtigungen für diese Entität hinzufügen, etwa „Fahren“ (für das Auto) oder „Bearbeiten“ (für den Blog).

from fastapi import BackgroundTasks, Depends, FastAPI

app = FastAPI()


def write_log(message: str):
    with open("log.txt", mode="a") as log:
        log.write(message)


def get_query(background_tasks: BackgroundTasks, q: str | None = None):
    if q:
        message = f"found query: {q}\n"
        background_tasks.add_task(write_log, message)
    return q


@app.post("/send-notification/{email}")

client = TestClient(app)


def test():
    log = Path("log.txt")
    if log.is_file():
        os.remove(log)  # pragma: no cover
    response = client.post("/send-notification/******@****.***?q=some-query")
    assert response.status_code == 200, response.text
    assert response.json() == {"message": "Message sent"}
    with open("./log.txt") as f:

    client = TestClient(app)
    log = Path("log.txt")
    if log.is_file():
        os.remove(log)  # pragma: no cover
    response = client.post("/send-notification/******@****.***?q=some-query")
    assert response.status_code == 200, response.text
    assert response.json() == {"message": "Message sent"}
    with open("./log.txt") as f:

.idea
.ipynb_checkpoints
.mypy_cache
.vscode
__pycache__
.pytest_cache
htmlcov
dist
site
.coverage
coverage.xml
.netlify
test.db
log.txt
Pipfile.lock
env3.*
env
docs_build
site_build
venv
docs.zip
archive.zip

# vim temporary files
*~
.*.sw?
.cache

# macOS

            operation.operationId = newOperationId
          }
        }
      }
    }

    await fs.promises.writeFile(
      filePath,
      JSON.stringify(openapiContent, null, 2),
    )
    console.log('File successfully modified')
  } catch (err) {
    console.error('Error:', err)
  }
}

const filePath = './openapi.json'

**FastAPI** は、それぞれの場合の処理​​方法と同じオブジェクトの再利用方法を知っているため、すべてのバックグラウンドタスクがマージされ、バックグラウンドで後で実行されます。

```Python hl_lines="13  15  22  25"
{!../../../docs_src/background_tasks/tutorial002.py!}
```

この例では、レスポンスが送信された *後* にメッセージが `log.txt` ファイルに書き込まれます。

リクエストにクエリがあった場合、バックグラウンドタスクでログに書き込まれます。

そして、*path operations 関数* で生成された別のバックグラウンドタスクは、`email` パスパラメータを使用してメッセージを書き込みます。

## 技術的な詳細

Do you want to just have a `str`? Or just a `dict`? Or a database class model instance directly? It all works the same way.

You actually don't have users that log in to your application but robots, bots, or other systems, that have just an access token? Again, it all works the same.