Then APIStar stopped to exist as a server and Starlette was created, and was a new better foundation for such a system. That was the final inspiration to build **FastAPI**.

    I consider **FastAPI** a "spiritual successor" to APIStar, while improving and increasing the features, typing system, and other parts, based on the learnings from all these previous tools.

## Used by **FastAPI**

# Get Current User

In the previous chapter the security system (which is based on the dependency injection system) was giving the *path operation function* a `token` as a `str`:

=== "Python 3.9+"

    ```Python hl_lines="12"
    {!> ../../../docs_src/security/tutorial001_an_py39.py!}
    ```

=== "Python 3.8+"

    ```Python hl_lines="11"
    {!> ../../../docs_src/security/tutorial001_an.py!}
    ```

=== "Python 3.8+ non-Annotated"

def test_read_system_status():
    access_token = get_access_token()
    response = client.get(
        "/status/", headers={"Authorization": f"Bearer {access_token}"}
    )
    assert response.status_code == 200, response.text
    assert response.json() == {"status": "ok"}


def test_read_system_status_no_token():
    response = client.get("/status/")

* The **file** that can be **executed** by the operating system, for example: `python`, `python.exe` or `uvicorn`.
* A particular program while it is **running** on the operating system, using the CPU, and storing things on memory. This is also called a **process**.

### What is a Process

The word **process** is normally used in a more specific way, only referring to the thing that is running in the operating system (like in the last point above):

## Einfach und leistungsstark

Obwohl das hierarchische Dependency Injection System sehr einfach zu definieren und zu verwenden ist, ist es dennoch sehr mächtig.

Sie können Abhängigkeiten definieren, die selbst wiederum Abhängigkeiten definieren können.

        return {"fresh_value": fresh_value}
    ```

## Zusammenfassung

Abgesehen von all den ausgefallenen Wörtern, die hier verwendet werden, ist das **Dependency Injection**-System recht simpel.

Einfach Funktionen, die genauso aussehen wie *Pfadoperation-Funktionen*.

Dennoch ist es sehr mächtig und ermöglicht Ihnen die Deklaration beliebig tief verschachtelter Abhängigkeits-„Graphen“ (Bäume).

    "Operating System :: OS Independent",
    "Programming Language :: Python :: 3",
    "Programming Language :: Python",
    "Topic :: Internet",
    "Topic :: Software Development :: Libraries :: Application Frameworks",
    "Topic :: Software Development :: Libraries :: Python Modules",
    "Topic :: Software Development :: Libraries",
    "Topic :: Software Development",
    "Typing :: Typed",

@needs_py39
def test_read_system_status(client: TestClient):
    access_token = get_access_token(client=client)
    response = client.get(
        "/status/", headers={"Authorization": f"Bearer {access_token}"}
    )
    assert response.status_code == 200, response.text
    assert response.json() == {"status": "ok"}


@needs_py39
def test_read_system_status_no_token(client: TestClient):

That way, you can create a token with an expiration of, let's say, 1 week. And then when the user comes back the next day with the token, you know that user is still logged in to your system.

Dieser ganze Erneuerungsprozess, während die Anwendung weiterhin bereitgestellt wird, ist einer der Hauptgründe, warum Sie ein **separates System zur Verarbeitung von HTTPS** mit einem TLS-Terminierungsproxy haben möchten, anstatt einfach die TLS-Zertifikate direkt mit dem Anwendungsserver zu verwenden (z. B. Uvicorn).

## Zusammenfassung