<div class="termy">

    ```console
    $ uvicorn main:app --host 0.0.0.0 --port 80

    <span style="color: green;">INFO</span>:     Uvicorn running on http://0.0.0.0:80 (Press CTRL+C to quit)
    ```

    </div>

=== "Hypercorn"

    <div class="termy">

    ```console
    $ hypercorn main:app --bind 0.0.0.0:80

    Running on 0.0.0.0:8080 over http (CTRL + C to quit)
    ```

    </div>

    // em space
    assertThat(parse("http://h/\u2003").encodedPath).isEqualTo("/%E2%80%83")
    // three-per-em space
    assertThat(parse("http://h/\u2004").encodedPath).isEqualTo("/%E2%80%84")
    // four-per-em space
    assertThat(parse("http://h/\u2005").encodedPath).isEqualTo("/%E2%80%85")
    // six-per-em space
    assertThat(parse("http://h/\u2006").encodedPath).isEqualTo("/%E2%80%86")
    // figure space

                        <mxPoint x="-4.941176470588289" y="-139.99999999999955" as="targetPoint"/>
                        <Array as="points">
                            <mxPoint x="-5" y="-80"/>
                            <mxPoint x="-5" y="-80"/>
                        </Array>
                    </mxGeometry>
                </mxCell>

In the output, you can see that it shows the **PID** (process ID) of each process (it's just a number).

You can see that:

* The Gunicorn **process manager** starts with PID `19499` (in your case it will be a different number).
* Then it starts `Listening at: http://0.0.0.0:80`.

Laut der letzten <a href="https://www.jetbrains.com/research/python-developers-survey-2018/#development-tools" class="external-link" target="_blank">Python-Entwickler-Umfrage</a>, deckt das etwa 80 % der Benutzer ab.

Das bedeutet, dass **FastAPI** speziell mit den Editoren getestet wurde, die von 80 % der Python-Entwickler verwendet werden. Und da die meisten anderen Editoren in der Regel ähnlich funktionieren, sollten alle diese Vorteile für praktisch alle Editoren funktionieren.

                        <mxPoint x="-4.941176470588289" y="-139.99999999999955" as="targetPoint"/>
                        <Array as="points">
                            <mxPoint x="-5" y="-80"/>
                            <mxPoint x="-5" y="-80"/>
                        </Array>
                    </mxGeometry>
                </mxCell>

Dans ce cas, votre `Dockerfile` pourrait ressembler à ceci :

```Dockerfile
FROM python:3.7

RUN pip install fastapi uvicorn

EXPOSE 80

COPY ./app /app

CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "80"]
```

## Créer le code **FastAPI**.

* Créer un répertoire `app` et y entrer.
* Créez un fichier `main.py` avec :

```Python
from typing import Optional

      - image: docker.io/istio/proxy_debug:unittest
        name: istio-proxy
        resources: {}
      - image: fake.docker.io/google-samples/hello-go-gke:1.0
        name: hello
        ports:
        - containerPort: 80
          name: http
        resources: {}
      initContainers:
      - image: docker.io/istio/proxy_init:unittest-test
        name: istio-init
        resources: {}
status: {}

* `--bind`: 구니콘이 관찰할 IP와 포트를 의미합니다. 콜론 (`:`)을 사용하여 IP와 포트를 구분합니다.
    * 만약에 `--bind 0.0.0.0:80` (구니콘 옵션) 대신 유비콘을 직접 실행하고 싶다면 `--host 0.0.0.0`과 `--port 80`을 사용해야 합니다.

출력에서 각 프로세스에 대한 **PID** (process ID)를 확인할 수 있습니다. (단순한 숫자입니다)

출력 내용:

* 구니콘 **프로세스 매니저**는 PID `19499`로 실행됩니다. (직접 실행할 경우 숫자가 다를 수 있습니다)
* 다음으로 `Listening at: http://0.0.0.0:80`을 시작합니다.
* 그런 다음 사용해야할 `uvicorn.workers.UvicornWorker`의 워커클래스를 탐지합니다.

## Источник

Источник - это совокупность протокола (`http`, `https`), домена (`myapp.com`, `localhost`, `localhost.tiangolo.com`) и порта (`80`, `443`, `8080`).

Поэтому это три разных источника:

* `http://localhost`
* `https://localhost`
* `http://localhost:8080`