!!! tip
    これらの**コンテナ**やDockerそしてKubernetesに関する項目が、まだあまり意味をなしていなくても心配しないでください。
    <!-- NOTE: the current version of docker.md is outdated compared to English one. -->

    コンテナ・イメージ、Docker、Kubernetesなどについては、次の章で詳しく説明します: [コンテナ内のFastAPI - Docker](docker.md){.internal-link target=_blank}.

## 開始前の事前のステップ

アプリケーションを**開始する前**に、いくつかのステップを実行したい場合が多くあります。

* Each application that you have running on your computer has some process behind it, each running program, each window, etc. And there are normally many processes running **at the same time** while a computer is on.
* There can be **multiple processes** of the **same program** running at the same time.

### About `{**note.dict(), "id": last_record_id}`

`note` is a Pydantic `Note` object.

`note.dict()` returns a `dict` with its data, something like:

```Python
{
    "text": "Some note",
    "completed": False,
}
```

but it doesn't have the `id` field.

So we create a new `dict`, that contains the key-value pairs from `note.dict()` with:

```Python
{**note.dict()}
```

## 0.101.0

### Features

* ✨ Enable Pydantic's serialization mode for responses, add support for Pydantic's `computed_field`, better OpenAPI for response models, proper required attributes, better generated clients. PR [#10011](https://github.com/tiangolo/fastapi/pull/10011) by [@tiangolo](https://github.com/tiangolo).

### Refactors

server["Server auf http://127.0.0.1:8000/app"]

browser --> proxy
proxy --> server
```

!!! tip "Tipp"
    Die IP `0.0.0.0` wird üblicherweise verwendet, um anzudeuten, dass das Programm alle auf diesem Computer/Server verfügbaren IPs abhört.

Die Benutzeroberfläche der Dokumentation würde benötigen, dass das OpenAPI-Schema deklariert, dass sich dieser API-`server` unter `/api/v1` (hinter dem Proxy) befindet. Zum Beispiel:

### Number of Processes on the Official Docker Image

The **number of processes** on this image is **computed automatically** from the CPU **cores** available.

This means that it will try to **squeeze** as much **performance** from the CPU as possible.

Asynchronous code just means that the language 💬 has a way to tell the computer / program 🤖 that at some point in the code, it 🤖 will have to wait for *something else* to finish somewhere else. Let's say that *something else* is called "slow-file" 📝.

So, during that time, the computer can go and do some other work, while "slow-file" 📝 finishes.

name: Smokeshow

on:
  workflow_run:
    workflows: [Test]
    types: [completed]

permissions:
  statuses: write

jobs:
  smokeshow:
    if: ${{ github.event.workflow_run.conclusion == 'success' }}
    runs-on: ubuntu-latest

    steps:
      - name: Dump GitHub context
        env:
          GITHUB_CONTEXT: ${{ toJson(github) }}
        run: echo "$GITHUB_CONTEXT"
      - uses: actions/setup-python@v5
        with:

## Servermaschine und Serverprogramm

Bei den Benennungen gibt es ein kleines Detail, das Sie beachten sollten. 💡

Das Wort „**Server**“ bezieht sich häufig sowohl auf den entfernten-/Cloud-Computer (die physische oder virtuelle Maschine) als auch auf das Programm, das auf dieser Maschine ausgeführt wird (z. B. Uvicorn).

Si vous souhaitez un rappel de 2 minutes sur l'utilisation des types en Python (même si vous ne comptez pas utiliser FastAPI), jetez un oeil au tutoriel suivant: [Python Types](python-types.md){.internal-link target=_blank}.

Vous écrivez du python standard avec des annotations de types:

```Python
from datetime import date