"🔑 👨‍💼" 🙆 👈 🐍 🎚 👈 👆 💪 ⚙️ `with` 📄.

🖼, <a href="https://docs.python.org/3/tutorial/inputoutput.html#reading-and-writing-files" class="external-link" target="_blank">👆 💪 ⚙️ `with` ✍ 📁</a>:

```Python
with open("./somefile.txt") as f:
    contents = f.read()
    print(contents)
```

🔘, `open("./somefile.txt")` ✍ 🎚 👈 🤙 "🔑 👨‍💼".

🕐❔ `with` 🍫 🏁, ⚫️ ⚒ 💭 🔐 📁, 🚥 📤 ⚠.

## コンテキストマネージャ

### 「コンテキストマネージャ」とは

「コンテキストマネージャ」とは、`with`文の中で使用できるPythonオブジェクトのことです。

例えば、<a href="https://docs.python.org/3/tutorial/inputoutput.html#reading-and-writing-files" class="external-link" target="_blank">ファイルを読み込むには`with`を使用することができます</a>:

```Python
with open("./somefile.txt") as f:
    contents = f.read()
    print(contents)
```

### 什么是“上下文管理器”

“上下文管理器”是您可以在`with`语句中使用的任何Python对象。

例如，<a href="https://docs.python.org/zh-cn/3/tutorial/inputoutput.html#reading-and-writing-files" class="external-link" target="_blank">您可以使用`with`读取文件</a>：

```Python
with open("./somefile.txt") as f:
    contents = f.read()
    print(contents)
```

在底层，`open("./somefile.txt")`创建了一个被称为“上下文管理器”的对象。

当`with`块结束时，它会确保关闭文件，即使发生了异常也是如此。

if [[ ${RESULT} != *"Server side encryption specified with SSE-C with compression not allowed"* ]]; then
	echo "BUG: Loading an SSE-C object to site with compression should fail. Succeeded though."
	exit_1
fi

# Add replication site
./mc admin replicate add minio1 minio2 --insecure
# sleep for replication to complete

That way, in many cases you can learn about containers and Docker and re-use that knowledge with many different tools and components.

So, you would run **multiple containers** with different things, like a database, a Python application, a web server with a React frontend application, and connect them together via their internal network.

[19499] [INFO] Listening at: http://0.0.0.0:80 (19499)
[19499] [INFO] Using worker: uvicorn.workers.UvicornWorker
[19511] [INFO] Booting worker with pid: 19511
[19513] [INFO] Booting worker with pid: 19513
[19514] [INFO] Booting worker with pid: 19514
[19515] [INFO] Booting worker with pid: 19515
[19511] [INFO] Started server process [19511]
[19511] [INFO] Waiting for application startup.
[19511] [INFO] Application startup complete.

```Python
{
    "name": "Barz",
    "price": 3,
    "description": None,
}
```

because it doesn't include the already stored attribute `"tax": 20.2`, the input model would take the default value of `"tax": 10.5`.

And the data would be saved with that "new" `tax` of `10.5`.

## Partial updates with `PATCH`

        uses: actions/setup-java@v4
        with:
          distribution: temurin
          java-version: 11
      - uses: actions/download-artifact@v4
        with:
          name: build-receipt.properties
          path: incoming-distributions/build-receipt.properties
      - name: Setup Gradle
        uses: gradle/actions/setup-gradle@v3
        with:
          cache-read-only: ${{ github.ref != 'refs/heads/master' }}

## Dataclasses in Nested Data Structures

You can also combine `dataclasses` with other type annotations to make nested data structures.

In some cases, you might still have to use Pydantic's version of `dataclasses`. For example, if you have errors with the automatically generated API documentation.

In that case, you can simply swap the standard `dataclasses` with `pydantic.dataclasses`, which is a drop-in replacement:

## Additional servers

!!! warning
    This is a more advanced use case. Feel free to skip it.

By default, **FastAPI** will create a `server` in the OpenAPI schema with the URL for the `root_path`.

But you can also provide other alternative `servers`, for example if you want *the same* docs UI to interact with a staging and production environments.