```python
>>> import tensorflow as tf
>>> tf.add(1, 2).numpy()
3
>>> hello = tf.constant('Hello, TensorFlow!')
>>> hello.numpy()
b'Hello, TensorFlow!'
```

For more examples, see the
[TensorFlow Tutorials](https://www.tensorflow.org/tutorials/).

## Contribution guidelines

**If you want to contribute to TensorFlow, be sure to review the
[Contribution Guidelines](CONTRIBUTING.md). This project adheres to TensorFlow's

- **[Gradle Community Resources](https://community.gradle.org/resources/)**: Discover a range of resources, tutorials, and guides to support your Gradle journey, from foundational concepts to advanced practices.

---

### 💬 **Community Support & Resources**

# Learn { #learn }

Here are the introductory sections and the tutorials to learn **FastAPI**.

* Security - HTTPS
* Running on startup
* Restarts
* **Replication (the number of processes running)**
* Memory
* Previous steps before starting

Up to this point, with all the tutorials in the docs, you have probably been running a **server program**, for example, using the `fastapi` command, that runs Uvicorn, running a **single process**.

Now you can import and use the client code. It could look like this, notice that you get autocompletion for the methods:

<img src="/img/tutorial/generate-clients/image02.png">

You will also get autocompletion for the payload to send:

<img src="/img/tutorial/generate-clients/image03.png">

/// tip

Notice the autocompletion for `name` and `price`, that was defined in the FastAPI application, in the `Item` model.

    "article"
);
suggester.indexer().indexFromDocument(reader, 4, 50);
```

### Search Analytics

```java
// Track user queries for analytics
QueryLog userQuery = new QueryLog("machine learning tutorials", "user456");
suggester.indexer().indexFromQueryLog(userQuery);

// Get trending searches
PopularWordsResponse trending = suggester.popularWords()
    .setSize(10)
    .execute()
    .getResponse();
```

/// tip

You don't need to see the code in `./scripts/docs.py`, you just use it in the command line.

///

All the documentation is in Markdown format in the directory `./docs/en/`.

Many of the tutorials have blocks of code.

In most of the cases, these blocks of code are actual complete applications that can be run as is.

これでクライアントコードを import して利用できます。例えば次のようになり、メソッドに対して補完が効きます:

<img src="/img/tutorial/generate-clients/image02.png">

送信するペイロードにも補完が適用されます:

<img src="/img/tutorial/generate-clients/image03.png">

/// tip | 豆知識

FastAPI アプリの `Item` モデルで定義した `name` と `price` に補完が効いている点に注目してください。

///

送信データに対するインラインエラーも表示されます:

<img src="/img/tutorial/generate-clients/image04.png">

レスポンスオブジェクトにも補完があります:

<img src="/img/tutorial/generate-clients/image02.png">

보낼 페이로드에 대해서도 자동 완성이 제공됩니다:

<img src="/img/tutorial/generate-clients/image03.png">

/// tip | 팁

`name`과 `price`에 대한 자동 완성은 FastAPI 애플리케이션에서 `Item` 모델에 정의된 내용입니다.

///

전송하는 데이터에 대해 인라인 오류도 표시됩니다:

<img src="/img/tutorial/generate-clients/image04.png">

응답 객체도 자동 완성을 제공합니다:

现在你可以导入并使用客户端代码了。它可能是这样，并且你会发现方法有自动补全：

<img src="/img/tutorial/generate-clients/image02.png">

要发送的载荷也会有自动补全：

<img src="/img/tutorial/generate-clients/image03.png">

/// tip | 提示

请注意 `name` 和 `price` 的自动补全，它们是在 FastAPI 应用中的 `Item` 模型里定义的。

///

你发送的数据如果不符合要求，会在编辑器中显示内联错误：

<img src="/img/tutorial/generate-clients/image04.png">

响应对象同样有自动补全：

<img src="/img/tutorial/generate-clients/image05.png">