* code would be responsible for populating a "real" {@code T} (which might still be the value
   * {@code null}!) before returning it to callers. Depending on how the code is structured, a
   * nullness analysis might not understand that the field has been populated. To avoid that problem
   * without having to add {@code @SuppressWarnings}, the code can call this method.
   *

   * code would be responsible for populating a "real" {@code T} (which might still be the value
   * {@code null}!) before returning it to callers. Depending on how the code is structured, a
   * nullness analysis might not understand that the field has been populated. To avoid that problem
   * without having to add {@code @SuppressWarnings}, the code can call this method.
   *

It is likely that `v1alpha2` will be removed in one of the future Kubernetes releases to be able to develop `v1`.

### Structured logging graduate to Beta

Structured logging reached its Beta milestone. Most log messages from kubelet and kube-scheduler have been converted. Users are encouraged to try out JSON output or parsing of the structured text format and provide feedback on possible solutions for the open issues, such as handling of multi-line strings in log values.

   * code would be responsible for populating a "real" {@code T} (which might still be the value
   * {@code null}!) before returning it to callers. Depending on how the code is structured, a
   * nullness analysis might not understand that the field has been populated. To avoid that problem
   * without having to add {@code @SuppressWarnings}, the code can call this method.
   *

///

## Use Cases { #use-cases }

You could use this to stream data from an **AI LLM** service, from **logs** or **telemetry**, or from other types of data that can be structured in **JSON** items.

/// tip

If you want to stream binary data, for example video or audio, check the advanced guide: [Stream Data](../advanced/stream-data.md).

///

# Tutorial - User Guide { #tutorial-user-guide }

This tutorial shows you how to use **FastAPI** with most of its features, step by step.

Each section gradually builds on the previous ones, but it's structured to separate topics, so that you can go directly to any specific one to solve your specific API needs.

It is also built to work as a future reference so you can come back and see exactly what you need.

## Run the code { #run-the-code }

# Stream Data { #stream-data }

If you want to stream data that can be structured as JSON, you should [Stream JSON Lines](../tutorial/stream-json-lines.md).

But if you want to **stream pure binary data** or strings, here's how you can do it.

/// info

Added in FastAPI 0.134.0.

///

## Use Cases { #use-cases }

You could use this if you want to stream pure strings, for example directly from the output of an **AI LLM** service.

```toml
[tool.fastapi]
entrypoint = "main:app"
```

That `entrypoint` will tell the `fastapi` command that it should import the app like:

```python
from main import app
```

If your code was structured like:

```
.
├── backend
│   ├── main.py
│   ├── __init__.py
```

Then you would set the `entrypoint` as:

```toml
[tool.fastapi]
entrypoint = "backend.main:app"
```

        That's a lot of work they are doing, but if more FastAPI users came to help others like them just a little bit more, it would be much less effort for them (and you and me 😅).

        By asking questions in a structured way (following this) it will be much easier to help you.

        And there's a high chance that you will find the solution along the way and you won't even have to submit it and wait for an answer. 😎

 * data configurations used by the Fess crawler system.
 *
 * <p>Data configurations define how the crawler should access and process
 * various data sources such as databases, CSV files, or other structured data.</p>
 */
public class DataConfigService extends FessAppService {

    /**
     * DBFlute behavior for data configuration operations.
     * Provides database access methods for DataConfig entities.
     */