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.

In fact, those blocks of code are not written inside the Markdown, they are Python files in the `./docs_src/` directory.

And those Python files are included/injected in the documentation when generating the site.

### Docs for tests

If you added the return type annotation, tools and editors would complain with a (correct) error telling you that your function is returning a type (e.g. a dict) that is different from what you declared (e.g. a Pydantic model).

In those cases, you can use the *path operation decorator* parameter `response_model` instead of the return type.

You can use the `response_model` parameter in any of the *path operations*:

* `@app.get()`
* `@app.post()`

Just keep in mind that when you read "server" in general, it could refer to one of those two things.

When referring to the remote machine, it's common to call it **server**, but also **machine**, **VM** (virtual machine), **node**. Those all refer to some type of remote machine, normally running Linux, where you run programs.

## Install the Server Program

    `Body` also returns objects of a subclass of `FieldInfo` directly. And there are others you will see later that are subclasses of the `Body` class.

    Remember that when you import `Query`, `Path`, and others from `fastapi`, those are actually functions that return special classes.

!!! tip

But in most cases, you will want to perform these steps only **once**.

So, you will want to have a **single process** to perform those **previous steps**, before starting the application.

### API Docs

If you go to the API docs, you will see that it has the **schemas** for the data to be sent in requests and received in responses:

<img src="/img/tutorial/generate-clients/image01.png">

You can see those schemas because they were declared with the models in the app.

That information is available in the app's **OpenAPI schema**, and then shown in the API docs (by Swagger UI).

So, even with the code above that doesn't use Pydantic explicitly, FastAPI is using Pydantic to convert those standard dataclasses to Pydantic's own flavor of dataclasses.

And of course, it supports the same:

* data validation
* data serialization
* data documentation, etc.

## Learn More

You can learn more about **GraphQL** in the <a href="https://graphql.org/" class="external-link" target="_blank">official GraphQL documentation</a>.

📥 👥 🔜 👀 🖼 ⚙️ **<a href="https://www.couchbase.com/" class="external-link" target="_blank">🗄</a>**, <abbr title="Document here refers to a JSON object (a dict), with keys and values, and those values can also be other JSON objects, arrays (lists), numbers, strings, booleans, etc.">📄</abbr> 🧢 ☁ 💽.

👆 💪 🛠️ ⚫️ 🙆 🎏 ☁ 💽 💖:

* **✳**
* **👸**
* **✳**
* **🇸🇲**
* **✳**, ♒️.

!!! tip

These types that have internal types are called "**generic**" types. And it's possible to declare them, even with their internal types.

To declare those types and the internal types, you can use the standard Python module `typing`. It exists specifically to support these type hints.

#### Newer versions of Python