/// tip

**GraphQL** solves some very specific use cases.

It has **advantages** and **disadvantages** when compared to common **web APIs**.

Make sure you evaluate if the **benefits** for your use case compensate the **drawbacks**. 🤓

///

## GraphQL Libraries

Here are some of the **GraphQL** libraries that have **ASGI** support. You could use them with **FastAPI**:

///

/// info

In this example we use invented custom headers `X-Key` and `X-Token`.

But in real cases, when implementing security, you would get more benefits from using the integrated [Security utilities (the next chapter)](../security/index.md){.internal-link target=_blank}.

///

## Dependencies errors and return values

Again, just with that same Python type declaration, **FastAPI** gives you automatic, interactive documentation (integrating Swagger UI).

Notice that the path parameter is declared to be an integer.

///

## Standards-based benefits, alternative documentation

</pre>
```

</div>

It is **HIGHLY encouraged** that you write or copy the code, edit it and run it locally.

Using it in your editor is what really shows you the benefits of FastAPI, seeing how little code you have to write, all the type checks, autocompletion, etc.

---

## Install FastAPI

The first step is to install FastAPI.

It means that **FastAPI** was specifically tested with the editors used by 80% of the Python developers. And as most of the other editors tend to work similarly, all its benefits should work for virtually all editors.

That way I could find the best ways to reduce code duplication as much as possible, to have completion everywhere, type and error checks, etc.

  }
}
```

After generating the new client, you would now have **clean method names**, with all the **autocompletion**, **inline errors**, etc:

<img src="/img/tutorial/generate-clients/image08.png">

## Benefits

When using the automatically generated clients you would get **autocompletion** for:

* Methods.
* Request payloads in the body, query parameters, etc.
* Response payloads.

To declare a **request** body, you use <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> models with all their power and benefits.

/// info

To send data, you should use one of: `POST` (the more common), `PUT`, `DELETE` or `PATCH`.

///

## Recap

With **FastAPI** you have the maximum flexibility provided by Pydantic models, while keeping your code simple, short and elegant.

But with all the benefits:

* Editor support (completion everywhere!)
* Data conversion (a.k.a. parsing / serialization)
* Data validation
* Schema documentation

   * Builder#build} is called, the builder is likely to perform better than an unsized {@link
   * #builder()} would have.
   *
   * <p>It is not specified if any performance benefits apply if {@code expectedSize} is close to,
   * but not exactly, the number of entries added to the builder.
   *
   * @since 23.1
   */
  public static <K, V> Builder<K, V> builderWithExpectedSize(int expectedSize) {

### Concurrency + Parallelism: Web + Machine Learning

With **FastAPI** you can take advantage of concurrency that is very common for web development (the same main attraction of NodeJS).

But you can also exploit the benefits of parallelism and multiprocessing (having multiple processes running in parallel) for **CPU bound** workloads like those in Machine Learning systems.