* «framework»: «framework» (do not translate to «cadre»)
* «performance»: «performance»

* «type hints»: «annotations de type»
* «type annotations»: «annotations de type»

* «autocomplete»: «autocomplétion»
* «autocompletion»: «autocomplétion»

* «the request» (what the client sends to the server): «la requête»
* «the response» (what the server sends back to the client): «la réponse»

* «the request body»: «le corps de la requête»

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.

///

* «/// tip»: «/// tip | Dica»
* «/// warning»: «/// warning | Atenção»
* «(you should)»: «(você deveria)»
* async context manager: gerenciador de contexto assíncrono
* autocomplete: autocompletar
* autocompletion: preenchimento automático
* bug: bug
* context manager: gerenciador de contexto
* cross domain: cross domain (do not translate to "domínio cruzado")
* cross origin: cross origin (do not translate to "origem cruzada")

    typer.secho(f"Successfully initialized: {new_path}", color=typer.colors.GREEN)
    update_languages()


@app.command()
def build_lang(
    lang: str = typer.Argument(
        ..., callback=lang_callback, autocompletion=complete_existing_lang
    ),
) -> None:
    """
    Build the docs for a language.
    """
    lang_path: Path = Path("docs") / lang
    if not lang_path.is_dir():

* performance: rendimiento
* program (verb): programar
* code (verb): programar
* type hints: anotaciones de tipos
* type annotations: anotaciones de tipos
* autocomplete: autocompletado
* completion (in the context of autocompletion): autocompletado
* feature: funcionalidad
* sponsor: sponsor
* host (in a podcast): host
* request (as in HTTP request): request
* response (as in HTTP response): response

///

## Recap { #recap }

With **FastAPI**, by using short, intuitive and standard Python type declarations, you get:

* Editor support: error checks, autocompletion, etc.
* Data "<abbr title="converting the string that comes from an HTTP request into Python data">parsing</abbr>"
* Data validation
* API annotation and automatic documentation

But then you have to call "that method that converts the first letter to upper case".

Was it `upper`? Was it `uppercase`? `first_uppercase`? `capitalize`?

Then, you try with the old programmer's friend, editor autocompletion.

You type the first parameter of the function, `first_name`, then a dot (`.`) and then hit `Ctrl+Space` to trigger the completion.

But, sadly, you get nothing useful:

<img src="/img/python-types/image01.png">

</div>

## Configure Your Editor { #configure-your-editor }

You would probably use an editor, make sure you configure it to use the same virtual environment you created (it will probably autodetect it) so that you can get autocompletion and inline errors.

For example:

* <a href="https://code.visualstudio.com/docs/python/environments#_select-and-activate-an-environment" class="external-link" target="_blank">VS Code</a>

* **Fewer bugs**: Reduce about 40% of human (developer) induced errors. *
* **Intuitive**: Great editor support. <abbr title="also known as auto-complete, autocompletion, IntelliSense">Completion</abbr> everywhere. Less time debugging.
* **Easy**: Designed to be easy to use and learn. Less time reading docs.

* **Fewer bugs**: Reduce about 40% of human (developer) induced errors. *
* **Intuitive**: Great editor support. <abbr title="also known as auto-complete, autocompletion, IntelliSense">Completion</abbr> everywhere. Less time debugging.
* **Easy**: Designed to be easy to use and learn. Less time reading docs.