# Request Files

You can define files to be uploaded by the client using `File`.

!!! info
    To receive uploaded files, first install <a href="https://github.com/Kludex/python-multipart" class="external-link" target="_blank">`python-multipart`</a>.

    E.g. `pip install python-multipart`.

    This is because uploaded files are sent as "form data".

## Import `File`

Import `File` and `UploadFile` from `fastapi`:

=== "Python 3.9+"

* **Cloud services** that handle this for you
    * The cloud service will probably **handle replication for you**. It would possibly let you define **a process to run**, or a **container image** to use, in any case, it would most probably be **a single Uvicorn process**, and the cloud service would be in charge of replicating it.

!!! tip

                ],
            ),
        ):
            return item

    # TODO: enable these tests once/if Form(embed=False) is supported
    # TODO: In that case, define if File() should support example/examples too
    # @app.post("/form_example")
    # def form_example(firstname: str = Form(example="John")):
    #     return firstname

    # @app.post("/form_examples")

#### "Schema"

Un "schema" es una definición o descripción de algo. No es el código que la implementa, sino solo una descripción abstracta.

#### "Schema" de la API

En este caso, <a href="https://github.com/OAI/OpenAPI-Specification" class="external-link" target="_blank">OpenAPI</a> es una especificación que dicta como se debe definir el schema de tu API.

```Python hl_lines="2  7"
{!../../../docs_src/custom_response/tutorial001b.py!}
```

!!! info
    The parameter `response_class` will also be used to define the "media type" of the response.

    In this case, the HTTP header `Content-Type` will be set to `application/json`.

    And it will be documented as such in OpenAPI.

!!! tip

    ```Python hl_lines="10"
    {!> ../../../docs_src/query_params_str_validations/tutorial003.py!}
    ```

## Add regular expressions

You can define a <abbr title="A regular expression, regex or regexp is a sequence of characters that define a search pattern for strings.">regular expression</abbr> `pattern` that the parameter should match:

=== "Python 3.10+"

    ```Python hl_lines="11"

```

</div>

If you use Hypercorn, it also has the option `--root-path`.

!!! note "Technical Details"
    The ASGI specification defines a `root_path` for this use case.

    And the `--root-path` command line option provides that `root_path`.

### Checking the current `root_path`

## 🛠️

↩️ 👥 ⚙️ 🇸🇲 🔗 &amp; 👥 🚫 🚚 🙆 😇 🔌-⚫️ 👷 ⏮️ **FastAPI**, 👥 💪 🛠️ 💽 <abbr title="Automatically updating the database to have any new column we define in our models.">🛠️</abbr> ⏮️ <a href="https://alembic.sqlalchemy.org" class="external-link" target="_blank">⚗</a> 🔗.

&amp; 📟 🔗 🇸🇲 &amp; 🇸🇲 🏷 🖖 🎏 🔬 📁, 👆 🔜 💪 🎭 🛠️ ⏮️ ⚗ 🍵 ✔️ ❎ FastAPI, Pydantic, ⚖️ 🕳 🙆.

    return burgers
```

### More technical details

You might have noticed that `await` can only be used inside of functions defined with `async def`.

But at the same time, functions defined with `async def` have to be "awaited". So, functions with `async def` can only be called inside of functions defined with `async def` too.

So, about the egg and the chicken, how do you call the first `async` function?

    * Como as estruturas de dados do Pydantic são apenas instâncias de classes que você define, a auto completação, _linting_, _mypy_ e a sua intuição devem funcionar corretamente com seus dados validados.
* Valida **estruturas complexas**:
    * Use modelos hierárquicos do Pydantic, `List` e `Dict` do `typing` do Python, etc.