```
.
├── Dockerfile
├── main.py
└── requirements.txt
```

Then you would just have to change the corresponding paths to copy the file inside the `Dockerfile`:

```{ .dockerfile .annotate hl_lines="10  13" }
FROM python:3.9

WORKDIR /code

COPY ./requirements.txt /code/requirements.txt

RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt

# (1)!
COPY ./main.py /code/

  owner_html_url: https://github.com/atpuxiner
- name: runhouse
  html_url: https://github.com/run-house/runhouse
  stars: 1043
  owner_login: run-house
  owner_html_url: https://github.com/run-house
- name: flock
  html_url: https://github.com/Onelevenvy/flock
  stars: 1010
  owner_login: Onelevenvy
  owner_html_url: https://github.com/Onelevenvy
- name: autollm
  html_url: https://github.com/viddexa/autollm

## Define `File` and `Form` parameters { #define-file-and-form-parameters }

Create file and form parameters the same way you would for `Body` or `Query`:

{* ../../docs_src/request_forms_and_files/tutorial001_an_py39.py hl[10:12] *}

The files and form fields will be uploaded as form data and you will receive the files and form fields.

And you can declare some of the files as `bytes` and some as `UploadFile`.

/// warning

Then set Cookies in it, and then return it:

{* ../../docs_src/response_cookies/tutorial001.py hl[10:12] *}

/// tip

Keep in mind that if you return a response directly instead of using the `Response` parameter, FastAPI will return it directly.

Create a response as described in [Return a Response Directly](response-directly.md){.internal-link target=_blank} and pass the headers as an additional parameter:

{* ../../docs_src/response_headers/tutorial001.py hl[10:12] *}

/// note | Technical Details

You could also use `from starlette.responses import Response` or `from starlette.responses import JSONResponse`.

If you check, the function is decorated with an `@asynccontextmanager`.

That converts the function into something called an "**async context manager**".

{* ../../docs_src/events/tutorial003.py hl[1,13] *}

A **context manager** in Python is something that you can use in a `with` statement, for example, `open()` can be used as a context manager:

```Python
with open("file.txt") as file:
    file.read()
```

First, import `BackgroundTasks` and define a parameter in your *path operation function* with a type declaration of `BackgroundTasks`:

{* ../../docs_src/background_tasks/tutorial001.py hl[1,13] *}

**FastAPI** will create the object of type `BackgroundTasks` for you and pass it as that parameter.

## Create a task function { #create-a-task-function }

Create a function to be run as the background task.

{* ../../docs_src/response_model/tutorial003_01_py310.py hl[7:10,13:14,18] *}

With this, we get tooling support, from editors and mypy as this code is correct in terms of types, but we also get the data filtering from FastAPI.

How does this work? Let's check that out. 🤓

```

### Include the `APIRouter`s for `users` and `items` { #include-the-apirouters-for-users-and-items }

Now, let's include the `router`s from the submodules `users` and `items`:

```Python hl_lines="10-11" title="app/main.py"
{!../../docs_src/bigger_applications/app/main.py!}
```

/// info

`users.router` contains the `APIRouter` inside of the file `app/routers/users.py`.

* Fix accepting valid types for response models, including Python types like `List[int]`. PR [#1017](https://github.com/tiangolo/fastapi/pull/1017) by [@patrickmckenna](https://github.com/patrickmckenna).
* Fix format in SQL tutorial. PR [#1015](https://github.com/tiangolo/fastapi/pull/1015) by [@vegarsti](https://github.com/vegarsti).

## 0.49.1