* It's now possible to use [Starlette's `StreamingResponse`](https://www.starlette.io/responses/#streamingresponse) with iterators, like [file-like](https://docs.python.org/3/glossary.html#term-file-like-object) objects (as those returned by `open()`).
    * It's now possible to use the low level utility `iterate_in_threadpool` from `starlette.concurrency` (for advanced scenarios).

The idea is to automate the acquisition and renewal of these certificates so that you can have **secure HTTPS, for free, forever**.

## HTTPS for Developers

Here's an example of how an HTTPS API could look like, step by step, paying attention mainly to the ideas important for developers.

### Domain Name

"_If you're looking to learn one **modern framework** for building REST APIs, check out **FastAPI** [...] It's fast, easy to use and easy to learn [...]_"

"_We've switched over to **FastAPI** for our **APIs** [...] I think you'll like it [...]_"

"_If you're looking to learn one **modern framework** for building REST APIs, check out **FastAPI** [...] It's fast, easy to use and easy to learn [...]_"

"_We've switched over to **FastAPI** for our **APIs** [...] I think you'll like it [...]_"

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

COPY ./app /code/app

CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "80"]

# If running behind a proxy like Nginx or Traefik add --proxy-headers
# CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "80", "--proxy-headers"]
```

</details>

## 컨테이너란

    When implementing the callback yourself, you could use something like <a href="https://www.python-httpx.org" class="external-link" target="_blank">HTTPX</a> or <a href="https://requests.readthedocs.io/" class="external-link" target="_blank">Requests</a>.

## Write the callback documentation code

This code won't be executed in your app, we only need it to *document* how that *external API* should look like.

# JSON Compatible Encoder

There are some cases where you might need to convert a data type (like a Pydantic model) to something compatible with JSON (like a `dict`, `list`, etc).

For example, if you need to store it in a database.

For that, **FastAPI** provides a `jsonable_encoder()` function.

## Using the `jsonable_encoder`

Let's imagine that you have a database `fake_db` that only receives JSON compatible data.

* This means that it will work well for large files like images, videos, large binaries, etc. without consuming all the memory.
* You can get metadata from the uploaded file.
* It has a <a href="https://docs.python.org/3/glossary.html#term-file-like-object" class="external-link" target="_blank">file-like</a> `async` interface.

#### Unwrapping a `dict` and extra keywords

And then adding the extra keyword argument `hashed_password=hashed_password`, like in:

```Python
UserInDB(**user_in.dict(), hashed_password=hashed_password)
```

...ends up being like:

```Python
UserInDB(
    username = user_dict["username"],
    password = user_dict["password"],
    email = user_dict["email"],

```console
$ pip install websockets

---> 100%
```

</div>

## WebSockets client

### In production

In your production system, you probably have a frontend created with a modern framework like React, Vue.js or Angular.

And to communicate using WebSockets with your backend you would probably use your frontend's utilities.