## HTTPS para Desenvolvedores

Aqui está um exemplo de como uma API HTTPS poderia ser estruturada, passo a passo, com foco principal nas ideias relevantes para desenvolvedores.

### Nome do domínio

A etapa inicial provavelmente seria **adquirir** algum **nome de domínio**. Então, você iria configurá-lo em um servidor DNS (possivelmente no mesmo provedor em nuvem).

In this example, we didn't declare any Pydantic model. In fact, the request body is not even <abbr title="converted from some plain format, like bytes, into Python objects">parsed</abbr> as JSON, it is read directly as `bytes`, and the function `magic_data_reader()` would be in charge of parsing it in some way.

Nevertheless, we can declare the expected schema for the request body.

Let's start with an example **use case** and then see how to solve it with this.

Let's imagine that you have some **machine learning models** that you want to use to handle requests. 🤖

The same models are shared among requests, so, it's not one model per request, or one per user or something similar.

Let's imagine that loading the model can **take quite some time**, because it has to read a lot of **data from disk**. So you don't want to do it for every request.

### Load Balancer { #load-balancer }

When using containers, you would normally have some component **listening on the main port**. It could possibly be another container that is also a **TLS Termination Proxy** to handle **HTTPS** or some similar tool.

                    try {
                        if ((index + j) % 3 == 0) {
                            // Some failures
                            breaker.call(() -> {
                                throw new RuntimeException("Test");
                            });
                        } else {
                            // Some successes
                            breaker.call(() -> "success");

///

It will:

* Return that status code in the response.
* Document it as such in the OpenAPI schema (and so, in the user interfaces):

<img src="/img/tutorial/response-status-code/image01.png">

/// note

Some response codes (see the next section) indicate that the response does not have a body.

FastAPI knows this, and will produce OpenAPI docs that state there is no response body.

///

     * Since it's an interface with only static final fields, there is no complex logic to test.
     */
    @Test
    void testConstants() {
        // A simple assertion to verify that some of the constants have the expected values.
        // This confirms that the class is on the classpath and its fields are accessible.

# limitations under the License.
# ==============================================================================
#
# Changes the behavior in pycpp.sh from "run all tests" to "verify that all
# tests can compile." Used in some CI jobs (macOS and Linux Arm64) where test
# execution is too expensive.
TFCI_PYCPP_SWAP_TO_BUILD_ENABLE=1

   * -XX:+ExplicitGCInvokesConcurrent} is used.
   *
   * <p>Whenever possible, it is preferable to test directly for some observable change resulting
   * from GC, as with {@link #awaitClear}. Because there are no guarantees for the order of GC
   * finalization processing, there may still be some unfinished work for the GC to do after this
   * method returns.
   *

Neste caso, o **FastAPI** perceberá que existe mais de um parâmetro de corpo na função (dois parâmetros que são modelos Pydantic).

Então, ele usará o nome dos parâmetros como chaves (nome dos campos) no corpo, e espera um corpo como:

```JSON
{
    "item": {
        "name": "Foo",
        "description": "The pretender",
        "price": 42.0,
        "tax": 3.2
    },