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",groupCheckedEnd:" elemnt(e)",badCreditCard:"Numărul de card introdus este incorect",badCVV:"Numărul CVV introdus este incorect",wrongFileDim:"Dimensiunea imaginii este incorectă,",imageTooTall:"imaginea nu poate fi mai înaltă decât",imageTooWide:"imaginea nu poate fi mai lată decât",imageTooSmall:"imaginea este prea mică",min:"min",max:"max",imageRatioNotAccepted:"Proportiile imaginii sunt incorecte",badBrazilTelephoneAnswer:"Numărul de telefon introdus este incorect.",badBrazilCEPAnswer:"CEP inc...

But in some cases you need to return a different status code than the default.

## Use case { #use-case }

For example, imagine that you want to return an HTTP status code of "OK" `200` by default.

But if the data didn't exist, you want to create it, and return an HTTP status code of "CREATED" `201`.

Porém em alguns casos você precisa retornar um código de status diferente do padrão.

## Caso de uso

Por exemplo, imagine que você deseja retornar um código de status HTTP de "OK" `200` por padrão.

Mas se o dado não existir, você quer criá-lo e retornar um código de status HTTP de "CREATED" `201`.

Let's see all this with an example.

Imagine you develop an app that allows creating invoices.

These invoices will have an `id`, `title` (optional), `customer`, and `total`.

The user of your API (an external developer) will create an invoice in your API with a POST request.

Then your API will (let's imagine):

* Send the invoice to some customer of the external developer.
* Collect the money.

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

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

## Using the `jsonable_encoder` { #using-the-jsonable-encoder }

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

For example, it doesn't receive `datetime` objects, as those are not compatible with JSON.

Being able to use asynchronous functions in your tests could be useful, for example, when you're querying your database asynchronously. Imagine you want to test sending requests to your FastAPI application and then verify that your backend successfully wrote the correct data in the database, while using an async database library.

Let's look at how we can make that work.

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.