real(complexT) floatT
imag(complexT) floatT
</pre>

<p>
The type of the arguments and return value correspond.
For <code>complex</code>, the two arguments must be of the same
floating-point type and the return type is the complex type
with the corresponding floating-point constituents:
<code>complex64</code> for <code>float32</code> arguments, and

Ela é bastante extensiva na especificação e cobre casos de uso muito complexos.

Ela inclui uma forma para autenticação usando “third party”/aplicações de terceiros.

Isso é o que todos os sistemas com “Login with Facebook, Google, Twitter, GitHub” usam por baixo.

### OAuth 1

Havia um OAuth 1, que é bem diferente do OAuth2, e mais complexo, isso incluía diretamente as especificações de como criptografar a comunicação.

real(complexT) floatT
imag(complexT) floatT
</pre>

<p>
The type of the arguments and return value correspond.
For <code>complex</code>, the two arguments must be of the same
<a href="#Numeric_types">floating-point type</a> and the return type is the
<a href="#Numeric_types">complex type</a>
with the corresponding floating-point constituents:

Guillaume Nodet <******@****.***> 1729859506 +0200

* Valida **estruturas complexas**:
    * Use modelos hierárquicos do Pydantic, `List` e `Dict` do `typing` do Python, etc.
    * Validadores permitem que esquemas de dados complexos sejam limpos e facilmente definidos, conferidos e documentados como JSON Schema.

It is quite an extensive specification and covers several complex use cases.

It includes ways to authenticate using a "third party".

That's what all the systems with "login with Facebook, Google, Twitter, GitHub" use underneath.

### OAuth 1

There was an OAuth 1, which is very different from OAuth2, and more complex, as it included direct specifications on how to encrypt the communication.

* Valide les **structures complexes**:
    * Utilise les modèles hiérarchique de Pydantic, le `typage` Python pour les `Lists`, `Dict`, etc.
    * Et les validateurs permettent aux schémas de données complexes d'être clairement et facilement définis, validés et documentés sous forme d'un schéma JSON.

class MergerTest {

    @Test
    void testMergerPreserveLocations() throws Exception {
        try (InputStream is = getClass().getResourceAsStream("/poms/factory/complex.xml")) {

            InputSource inputSource = new InputSource(null, "classpath:/poms/factory/complex.xml");
            Model model = new MavenStaxReader().read(is, true, inputSource);
            InputLocation propertiesLocation = model.getLocation("properties");

* Valideer **complexe structuren**:
    * Gebruik van hiërarchische Pydantic modellen, Python `typing`'s `List` en `Dict`, enz.
    * Met validators kunnen complexe dataschema's duidelijk en eenvoudig worden gedefinieerd, gecontroleerd en gedocumenteerd als JSON Schema.

    - [Value deprecation](#value-deprecation)

<!-- markdown-toc end -->

# Updating charts and values.yaml

## Acceptable Pull Requests

Helm charts `values.yaml` represent a complex user facing API that tends to grow uncontrollably over time
due to design choices in Helm.
The underlying Kubernetes resources we configure have 1000s of fields; given enough users and bespoke use cases,