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

func new(Type) *Type

// The complex built-in function constructs a complex value from two
// floating-point values. The real and imaginary parts must be of the same
// size, either float32 or float64 (or assignable to them), and the return
// value will be the corresponding complex type (complex64 for float32,
// complex128 for float64).
func complex(r, i FloatType) ComplexType

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.

    String SELF_COMBINATION_MERGE = "merge";

    String SELF_COMBINATION_REMOVE = "remove";

    /**
     * In case of complex XML structures, combining can be done based on id.
     */
    String ID_COMBINATION_MODE_ATTRIBUTE = "combine.id";

    /**
     * In case of complex XML structures, combining can be done based on keys.
     * This is a comma separated list of attribute names.
     */

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");

    - [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,

const Σ = 1 - 0.707i       //            (untyped complex constant)
const Δ = Σ + 2.0e-4       //            (untyped complex constant)
const Φ = iota*1i - 1/1i   //            (untyped complex constant)
</pre>

<p>
Applying the built-in function <code>complex</code> to untyped
integer, rune, or floating-point constants yields
an untyped complex constant.
</p>

<pre>

* Validate **complex structures**:
    * Use of hierarchical Pydantic models, Python `typing`’s `List` and `Dict`, etc.
    * And validators allow complex data schemas to be clearly and easily defined, checked and documented as JSON Schema.

- **Flexibility and Control:**
Java serialization offers limited control over the serialization process, such as excluding certain fields, customizing naming conventions, and handling complex data structures more gracefully.

- **Security:**
Java serialization poses security risks, especially related to deserialization vulnerabilities.

- **Version Compatibility:**

# Extra Data Types

Up to now, you have been using common data types, like:

* `int`
* `float`
* `str`
* `bool`

But you can also use more complex data types.

And you will still have the same features as seen up to now:

* Great editor support.
* Data conversion from incoming requests.
* Data conversion for response data.
* Data validation.
* Automatic annotation and documentation.

## Other data types