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

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.

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

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,

* 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.

        assertNotNull(builder);

        DefaultModelBuildingRequest request = new DefaultModelBuildingRequest();
        request.setProcessPlugins(true);
        request.setPomFile(getPom("complex"));
        request.setSystemProperties(sysProperties);

        ModelBuildingResult result = builder.build(request);
        assertNotNull(result);
        assertNotNull(result.getEffectiveModel());

# 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

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:

# Important: "tfrun foo | bar" is "( tfrun foo ) | bar", not "tfrun (foo | bar)".
# Therefore, "tfrun" commands cannot include pipes -- which is
# probably for the better. If a pipe is necessary for something, it is probably
# complex. Write a well-documented script under utilities/ to encapsulate the
# functionality instead.
tfrun() { "$@"; }

if [[ `uname -s | grep -P '^MSYS_NT'` ]]; then
  source ./ci/official/utilities/windows.sh