import org.jetbrains.kotlin.analysis.low.level.api.fir.resolve.extensions.llResolveExtensionTool
import org.jetbrains.kotlin.analysis.project.structure.KtModule
import org.jetbrains.kotlin.analysis.project.structure.allDirectDependencies
import org.jetbrains.kotlin.analysis.providers.KotlinDeclarationProvider
import org.jetbrains.kotlin.analysis.providers.KotlinPackageProvider

## Request and Response

MinIO will make a `POST` request with a JSON body to the given plugin URL. If the auth token parameter is set, it will be sent as an authorization header.

The JSON body structure can be seen from this sample:

<details><summary>Request Body Sample</summary>

```json
{
  "input": {
    "account": "minio",
    "groups": null,
    "action": "s3:ListBucket",
    "bucket": "test",

### Response

If the token is valid and access is approved, the plugin must return a `200` (OK) HTTP status code.

A `200 OK` Response should have `application/json` content-type and body with the following structure:

```json
{
    "user": <string>,
    "maxValiditySeconds": <integer>,
    "claims": <key-value-pairs>
}
```

-- multiple versions of the ingress can be used, to minimize upgrade risks

- the new chart uses the default namespace service account, and doesn't require
additional RBAC permissions.

- simplified label and chart structure.
- ability to run a pilot dedicated for the gateway, isolated from the main pilot. This is more robust, safer on upgrades
and allows a bit more flexibility.

import org.jetbrains.kotlin.analysis.api.symbols.KtSymbolProvider
import org.jetbrains.kotlin.analysis.api.symbols.KtSymbolProviderByJavaPsi
import org.jetbrains.kotlin.analysis.project.structure.KtModule

@OptIn(KtAnalysisApiInternals::class, KtAnalysisNonPublicApi::class)
@Suppress("LeakingThis")
class KtFe10AnalysisSession(
    val analysisContext: Fe10AnalysisContext,
    override val useSiteModule: KtModule,

**FastAPI** provides a convenience tool to structure your application while keeping all the flexibility.

!!! info
    If you come from Flask, this would be the equivalent of Flask's Blueprints.

## An example file structure

Let's say you have a file structure like this:

```
.
├── app
│   ├── __init__.py
│   ├── main.py
│   ├── dependencies.py

In this example we'll create a temporary database only for the tests.

## File structure

We create a new file at `sql_app/tests/test_sql_app.py`.

So the new file structure looks like:

``` hl_lines="9-11"
.
└── sql_app
    ├── __init__.py
    ├── crud.py
    ├── database.py
    ├── main.py
    ├── models.py

       <name>theme</name>
       <value>classic</value>
     </parameter>
   </parameters>
  </plugin>
</plugins>
+-----+

Unified source directory

 Unified source directory structure that is analogous to the repository
 itself. This way locations of intermediary artifacts of a build would be
 in a known location. This would also help with developer setup i.e. getting

# TensorFlow continuous integration

> **Warning** This folder is still under construction. It is part of an ongoing
> effort to improve the structure of CI and build related files within the
> TensorFlow repo. This warning will be removed when the contents of this
> directory are stable and appropriate documentation around its usage is in
> place.

Maintainer: TensorFlow DevInfra

- **core-configuration**: Allows the build structure and work, such as tasks, to be specified. This includes the project model, the DSL and so on.
- **core-execution**: Runs the work efficiently. This includes scheduling, execution, caching and so on.