```

In a given setup, there are `n` MinIO instances talking to `m` KES servers but only `1` central KMS. The most simple setup consists of `1` MinIO server or cluster talking to `1` KMS via `1` KES server.

The main difference between various MinIO-KMS deployments is the KMS implementation. The following table helps you select the right option for your use case:

The main tasks that you can do right now are:

* [Help others with questions in GitHub](#help-others-with-questions-in-github){.internal-link target=_blank} (see the section above).
* [Review Pull Requests](#review-pull-requests){.internal-link target=_blank} (see the section above).

Those two tasks are what **consume time the most**. That's the main work of maintaining FastAPI.

For a quick installation, docker-compose reference configs are also available on the [Keycloak GitHub](https://github.com/keycloak/keycloak-containers/tree/main/docker-compose-examples).

### Configure Keycloak Realm

- Go to Clients
  - Click on account
    - Settings
    - Change `Access Type` to `confidential`.
    - Save
  - Click on credentials tab

 *
 * <p>This class provides XML merging functionality for Maven's XML handling
 * and specifies the combination modes that control how XML elements are merged.</p>
 *
 * <p>The merger supports two main types of combinations:</p>
 * <ul>
 *   <li>Children combination: Controls how child elements are combined</li>
 *   <li>Self combination: Controls how the element itself is combined</li>
 * </ul>
 *

/**
 * Utility class for text normalization and processing.
 *
 * This class provides methods to normalize text by reading characters from a provided Reader
 * and processing them according to specific rules. The main functionality is encapsulated
 * within the nested {@link TextNormalizeContext} class.
 *
 * <p>The text normalization process includes:
 * <ul>

شما پایتون استاندارد را با استفاده از تایپ ها مینویسید:

```Python
from datetime import date

from pydantic import BaseModel

# Declare a variable as a str
# and get editor support inside the function
def main(user_id: str):
    return user_id


# A Pydantic model
class User(BaseModel):
    id: int
    name: str
    joined: date
```

که سپس میتوان به این شکل از آن استفاده کرد:

```Python

With **FastAPI** you can take advantage of concurrency that is very common for web development (the same main attraction of NodeJS).

But you can also exploit the benefits of parallelism and multiprocessing (having multiple processes running in parallel) for **CPU bound** workloads like those in Machine Learning systems.

{* ../../docs_src/python_types/tutorial004.py hl[2] *}

## Declaring types { #declaring-types }

You just saw the main place to declare type hints. As function parameters.

This is also the main place you would use them with **FastAPI**.

### Simple types { #simple-types }

You can declare all the standard Python types, not only `str`.

You can use, for example:

        new CyclicBarrier(
            6 // for the setter threads
                + 50 // for the listeners
                + 50 // for the blocking get threads,
                + 1); // for the main thread
    ExecutorService executor = newFixedThreadPool(barrier.getParties());
    AtomicReference<AbstractFuture<String>> currentFuture = Atomics.newReference();
    AtomicInteger numSuccessfulSetCalls = new AtomicInteger();

	verify_resiliency_healing "${FUNCNAME[0]}" "${WANT}"
}

function main() {
	if [ ! -f ./mc ]; then
		wget -q https://dl.minio.io/client/mc/release/linux-amd64/mc && chmod +x ./mc
	fi

	export MC_HOST_myminio=http://minioadmin:minioadmin@localhost:9000

	cleanup_and_prune