}).orElseGet(() -> {
            throwValidationErrorApi(messages -> messages.addErrorsCrudFailedToCreateInstance(GLOBAL));
            return null;
        });
        stemmerOverrideService.store(body.dictId, entity);
        return asJson(
                new ApiResult.ApiUpdateResponse().id(String.valueOf(entity.getId())).created(true).status(ApiResult.Status.OK).result());
    }

    /**

There are some cases where you might need to convert a data type (like a Pydantic model) to something compatible with JSON (like a `dict`, `list`, etc).

For example, if you need to store it in a database.

For that, **FastAPI** provides a `jsonable_encoder()` function.

## Using the `jsonable_encoder` { #using-the-jsonable-encoder }

| inline data    | binary         | Inline data if any, see Inline Data section for encoding.  
| [EOF] | |

## v1.0-v1.2 Versions

`xl.meta` carries three types of object entries which designate the type of version object stored.

- ObjectType (default)
- LegacyObjectType (preserves existing deployments and older xl.json format)
- DeleteMarker (a versionId to capture the DELETE sequences implemented primarily for AWS spec compatibility)

The drives should all be of approximately the same size.

## Get Started with MinIO in Erasure Code

### 1. Prerequisites

Install MinIO - [MinIO Quickstart Guide](https://docs.min.io/community/minio-object-store/operations/deployments/baremetal-deploy-minio-on-redhat-linux.html)

This document explains how to setup Prometheus and configure it to scrape data from MinIO servers.

## Prerequisites

To get started with MinIO, refer [MinIO QuickStart Document](https://docs.min.io/community/minio-object-store/operations/deployments/baremetal-deploy-minio-on-redhat-linux.html).
Follow below steps to get started with MinIO monitoring using Prometheus.

### 1. Download Prometheus

 * Null row keys, columns keys, and values are not supported.
 *
 * <p>Lookups by row key are often faster than lookups by column key, because the data is stored in
 * a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still runs
 * quickly, since the row key is provided. However, {@code column(columnKey).size()} takes longer,

 * Null row keys, columns keys, and values are not supported.
 *
 * <p>Lookups by row key are often faster than lookups by column key, because the data is stored in
 * a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still runs
 * quickly, since the row key is provided. However, {@code column(columnKey).size()} takes longer,

	dt.logEntry(duration)
}

// LogFailure logs an action that hit the timeout
func (dt *dynamicTimeout) LogFailure() {
	dt.logEntry(maxDuration)
}

// logEntry stores a log entry
func (dt *dynamicTimeout) logEntry(duration time.Duration) {
	if duration < 0 {
		return
	}
	entries := int(atomic.AddInt64(&dt.entries, 1))
	index := entries - 1
	if index < dynamicTimeoutLogSize {

	Line() int
	// Col reports the source column number of the token.
	Col() int
	// Close does any teardown required.
	Close()
}

// A Token is a scan token plus its string value.
// A macro is stored as a sequence of Tokens with spaces stripped.
type Token struct {
	ScanToken
	text string
}

// Make returns a Token with the given rune (ScanToken) and text representation.

        validate(form, messages -> {}, this::asEditHtml);
        verifyToken(this::asEditHtml);
        getDuplicateHost(form).ifPresent(entity -> {
            try {
                duplicateHostService.store(entity);
                saveInfo(messages -> messages.addSuccessCrudCreateCrudTable(GLOBAL));
            } catch (final Exception e) {
                logger.warn("Failed to process a request.", e);