func newRecordsMessage(payload []byte) []byte {
	return genMessage(recordsHeader, payload)
}

// payloadLenForMsgLen computes the length of the payload in a record
// message given the total length of the message.
func payloadLenForMsgLen(messageLength int) int {
	headerLength := len(recordsHeader)
	payloadLength := messageLength - 4 - 4 - 4 - headerLength - 4
	return payloadLength
}

	TargetHTTP
	TargetKafka
)

// TargetStats contains statistics for a target.
type TargetStats struct {
	// QueueLength is the queue length if any messages are queued.
	QueueLength int

	// TotalMessages is the total number of messages sent in the lifetime of the target
	TotalMessages int64

	// FailedMessages should log message count that failed to send.
	FailedMessages int64

	BackendFS = BackendType(madmin.FS)
	// Multi disk BackendErasure (single, distributed) backend.
	BackendErasure = BackendType(madmin.Erasure)
	// Add your own backend.
)

// StorageInfo - represents total capacity of underlying storage.
type StorageInfo = madmin.StorageInfo

// objectHistogramInterval is an interval that will be
// used to report the histogram of objects data sizes
type objectHistogramInterval struct {

	notificationEventsErrorsTotalMD     = NewCounterMD(notificationEventsErrorsTotal, "Events that were failed to be sent to the targets")
	notificationEventsSentTotalMD       = NewCounterMD(notificationEventsSentTotal, "Total number of events sent to the targets")
	notificationEventsSkippedTotalMD    = NewCounterMD(notificationEventsSkippedTotal, "Events that were skipped to be sent to the targets due to the in-memory queue being full")
)

from fastapi import APIRouter, FastAPI
from pydantic import BaseModel, HttpUrl

app = FastAPI()


class Invoice(BaseModel):
    id: str
    title: Union[str, None] = None
    customer: str
    total: float


class InvoiceEvent(BaseModel):
    description: str
    paid: bool


class InvoiceEventReceived(BaseModel):
    ok: bool


invoices_callback_router = APIRouter()

	DB.Create(&users)

	rows, err := DB.Select("name, count(*) as total").Table("users").Group("name").Having("name IN ?", []string{users[0].Name, users[1].Name}).Rows()
	if err != nil {
		t.Fatalf("got error %v", err)
	}

	defer rows.Close()
	for rows.Next() {
		var name string
		var total int64
		rows.Scan(&name, &total)

		if name == users[0].Name && total != 3 {

          },
          "expr": "sum(container_memory_working_set_bytes{container=\"istio-proxy\"})",
          "format": "time_series",
          "hide": false,
          "intervalFactor": 2,
          "legendFormat": "Total (k8s)",
          "refId": "A",
          "step": 2
        }
      ],
      "title": "Memory",
      "type": "timeseries"
    },
    {
      "datasource": {
        "type": "prometheus",

		size = diskAssumeUnknownSize
	}

	var available uint64
	var total uint64
	var nDisks int
	for _, disk := range di {
		if disk == nil || disk.Total == 0 {
			// Disk offline, no inodes or something else is wrong.
			continue
		}
		nDisks++
		total += disk.Total
		available += disk.Total - disk.Used
	}

	if nDisks < len(di)/2 || nDisks <= 0 {
		var errs []error

    * In requests and responses will be represented as a `str` in ISO 8601 format, like: `14:23:55.003`.
* `datetime.timedelta`:
    * A Python `datetime.timedelta`.
    * In requests and responses will be represented as a `float` of total seconds.

	ilmTransitionMissedImmediateTasksMD = NewCounterMD(transitionMissedImmediateTasks, "Number of missed immediate ILM transition tasks")
	ilmVersionsScannedMD                = NewCounterMD(versionsScanned, "Total number of object versions checked for ILM actions since server start")
)

// loadILMMetrics - `MetricsLoaderFn` for ILM metrics.
func loadILMMetrics(_ context.Context, m MetricValues, _ *metricsCache) error {