labels.jobStatus=Status
labels.labelTypeIds=Label
labels.lang=Sprache
labels.outputs=Ziel
labels.pos=POS
labels.purgeJobLogDay=Bereinige Suchprotokoll nach
labels.purgeUserInfoDay=Bereinige Benutzer nach
labels.reading=Lesen
labels.roleTypeIds=Rollen-ID
labels.scriptData=Skript
labels.scriptResult=Suchergebnis
labels.scriptType=Executor
labels.segmentation=Segmentierung
labels.startTime=Startzeitpunkt
labels.target=Ziel

gain (about 100 nanoseconds), please note that in **FastAPI** the effect would be quite opposite. In these cases, it's better to use `async def` unless your *path operation functions* use code that performs blocking <abbr title="Input/Output: disk reading or writing, network communications.">I/O</abbr>.

Still, in both situations, chances are that **FastAPI** will [still be faster](index.md#performance){.internal-link target=_blank} than (or at least comparable to) your previous framework....

Aún así, en ambas situaciones, es probable que **FastAPI** sea [aún más rápido](index.md#rendimiento){.Internal-link target=_blank} que (o al menos comparable) a tu framework anterior.

		}
		// read the response body.
		actualContent, err := io.ReadAll(rec.Body)
		if err != nil {
			t.Fatalf("Test %d: %s: Failed reading response body: <ERROR> %v", i+1, instanceType, err)
		}

		if rec.Code == http.StatusOK || rec.Code == http.StatusPartialContent {
			if !bytes.Equal(testCase.expectedContent, actualContent) {

labels.labelTypeIds	=	Étiquettes
labels.lang	=	langue
labels.outputs	=	Cible
labels.pos	=	PDV
labels.purgeJobLogDay	=	Purger le journal des tâches avant
labels.purgeUserInfoDay	=	Purger l'utilisateur avant
labels.reading	=	Lecture
labels.roleTypeIds	=	ID de rôle
labels.scriptData	=	Scénario
labels.scriptResult	=	Résultat
labels.scriptType	=	Exécuteur
labels.segmentation	=	Segmentation
labels.startTime	=	Heure de début

	return p.storage.Endpoint()
}

func (p *xlStorageDiskIDCheck) Hostname() string {
	return p.storage.Hostname()
}

func (p *xlStorageDiskIDCheck) Healing() *healingTracker {
	return p.storage.Healing()
}

func (p *xlStorageDiskIDCheck) NSScanner(ctx context.Context, cache dataUsageCache, updates chan<- dataUsageEntry, scanMode madmin.HealScanMode, _ func() bool) (dataUsageCache, error) {

*p /= 2
*p += i
</pre>

<p>
If <code>i</code> and <code>*p</code> start equal to 2,
the original code does <code>*p = 3</code>,
so a racing thread can read only 2 or 3 from <code>*p</code>.
The rewritten code does <code>*p = 1</code> and then <code>*p = 3</code>,
allowing a racing thread to read 1 as well.
</p>

<p>
Note that all these optimizations are permitted in C/C++ compilers:

labels.jobName = 이름
labels.jobStatus = 상태
labels.labelTypeIds = 레이블(Label)
labels.lang = 언어
labels.outputs = 대상
labels.pos = 품사
labels.purgeJobLogDay = 이전 작업 로그 삭제
labels.purgeUserInfoDay = 이전의 사용자 로그를 삭제
labels.reading = 읽기
labels.roleTypeIds = Role ID
labels.scriptData = 스크립트
labels.scriptResult = 결과
labels.scriptType = 실행 방법
labels.segmentation = 분할
labels.startTime = 시작 시간
labels.target = 대상
labels.token = 토큰

      /*
       * requireNonNull is safe because we accepted an Iterable of non-null Future instances, and we
       * don't overwrite an element in the array until after reading it.
       */
      ListenableFuture<? extends T> inputFuture = requireNonNull(inputFutures[inputFutureIndex]);
      // Null out our reference to this future, so it can be GCed

    val response = call.execute()
    val inputStream = response.body.byteStream()
    assertThat(inputStream.read().toChar()).isEqualTo('A')
    call.cancel()
    assertFailsWith<IOException> {
      // Reading 'B' may succeed if it's buffered.
      inputStream.read()

      // But 'C' shouldn't be buffered (the response is throttled) and this should fail.
      inputStream.read()
    }
    inputStream.close()