So, behind the scenes, it will actually work as if everything was the same single app.

///

/// check

You don't have to worry about performance when including routers.

This will take microseconds and will only happen at startup.

So it won't affect performance. ⚡

///

				})

				for apiName, latency := range disk.Metrics.LastMinute {
					metrics = append(metrics, MetricV2{
						Description:    getNodeDriveAPILatencyMD(),
						Value:          float64(latency.Avg().Microseconds()),
						VariableLabels: map[string]string{"drive": disk.DrivePath, "api": "storage." + apiName},
					})
				}
			}
		}

		metrics = append(metrics, MetricV2{

    class ModelWithDatetimeField(BaseModel):
        dt_field: datetime

        @field_serializer("dt_field")
        def serialize_datetime(self, dt_field: datetime):
            return dt_field.replace(microsecond=0, tzinfo=timezone.utc).isoformat()

    app = FastAPI()
    model = ModelWithDatetimeField(dt_field=datetime(2019, 1, 1, 8))

    @app.get("/model", response_model=ModelWithDatetimeField)
    def get_model():

						duration = time.Duration(val) * time.Nanosecond
					case ts.Unit.IsSetMILLIS():
						duration = time.Duration(val) * time.Millisecond
					case ts.Unit.IsSetMICROS():
						duration = time.Duration(val) * time.Microsecond
					default:
						return nil, errors.New("Invalid LogicalType annotation found")
					}
					value = sql.FormatSQLTimestamp(time.Unix(0, 0).Add(duration))
				}

			defer wg.Done()
			for range opsPerGoroutine {
				_ = httpStats.toServerHTTPStats(false)
				_ = httpStats.totalS3Requests.Load(false)
				_ = httpStats.currentS3Requests.Load(false)
				time.Sleep(1 * time.Microsecond)
			}
		}(i)
	}
	wg.Wait()

	finalStats := httpStats.toServerHTTPStats(false)
	totalRequests := 0
	for _, v := range finalStats.TotalS3Requests.APIStats {
		totalRequests += v
	}

    class ModelWithCustomEncoder(BaseModel):
        dt_field: datetime

        @field_serializer("dt_field")
        def serialize_dt_field(self, dt):
            return dt.replace(microsecond=0, tzinfo=timezone.utc).isoformat()

    class ModelWithCustomEncoderSubclass(ModelWithCustomEncoder):
        pass

    model = ModelWithCustomEncoder(dt_field=datetime(2019, 1, 1, 8))

À la place, en étant "asynchrone", une fois terminée, une tâche peut légèrement attendre (quelques microsecondes) que l'ordinateur / le programme finisse ce qu'il était en train de faire, et revienne récupérer le résultat.

pkg testing, method (*B) ReportMetric(float64, string)
pkg testing, type BenchmarkResult struct, Extra map[string]float64
pkg text/template, method (ExecError) Unwrap() error
pkg time, method (Duration) Microseconds() int64
pkg time, method (Duration) Milliseconds() int64
pkg unicode, const Version = "11.0.0"
pkg unicode, var Dogra *RangeTable
pkg unicode, var Gunjala_Gondi *RangeTable

	return &dynamicSleeper{
		factor:    factor,
		cycle:     make(chan struct{}),
		maxSleep:  maxWait,
		minSleep:  100 * time.Microsecond,
		isScanner: isScanner,
	}
}

// Timer returns a timer that has started.
// When the returned function is called it will wait.
func (d *dynamicSleeper) Timer(ctx context.Context) func() {

- Protobuf serialization of metav1.MicroTime timestamps (used in `Lease` and `Event` API objects) has been corrected to truncate to microsecond precision, to match the documented behavior and JSON/YAML serialization. Any existing persisted data is truncated to microsecond when read from etcd. ([#111936](https://github.com/kubernetes/kubernetes/pull/111936), [@haoruan](https://github.com/haoruan))