### Feature

- Kubelet TCP and HTTP probes are more effective using networking resources: conntrack entries, sockets, ... 

    }

    public void setEndTime_Avg(ConditionOptionCall<AvgAggregationBuilder> opLambda) {
        setEndTime_Avg("endTime", opLambda);
    }

    public void setEndTime_Avg(String name, ConditionOptionCall<AvgAggregationBuilder> opLambda) {
        AvgAggregationBuilder builder = regAvgA(name, "endTime");
        if (opLambda != null) {
            opLambda.callback(builder);
        }
    }

sqlite_file_name = "database.db"
sqlite_url = f"sqlite:///{sqlite_file_name}"

connect_args = {"check_same_thread": False}
engine = create_engine(sqlite_url, connect_args=connect_args)


def create_db_and_tables():
    SQLModel.metadata.create_all(engine)


def get_session():
    with Session(engine) as session:
        yield session


SessionDep = Annotated[Session, Depends(get_session)]

app = FastAPI()

Pode ser muito útil para configurar **recursos** que você precisa usar por toda aplicação, e que são **compartilhados** entre as requisições, e/ou que você precisa **limpar** depois. Por exemplo, o pool de uma conexão com o banco de dados ou carregamento de um modelo compartilhado de aprendizado de máquina (_machine learning_).

## Caso de uso

## Benchmarks y velocidad

Cuando revisas los benchmarks, es común ver varias herramientas de diferentes tipos comparadas como equivalentes.

Específicamente, para ver Uvicorn, Starlette y FastAPI comparadas entre sí (entre muchas otras herramientas).

Cuanto más sencillo sea el problema resuelto por la herramienta, mejor rendimiento obtendrá. Y la mayoría de los benchmarks no prueban las funciones adicionales proporcionadas por la herramienta.

      .addQuicHint("www.google.com", 443, 443)
      .build()

  @After
  fun tearDown() {
    engine.shutdown()
    cacheDir.deleteRecursively()
  }

  @Test
  fun get() {
    val executor = Executors.newCachedThreadPool()

    val completableFuture = execute(engine, executor, "https://google.com/robots.txt")

    try {
      val response = completableFuture.get(10, TimeUnit.SECONDS)

func (m *bucketMeasurement) updateExponentialMovingAverage(endTime time.Time) {
	// Calculate aggregate avg bandwidth and exp window avg
	m.lock.Lock()
	defer func() {
		m.startTime = endTime
		m.lock.Unlock()
	}()

	if m.startTime.IsZero() {
		return
	}

	if endTime.Before(m.startTime) {
		return
	}

	duration := endTime.Sub(m.startTime)

smart.deploy.mode.location = fess_env.properties: lasta_di.smart.deploy.mode

# package for smart deploy target e.g. org.docksidestage.app
smart.package1 = org.codelibs.fess.app

# script engine

sqlite_file_name = "database.db"
sqlite_url = f"sqlite:///{sqlite_file_name}"

connect_args = {"check_same_thread": False}
engine = create_engine(sqlite_url, connect_args=connect_args)


def create_db_and_tables():
    SQLModel.metadata.create_all(engine)


def get_session():
    with Session(engine) as session:
        yield session


app = FastAPI()


@app.on_event("startup")
def on_startup():

sqlite_file_name = "database.db"
sqlite_url = f"sqlite:///{sqlite_file_name}"

connect_args = {"check_same_thread": False}
engine = create_engine(sqlite_url, connect_args=connect_args)


def create_db_and_tables():
    SQLModel.metadata.create_all(engine)


def get_session():
    with Session(engine) as session:
        yield session


SessionDep = Annotated[Session, Depends(get_session)]
app = FastAPI()