latency, higher throughput (due to [TCP slow start](https://www.igvita.com/2011/10/20/faster-web-vs-tcp-slow-start/)) and conserved battery. OkHttp uses a [ConnectionPool](https://square.github.io/okhttp/4.x/okhttp/okhttp3/-connection-pool/) that automatically reuses HTTP/1.x connections and multiplexes HTTP/2 connections.

In OkHttp some fields of the address come from the URL (scheme, hostname, port) and the rest come from the [OkHttpClient](https://square.github.io/okhttp/4.x/okhttp/ok...

        You can use [the template](https://github.com/gradle/gradle-issue-reproducer) with a Gradle GitHub action set up to showcase your problem.
        In the rare cases where this is infeasible, we will also accept a detailed set of instructions.
        You can also use [Gradle Project Replicator](https://github.com/android/project-replicator) to reproduce the structure of your project.
    validations:

* <a href="https://sqlmodel.tiangolo.com/" class="external-link" target="_blank">Enlace externo</a>
* <a href="https://fastapi.tiangolo.com/css/styles.css" class="external-link" target="_blank">Enlace a un estilo</a>
* <a href="https://fastapi.tiangolo.com/js/logic.js" class="external-link" target="_blank">Enlace a un script</a>
* <a href="https://fastapi.tiangolo.com/img/foo.jpg" class="external-link" target="_blank">Enlace a una imagen</a>

Hay algunos casos en los que podrías necesitar modificar el esquema de OpenAPI generado.

En esta sección verás cómo hacerlo.

## El proceso normal { #the-normal-process }

El proceso normal (por defecto) es el siguiente.

Una aplicación (instance) de `FastAPI` tiene un método `.openapi()` que se espera que devuelva el esquema de OpenAPI.

## TensorFlow models are programs

TensorFlow
[**models**](https://developers.google.com/machine-learning/glossary/#model) (to
use a term commonly used by machine learning practitioners) are expressed as
programs that TensorFlow executes. TensorFlow programs are encoded as
computation
[**graphs**](https://developers.google.com/machine-learning/glossary/#graph).
Since models are practically programs that TensorFlow executes, using untrusted

import org.mockito.MockitoAnnotations;

import jcifs.CIFSContext;
import jcifs.CIFSException;
import jcifs.Configuration;
import jcifs.SmbConstants;
import jcifs.internal.smb1.com.ServerData;
import jcifs.internal.smb1.com.SmbComNegotiateResponse;
import jcifs.internal.smb1.com.SmbComTreeConnectAndXResponse;
import jcifs.internal.smb2.nego.Smb2NegotiateResponse;
import jcifs.internal.smb2.tree.Smb2TreeConnectResponse;

class SmbTreeImplTest {

{* ../../docs_src/dependencies/tutorial005_an_py310.py hl[8:9] *}

Esse código declara um parâmetro de consulta opcional, `q`, com o tipo `str`, e então retorna esse parâmetro.

Isso é bastante simples (e não muito útil), mas irá nos ajudar a focar em como as subdependências funcionam.

## Segunda dependência, "dependable" e "dependente" { #second-dependency-dependable-and-dependant }

## Guía oficial { #official-guide }

Pydantic tiene una <a href="https://docs.pydantic.dev/latest/migration/" class="external-link" target="_blank">Guía de migración</a> oficial de v1 a v2.

<!--- reproduce this bug. Include code to reproduce, if relevant -->
<!--- and make sure you have followed https://github.com/minio/minio/tree/release/docs/debugging to capture relevant logs -->

1.
2.
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## Context
<!--- How has this issue affected you? What are you trying to accomplish? -->
<!--- Providing context helps us come up with a solution that is most useful in the real world -->

## Regression

 * limitations under the License.
 */

package com.google.common.collect;

import static com.google.common.base.Preconditions.checkNotNull;
import static java.util.Collections.singletonMap;
import static java.util.stream.Collectors.collectingAndThen;
import static java.util.stream.Collectors.toMap;

import com.google.common.annotations.GwtCompatible;
import com.google.common.annotations.GwtIncompatible;