if err != nil {
		metricsLogIf(ctx, err)
	} else if startTime > 0 {
		m.Set(processStartTimeSeconds, float64(startTime))
	}
}

func loadProcIOMetrics(ctx context.Context, io procfs.ProcIO, m MetricValues) {
	if io.RChar > 0 {
		m.Set(processIORCharBytes, float64(io.RChar))
	}

	if io.ReadBytes > 0 {
		m.Set(processIOReadBytes, float64(io.ReadBytes))
	}

	if io.WChar > 0 {

	// a large number of users
	r, err := ies.client.Get(cctx, basePrefix, etcd.WithPrefix())
	if err != nil {
		return err
	}

	// Parse all users values to create the proper data model
	for _, userKv := range r.Kvs {
		if err = ies.getUserKV(ctx, userKv, userType, m, basePrefix); err != nil && err != errNoSuchUser {
			return err
		}
	}
	return nil
}

Y porque el esquema generado es del estándar [OpenAPI](https://github.com/OAI/OpenAPI-Specification/blob/master/versions/3.1.0.md), hay muchas herramientas compatibles.

Debido a esto, el propio **FastAPI** proporciona una documentación de API alternativa (usando ReDoc), a la cual puedes acceder en [http://127.0.0.1:8000/redoc](http://127.0.0.1:8000/redoc):

<img src="/img/tutorial/path-params/image02.png">

import java.util.function.Function;

import org.codelibs.curl.io.ContentCache;

/**
 * The CurlResponse class represents the response from a cURL request.
 * It implements the Closeable interface to allow proper resource management.
 */
public class CurlResponse implements Closeable {

    /**
     * Constructs a new CurlResponse.
     */
    public CurlResponse() {
        // nothing
    }

    /**

///

### Pydantic v1 y v2 en la misma app { #pydantic-v1-and-v2-on-the-same-app }

**No está soportado** por Pydantic tener un modelo de Pydantic v2 con sus propios campos definidos como modelos de Pydantic v1 o viceversa.

```mermaid
graph TB
    subgraph "❌ Not Supported"
        direction TB
        subgraph V2["Pydantic v2 Model"]
            V1Field["Pydantic v1 Model"]

                throw new IOException("Failed to create new transport");
            }

            // Reconnect
            channel.setState(ChannelState.CONNECTING);
            // Connection would be ensured through proper transport interface

            // Re-establish channel binding
            manager.performChannelBinding(channel);

            // Update channel with new transport
            channel.setTransport(newTransport);

 *
 * <p>The job supports selective crawling by specifying configuration IDs for different
 * types of crawlers (web, file, data). It manages the crawler process lifecycle,
 * handles timeout scenarios, and ensures proper cleanup of resources.</p>
 *
 * <p>Key features:</p>
 * <ul>
 *   <li>Concurrent crawler process management with configurable limits</li>
 *   <li>Selective crawling based on configuration IDs</li>

import jakarta.servlet.ServletContext;

/**
 * Job for executing Python scripts within the Fess search engine environment.
 * This job extends ExecJob to provide Python-specific functionality for running
 * Python scripts with proper environment setup and argument passing.
 *
 * <p>Python scripts are executed in the WEB-INF/env/python/resources directory
 * and have access to the Fess system environment including OpenSearch URL and session ID.</p>
 */

        // Setup
        TestLoginCredential credential = new TestLoginCredential("user", "pass");
        authenticator.setLoginCredential(credential);

        HtmlResponse metadataResponse = null; // Would need proper LastaFlute context to create
        authenticator.setResponseForType(SsoResponseType.METADATA, metadataResponse);

        String logoutUrl = "https://sso.example.com/logout";
        authenticator.setLogoutUrl(logoutUrl);

import jcifs.CIFSException;

/**
 * JAAS kerberos authenticator
 *
 * Either configure JAAS for credential caching or reuse a single instance of this authenticator -otherwise you won't
 * get proper ticket caching.
 *
 * Be advised that short/NetBIOS name usage is not supported with this authenticator. Always specify full FQDNs/Realm.