Guía de inicio rápido: Cómo usar bibliotecas cliente

En esta página, se muestra cómo comenzar a usar la API de Cloud Natural Language en el lenguaje de programación de tu preferencia con las bibliotecas cliente de Google Cloud.

Antes de comenzar

1. Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.

2. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

   Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

   Go to project selector

3. Make sure that billing is enabled for your Google Cloud project.

4. Enable the Cloud Natural Language API.

   Enable the API

5. Create a service account:

   1. In the Google Cloud console, go to the Create service account page.

      Go to Create service account
   2. Select your project.

   3. In the Service account name field, enter a name. The Google Cloud console fills in the Service account ID field based on this name.

      In the Service account description field, enter a description. For example, Service account for quickstart.

   4. Click Create and continue.

   5. Click Done to finish creating the service account.

      Do not close your browser window. You will use it in the next step.

6. Create a service account key:

   1. In the Google Cloud console, click the email address for the service account that you created.
   2. Click Keys.
   3. Click Add key, and then click Create new key.
   4. Click Create. A JSON key file is downloaded to your computer.
   5. Click Close.

7. Set the environment variable GOOGLE_APPLICATION_CREDENTIALS to the path of the JSON file that contains your credentials. This variable applies only to your current shell session, so if you open a new session, set the variable again.

   Example: Linux or macOS

   export GOOGLE_APPLICATION_CREDENTIALS="KEY_PATH"

   Replace KEY_PATH with the path of the JSON file that contains your credentials.

   For example:

   export GOOGLE_APPLICATION_CREDENTIALS="/home/user/Downloads/service-account-file.json"

   Example: Windows

   For PowerShell:

   $env:GOOGLE_APPLICATION_CREDENTIALS="KEY_PATH"

   Replace KEY_PATH with the path of the JSON file that contains your credentials.

   For example:

   $env:GOOGLE_APPLICATION_CREDENTIALS="C:\Users\username\Downloads\service-account-file.json"

   For command prompt:

   set GOOGLE_APPLICATION_CREDENTIALS=KEY_PATH

   Replace KEY_PATH with the path of the JSON file that contains your credentials.

8. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

   Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

   Go to project selector

9. Make sure that billing is enabled for your Google Cloud project.

10. Enable the Cloud Natural Language API.

    Enable the API

11. Create a service account:

    1. In the Google Cloud console, go to the Create service account page.

       Go to Create service account
    2. Select your project.

    3. In the Service account name field, enter a name. The Google Cloud console fills in the Service account ID field based on this name.

       In the Service account description field, enter a description. For example, Service account for quickstart.

    4. Click Create and continue.

    5. Click Done to finish creating the service account.

       Do not close your browser window. You will use it in the next step.

12. Create a service account key:

    1. In the Google Cloud console, click the email address for the service account that you created.
    2. Click Keys.
    3. Click Add key, and then click Create new key.
    4. Click Create. A JSON key file is downloaded to your computer.
    5. Click Close.

13. Set the environment variable GOOGLE_APPLICATION_CREDENTIALS to the path of the JSON file that contains your credentials. This variable applies only to your current shell session, so if you open a new session, set the variable again.

    Example: Linux or macOS

    export GOOGLE_APPLICATION_CREDENTIALS="KEY_PATH"

    Replace KEY_PATH with the path of the JSON file that contains your credentials.

    For example:

    export GOOGLE_APPLICATION_CREDENTIALS="/home/user/Downloads/service-account-file.json"

    Example: Windows

    For PowerShell:

    $env:GOOGLE_APPLICATION_CREDENTIALS="KEY_PATH"

    Replace KEY_PATH with the path of the JSON file that contains your credentials.

    For example:

    $env:GOOGLE_APPLICATION_CREDENTIALS="C:\Users\username\Downloads\service-account-file.json"

    For command prompt:

    set GOOGLE_APPLICATION_CREDENTIALS=KEY_PATH

    Replace KEY_PATH with the path of the JSON file that contains your credentials.

Instala la biblioteca cliente

Comienza a usarlo

go get cloud.google.com/go/language/apiv1

Java

If you are using Maven, add the following to your pom.xml file. For more information about BOMs, see The Google Cloud Platform Libraries BOM.

<dependencyManagement>
  <dependencies>
    <dependency>
      <groupId>com.google.cloud</groupId>
      <artifactId>libraries-bom</artifactId>
      <version>26.49.0</version>
      <type>pom</type>
      <scope>import</scope>
    </dependency>
  </dependencies>
</dependencyManagement>

<dependencies>
  <dependency>
    <groupId>com.google.cloud</groupId>
    <artifactId>google-cloud-language</artifactId>
  </dependency>
</dependencies>

If you are using Gradle, add the following to your dependencies:

implementation 'com.google.cloud:google-cloud-language:2.53.0'

If you are using sbt, add the following to your dependencies:

libraryDependencies += "com.google.cloud" % "google-cloud-language" % "2.53.0"

If you're using Visual Studio Code, IntelliJ, or Eclipse, you can add client libraries to your project using the following IDE plugins:

• Cloud Code for VS Code
• Cloud Code for IntelliJ
• Cloud Tools for Eclipse

The plugins provide additional functionality, such as key management for service accounts. Refer to each plugin's documentation for details.

Note: Cloud Java client libraries do not currently support Android.

Node.js

Antes de instalar la biblioteca, asegúrate de haber preparado tu entorno para el desarrollo en Node.js.

npm install --save @google-cloud/language

Python

Antes de instalar la biblioteca, asegúrate de haber preparado tu entorno para el desarrollo en Python.

pip install --upgrade google-cloud-language

Analizar un texto

Ahora puedes usar la API de Natural Language para analizar un texto. Ejecuta el siguiente código para realizar tu primer análisis de opiniones de texto:

Go

Ver en GitHub Comentarios

// Sample language-quickstart uses the Google Cloud Natural API to analyze the
// sentiment of "Hello, world!".
package main

import (
	"context"
	"fmt"
	"log"

	language "cloud.google.com/go/language/apiv1"
	languagepb "google.golang.org/genproto/googleapis/cloud/language/v1"
)

func main() {
	ctx := context.Background()

	// Creates a client.
	client, err := language.NewClient(ctx)
	if err != nil {
		log.Fatalf("Failed to create client: %v", err)
	}
	defer client.Close()

	// Sets the text to analyze.
	text := "Hello, world!"

	// Detects the sentiment of the text.
	sentiment, err := client.AnalyzeSentiment(ctx, &languagepb.AnalyzeSentimentRequest{
		Document: &languagepb.Document{
			Source: &languagepb.Document_Content{
				Content: text,
			},
			Type: languagepb.Document_PLAIN_TEXT,
		},
		EncodingType: languagepb.EncodingType_UTF8,
	})
	if err != nil {
		log.Fatalf("Failed to analyze text: %v", err)
	}

	fmt.Printf("Text: %v\n", text)
	if sentiment.DocumentSentiment.Score >= 0 {
		fmt.Println("Sentiment: positive")
	} else {
		fmt.Println("Sentiment: negative")
	}
}

Java

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// Imports the Google Cloud client library
import com.google.cloud.language.v1.Document;
import com.google.cloud.language.v1.Document.Type;
import com.google.cloud.language.v1.LanguageServiceClient;
import com.google.cloud.language.v1.Sentiment;

public class QuickstartSample {
  public static void main(String... args) throws Exception {
    // Instantiates a client
    try (LanguageServiceClient language = LanguageServiceClient.create()) {

      // The text to analyze
      String text = "Hello, world!";
      Document doc = Document.newBuilder().setContent(text).setType(Type.PLAIN_TEXT).build();

      // Detects the sentiment of the text
      Sentiment sentiment = language.analyzeSentiment(doc).getDocumentSentiment();

      System.out.printf("Text: %s%n", text);
      System.out.printf("Sentiment: %s, %s%n", sentiment.getScore(), sentiment.getMagnitude());
    }
  }
}

Node.js

Antes de ejecutar el ejemplo, asegúrate de haber preparado tu entorno para el desarrollo en Node.js.

Ver en GitHub Comentarios

async function quickstart() {
  // Imports the Google Cloud client library
  const language = require('@google-cloud/language');

  // Instantiates a client
  const client = new language.LanguageServiceClient();

  // The text to analyze
  const text = 'Hello, world!';

  const document = {
    content: text,
    type: 'PLAIN_TEXT',
  };

  // Detects the sentiment of the text
  const [result] = await client.analyzeSentiment({document: document});
  const sentiment = result.documentSentiment;

  console.log(`Text: ${text}`);
  console.log(`Sentiment score: ${sentiment.score}`);
  console.log(`Sentiment magnitude: ${sentiment.magnitude}`);
}

Python

Antes de ejecutar el ejemplo, asegúrate de haber preparado tu entorno para el desarrollo en Python.

Ver en GitHub Comentarios

# Imports the Google Cloud client library
from google.cloud import language_v1

# Instantiates a client
client = language_v1.LanguageServiceClient()

# The text to analyze
text = u"Hello, world!"
document = language_v1.Document(
    content=text, type_=language_v1.Document.Type.PLAIN_TEXT
)

# Detects the sentiment of the text
sentiment = client.analyze_sentiment(
    request={"document": document}
).document_sentiment

print("Text: {}".format(text))
print("Sentiment: {}, {}".format(sentiment.score, sentiment.magnitude))

¡Felicitaciones! Enviaste tu primera solicitud a la API de Natural Language.

¿Cómo fue?

¡Funcionó!

¡Excelente! ¿Qué te gustó de la guía de inicio rápido? ¿Qué podríamos mejorar? Envíanos tus comentarios.

No puedo avanzar.

Lo sentimos. Queremos saber qué ocurrió. Queremos corregirlo.

Limpia

Sigue estos pasos para evitar que se apliquen cargos a tu cuenta de Google Cloud por los recursos que usaste en esta página.

• Usa Cloud Console para borrar tu proyecto si no lo necesitas.

¿Qué sigue?

• Obtén más información sobre nuestras las bibliotecas cliente de la API de Cloud Natural Language.
• Consulta los Conceptos básicos de Natural Language para obtener información conceptual sobre la formación de solicitudes de la API de Natural Language y manejar respuestas.
• Revisa con atención el Instructivo de análisis de opiniones y explora las Aplicaciones de muestra.