Realize uma análise de sentimento com bibliotecas de cliente

Realize uma análise de sentimento com bibliotecas de cliente

Esta página mostra como começar a usar a Cloud Natural Language API na sua linguagem de programação favorita através das bibliotecas cliente do Google Cloud.

Antes de começar

Sign in to your Google Account.

If you don't already have one, sign up for a new account.

Install the Google Cloud CLI.

Se estiver a usar um fornecedor de identidade (IdP) externo, primeiro, tem de iniciar sessão na CLI gcloud com a sua identidade federada.

Para inicializar a CLI gcloud, execute o seguinte comando:

gcloud init

Create or select 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.

• Create a Google Cloud project:

  gcloud projects create PROJECT_ID

  Replace PROJECT_ID with a name for the Google Cloud project you are creating.

• Select the Google Cloud project that you created:

  gcloud config set project PROJECT_ID

  Replace PROJECT_ID with your Google Cloud project name.

Verify that billing is enabled for your Google Cloud project.

Enable the Cloud Natural Language API:

gcloud services enable language.googleapis.com

Create local authentication credentials for your user account:

gcloud auth application-default login

Note: If the gcloud CLI prints a warning that your account doesn't have the serviceusage.services.use permission, then some gcloud CLI commands and client libraries might not work. Ask an administrator to grant you the Service Usage Consumer IAM role (roles/serviceusage.serviceUsageConsumer), then run the following command:

gcloud auth application-default set-quota-project PROJECT_ID

If an authentication error is returned, and you are using an external identity provider (IdP), confirm that you have signed in to the gcloud CLI with your federated identity.

Install the Google Cloud CLI.

Se estiver a usar um fornecedor de identidade (IdP) externo, primeiro, tem de iniciar sessão na CLI gcloud com a sua identidade federada.

Para inicializar a CLI gcloud, execute o seguinte comando:

gcloud init

Create or select 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.

• Create a Google Cloud project:

  gcloud projects create PROJECT_ID

  Replace PROJECT_ID with a name for the Google Cloud project you are creating.

• Select the Google Cloud project that you created:

  gcloud config set project PROJECT_ID

  Replace PROJECT_ID with your Google Cloud project name.

Verify that billing is enabled for your Google Cloud project.

Enable the Cloud Natural Language API:

gcloud services enable language.googleapis.com

Create local authentication credentials for your user account:

gcloud auth application-default login

Note: If the gcloud CLI prints a warning that your account doesn't have the serviceusage.services.use permission, then some gcloud CLI commands and client libraries might not work. Ask an administrator to grant you the Service Usage Consumer IAM role (roles/serviceusage.serviceUsageConsumer), then run the following command:

gcloud auth application-default set-quota-project PROJECT_ID

If an authentication error is returned, and you are using an external identity provider (IdP), confirm that you have signed in to the gcloud CLI with your federated identity.

Instale a biblioteca de cliente

Go

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>26.66.0</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:2.73.0'

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

libraryDependencies += "com.google.cloud" % "google-cloud-language" % "2.73.0"

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 a biblioteca, certifique-se de que preparou o seu ambiente para o desenvolvimento de Node.js.

npm install @google-cloud/language

Python

Antes de instalar a biblioteca, certifique-se de que preparou o seu ambiente para o desenvolvimento em Python.

pip install --upgrade google-cloud-language

Analise algum texto

Agora, pode usar a API Natural Language para analisar algum texto. Execute o seguinte código para realizar a sua primeira análise de sentimentos de texto:

Go

// 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"
	"cloud.google.com/go/language/apiv1/languagepb"
)

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

// 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 executar o exemplo, certifique-se de que preparou o seu ambiente para o desenvolvimento de Node.js.

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 executar o exemplo, certifique-se de que preparou o seu ambiente para o desenvolvimento em Python.

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

# Instantiates a client.
client = language_v1.LanguageServiceClient()

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

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

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

Parabéns! Enviou o seu primeiro pedido à API Natural Language.

Como correu?

Funcionou!

Ótimo! Do que é que gostou no início rápido? O que poderíamos ter feito melhor? Informe-nos!.

O envio bloqueou.

Lamentamos esta situação. Diga-nos o que correu mal. Vamos querer corrigi-lo.

Limpar

Para evitar incorrer em custos na sua Google Cloud conta pelos recursos usados nesta página, elimine o Google Cloud projeto com os recursos.

• Use o Google Cloud console para eliminar o projeto se não precisar dele.

O que se segue?

• Saiba mais sobre as nossas bibliotecas de cliente da API Cloud Natural Language.
• Consulte os Básicos da linguagem natural para ver informações conceptuais sobre a formação de pedidos da API Natural Language e o processamento de respostas.
• Siga o tutorial de análise de sentimentos e procure as aplicações de exemplo.