Quickstart: Using Client Libraries

This page shows you how to get started with the Cloud Natural Language API in your favorite programming language using the Google Cloud Client Libraries.

Before you begin

  1. Sign in to your Google Account.

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

  2. Set up a Cloud Console project.

    Set up a project

    Click to:

    • Create or select a project.
    • Enable the Google Natural Language API for that project.
    • Create a service account.
    • Download a private key as JSON.

    You can view and manage these resources at any time in the Cloud Console.

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

Install the client library

C#

Install-Package Google.Cloud.Language.V1 -Pre

Go

go get -u 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>16.2.1</version>
      <type>pom</type>
      <scope>import</scope>
    </dependency>
  </dependencies>
</dependencyManagement>

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

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

implementation platform('com.google.cloud:libraries-bom:16.3.0')

compile 'com.google.cloud:google-cloud-language'

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

libraryDependencies += "com.google.cloud" % "google-cloud-language" % "1.101.9"

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

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

Node.js

Before installing the library, make sure you've prepared your environment for Node.js development.

npm install --save @google-cloud/language

PHP

composer require google/cloud

Python

Before installing the library, make sure you've prepared your environment for Python development.

pip install --upgrade google-cloud-language

Ruby

gem install google-cloud-language

Analyze some text

Now you can use the Natural Language API to analyze some text. Run the following code to perform your first text sentiment analysis:

C#


using Google.Cloud.Language.V1;
using System;

namespace GoogleCloudSamples
{
    public class QuickStart
    {
        public static void Main(string[] args)
        {
            // The text to analyze.
            string text = "Hello World!";
            var client = LanguageServiceClient.Create();
            var response = client.AnalyzeSentiment(new Document()
            {
                Content = text,
                Type = Document.Types.Type.PlainText
            });
            var sentiment = response.DocumentSentiment;
            Console.WriteLine($"Score: {sentiment.Score}");
            Console.WriteLine($"Magnitude: {sentiment.Magnitude}");
        }
    }
}

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"
	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)
	}

	// 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

Before running the example, make sure you've prepared your environment for Node.js development.

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}`);
}

PHP

# Includes the autoloader for libraries installed with composer
require __DIR__ . '/vendor/autoload.php';

# Imports the Google Cloud client library
use Google\Cloud\Language\LanguageClient;

# Your Google Cloud Platform project ID
$projectId = 'YOUR_PROJECT_ID';

# Instantiates a client
$language = new LanguageClient([
    'projectId' => $projectId
]);

# The text to analyze
$text = 'Hello, world!';

# Detects the sentiment of the text
$annotation = $language->analyzeSentiment($text);
$sentiment = $annotation->sentiment();

echo 'Text: ' . $text . '
Sentiment: ' . $sentiment['score'] . ', ' . $sentiment['magnitude'];

Python

Before running the example, make sure you've prepared your environment for Python development.

# 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))

Ruby

# Imports the Google Cloud client library
require "google/cloud/language"

# Instantiates a client
language = Google::Cloud::Language.language_service

# The text to analyze
text = "Hello, world!"

# Detects the sentiment of the text
document = { content: text, type: :PLAIN_TEXT }
response = language.analyze_sentiment document: document

# Get document sentiment from response
sentiment = response.document_sentiment

puts "Text: #{text}"
puts "Score: #{sentiment.score}, #{sentiment.magnitude}"

Congratulations! You've sent your first request to the Natural Language API.

How did it go?

Clean up

To avoid incurring charges to your Google Cloud account for the resources used in this quickstart, follow these steps.

  • Use the Cloud Console to delete your project if you do not need it.

What's next