Natural Language Client Libraries

This page shows how to get started with the Cloud Client Libraries for the Cloud Natural Language API. Read more about the client libraries for Cloud APIs, including the older Google APIs Client Libraries, in Client Libraries Explained.

Installing the client library

C#

For more information, see Setting Up a C# Development Environment.

If you are using Visual Studio 2017 or higher, open nuget package manager window and type the following:

Install-Package Google.Apis

If you are using .NET Core command-line interface tools to install your dependencies, run the following command:

dotnet add package Google.Apis

Go

For more information, see Setting Up a Go Development Environment.

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

Java

For more information, see Setting Up a Java Development Environment.

如果您使用的是 Maven,请将以下代码添加到您的 pom.xml 文件中。如需详细了解 BOM,请参阅 Google Cloud Platform 库 BOM

<dependencyManagement>
  <dependencies>
    <dependency>
      <groupId>com.google.cloud</groupId>
      <artifactId>libraries-bom</artifactId>
      <version>20.6.0</version>
      <type>pom</type>
      <scope>import</scope>
    </dependency>
  </dependencies>
</dependencyManagement>

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

如果您使用的是 Gradle,请将以下代码添加到您的依赖项中:

implementation platform('com.google.cloud:libraries-bom:20.6.0')

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

如果您使用的是 sbt,请将以下代码添加到您的依赖项中:

libraryDependencies += "com.google.cloud" % "google-cloud-language" % "1.103.1"

如果您使用的是 IntelliJ 或 Eclipse,请通过以下 IDE 插件将客户端库添加到您的项目中:

上述插件还提供其他功能,例如服务帐号密钥管理。如需了解详情,请参阅各个插件相应的文档。

Node.js

For more information, see Setting Up a Node.js Development Environment.

npm install --save @google-cloud/language

PHP

For more information, see Using PHP on Google Cloud.

composer require google/apiclient

Python

For more information, see Setting Up a Python Development Environment.

pip install --upgrade google-cloud-language

Ruby

For more information, see Setting Up a Ruby Development Environment.

gem install google-api-client

Setting up authentication

To run the client library, you must first set up authentication by creating a service account and setting an environment variable. Complete the following steps to set up authentication. For other ways to authenticate, see the GCP authentication documentation.

Cloud Console

创建服务帐号:

  1. 在 Cloud Console 中,转到创建服务帐号页面。

    转到“创建服务帐号”
  2. 选择一个项目。
  3. 服务帐号名称字段中,输入一个名称。 Cloud Console 会根据此名称填充服务帐号 ID 字段。

    服务帐号说明字段中,输入说明。例如,Service account for quickstart

  4. 点击创建
  5. 点击选择角色字段。

    快速访问下,点击基本,然后点击所有者

  6. 点击继续
  7. 点击完成以完成服务帐号的创建过程。

    不要关闭浏览器窗口。您将在下一步骤中用到它。

创建服务帐号密钥:

  1. 在 Cloud Console 中,点击您创建的服务帐号的电子邮件地址。
  2. 点击密钥
  3. 依次点击添加密钥创建新密钥
  4. 点击创建。JSON 密钥文件将下载到您的计算机上。
  5. 点击关闭

命令行

您可以使用本地机器上的 Cloud SDK 或在 Cloud Shell 中运行以下命令。

  1. 创建服务帐号。将 NAME 替换为服务帐号的名称。

    gcloud iam service-accounts create NAME
  2. 向服务帐号授予权限。将 PROJECT_ID 替换为您的项目 ID。

    gcloud projects add-iam-policy-binding PROJECT_ID --member="serviceAccount:NAME@PROJECT_ID.iam.gserviceaccount.com" --role="roles/owner"
  3. 生成密钥文件。将 FILE_NAME 替换为密钥文件的名称。

    gcloud iam service-accounts keys create FILE_NAME.json --iam-account=NAME@PROJECT_ID.iam.gserviceaccount.com

通过设置环境变量 GOOGLE_APPLICATION_CREDENTIALS 向应用代码提供身份验证凭据。 此变量仅适用于当前的 Shell 会话,因此,如果您打开新的会话,请重新设置该变量。

Linux 或 macOS

export GOOGLE_APPLICATION_CREDENTIALS="KEY_PATH"

KEY_PATH 替换为包含您的服务帐号密钥的 JSON 文件的路径。

例如:

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

Windows

对于 PowerShell:

$env:GOOGLE_APPLICATION_CREDENTIALS="KEY_PATH"

KEY_PATH 替换为包含您的服务帐号密钥的 JSON 文件的路径。

例如:

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

对于命令提示符:

set GOOGLE_APPLICATION_CREDENTIALS=KEY_PATH

KEY_PATH 替换为包含您的服务帐号密钥的 JSON 文件的路径。

Using the client library

The following example shows how to use the client library.

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)
	}
	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

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

# 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))

Additional resources