Perform sentiment analysis by 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

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

Install the Google Cloud CLI.

If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity .

To initialize the gcloud CLI, run the following command:

gcloud  
init

Create or select a Google Cloud 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

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.

If you're using an external identity provider (IdP), you must first sign in to the gcloud CLI with your federated identity .

To initialize the gcloud CLI, run the following command:

gcloud  
init

Create or select a Google Cloud 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

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 client library

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:

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 @google-cloud/language

Python

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

pip install --upgrade 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:

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

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 
 } 
 ` 
 ); 
 }

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 
 = 
 "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 
 } 
 " 
 )

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 on this page, delete the Google Cloud project with the resources.

Use the Google Cloud console to delete your project if you do not need it.

What's next

Find out more about our Cloud Natural Language API Client Libraries .
Consult the Natural Language Basics for conceptual information on forming Natural Language API requests and handling responses.
Work through the Sentiment Analysis Tutorial and browse the Sample Applications .