Analyzing Sentiment

  func 
  
 analyzeSentimentFromGCS 
 ( 
 ctx 
  
 context 
 . 
 Context 
 , 
  
 gcsURI 
  
 string 
 ) 
  
 ( 
 * 
 languagepb 
 . 
 AnalyzeSentimentResponse 
 , 
  
 error 
 ) 
  
 { 
  
 return 
  
 client 
 . 
 AnalyzeSentiment 
 ( 
 ctx 
 , 
  
& languagepb 
 . 
 AnalyzeSentimentRequest 
 { 
  
 Document 
 : 
  
& languagepb 
 . 
 Document 
 { 
  
 Source 
 : 
  
& languagepb 
 . 
 Document_GcsContentUri 
 { 
  
 GcsContentUri 
 : 
  
 gcsURI 
 , 
  
 }, 
  
 Type 
 : 
  
 languagepb 
 . 
 Document_PLAIN_TEXT 
 , 
  
 }, 
  
 }) 
 } 
 

  // Instantiate the Language client com.google.cloud.language.v2.LanguageServiceClient 
 try 
  
 ( 
 LanguageServiceClient 
  
 language 
  
 = 
  
 LanguageServiceClient 
 . 
 create 
 ()) 
  
 { 
  
 Document 
  
 doc 
  
 = 
  
 Document 
 . 
 newBuilder 
 (). 
 setGcsContentUri 
 ( 
 gcsUri 
 ). 
 setType 
 ( 
 Type 
 . 
 PLAIN_TEXT 
 ). 
 build 
 (); 
  
 AnalyzeSentimentResponse 
  
 response 
  
 = 
  
 language 
 . 
 analyzeSentiment 
 ( 
 doc 
 ); 
  
 Sentiment 
  
 sentiment 
  
 = 
  
 response 
 . 
 getDocumentSentiment 
 (); 
  
 if 
  
 ( 
 sentiment 
  
 == 
  
 null 
 ) 
  
 { 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 "No sentiment found" 
 ); 
  
 } 
  
 else 
  
 { 
  
 System 
 . 
 out 
 . 
 printf 
 ( 
 "Sentiment magnitude : %.3f\n" 
 , 
  
 sentiment 
 . 
 getMagnitude 
 ()); 
  
 System 
 . 
 out 
 . 
 printf 
 ( 
 "Sentiment score : %.3f\n" 
 , 
  
 sentiment 
 . 
 getScore 
 ()); 
  
 } 
  
 return 
  
 sentiment 
 ; 
 } 
 

  // Imports the Google Cloud client library 
 const 
  
 language 
  
 = 
  
 require 
 ( 
 ' @google-cloud/language 
' 
 ). 
 v2 
 ; 
 // Creates a client 
 const 
  
 client 
  
 = 
  
 new 
  
 language 
 . 
  LanguageServiceClient 
 
 (); 
 /** 
 * TODO(developer): Uncomment the following lines to run this code 
 */ 
 // const bucketName = 'Your bucket name, e.g. my-bucket'; 
 // const fileName = 'Your file name, e.g. my-file.txt'; 
 // Prepares a document, representing a text file in Cloud Storage 
 const 
  
 document 
  
 = 
  
 { 
  
 gcsContentUri 
 : 
  
 `gs:// 
 ${ 
 bucketName 
 } 
 / 
 ${ 
 fileName 
 } 
 ` 
 , 
  
 type 
 : 
  
 'PLAIN_TEXT' 
 , 
 }; 
 // Detects the sentiment of the document 
 const 
  
 [ 
 result 
 ] 
  
 = 
  
 await 
  
 client 
 . 
 analyzeSentiment 
 ({ 
 document 
 }); 
 const 
  
 sentiment 
  
 = 
  
 result 
 . 
 documentSentiment 
 ; 
 console 
 . 
 log 
 ( 
 'Document sentiment:' 
 ); 
 console 
 . 
 log 
 ( 
 `  Score: 
 ${ 
 sentiment 
 . 
 score 
 } 
 ` 
 ); 
 console 
 . 
 log 
 ( 
 `  Magnitude: 
 ${ 
 sentiment 
 . 
 magnitude 
 } 
 ` 
 ); 
 const 
  
 sentences 
  
 = 
  
 result 
 . 
 sentences 
 ; 
 sentences 
 . 
 forEach 
 ( 
 sentence 
  
 = 
>  
 { 
  
 console 
 . 
 log 
 ( 
 `Sentence: 
 ${ 
 sentence 
 . 
 text 
 . 
 content 
 } 
 ` 
 ); 
  
 console 
 . 
 log 
 ( 
 `  Score: 
 ${ 
 sentence 
 . 
 sentiment 
 . 
 score 
 } 
 ` 
 ); 
  
 console 
 . 
 log 
 ( 
 `  Magnitude: 
 ${ 
 sentence 
 . 
 sentiment 
 . 
 magnitude 
 } 
 ` 
 ); 
 }); 
 

  from 
  
 google.cloud 
  
 import 
 language_v2 
 def 
  
 sample_analyze_sentiment 
 ( 
 gcs_content_uri 
 : 
 str 
 = 
 "gs://cloud-samples-data/language/sentiment-positive.txt" 
 , 
 ) 
 - 
> None 
 : 
  
 """ 
 Analyzes Sentiment in text file stored in Cloud Storage. 
 Args: 
 gcs_content_uri: Google Cloud Storage URI where the file content is located. 
 e.g. gs://[Your Bucket]/[Path to File] 
 """ 
 client 
 = 
 language_v2 
 . 
 LanguageServiceClient 
 () 
 # Available types: PLAIN_TEXT, HTML 
 document_type_in_plain_text 
 = 
 language_v2 
 . 
 Document 
 . 
 Type 
 . 
 PLAIN_TEXT 
 # Optional. If not specified, the language is automatically detected. 
 # For list of supported languages: 
 # https://cloud.google.com/natural-language/docs/languages 
 language_code 
 = 
 "en" 
 document 
 = 
 { 
 "gcs_content_uri" 
 : 
 gcs_content_uri 
 , 
 "type_" 
 : 
 document_type_in_plain_text 
 , 
 "language_code" 
 : 
 language_code 
 , 
 } 
 # Available values: NONE, UTF8, UTF16, UTF32 
 # See https://cloud.google.com/natural-language/docs/reference/rest/v2/EncodingType. 
 encoding_type 
 = 
 language_v2 
 . 
 EncodingType 
 . 
 UTF8 
 response 
 = 
 client 
 . 
  analyze_sentiment 
 
 ( 
 request 
 = 
 { 
 "document" 
 : 
 document 
 , 
 "encoding_type" 
 : 
 encoding_type 
 } 
 ) 
 # Get overall sentiment of the input document 
 print 
 ( 
 f 
 "Document sentiment score: 
 { 
 response 
 . 
 document_sentiment 
 . 
 score 
 } 
 " 
 ) 
 print 
 ( 
 f 
 "Document sentiment magnitude: 
 { 
 response 
 . 
 document_sentiment 
 . 
 magnitude 
 } 
 " 
 ) 
 # Get sentiment for all sentences in the document 
 for 
 sentence 
 in 
 response 
 . 
 sentences 
 : 
 print 
 ( 
 f 
 "Sentence text: 
 { 
 sentence 
 . 
 text 
 . 
 content 
 } 
 " 
 ) 
 print 
 ( 
 f 
 "Sentence sentiment score: 
 { 
 sentence 
 . 
 sentiment 
 . 
 score 
 } 
 " 
 ) 
 print 
 ( 
 f 
 "Sentence sentiment magnitude: 
 { 
 sentence 
 . 
 sentiment 
 . 
 magnitude 
 } 
 " 
 ) 
 # Get the language of the text, which will be the same as 
 # the language specified in the request or, if not specified, 
 # the automatically-detected language. 
 print 
 ( 
 f 
 "Language of the text: 
 { 
 response 
 . 
 language_code 
 } 
 " 
 )