Language region tag update [(#1643)](GoogleCloudPlatform/python-docs-samples#1643)

Author: alixhami

samples/snippets/quickstart.py

@@ -18,16 +18,16 @@
 def run_quickstart():
     # [START language_quickstart]
     # Imports the Google Cloud client library
-    # [START migration_import]
+    # [START language_python_migration_imports]
     from google.cloud import language
     from google.cloud.language import enums
     from google.cloud.language import types
-    # [END migration_import]
+    # [END language_python_migration_imports]
 
     # Instantiates a client
-    # [START migration_client]
+    # [START language_python_migration_client]
     client = language.LanguageServiceClient()
-    # [END migration_client]
+    # [END language_python_migration_client]
 
     # The text to analyze
     text = u'Hello, world!'

samples/snippets/snippets.py

@@ -30,7 +30,7 @@
 import six
 
 
-# [START def_sentiment_text]
+# [START language_sentiment_text]
 def sentiment_text(text):
     """Detects sentiment in the text."""
     client = language.LanguageServiceClient()
@@ -39,45 +39,45 @@ def sentiment_text(text):
         text = text.decode('utf-8')
 
     # Instantiates a plain text document.
-    # [START migration_document_text]
-    # [START migration_analyze_sentiment]
+    # [START language_python_migration_document_text]
+    # [START language_python_migration_sentiment_text]
     document = types.Document(
         content=text,
         type=enums.Document.Type.PLAIN_TEXT)
-    # [END migration_document_text]
+    # [END language_python_migration_document_text]
 
     # Detects sentiment in the document. You can also analyze HTML with:
     #   document.type == enums.Document.Type.HTML
     sentiment = client.analyze_sentiment(document).document_sentiment
 
     print('Score: {}'.format(sentiment.score))
     print('Magnitude: {}'.format(sentiment.magnitude))
-    # [END migration_analyze_sentiment]
-# [END def_sentiment_text]
+    # [END language_python_migration_sentiment_text]
+# [END language_sentiment_text]
 
 
-# [START def_sentiment_file]
+# [START language_sentiment_gcs]
 def sentiment_file(gcs_uri):
     """Detects sentiment in the file located in Google Cloud Storage."""
     client = language.LanguageServiceClient()
 
     # Instantiates a plain text document.
-    # [START migration_document_gcs_uri]
+    # [START language_python_migration_document_gcs]
     document = types.Document(
         gcs_content_uri=gcs_uri,
         type=enums.Document.Type.PLAIN_TEXT)
-    # [END migration_document_gcs_uri]
+    # [END language_python_migration_document_gcs]
 
     # Detects sentiment in the document. You can also analyze HTML with:
     #   document.type == enums.Document.Type.HTML
     sentiment = client.analyze_sentiment(document).document_sentiment
 
     print('Score: {}'.format(sentiment.score))
     print('Magnitude: {}'.format(sentiment.magnitude))
-# [END def_sentiment_file]
+# [END language_sentiment_gcs]
 
 
-# [START def_entities_text]
+# [START language_entities_text]
 def entities_text(text):
     """Detects entities in the text."""
     client = language.LanguageServiceClient()
@@ -86,7 +86,7 @@ def entities_text(text):
         text = text.decode('utf-8')
 
     # Instantiates a plain text document.
-    # [START migration_analyze_entities]
+    # [START language_python_migration_entities_text]
     document = types.Document(
         content=text,
         type=enums.Document.Type.PLAIN_TEXT)
@@ -107,11 +107,11 @@ def entities_text(text):
         print(u'{:<16}: {}'.format('salience', entity.salience))
         print(u'{:<16}: {}'.format('wikipedia_url',
               entity.metadata.get('wikipedia_url', '-')))
-    # [END migration_analyze_entities]
-# [END def_entities_text]
+    # [END language_python_migration_entities_text]
+# [END language_entities_text]
 
 
-# [START def_entities_file]
+# [START language_entities_gcs]
 def entities_file(gcs_uri):
     """Detects entities in the file located in Google Cloud Storage."""
     client = language.LanguageServiceClient()
@@ -137,10 +137,10 @@ def entities_file(gcs_uri):
         print(u'{:<16}: {}'.format('salience', entity.salience))
         print(u'{:<16}: {}'.format('wikipedia_url',
               entity.metadata.get('wikipedia_url', '-')))
-# [END def_entities_file]
+# [END language_entities_gcs]
 
 
-# [START def_syntax_text]
+# [START language_syntax_text]
 def syntax_text(text):
     """Detects syntax in the text."""
     client = language.LanguageServiceClient()
@@ -149,7 +149,7 @@ def syntax_text(text):
         text = text.decode('utf-8')
 
     # Instantiates a plain text document.
-    # [START migration_analyze_syntax]
+    # [START language_python_migration_syntax_text]
     document = types.Document(
         content=text,
         type=enums.Document.Type.PLAIN_TEXT)
@@ -165,11 +165,11 @@ def syntax_text(text):
     for token in tokens:
         print(u'{}: {}'.format(pos_tag[token.part_of_speech.tag],
                                token.text.content))
-    # [END migration_analyze_syntax]
-# [END def_syntax_text]
+    # [END language_python_migration_syntax_text]
+# [END language_syntax_text]
 
 
-# [START def_syntax_file]
+# [START language_syntax_gcs]
 def syntax_file(gcs_uri):
     """Detects syntax in the file located in Google Cloud Storage."""
     client = language.LanguageServiceClient()
@@ -190,10 +190,10 @@ def syntax_file(gcs_uri):
     for token in tokens:
         print(u'{}: {}'.format(pos_tag[token.part_of_speech.tag],
                                token.text.content))
-# [END def_syntax_file]
+# [END language_syntax_gcs]
 
 
-# [START def_entity_sentiment_text]
+# [START language_entity_sentiment_text]
 def entity_sentiment_text(text):
     """Detects entity sentiment in the provided text."""
     client = language.LanguageServiceClient()
@@ -223,9 +223,10 @@ def entity_sentiment_text(text):
             print(u'  Type : {}'.format(mention.type))
         print(u'Salience: {}'.format(entity.salience))
         print(u'Sentiment: {}\n'.format(entity.sentiment))
-# [END def_entity_sentiment_text]
+# [END language_entity_sentiment_text]
 
 
+# [START language_entity_sentiment_gcs]
 def entity_sentiment_file(gcs_uri):
     """Detects entity sentiment in a Google Cloud Storage file."""
     client = language.LanguageServiceClient()
@@ -251,9 +252,10 @@ def entity_sentiment_file(gcs_uri):
             print(u'  Type : {}'.format(mention.type))
         print(u'Salience: {}'.format(entity.salience))
         print(u'Sentiment: {}\n'.format(entity.sentiment))
+# [END language_entity_sentiment_gcs]
 
 
-# [START def_classify_text]
+# [START language_classify_text]
 def classify_text(text):
     """Classifies content categories of the provided text."""
     client = language.LanguageServiceClient()
@@ -271,10 +273,10 @@ def classify_text(text):
         print(u'=' * 20)
         print(u'{:<16}: {}'.format('name', category.name))
         print(u'{:<16}: {}'.format('confidence', category.confidence))
-# [END def_classify_text]
+# [END language_classify_text]
 
 
-# [START def_classify_file]
+# [START language_classify_gcs]
 def classify_file(gcs_uri):
     """Classifies content categories of the text in a Google Cloud Storage
     file.
@@ -291,7 +293,7 @@ def classify_file(gcs_uri):
         print(u'=' * 20)
         print(u'{:<16}: {}'.format('name', category.name))
         print(u'{:<16}: {}'.format('confidence', category.confidence))
-# [END def_classify_file]
+# [END language_classify_gcs]
 
 
 if __name__ == '__main__':