chore: increase default timeout; update templates (via synth) (#16)

language/v1/language_classify_gcs.py

@@ -43,7 +43,6 @@ def sample_classify_text(gcs_content_uri):
 
     # gcs_content_uri = 'gs://cloud-samples-data/language/classify-entertainment.txt'
 
-    # [START language_python_migration_document_gcs]
     # Available types: PLAIN_TEXT, HTML
     type_ = enums.Document.Type.PLAIN_TEXT
 
@@ -52,7 +51,6 @@ def sample_classify_text(gcs_content_uri):
     # https://cloud.google.com/natural-language/docs/languages
     language = "en"
     document = {"gcs_content_uri": gcs_content_uri, "type": type_, "language": language}
-    # [END language_python_migration_document_gcs]
 
     response = client.classify_text(document)
     # Loop through classified categories returned from the API

language/v1/language_classify_text.py

@@ -41,7 +41,6 @@ def sample_classify_text(text_content):
 
     # text_content = 'That actor on TV makes movies in Hollywood and also stars in a variety of popular new TV shows.'
 
-    # [START language_python_migration_document_text]
     # Available types: PLAIN_TEXT, HTML
     type_ = enums.Document.Type.PLAIN_TEXT
 
@@ -50,7 +49,6 @@ def sample_classify_text(text_content):
     # https://cloud.google.com/natural-language/docs/languages
     language = "en"
     document = {"content": text_content, "type": type_, "language": language}
-    # [END language_python_migration_document_text]
 
     response = client.classify_text(document)
     # Loop through classified categories returned from the API

language/v1/language_entities_text.py

@@ -41,7 +41,6 @@ def sample_analyze_entities(text_content):
 
     # text_content = 'California is a state.'
 
-    # [START language_python_migration_entities_text]
     # Available types: PLAIN_TEXT, HTML
     type_ = enums.Document.Type.PLAIN_TEXT
 
@@ -77,7 +76,6 @@ def sample_analyze_entities(text_content):
             print(
                 u"Mention type: {}".format(enums.EntityMention.Type(mention.type).name)
             )
-    # [END language_python_migration_entities_text]
 
     # Get the language of the text, which will be the same as
     # the language specified in the request or, if not specified,

language/v1/language_sentiment_text.py

@@ -41,7 +41,6 @@ def sample_analyze_sentiment(text_content):
 
     # text_content = 'I am so happy and joyful.'
 
-    # [START language_python_migration_sentiment_text]
     # Available types: PLAIN_TEXT, HTML
     type_ = enums.Document.Type.PLAIN_TEXT
 
@@ -62,8 +61,6 @@ def sample_analyze_sentiment(text_content):
             response.document_sentiment.magnitude
         )
     )
-    # [END language_python_migration_sentiment_text]
-
     # Get sentiment for all sentences in the document
     for sentence in response.sentences:
         print(u"Sentence text: {}".format(sentence.text.content))

language/v1/language_syntax_text.py

@@ -50,7 +50,6 @@ def sample_analyze_syntax(text_content):
     language = "en"
     document = {"content": text_content, "type": type_, "language": language}
 
-    # [START language_python_migration_syntax_text]
     # Available values: NONE, UTF8, UTF16, UTF32
     encoding_type = enums.EncodingType.UTF8
 
@@ -64,7 +63,7 @@ def sample_analyze_syntax(text_content):
             u"Location of this token in overall document: {}".format(text.begin_offset)
         )
         # Get the part of speech information for this token.
-        # Parts of speech are as defined in:
+        # Parts of spech are as defined in:
         # http://www.lrec-conf.org/proceedings/lrec2012/pdf/274_Paper.pdf
         part_of_speech = token.part_of_speech
         # Get the tag, e.g. NOUN, ADJ for Adjective, et al.
@@ -73,8 +72,6 @@ def sample_analyze_syntax(text_content):
                 enums.PartOfSpeech.Tag(part_of_speech.tag).name
             )
         )
-        # [END language_python_migration_syntax_text]
-
         # Get the voice, e.g. ACTIVE or PASSIVE
         print(u"Voice: {}".format(enums.PartOfSpeech.Voice(part_of_speech.voice).name))
         # Get the tense, e.g. PAST, FUTURE, PRESENT, et al.