Update readme (#1124)

* update readme

* keep entity sentiment in v1beta2 as well

* update readme

Author: dizcology

language/cloud-client/v1/README.rst

@@ -76,7 +76,7 @@ To run this sample:
     $ python snippets.py
 
     usage: snippets.py [-h]
-                       {sentiment-text,sentiment-file,entities-text,entities-file,syntax-text,syntax-file}
+                       {sentiment-entities-text,sentiment-entities-file,sentiment-text,sentiment-file,entities-text,entities-file,syntax-text,syntax-file}
                        ...
     
     This application demonstrates how to perform basic operations with the
@@ -86,7 +86,12 @@ To run this sample:
     https://cloud.google.com/natural-language/docs.
     
     positional arguments:
-      {sentiment-text,sentiment-file,entities-text,entities-file,syntax-text,syntax-file}
+      {sentiment-entities-text,sentiment-entities-file,sentiment-text,sentiment-file,entities-text,entities-file,syntax-text,syntax-file}
+        sentiment-entities-text
+                            Detects entity sentiment in the provided text.
+        sentiment-entities-file
+                            Detects entity sentiment in a Google Cloud Storage
+                            file.
         sentiment-text      Detects sentiment in the text.
         sentiment-file      Detects sentiment in the file located in Google Cloud
                             Storage.

language/cloud-client/v1beta2/README.rst

@@ -76,7 +76,7 @@ To run this sample:
     $ python snippets.py
 
     usage: snippets.py [-h]
-                       {sentiment-entities-text,sentiment-entities-file,sentiment-text,sentiment-file,entities-text,entities-file,syntax-text,syntax-file}
+                       {classify-text,classify-file,sentiment-entities-text,sentiment-entities-file,sentiment-text,sentiment-file,entities-text,entities-file,syntax-text,syntax-file}
                        ...
     
     This application demonstrates how to perform basic operations with the
@@ -86,7 +86,10 @@ To run this sample:
     https://cloud.google.com/natural-language/docs.
     
     positional arguments:
-      {sentiment-entities-text,sentiment-entities-file,sentiment-text,sentiment-file,entities-text,entities-file,syntax-text,syntax-file}
+      {classify-text,classify-file,sentiment-entities-text,sentiment-entities-file,sentiment-text,sentiment-file,entities-text,entities-file,syntax-text,syntax-file}
+        classify-text       Classifies content categories of the provided text.
+        classify-file       Classifies content categories of the text in a Google
+                            Cloud Storage file.
         sentiment-entities-text
                             Detects entity sentiment in the provided text.
         sentiment-entities-file

language/cloud-client/v1beta2/snippets.py

@@ -22,6 +22,7 @@
 """
 
 import argparse
+import sys
 
 # [START beta_import]
 from google.cloud import language_v1beta2
@@ -125,6 +126,66 @@ def entities_file(gcs_uri):
               entity.metadata.get('wikipedia_url', '-')))
 
 
+# [START def_entity_sentiment_text]
+def entity_sentiment_text(text):
+    """Detects entity sentiment in the provided text."""
+    client = language_v1beta2.LanguageServiceClient()
+
+    if isinstance(text, six.binary_type):
+        text = text.decode('utf-8')
+
+    document = types.Document(
+        content=text.encode('utf-8'),
+        type=enums.Document.Type.PLAIN_TEXT)
+
+    # Detect and send native Python encoding to receive correct word offsets.
+    encoding = enums.EncodingType.UTF32
+    if sys.maxunicode == 65535:
+        encoding = enums.EncodingType.UTF16
+
+    result = client.analyze_entity_sentiment(document, encoding)
+
+    for entity in result.entities:
+        print('Mentions: ')
+        print(u'Name: "{}"'.format(entity.name))
+        for mention in entity.mentions:
+            print(u'  Begin Offset : {}'.format(mention.text.begin_offset))
+            print(u'  Content : {}'.format(mention.text.content))
+            print(u'  Magnitude : {}'.format(mention.sentiment.magnitude))
+            print(u'  Sentiment : {}'.format(mention.sentiment.score))
+            print(u'  Type : {}'.format(mention.type))
+        print(u'Salience: {}'.format(entity.salience))
+        print(u'Sentiment: {}\n'.format(entity.sentiment))
+# [END def_entity_sentiment_text]
+
+
+def entity_sentiment_file(gcs_uri):
+    """Detects entity sentiment in a Google Cloud Storage file."""
+    client = language_v1beta2.LanguageServiceClient()
+
+    document = types.Document(
+        gcs_content_uri=gcs_uri,
+        type=enums.Document.Type.PLAIN_TEXT)
+
+    # Detect and send native Python encoding to receive correct word offsets.
+    encoding = enums.EncodingType.UTF32
+    if sys.maxunicode == 65535:
+        encoding = enums.EncodingType.UTF16
+
+    result = client.analyze_entity_sentiment(document, encoding)
+
+    for entity in result.entities:
+        print(u'Name: "{}"'.format(entity.name))
+        for mention in entity.mentions:
+            print(u'  Begin Offset : {}'.format(mention.text.begin_offset))
+            print(u'  Content : {}'.format(mention.text.content))
+            print(u'  Magnitude : {}'.format(mention.sentiment.magnitude))
+            print(u'  Sentiment : {}'.format(mention.sentiment.score))
+            print(u'  Type : {}'.format(mention.type))
+        print(u'Salience: {}'.format(entity.salience))
+        print(u'Sentiment: {}\n'.format(entity.sentiment))
+
+
 def syntax_text(text):
     """Detects syntax in the text."""
     client = language_v1beta2.LanguageServiceClient()
@@ -174,7 +235,7 @@ def syntax_file(gcs_uri):
 
 # [START def_classify_text]
 def classify_text(text):
-    """Classifies the provided text."""
+    """Classifies content categories of the provided text."""
     # [START beta_client]
     client = language_v1beta2.LanguageServiceClient()
     # [END beta_client]
@@ -197,7 +258,9 @@ def classify_text(text):
 
 # [START def_classify_file]
 def classify_file(gcs_uri):
-    """Classifies the text in a Google Cloud Storage file."""
+    """Classifies content categories of the text in a Google Cloud Storage
+    file.
+    """
     client = language_v1beta2.LanguageServiceClient()
 
     document = types.Document(
@@ -227,6 +290,14 @@ def classify_file(gcs_uri):
         'classify-file', help=classify_file.__doc__)
     classify_text_parser.add_argument('gcs_uri')
 
+    sentiment_entities_text_parser = subparsers.add_parser(
+        'sentiment-entities-text', help=entity_sentiment_text.__doc__)
+    sentiment_entities_text_parser.add_argument('text')
+
+    sentiment_entities_file_parser = subparsers.add_parser(
+        'sentiment-entities-file', help=entity_sentiment_file.__doc__)
+    sentiment_entities_file_parser.add_argument('gcs_uri')
+
     sentiment_text_parser = subparsers.add_parser(
         'sentiment-text', help=sentiment_text.__doc__)
     sentiment_text_parser.add_argument('text')
@@ -265,6 +336,10 @@ def classify_file(gcs_uri):
         syntax_text(args.text)
     elif args.command == 'syntax-file':
         syntax_file(args.gcs_uri)
+    elif args.command == 'sentiment-entities-text':
+        entity_sentiment_text(args.text)
+    elif args.command == 'sentiment-entities-file':
+        entity_sentiment_file(args.gcs_uri)
     elif args.command == 'classify-text':
         classify_text(args.text)
     elif args.command == 'classify-file':

language/cloud-client/v1beta2/snippets_test.py

@@ -69,6 +69,26 @@ def test_syntax_file(capsys):
     assert 'NOUN: President' in out
 
 
+def test_sentiment_entities_text(capsys):
+    snippets.entity_sentiment_text(
+        'President Obama is speaking at the White House.')
+    out, _ = capsys.readouterr()
+    assert 'Content : White House' in out
+
+
+def test_sentiment_entities_file(capsys):
+    snippets.entity_sentiment_file(TEST_FILE_URL)
+    out, _ = capsys.readouterr()
+    assert 'Content : White House' in out
+
+
+def test_sentiment_entities_utf(capsys):
+    snippets.entity_sentiment_text(
+        'foo→bar')
+    out, _ = capsys.readouterr()
+    assert 'Begin Offset : 4' in out
+
+
 def test_classify_text(capsys):
     snippets.classify_text(
         'Android is a mobile operating system developed by Google, '