Adding usage doc for Natural Language API.

googleapis · Aug 23, 2016 · d36ad4d · d36ad4d
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diff --git a/docs/index.rst b/docs/index.rst
@@ -148,6 +148,13 @@
 
   vision-usage
 
+.. toctree::
+  :maxdepth: 0
+  :hidden:
+  :caption: Natural Language
+
+  language-usage
+
 .. toctree::
   :maxdepth: 0
   :hidden:

diff --git a/docs/language-usage.rst b/docs/language-usage.rst
@@ -0,0 +1,279 @@
+Using the API
+=============
+
+The `Google Natural Language`_ API can be used to reveal the
+structure and meaning of text via powerful machine
+learning models. You can use it to extract information about
+people, places, events and much more, mentioned in text documents,
+news articles or blog posts. You can use it to understand
+sentiment about your product on social media or parse intent from
+customer conversations happening in a call center or a messaging
+app. You can analyze text uploaded in your request or integrate
+with your document storage on Google Cloud Storage.
+
+.. warning::
+
+   This is a Beta release of Google Cloud Natural Language API. This
+   API is not intended for real-time usage in critical applications.
+
+.. _Google Natural Language: https://cloud.google.com/natural-language/docs/getting-started
+
+Client
+------
+
+:class:`~gcloud.language.client.Client` objects provide a
+means to configure your application. Each instance holds
+both a ``project`` and an authenticated connection to the
+Natural Language service.
+
+For an overview of authentication in ``gcloud-python``, see
+:doc:`gcloud-auth`.
+
+Assuming your environment is set up as described in that document,
+create an instance of :class:`~gcloud.language.client.Client`.
+
+  .. code-block:: python
+
+     >>> from gcloud import language
+     >>> client = language.Client()
+
+By default the ``language`` is ``'en'`` and the ``encoding`` is
+UTF-8. To over-ride these values:
+
+  .. code-block:: python
+
+     >>> client = language.Client(language='es',
+     ...                          encoding=encoding=language.Encoding.UTF16)
+
+The encoding can be one of
+:attr:`Encoding.UTF8 <gcloud.language.document.Encoding.UTF8>`,
+:attr:`Encoding.UTF16 <gcloud.language.document.Encoding.UTF16>`, or
+:attr:`Encoding.UTF32 <gcloud.language.document.Encoding.UTF32>`.
+
+Methods
+-------
+
+The Google Natural Language API has three supported methods
+
+- `analyzeEntities`_
+- `analyzeSentiment`_
+- `annotateText`_
+
+and each method uses a `Document`_ for representing text. To
+create a :class:`~gcloud.language.document.Document`,
+
+  .. code-block:: python
+
+     >>> text_content = (
+     ...     'Google, headquartered in Mountain View, unveiled the '
+     ...     'new Android phone at the Consumer Electronic Show.  '
+     ...     'Sundar Pichai said in his keynote that users love '
+     ...     'their new Android phones.')
+     >>> document = client.document_from_text(text_content)
+
+By using :meth:`~gcloud.language.client.Client.document_from_text`,
+the document's type is plain text:
+
+  .. code-block:: python
+
+     >>> document.doc_type == language.Document.PLAIN_TEXT
+     True
+
+In addition, the document's language defaults to the language on
+the client
+
+  .. code-block:: python
+
+     >>> document.language
+     'en'
+     >>> document.language == client.language
+     True
+
+In addition, the
+:meth:`~gcloud.language.client.Client.document_from_html`,
+factory can be used to created an HTML document. In this
+method and the from text method, the language can be
+over-ridden:
+
+  .. code-block:: python
+
+     >>> html_content = """\
+     ... <html>
+     ...   <head>
+     ...     <title>El Tiempo de las Historias</time>
+     ...   </head>
+     ...   <body>
+     ...     <p>La vaca salt&oacute; sobre la luna.</p>
+     ...   </body>
+     ... </html>
+     ... """
+     >>> document = client.document_from_html(html_content,
+     ...                                      language='es')
+
+The ``language`` argument can be either ISO-639-1 or BCP-47 language
+codes; at the time, only English, Spanish, and Japanese `are supported`_.
+However, the ``analyzeSentiment`` method `only supports`_ English text.
+
+.. _are supported: https://cloud.google.com/natural-language/docs/
+.. _only supports: https://cloud.google.com/natural-language/reference/rest/v1beta1/documents/analyzeSentiment#body.request_body.FIELDS.document
+
+The document type (``doc_type``) value can be one of
+:attr:`Document.PLAIN_TEXT <gcloud.language.document.Document.PLAIN_TEXT>` or
+:attr:`Document.HTML <gcloud.language.document.Document.HTML>`.
+
+In addition to supplying the text / HTML content, a document can refer
+to content stored in `Google Cloud Storage`_. We can use the
+:meth:`~gcloud.language.client.Client.document_from_blob` method:
+
+  .. code-block:: python
+
+     >>> document = client.document_from_blob(bucket='my-text-bucket',
+     ...                                      blob='sentiment-me.txt')
+     >>> document.gcs_url
+     'gs://my-text-bucket/sentiment-me.txt'
+     >>> document.doc_type == language.Document.PLAIN_TEXT
+     True
+
+and the :meth:`~gcloud.language.client.Client.document_from_uri`
+method. In either case, the document type can be specified with
+the ``doc_type`` argument:
+
+  .. code-block:: python
+
+     >>> gcs_url = 'gs://my-text-bucket/sentiment-me.txt'
+     >>> document = client.document_from_uri(
+     ...     gcs_url, doc_type=language.Document.HTML)
+     >>> document.gcs_url == gcs_url
+     True
+     >>> document.doc_type == language.Document.HTML
+     True
+
+.. _analyzeEntities: https://cloud.google.com/natural-language/reference/rest/v1beta1/documents/analyzeEntities
+.. _analyzeSentiment: https://cloud.google.com/natural-language/reference/rest/v1beta1/documents/analyzeSentiment
+.. _annotateText: https://cloud.google.com/natural-language/reference/rest/v1beta1/documents/annotateText
+.. _Document: https://cloud.google.com/natural-language/reference/rest/v1beta1/Document
+.. _Google Cloud Storage: https://cloud.google.com/storage/
+
+Analyze Entities
+----------------
+
+The :meth:`~gcloud.language.document.Document.analyze_entities` method
+finds named entities (i.e. proper names) in the text and returns them
+as a :class:`list` of :class:`~gcloud.language.entity.Entity` objects.
+Each entity has a corresponding type, salience (prominence), associated
+metadata and other properties.
+
+  .. code-block:: python
+
+     >>> text_content = ("Michelangelo Caravaggio, Italian painter, is "
+     ...                 "known for 'The Calling of Saint Matthew'.")
+     >>> document = client.document(text_content)
+     >>> entities = document.analyze_entities()
+     >>> for entity in entities:
+     ...     print('=' * 20)
+     ...     print('    name: %s' % (entity.name,))
+     ...     print('    type: %s' % (entity.entity_type,))
+     ...     print('metadata: %s' % (entity.metadata,))
+     ...     print('salience: %s' % (entity.salience,))
+     ====================
+         name: Michelangelo Caravaggio
+         type: PERSON
+     metadata: {'wikipedia_url': 'http://en.wikipedia.org/wiki/Caravaggio'}
+     salience: 0.75942981
+     ====================
+         name: Italian
+         type: LOCATION
+     metadata: {'wikipedia_url': 'http://en.wikipedia.org/wiki/Italy'}
+     salience: 0.20193423
+     ====================
+         name: The Calling of Saint Matthew
+         type: WORK_OF_ART
+     metadata: {'wikipedia_url': 'http://en.wikipedia.org/wiki/index.html?curid=2838808'}
+     salience: 0.03863598
+
+Analyze Sentiment
+-----------------
+
+The :meth:`~gcloud.language.document.Document.analyze_sentiment` method
+analyzes the sentiment of the provided text and returns a
+:class:`~gcloud.language.sentiment.Sentiment`. Currently, this method
+only supports English text.
+
+  .. code-block:: python
+
+     >>> text_content = "Jogging isn't very fun."
+     >>> document = client.document(text_content)
+     >>> sentiment = document.analyze_sentiment()
+     >>> print(sentiment.polarity)
+     -1
+     >>> print(sentiment.magnitude)
+     0.8
+
+Annotate Text
+-------------
+
+The :meth:`~gcloud.language.document.Document.annotate_text` method
+analyzes a document and is intended for users who are familiar with
+machine learning and need in-depth text features to build upon.
+
+The method returns a named tuple with four entries:
+
+* ``sentences``: A :class:`list` of sentences in the text
+* ``tokens``: A :class:`list` of :class:`~gcloud.language.token.Token`
+  object (e.g. words, punctuation)
+* ``sentiment``: The :class:`~gcloud.language.sentiment.Sentiment` of
+  the text (as returned by
+  :meth:`~gcloud.language.document.Document.analyze_sentiment`)
+* ``entities``: :class:`list` of :class:`~gcloud.language.entity.Entity`
+  objects extracted from the text (as returned by
+  :meth:`~gcloud.language.document.Document.analyze_entities`)
+
+By default :meth:`~gcloud.language.document.Document.annotate_text` has
+three arguments ``include_syntax``, ``include_entities`` and
+``include_sentiment`` which are all :data:`True`. However, each of these
+`Features`_ can be selectively turned off by setting the corresponding
+arguments to :data:`False`.
+
+When ``include_syntax=False``, ``sentences`` and ``tokens`` in the
+response is :data:`None`. When ``include_sentiment``, ``sentiment`` in
+the response is :data:`None`. When ``include_entities``, ``entities`` in
+the response is :data:`None`.
+
+  .. code-block:: python
+
+     >>> text_content = 'The cow jumped over the Moon.'
+     >>> document = client.document(text_content)
+     >>> annotations = document.annotate_text()
+     >>> # Sentences present if include_syntax=True
+     >>> print(annotations.sentences)
+     ['The cow jumped over the Moon.']
+     >>> # Tokens present if include_syntax=True
+     >>> for token in annotations.tokens:
+     ...     msg = '%11s: %s' % (token.part_of_speech, token.text_content)
+     ...     print(msg)
+      DETERMINER: The
+            NOUN: cow
+            VERB: jumped
+      ADPOSITION: over
+      DETERMINER: the
+            NOUN: Moon
+     PUNCTUATION: .
+     >>> # Sentiment present if include_sentiment=True
+     >>> print(annotations.sentiment.polarity)
+     1
+     >>> print(annotations.sentiment.magnitude)
+     0.1
+     >>> # Entities present if include_entities=True
+     >>> for entity in annotations.entities:
+     ...     print('=' * 20)
+     ...     print('    name: %s' % (entity.name,))
+     ...     print('    type: %s' % (entity.entity_type,))
+     ...     print('metadata: %s' % (entity.metadata,))
+     ...     print('salience: %s' % (entity.salience,))
+     ====================
+         name: Moon
+         type: LOCATION
+     metadata: {'wikipedia_url': 'http://en.wikipedia.org/wiki/Natural_satellite'}
+     salience: 0.11793101
+
+.. _Features: https://cloud.google.com/natural-language/reference/rest/v1beta1/documents/annotateText#Features