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Jon Wayne Parrott
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Merge pull request GoogleCloudPlatform#593 from GoogleCloudPlatform/nl15
Language API changes
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‎language/api/README.rst

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.. This file is automatically generated. Do not edit this file directly.
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Google Cloud Natural Language API Python Samples
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===============================================================================
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This directory contains samples for Google Cloud Natural Language API. The `Google Cloud Natural Language API`_ provides natural language understanding technologies to developers, including sentiment analysis, entity recognition, and syntax analysis. This API is part of the larger Cloud Machine Learning API.
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.. _Google Cloud Natural Language API: https://cloud.google.com/natural-language/docs/
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Setup
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-------------------------------------------------------------------------------
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Authentication
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++++++++++++++
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Authentication is typically done through `Application Default Credentials`_,
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which means you do not have to change the code to authenticate as long as
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your environment has credentials. You have a few options for setting up
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authentication:
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#. When running locally, use the `Google Cloud SDK`_
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.. code-block:: bash
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gcloud beta auth application-default login
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#. When running on App Engine or Compute Engine, credentials are already
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set-up. However, you may need to configure your Compute Engine instance
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with `additional scopes`_.
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#. You can create a `Service Account key file`_. This file can be used to
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authenticate to Google Cloud Platform services from any environment. To use
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the file, set the ``GOOGLE_APPLICATION_CREDENTIALS`` environment variable to
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the path to the key file, for example:
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.. code-block:: bash
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export GOOGLE_APPLICATION_CREDENTIALS=/path/to/service_account.json
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.. _Application Default Credentials: https://cloud.google.com/docs/authentication#getting_credentials_for_server-centric_flow
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.. _additional scopes: https://cloud.google.com/compute/docs/authentication#using
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.. _Service Account key file: https://developers.google.com/identity/protocols/OAuth2ServiceAccount#creatinganaccount
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Install Dependencies
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++++++++++++++++++++
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#. Install `pip`_ and `virtualenv`_ if you do not already have them.
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#. Create a virtualenv. Samples are compatible with Python 2.7 and 3.4+.
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.. code-block:: bash
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$ virtualenv env
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$ source env/bin/activate
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#. Install the dependencies needed to run the samples.
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.. code-block:: bash
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$ pip install -r requirements.txt
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.. _pip: https://pip.pypa.io/
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.. _virtualenv: https://virtualenv.pypa.io/
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Samples
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-------------------------------------------------------------------------------
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Analyze syntax
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+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
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To run this sample:
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.. code-block:: bash
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$ python analyze.py
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usage: analyze.py [-h] {entities,sentiment,syntax} text
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Analyzes text using the Google Cloud Natural Language API.
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positional arguments:
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{entities,sentiment,syntax}
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text
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optional arguments:
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-h, --help show this help message and exit
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.. _Google Cloud SDK: https://cloud.google.com/sdk/

‎language/api/analyze.py

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['https://www.googleapis.com/auth/cloud-platform'])
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http = httplib2.Http()
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scoped_credentials.authorize(http)
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return discovery.build('language', 'v1beta1', http=http)
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return discovery.build('language', 'v1',
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http=http,
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credentials=credentials)
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def get_native_encoding_type():
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'type': 'PLAIN_TEXT',
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'content': text,
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},
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'encodingType': encoding,
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'encoding_type': encoding,
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}
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service = get_service()
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return response
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def analyze_sentiment(text):
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def analyze_sentiment(text, encoding='UTF32'):
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body = {
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'document': {
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'type': 'PLAIN_TEXT',
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'content': text,
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}
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},
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'encoding_type': encoding
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}
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service = get_service()
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'type': 'PLAIN_TEXT',
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'content': text,
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},
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'features': {
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'extract_syntax': True,
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},
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'encodingType': encoding,
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'encoding_type': encoding
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}
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service = get_service()
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request = service.documents().annotateText(body=body)
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request = service.documents().analyzeSyntax(body=body)
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response = request.execute()
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return response
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if args.command == 'entities':
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result = analyze_entities(args.text, get_native_encoding_type())
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elif args.command == 'sentiment':
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result = analyze_sentiment(args.text)
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result = analyze_sentiment(args.text, get_native_encoding_type())
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elif args.command == 'syntax':
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result = analyze_syntax(args.text, get_native_encoding_type())
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‎language/api/analyze_test.py

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'your face is really ugly and i hate it.')
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sentiment = result['documentSentiment']
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assert sentiment['polarity'] < 0
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assert sentiment['score'] < 0
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assert sentiment['magnitude'] < 1
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result = analyze.analyze_sentiment(
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'cheerio, mate - I greatly admire the pallor of your visage, and your '
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'angle of repose leaves little room for improvement.')
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sentiment = result['documentSentiment']
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assert sentiment['polarity'] > 0
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assert sentiment['score'] > 0
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assert sentiment['magnitude'] < 1
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‎language/cloud-client/README.rst

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.. This file is automatically generated. Do not edit this file directly.
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Google Cloud Natural Language API Python Samples
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===============================================================================
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This directory contains samples for Google Cloud Natural Language API. The `Google Cloud Natural Language API`_ provides natural language understanding technologies to developers, including sentiment analysis, entity recognition, and syntax analysis. This API is part of the larger Cloud Machine Learning API.
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.. _Google Cloud Natural Language API: https://cloud.google.com/natural-language/docs/
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Setup
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-------------------------------------------------------------------------------
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Authentication
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++++++++++++++
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Authentication is typically done through `Application Default Credentials`_,
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which means you do not have to change the code to authenticate as long as
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your environment has credentials. You have a few options for setting up
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authentication:
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#. When running locally, use the `Google Cloud SDK`_
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.. code-block:: bash
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gcloud beta auth application-default login
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#. When running on App Engine or Compute Engine, credentials are already
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set-up. However, you may need to configure your Compute Engine instance
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with `additional scopes`_.
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#. You can create a `Service Account key file`_. This file can be used to
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authenticate to Google Cloud Platform services from any environment. To use
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the file, set the ``GOOGLE_APPLICATION_CREDENTIALS`` environment variable to
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the path to the key file, for example:
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.. code-block:: bash
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export GOOGLE_APPLICATION_CREDENTIALS=/path/to/service_account.json
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.. _Application Default Credentials: https://cloud.google.com/docs/authentication#getting_credentials_for_server-centric_flow
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.. _additional scopes: https://cloud.google.com/compute/docs/authentication#using
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.. _Service Account key file: https://developers.google.com/identity/protocols/OAuth2ServiceAccount#creatinganaccount
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Install Dependencies
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++++++++++++++++++++
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#. Install `pip`_ and `virtualenv`_ if you do not already have them.
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#. Create a virtualenv. Samples are compatible with Python 2.7 and 3.4+.
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.. code-block:: bash
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$ virtualenv env
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$ source env/bin/activate
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#. Install the dependencies needed to run the samples.
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.. code-block:: bash
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$ pip install -r requirements.txt
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.. _pip: https://pip.pypa.io/
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.. _virtualenv: https://virtualenv.pypa.io/
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Samples
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-------------------------------------------------------------------------------
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Quickstart
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+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
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To run this sample:
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.. code-block:: bash
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$ python quickstart.py
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The client library
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-------------------------------------------------------------------------------
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This sample uses the `Google Cloud Client Library for Python`_.
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You can read the documentation for more details on API usage and use GitHub
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to `browse the source`_ and `report issues`_.
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.. Google Cloud Client Library for Python:
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https://googlecloudplatform.github.io/google-cloud-python/
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.. browse the source:
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https://github.com/GoogleCloudPlatform/google-cloud-python
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.. report issues:
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https://github.com/GoogleCloudPlatform/google-cloud-python/issues
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.. _Google Cloud SDK: https://cloud.google.com/sdk/

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