Metadata-Version: 2.1
Name: gcloud
Version: 0.17.0
Summary: API Client library for Google Cloud
Home-page: https://github.com/GoogleCloudPlatform/gcloud-python
Author: Google Cloud Platform
Author-email: jjg+gcloud-python@google.com
License: Apache 2.0
Description: Google Cloud Python Client
        ==========================
        
            Python idiomatic client for `Google Cloud Platform`_ services.
        
        .. _Google Cloud Platform: https://cloud.google.com/
        
        |pypi| |build| |coverage| |versions|
        
        -  `Homepage`_
        -  `API Documentation`_
        
        .. _Homepage: https://googlecloudplatform.github.io/gcloud-python/
        .. _API Documentation: http://googlecloudplatform.github.io/gcloud-python/stable/
        
        This client supports the following Google Cloud Platform services:
        
        -  `Google Cloud Datastore`_
        -  `Google Cloud Storage`_
        -  `Google Cloud Pub/Sub`_
        -  `Google BigQuery`_
        -  `Google Cloud Resource Manager`_
        -  `Google Cloud Logging`_
        
        .. _Google Cloud Datastore: https://github.com/GoogleCloudPlatform/gcloud-python#google-cloud-datastore
        .. _Google Cloud Storage: https://github.com/GoogleCloudPlatform/gcloud-python#google-cloud-storage
        .. _Google Cloud Pub/Sub: https://github.com/GoogleCloudPlatform/gcloud-python#google-cloud-pubsub
        .. _Google BigQuery: https://github.com/GoogleCloudPlatform/gcloud-python#google-bigquery
        .. _Google Cloud Resource Manager: https://github.com/GoogleCloudPlatform/gcloud-python#google-cloud-resource-manager
        .. _Google Cloud Logging: https://github.com/GoogleCloudPlatform/gcloud-python#google-cloud-logging
        
        If you need support for other Google APIs, check out the
        `Google APIs Python Client library`_.
        
        .. _Google APIs Python Client library: https://github.com/google/google-api-python-client
        
        Quick Start
        -----------
        
        ::
        
            $ pip install --upgrade gcloud
        
        Example Applications
        --------------------
        
        -  `getting-started-python`_ - A sample and `tutorial`_ that demonstrates how to build a complete web application using Cloud Datastore, Cloud Storage, and Cloud Pub/Sub and deploy it to Google App Engine or Google Compute Engine.
        -  `gcloud-python-expenses-demo`_ - A sample expenses demo using Cloud Datastore and Cloud Storage
        
        .. _getting-started-python: https://github.com/GoogleCloudPlatform/getting-started-python
        .. _tutorial: https://cloud.google.com/python
        .. _gcloud-python-expenses-demo: https://github.com/GoogleCloudPlatform/gcloud-python-expenses-demo
        
        Authentication
        --------------
        
        With ``gcloud-python`` we try to make authentication as painless as possible.
        Check out the `Authentication section`_ in our documentation to learn more.
        You may also find the `authentication document`_ shared by all the ``gcloud-*``
        libraries to be helpful.
        
        .. _Authentication section: http://gcloud-python.readthedocs.org/en/latest/gcloud-auth.html
        .. _authentication document: https://github.com/GoogleCloudPlatform/gcloud-common/tree/master/authentication
        
        Google Cloud Datastore
        ----------------------
        
        Google `Cloud Datastore`_ (`Datastore API docs`_) is a fully managed, schemaless
        database for storing non-relational data. Cloud Datastore automatically scales
        with your users and supports ACID transactions, high availability of reads and
        writes, strong consistency for reads and ancestor queries, and eventual
        consistency for all other queries.
        
        .. _Cloud Datastore: https://cloud.google.com/datastore/docs
        .. _Datastore API docs: https://cloud.google.com/datastore/docs/apis/v1beta3/
        
        See the ``gcloud-python`` API `datastore documentation`_ to learn how to
        interact with the Cloud Datastore using this Client Library.
        
        .. _datastore documentation: https://googlecloudplatform.github.io/gcloud-python/stable/datastore-client.html
        
        See the `official Google Cloud Datastore documentation`_ for more details on how
        to activate Cloud Datastore for your project.
        
        .. _official Google Cloud Datastore documentation: https://cloud.google.com/datastore/docs/activate
        
        .. code:: python
        
            from gcloud import datastore
            # Create, populate and persist an entity
            entity = datastore.Entity(key=datastore.Key('EntityKind'))
            entity.update({
                'foo': u'bar',
                'baz': 1337,
                'qux': False,
            })
            # Then query for entities
            query = datastore.Query(kind='EntityKind')
            for result in query.fetch():
                print result
        
        Google Cloud Storage
        --------------------
        
        Google `Cloud Storage`_ (`Storage API docs`_) allows you to store data on Google
        infrastructure with very high reliability, performance and availability, and can
        be used to distribute large data objects to users via direct download.
        
        .. _Cloud Storage: https://cloud.google.com/storage/docs
        .. _Storage API docs: https://cloud.google.com/storage/docs/json_api/v1
        
        See the ``gcloud-python`` API `storage documentation`_ to learn how to connect
        to Cloud Storage using this Client Library.
        
        .. _storage documentation: https://googlecloudplatform.github.io/gcloud-python/stable/storage-client.html
        
        You need to create a Google Cloud Storage bucket to use this client library.
        Follow along with the `official Google Cloud Storage documentation`_ to learn
        how to create a bucket.
        
        .. _official Google Cloud Storage documentation: https://cloud.google.com/storage/docs/cloud-console#_creatingbuckets
        
        .. code:: python
        
            from gcloud import storage
            client = storage.Client()
            bucket = client.get_bucket('bucket-id-here')
            # Then do other things...
            blob = bucket.get_blob('remote/path/to/file.txt')
            print blob.download_as_string()
            blob.upload_from_string('New contents!')
            blob2 = bucket.blob('remote/path/storage.txt')
            blob2.upload_from_filename(filename='/local/path.txt')
        
        Google Cloud Pub/Sub
        --------------------
        
        Google `Cloud Pub/Sub`_ (`Pub/Sub API docs`_) is designed to provide reliable,
        many-to-many, asynchronous messaging between applications. Publisher
        applications can send messages to a ``topic`` and other applications can
        subscribe to that topic to receive the messages. By decoupling senders and
        receivers, Google Cloud Pub/Sub allows developers to communicate between
        independently written applications.
        
        .. _Cloud Pub/Sub: https://cloud.google.com/pubsub/docs
        .. _Pub/Sub API docs: https://cloud.google.com/pubsub/reference/rest/
        
        See the ``gcloud-python`` API `Pub/Sub documentation`_ to learn how to connect
        to Cloud Pub/Sub using this Client Library.
        
        .. _Pub/Sub documentation: https://googlecloudplatform.github.io/gcloud-python/stable/pubsub-usage.html
        
        To get started with this API, you'll need to create
        
        .. code:: python
        
            from gcloud import pubsub
        
            client = pubsub.Client()
            topic = client.topic('topic_name')
            topic.create()
        
            topic.publish('this is the message_payload',
                          attr1='value1', attr2='value2')
        
        Google BigQuery
        ---------------
        
        Querying massive datasets can be time consuming and expensive without the
        right hardware and infrastructure. Google `BigQuery`_ (`BigQuery API docs`_)
        solves this problem by enabling super-fast, SQL-like queries against
        append-only tables, using the processing power of Google's infrastructure.
        
        .. _BigQuery: https://cloud.google.com/bigquery/what-is-bigquery
        .. _BigQuery API docs: https://cloud.google.com/bigquery/docs/reference/v2/
        
        This package is still being implemented, but it is almost complete!
        
        Load data from CSV
        ~~~~~~~~~~~~~~~~~~
        
        .. code:: python
        
            import csv
        
            from gcloud import bigquery
            from gcloud.bigquery import SchemaField
        
            client = bigquery.Client()
        
            dataset = client.dataset('dataset_name')
            dataset.create()  # API request
        
            SCHEMA = [
                SchemaField('full_name', 'STRING', mode='required'),
                SchemaField('age', 'INTEGER', mode='required'),
            ]
            table = dataset.table('table_name', SCHEMA)
            table.create()
        
            with open('csv_file', 'rb') as readable:
                table.upload_from_file(
                    readable, source_format='CSV', skip_leading_rows=1)
        
        Perform a synchronous query
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        .. code:: python
        
            # Perform a synchronous query.
            QUERY = (
                'SELECT name FROM [bigquery-public-data:usa_names.usa_1910_2013] '
                'WHERE state = "TX"')
            query = client.run_sync_query('%s LIMIT 100' % QUERY)
            query.timeout_ms = TIMEOUT_MS
            query.run()
        
            for row in query.rows:
                print row
        
        
        See the ``gcloud-python`` API `BigQuery documentation`_ to learn how to connect
        to BigQuery using this Client Library.
        
        .. _BigQuery documentation: https://googlecloudplatform.github.io/gcloud-python/stable/bigquery-usage.html
        
        Google Cloud Resource Manager
        -----------------------------
        
        The Cloud `Resource Manager`_ API (`Resource Manager API docs`_) provides
        methods that you can use to programmatically manage your projects in the
        Google Cloud Platform.
        
        .. _Resource Manager: https://cloud.google.com/resource-manager/
        .. _Resource Manager API docs: https://cloud.google.com/resource-manager/reference/rest/
        
        See the ``gcloud-python`` API `Resource Manager documentation`_ to learn how to
        manage projects using this Client Library.
        
        .. _Resource Manager documentation: https://googlecloudplatform.github.io/gcloud-python/stable/resource-manager-api.html
        
        Google Cloud Logging
        --------------------
        
        `Stackdriver Logging`_ API (`Logging API docs`_) allows you to store, search,
        analyze, monitor, and alert on log data and events from Google Cloud Platform.
        
        .. _Stackdriver Logging: https://cloud.google.com/logging/
        .. _Logging API docs: https://cloud.google.com/logging/docs/
        
        .. code:: python
        
            from gcloud import logging
            client = logging.Client()
            logger = client.logger('log_name')
            logger.log_text("A simple entry")  # API call
        
        Example of fetching entries:
        
        .. code:: python
        
            entries, token = logger.list_entries()
            for entry in entries:
                print entry.payload
        
        See the ``gcloud-python`` API `logging documentation`_ to learn how to connect
        to Cloud logging using this Client Library.
        
        .. _logging documentation: https://googlecloudplatform.github.io/gcloud-python/stable/logging-usage.html
        
        Contributing
        ------------
        
        Contributions to this library are always welcome and highly encouraged.
        
        See `CONTRIBUTING`_ for more information on how to get started.
        
        .. _CONTRIBUTING: https://github.com/GoogleCloudPlatform/gcloud-python/blob/master/CONTRIBUTING.rst
        
        License
        -------
        
        Apache 2.0 - See `LICENSE`_ for more information.
        
        .. _LICENSE: https://github.com/GoogleCloudPlatform/gcloud-python/blob/master/LICENSE
        
        .. |build| image:: https://travis-ci.org/GoogleCloudPlatform/gcloud-python.svg?branch=master
           :target: https://travis-ci.org/GoogleCloudPlatform/gcloud-python
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           :target: https://pypi.python.org/pypi/gcloud
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Platform: Posix; MacOS X; Windows
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Topic :: Internet
Provides-Extra: grpc