{ "info": { "author": "Google Cloud Platform", "author_email": "jjg+gcloud-python at google com", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Intended Audience :: Developers", "License :: OSI Approved :: Apache Software License", "Operating System :: OS Independent", "Programming Language :: Python :: 2", "Programming Language :: Python :: 2.6", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.4", "Programming Language :: Python :: 3.5", "Topic :: Internet" ], "description": "Google Cloud Python Client\n==========================\n\n Python idiomatic client for `Google Cloud Platform`_ services.\n\n.. _Google Cloud Platform: https://cloud.google.com/\n\n|pypi| |versions|\n\n``google-cloud``\n----------------\n\n**Warning**: This package has moved. It has been renamed to\n`google-cloud on PyPI`_. No new releases will be made for\n``gcloud``.\n\n.. _google-cloud on PyPI: https://pypi.python.org/pypi/google-cloud\n\nOverview\n--------\n\n- `Homepage`_\n- `API Documentation`_\n\n.. _Homepage: https://googlecloudplatform.github.io/gcloud-python/\n.. _API Documentation: http://googlecloudplatform.github.io/gcloud-python/stable/\n\nThis client supports the following Google Cloud Platform services:\n\n- Google Cloud `Datastore`_\n- Google Cloud `Storage`_\n- Google Cloud `Pub/Sub`_\n- Google `BigQuery`_\n- Google Cloud `Resource Manager`_\n- Google `Stackdriver Logging`_\n\n.. _Datastore: https://github.com/GoogleCloudPlatform/gcloud-python#google-cloud-datastore\n.. _Storage: https://github.com/GoogleCloudPlatform/gcloud-python#google-cloud-storage\n.. _Pub/Sub: https://github.com/GoogleCloudPlatform/gcloud-python#google-cloud-pubsub\n.. _BigQuery: https://github.com/GoogleCloudPlatform/gcloud-python#google-bigquery\n.. _Resource Manager: https://github.com/GoogleCloudPlatform/gcloud-python#google-cloud-resource-manager\n.. _Stackdriver Logging: https://github.com/GoogleCloudPlatform/gcloud-python#google-cloud-logging\n\nIf you need support for other Google APIs, check out the\n`Google APIs Python Client library`_.\n\n.. _Google APIs Python Client library: https://github.com/google/google-api-python-client\n\nQuick Start\n-----------\n\n::\n\n $ pip install --upgrade gcloud\n\nExample Applications\n--------------------\n\n- `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.\n- `gcloud-python-expenses-demo`_ - A sample expenses demo using Cloud Datastore and Cloud Storage\n\n.. _getting-started-python: https://github.com/GoogleCloudPlatform/getting-started-python\n.. _tutorial: https://cloud.google.com/python\n.. _gcloud-python-expenses-demo: https://github.com/GoogleCloudPlatform/gcloud-python-expenses-demo\n\nAuthentication\n--------------\n\nWith ``gcloud-python`` we try to make authentication as painless as possible.\nCheck out the `Authentication section`_ in our documentation to learn more.\nYou may also find the `authentication document`_ shared by all the ``gcloud-*``\nlibraries to be helpful.\n\n.. _Authentication section: http://gcloud-python.readthedocs.org/en/latest/gcloud-auth.html\n.. _authentication document: https://github.com/GoogleCloudPlatform/gcloud-common/tree/master/authentication\n\nGoogle Cloud Datastore\n----------------------\n\nGoogle `Cloud Datastore`_ (`Datastore API docs`_) is a fully managed, schemaless\ndatabase for storing non-relational data. Cloud Datastore automatically scales\nwith your users and supports ACID transactions, high availability of reads and\nwrites, strong consistency for reads and ancestor queries, and eventual\nconsistency for all other queries.\n\n.. _Cloud Datastore: https://cloud.google.com/datastore/docs\n.. _Datastore API docs: https://cloud.google.com/datastore/docs/apis/v1beta3/\n\nSee the ``gcloud-python`` API `datastore documentation`_ to learn how to\ninteract with the Cloud Datastore using this Client Library.\n\n.. _datastore documentation: https://googlecloudplatform.github.io/gcloud-python/stable/datastore-client.html\n\nSee the `official Google Cloud Datastore documentation`_ for more details on how\nto activate Cloud Datastore for your project.\n\n.. _official Google Cloud Datastore documentation: https://cloud.google.com/datastore/docs/activate\n\n.. code:: python\n\n from gcloud import datastore\n # Create, populate and persist an entity\n entity = datastore.Entity(key=datastore.Key('EntityKind'))\n entity.update({\n 'foo': u'bar',\n 'baz': 1337,\n 'qux': False,\n })\n # Then query for entities\n query = datastore.Query(kind='EntityKind')\n for result in query.fetch():\n print result\n\nGoogle Cloud Storage\n--------------------\n\nGoogle `Cloud Storage`_ (`Storage API docs`_) allows you to store data on Google\ninfrastructure with very high reliability, performance and availability, and can\nbe used to distribute large data objects to users via direct download.\n\n.. _Cloud Storage: https://cloud.google.com/storage/docs\n.. _Storage API docs: https://cloud.google.com/storage/docs/json_api/v1\n\nSee the ``gcloud-python`` API `storage documentation`_ to learn how to connect\nto Cloud Storage using this Client Library.\n\n.. _storage documentation: https://googlecloudplatform.github.io/gcloud-python/stable/storage-client.html\n\nYou need to create a Google Cloud Storage bucket to use this client library.\nFollow along with the `official Google Cloud Storage documentation`_ to learn\nhow to create a bucket.\n\n.. _official Google Cloud Storage documentation: https://cloud.google.com/storage/docs/cloud-console#_creatingbuckets\n\n.. code:: python\n\n from gcloud import storage\n client = storage.Client()\n bucket = client.get_bucket('bucket-id-here')\n # Then do other things...\n blob = bucket.get_blob('remote/path/to/file.txt')\n print blob.download_as_string()\n blob.upload_from_string('New contents!')\n blob2 = bucket.blob('remote/path/storage.txt')\n blob2.upload_from_filename(filename='/local/path.txt')\n\nGoogle Cloud Pub/Sub\n--------------------\n\nGoogle `Cloud Pub/Sub`_ (`Pub/Sub API docs`_) is designed to provide reliable,\nmany-to-many, asynchronous messaging between applications. Publisher\napplications can send messages to a ``topic`` and other applications can\nsubscribe to that topic to receive the messages. By decoupling senders and\nreceivers, Google Cloud Pub/Sub allows developers to communicate between\nindependently written applications.\n\n.. _Cloud Pub/Sub: https://cloud.google.com/pubsub/docs\n.. _Pub/Sub API docs: https://cloud.google.com/pubsub/reference/rest/\n\nSee the ``gcloud-python`` API `Pub/Sub documentation`_ to learn how to connect\nto Cloud Pub/Sub using this Client Library.\n\n.. _Pub/Sub documentation: https://googlecloudplatform.github.io/gcloud-python/stable/pubsub-usage.html\n\nTo get started with this API, you'll need to create\n\n.. code:: python\n\n from gcloud import pubsub\n\n client = pubsub.Client()\n topic = client.topic('topic_name')\n topic.create()\n\n topic.publish('this is the message_payload',\n attr1='value1', attr2='value2')\n\nGoogle BigQuery\n---------------\n\nQuerying massive datasets can be time consuming and expensive without the\nright hardware and infrastructure. Google\n`BigQuery`__ (`BigQuery API docs`_)\nsolves this problem by enabling super-fast, SQL-like queries against\nappend-only tables, using the processing power of Google's infrastructure.\n\n.. _BQ-indirect: https://cloud.google.com/bigquery/what-is-bigquery\n.. _BigQuery API docs: https://cloud.google.com/bigquery/docs/reference/v2/\n__ `BQ-indirect`_\n\nThis package is still being implemented, but it is almost complete!\n\nLoad data from CSV\n~~~~~~~~~~~~~~~~~~\n\n.. code:: python\n\n import csv\n\n from gcloud import bigquery\n from gcloud.bigquery import SchemaField\n\n client = bigquery.Client()\n\n dataset = client.dataset('dataset_name')\n dataset.create() # API request\n\n SCHEMA = [\n SchemaField('full_name', 'STRING', mode='required'),\n SchemaField('age', 'INTEGER', mode='required'),\n ]\n table = dataset.table('table_name', SCHEMA)\n table.create()\n\n with open('csv_file', 'rb') as readable:\n table.upload_from_file(\n readable, source_format='CSV', skip_leading_rows=1)\n\nPerform a synchronous query\n~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n.. code:: python\n\n # Perform a synchronous query.\n QUERY = (\n 'SELECT name FROM [bigquery-public-data:usa_names.usa_1910_2013] '\n 'WHERE state = \"TX\"')\n query = client.run_sync_query('%s LIMIT 100' % QUERY)\n query.timeout_ms = TIMEOUT_MS\n query.run()\n\n for row in query.rows:\n print row\n\n\nSee the ``gcloud-python`` API `BigQuery documentation`_ to learn how to connect\nto BigQuery using this Client Library.\n\n.. _BigQuery documentation: https://googlecloudplatform.github.io/gcloud-python/stable/bigquery-usage.html\n\nGoogle Cloud Resource Manager\n-----------------------------\n\nThe Cloud `Resource Manager`__ API (`Resource Manager API docs`_) provides\nmethods that you can use to programmatically manage your projects in the\nGoogle Cloud Platform.\n\n.. _RM-indirect: https://cloud.google.com/resource-manager/\n.. _Resource Manager API docs: https://cloud.google.com/resource-manager/reference/rest/\n__ `RM-indirect`_\n\nSee the ``gcloud-python`` API `Resource Manager documentation`_ to learn how to\nmanage projects using this Client Library.\n\n.. _Resource Manager documentation: https://googlecloudplatform.github.io/gcloud-python/stable/resource-manager-api.html\n\nGoogle Stackdriver Logging\n--------------------------\n\n`Stackdriver Logging`__ API (`Logging API docs`_) allows you to store, search,\nanalyze, monitor, and alert on log data and events from Google Cloud Platform.\n\n.. _SL-indirect: https://cloud.google.com/logging/\n.. _Logging API docs: https://cloud.google.com/logging/docs/\n__ `SL-indirect`_\n\n.. code:: python\n\n from gcloud import logging\n client = logging.Client()\n logger = client.logger('log_name')\n logger.log_text(\"A simple entry\") # API call\n\nExample of fetching entries:\n\n.. code:: python\n\n entries, token = logger.list_entries()\n for entry in entries:\n print entry.payload\n\nSee the 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