Move to google-cloud

appengine/flexible/datastore/main.py

@@ -18,7 +18,7 @@
 import socket
 
 from flask import Flask, request
-from gcloud import datastore
+from google.cloud import datastore
 
 
 app = Flask(__name__)

appengine/flexible/datastore/requirements.txt

@@ -1,4 +1,4 @@
 Flask==0.11.1
-gcloud==0.18.3
+google-cloud-datastore==0.20.0
 gunicorn==19.6.0
 oauth2client==3.0.0

appengine/flexible/django_cloudsql/requirements.txt

@@ -1,4 +1,4 @@
 Django==1.10.1
-mysqlclient==1.3.7
+mysqlclient==1.3.8
 wheel==0.30.0a0
 gunicorn==19.6.0

appengine/flexible/endpoints/requirements.txt

@@ -1,8 +1,6 @@
 Flask==0.11.1
 flask-cors==3.0.2
 gunicorn==19.6.0
-gcloud==0.18.3
 six==1.10.0
 pyyaml==3.12
 requests==2.11.1
-google-api-python-client==1.5.3

appengine/flexible/pubsub/main.py

@@ -19,7 +19,7 @@
 import os
 
 from flask import current_app, Flask, render_template, request
-from gcloud import pubsub
+from google.cloud import pubsub
 
 
 app = Flask(__name__)

appengine/flexible/pubsub/requirements.txt

@@ -1,4 +1,4 @@
 Flask==0.11.1
-gcloud==0.18.3
+google-cloud-pubsub==0.20.0
 gunicorn==19.6.0
 oauth2client==3.0.0

appengine/flexible/storage/main.py

@@ -17,7 +17,7 @@
 import os
 
 from flask import Flask, request
-from gcloud import storage
+from google.cloud import storage
 
 # [start config]
 app = Flask(__name__)

appengine/flexible/storage/requirements.txt

@@ -1,3 +1,3 @@
 Flask==0.11.1
-gcloud==0.18.3
+google-cloud-storage==0.20.0
 gunicorn==19.6.0

bigquery/cloud-client/async_query.py

@@ -27,7 +27,7 @@
 import time
 import uuid
 
-from gcloud import bigquery
+from google.cloud import bigquery
 
 
 def async_query(query):

bigquery/cloud-client/export_data_to_gcs.py

@@ -29,7 +29,7 @@
 import time
 import uuid
 
-from gcloud import bigquery
+from google.cloud import bigquery
 
 
 def export_data_to_gcs(dataset_name, table_name, destination):

bigquery/cloud-client/load_data_from_file.py

@@ -27,7 +27,7 @@
 
 import argparse
 import time
-from gcloud import bigquery
+from google.cloud import bigquery
 
 
 def load_data_from_file(dataset_name, table_name, source_file_name):

bigquery/cloud-client/load_data_from_gcs.py

@@ -29,7 +29,7 @@
 import time
 import uuid
 
-from gcloud import bigquery
+from google.cloud import bigquery
 
 
 def load_data_from_gcs(dataset_name, table_name, source):

bigquery/cloud-client/requirements.txt

@@ -1 +1 @@
-gcloud==0.18.3
+google-cloud-bigquery==0.20.0

bigquery/cloud-client/snippets.py

@@ -28,8 +28,8 @@
 import time
 import uuid
 
-from gcloud import bigquery
-import gcloud.bigquery.job
+from google.cloud import bigquery
+import google.cloud.bigquery.job
 
 
 def list_projects():
@@ -145,7 +145,7 @@ def list_rows(dataset_name, table_name, project=None):
             break
 
     # Use format to create a simple table.
-    format_string = '{:<16} ' * len(table.schema)
+    format_string = '{!s:<16} ' * len(table.schema)
 
     # Print schema field names
     field_names = [field.name for field in table.schema]
@@ -177,7 +177,7 @@ def copy_table(dataset_name, table_name, new_table_name, project=None):
 
     # Create the table if it doesn't exist.
     job.create_disposition = (
-        gcloud.bigquery.job.CreateDisposition.CREATE_IF_NEEDED)
+        google.cloud.bigquery.job.CreateDisposition.CREATE_IF_NEEDED)
 
     # Start the job.
     job.begin()

bigquery/cloud-client/snippets_test.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from gcloud import bigquery
+from google.cloud import bigquery
 import pytest
 
 import snippets

bigquery/cloud-client/stream_data.py

@@ -29,7 +29,7 @@
 import json
 from pprint import pprint
 
-from gcloud import bigquery
+from google.cloud import bigquery
 
 
 def stream_data(dataset_name, table_name, json_data):

bigquery/cloud-client/sync_query.py

@@ -26,7 +26,7 @@
 import argparse
 
 # [START sync_query]
-from gcloud import bigquery
+from google.cloud import bigquery
 
 
 def sync_query(query):

bigquery/dml/insert_sql.py

@@ -33,7 +33,7 @@
 # [START insert_sql]
 import argparse
 
-from gcloud import bigquery
+from google.cloud import bigquery
 
 
 def insert_sql(project, default_dataset, sql_path):

bigquery/dml/requirements.txt

@@ -1,5 +1,5 @@
 flake8==3.0.4
-gcloud==0.18.3
+google-cloud-bigquery==0.20.0
 PyMySQL==0.7.9
 six==1.10.0
 SQLAlchemy==1.1.0b3

bigtable/hello/main.py

@@ -26,79 +26,79 @@
 
 import argparse
 
-from gcloud import bigtable
+from google.cloud import bigtable
 
 
 def main(project_id, instance_id, table_id):
     # [START connecting_to_bigtable]
     # The client must be created with admin=True because it will create a
     # table.
-    with bigtable.Client(project=project_id, admin=True) as client:
-        instance = client.instance(instance_id)
-        # [END connecting_to_bigtable]
-
-        # [START creating_a_table]
-        print('Creating the {} table.'.format(table_id))
-        table = instance.table(table_id)
-        table.create()
-        column_family_id = 'cf1'
-        cf1 = table.column_family(column_family_id)
-        cf1.create()
-        # [END creating_a_table]
-
-        # [START writing_rows]
-        print('Writing some greetings to the table.')
-        column_id = 'greeting'.encode('utf-8')
-        greetings = [
-            'Hello World!',
-            'Hello Cloud Bigtable!',
-            'Hello Python!',
-        ]
-
-        for i, value in enumerate(greetings):
-            # Note: This example uses sequential numeric IDs for simplicity,
-            # but this can result in poor performance in a production
-            # application.  Since rows are stored in sorted order by key,
-            # sequential keys can result in poor distribution of operations
-            # across nodes.
-            #
-            # For more information about how to design a Bigtable schema for
-            # the best performance, see the documentation:
-            #
-            #     https://cloud.google.com/bigtable/docs/schema-design
-            row_key = 'greeting{}'.format(i)
-            row = table.row(row_key)
-            row.set_cell(
-                column_family_id,
-                column_id,
-                value.encode('utf-8'))
-            row.commit()
-        # [END writing_rows]
-
-        # [START getting_a_row]
-        print('Getting a single greeting by row key.')
-        key = 'greeting0'
-        row = table.read_row(key.encode('utf-8'))
-        value = row.cells[column_family_id][column_id][0].value
-        print('\t{}: {}'.format(key, value.decode('utf-8')))
-        # [END getting_a_row]
-
-        # [START scanning_all_rows]
-        print('Scanning for all greetings:')
-        partial_rows = table.read_rows()
-        partial_rows.consume_all()
-
-        for row_key, row in partial_rows.rows.items():
-            key = row_key.decode('utf-8')
-            cell = row.cells[column_family_id][column_id][0]
-            value = cell.value.decode('utf-8')
-            print('\t{}: {}'.format(key, value))
-        # [END scanning_all_rows]
-
-        # [START deleting_a_table]
-        print('Deleting the {} table.'.format(table_id))
-        table.delete()
-        # [END deleting_a_table]
+    client = bigtable.Client(project=project_id, admin=True)
+    instance = client.instance(instance_id)
+    # [END connecting_to_bigtable]
+
+    # [START creating_a_table]
+    print('Creating the {} table.'.format(table_id))
+    table = instance.table(table_id)
+    table.create()
+    column_family_id = 'cf1'
+    cf1 = table.column_family(column_family_id)
+    cf1.create()
+    # [END creating_a_table]
+
+    # [START writing_rows]
+    print('Writing some greetings to the table.')
+    column_id = 'greeting'.encode('utf-8')
+    greetings = [
+        'Hello World!',
+        'Hello Cloud Bigtable!',
+        'Hello Python!',
+    ]
+
+    for i, value in enumerate(greetings):
+        # Note: This example uses sequential numeric IDs for simplicity,
+        # but this can result in poor performance in a production
+        # application.  Since rows are stored in sorted order by key,
+        # sequential keys can result in poor distribution of operations
+        # across nodes.
+        #
+        # For more information about how to design a Bigtable schema for
+        # the best performance, see the documentation:
+        #
+        #     https://cloud.google.com/bigtable/docs/schema-design
+        row_key = 'greeting{}'.format(i)
+        row = table.row(row_key)
+        row.set_cell(
+            column_family_id,
+            column_id,
+            value.encode('utf-8'))
+        row.commit()
+    # [END writing_rows]
+
+    # [START getting_a_row]
+    print('Getting a single greeting by row key.')
+    key = 'greeting0'
+    row = table.read_row(key.encode('utf-8'))
+    value = row.cells[column_family_id][column_id][0].value
+    print('\t{}: {}'.format(key, value.decode('utf-8')))
+    # [END getting_a_row]
+
+    # [START scanning_all_rows]
+    print('Scanning for all greetings:')
+    partial_rows = table.read_rows()
+    partial_rows.consume_all()
+
+    for row_key, row in partial_rows.rows.items():
+        key = row_key.decode('utf-8')
+        cell = row.cells[column_family_id][column_id][0]
+        value = cell.value.decode('utf-8')
+        print('\t{}: {}'.format(key, value))
+    # [END scanning_all_rows]
+
+    # [START deleting_a_table]
+    print('Deleting the {} table.'.format(table_id))
+    table.delete()
+    # [END deleting_a_table]
 
 
 if __name__ == '__main__':

bigtable/hello/requirements.txt

@@ -1 +1 @@
-gcloud[grpc]==0.18.3
+google-cloud-bigtable==0.20.0

bigtable/hello_happybase/main.py

@@ -26,8 +26,8 @@
 
 import argparse
 
-from gcloud import bigtable
-from gcloud.bigtable import happybase
+from google.cloud import bigtable
+from google.cloud import happybase
 
 
 def main(project_id, instance_id, table_name):

bigtable/hello_happybase/requirements.txt

@@ -1 +1 @@
-gcloud[grpc]==0.18.3
+google-cloud-happybase==0.20.0

blog/introduction_to_data_models_in_cloud_datastore/blog.py

@@ -14,7 +14,7 @@
 import argparse
 import datetime
 
-from gcloud import datastore
+from google.cloud import datastore
 
 
 def path_to_key(datastore, path):

blog/introduction_to_data_models_in_cloud_datastore/requirements.txt

@@ -1 +1 @@
-gcloud==0.18.3
+google-cloud-datastore==0.20.0

blog/introduction_to_data_models_in_cloud_datastore/wiki.py

@@ -14,7 +14,7 @@
 import argparse
 import datetime
 
-from gcloud import datastore
+from google.cloud import datastore
 
 
 def path_to_key(datastore, path):

container_engine/django_tutorial/requirements.txt

@@ -1,4 +1,4 @@
 Django==1.10.1
-mysqlclient==1.3.7
+mysqlclient==1.3.8
 wheel==0.30.0a0
 gunicorn==19.6.0

dataproc/create_cluster_and_submit_job.py

@@ -17,7 +17,7 @@
 import os
 
 from apiclient import discovery
-from gcloud import storage
+from google.cloud import storage
 from oauth2client.client import GoogleCredentials
 
 # Currently only the "global" region is supported

dataproc/requirements.txt

@@ -1,2 +1,2 @@
 google-api-python-client==1.5.3
-gcloud==0.18.3
+google-cloud==0.20.0

datastore/api/requirements.txt

@@ -1 +1 @@
-gcloud==0.18.3
+google-cloud-datastore==0.20.0