BigQuery Beta 2 Changes

bigquery/.coveragerc

@@ -9,3 +9,5 @@ exclude_lines =
     pragma: NO COVER
     # Ignore debug-only repr
     def __repr__
+    # Ignore abstract methods
+    raise NotImplementedError

bigquery/README.rst

@@ -38,12 +38,27 @@ Using the API
 
 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.
+solves this problem by enabling super-fast, SQL queries against
+append-mostly 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/
 
+Create a dataset
+~~~~~~~~~~~~~~~~
+
+.. code:: python
+
+    from google.cloud import bigquery
+    from google.cloud.bigquery import Dataset
+
+    client = bigquery.Client()
+
+    dataset_ref = client.dataset('dataset_name')
+    dataset = Dataset(dataset_ref)
+    dataset.description = 'my dataset'
+    dataset = client.create_dataset(dataset)  # API request
+
 Load data from CSV
 ~~~~~~~~~~~~~~~~~~
 
@@ -52,39 +67,43 @@ Load data from CSV
     import csv
 
     from google.cloud import bigquery
+    from google.cloud.bigquery import LoadJobConfig
     from google.cloud.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()
+    table_ref = client.dataset('dataset_name').table('table_name')
+
+    load_config = LoadJobConfig()
+    load_config.skip_leading_rows = 1
+    load_config.schema = SCHEMA
 
-    with open('csv_file', 'rb') as readable:
-        table.upload_from_file(
-            readable, source_format='CSV', skip_leading_rows=1)
+    # Contents of csv_file.csv:
+    #     Name,Age
+    #     Tim,99
+    with open('csv_file.csv', 'rb') as readable:
+        client.load_table_from_file(
+            readable, table_ref, job_config=load_config)  # API request
 
-Perform a synchronous query
-~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Perform a query
+~~~~~~~~~~~~~~~
 
 .. code:: python
 
-    # Perform a synchronous query.
+    # Perform a 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)
+        'SELECT name FROM `bigquery-public-data.usa_names.usa_1910_2013` '
+        'WHERE state = "TX" '
+        'LIMIT 100')
+    query_job = client.query(QUERY)  # API request
+    rows = query_job.result()  # Waits for query to finish
+
+    for row in rows:
+        print(row.name)
 
 
 See the ``google-cloud-python`` API `BigQuery documentation`_ to learn how

bigquery/google/cloud/bigquery/__init__.py

@@ -26,17 +26,63 @@
 from pkg_resources import get_distribution
 __version__ = get_distribution('google-cloud-bigquery').version
 
-from google.cloud.bigquery._helpers import ArrayQueryParameter
-from google.cloud.bigquery._helpers import ScalarQueryParameter
-from google.cloud.bigquery._helpers import StructQueryParameter
+from google.cloud.bigquery._helpers import DEFAULT_RETRY
 from google.cloud.bigquery.client import Client
-from google.cloud.bigquery.dataset import AccessGrant
+from google.cloud.bigquery.dataset import AccessEntry
 from google.cloud.bigquery.dataset import Dataset
+from google.cloud.bigquery.dataset import DatasetReference
+from google.cloud.bigquery.job import CopyJob
+from google.cloud.bigquery.job import CopyJobConfig
+from google.cloud.bigquery.job import ExtractJob
+from google.cloud.bigquery.job import ExtractJobConfig
+from google.cloud.bigquery.job import QueryJob
+from google.cloud.bigquery.job import QueryJobConfig
+from google.cloud.bigquery.job import LoadJob
+from google.cloud.bigquery.job import LoadJobConfig
+from google.cloud.bigquery.query import ArrayQueryParameter
+from google.cloud.bigquery.query import ScalarQueryParameter
+from google.cloud.bigquery.query import StructQueryParameter
+from google.cloud.bigquery.query import UDFResource
 from google.cloud.bigquery.schema import SchemaField
 from google.cloud.bigquery.table import Table
+from google.cloud.bigquery.table import TableReference
+from google.cloud.bigquery.external_config import ExternalConfig
+from google.cloud.bigquery.external_config import BigtableOptions
+from google.cloud.bigquery.external_config import BigtableColumnFamily
+from google.cloud.bigquery.external_config import BigtableColumn
+from google.cloud.bigquery.external_config import CSVOptions
+from google.cloud.bigquery.external_config import GoogleSheetsOptions
 
 __all__ = [
-    '__version__', 'AccessGrant', 'ArrayQueryParameter', 'Client',
-    'Dataset', 'ScalarQueryParameter', 'SchemaField', 'StructQueryParameter',
+    '__version__',
+    'Client',
+    # Queries
+    'QueryJob',
+    'QueryJobConfig',
+    'ArrayQueryParameter',
+    'ScalarQueryParameter',
+    'StructQueryParameter',
+    # Datasets
+    'Dataset',
+    'DatasetReference',
+    'AccessEntry',
+    # Tables
     'Table',
+    'TableReference',
+    'CopyJob',
+    'CopyJobConfig',
+    'ExtractJob',
+    'ExtractJobConfig',
+    'LoadJob',
+    'LoadJobConfig',
+    # Shared helpers
+    'SchemaField',
+    'UDFResource',
+    'ExternalConfig',
+    'BigtableOptions',
+    'BigtableColumnFamily',
+    'BigtableColumn',
+    'CSVOptions',
+    'GoogleSheetsOptions',
+    'DEFAULT_RETRY',
 ]