def testGetModelDetailsEmptyFields(self):
client = Mock()
model = Mock(project='project_id',
dataset_id='dataset_id',
model_id='model_id',
description=None,
labels={},
created=datetime.datetime(2020,
7,
14,
13,
23,
45,
67,
tzinfo=None),
expires=datetime.datetime(2021,
7,
14,
13,
23,
45,
67,
tzinfo=None),
location='US',
modified=datetime.datetime(2020,
7,
15,
15,
11,
23,
32,
tzinfo=None),
model_type=0,
label_columns=[],
feature_columns=[],
training_runs=[Mock(start_time=Mock(seconds=1234567))])
client.get_model = Mock(return_value=model)
bigquery = BigQueryService(client)
expected = {
'details': {
'id': 'project_id.dataset_id.model_id',
'name': 'model_id',
'description': None,
'labels': None,
'date_created': '2020-07-14T13:23:45.000067',
'expires': '2021-07-14T13:23:45.000067',
'location': 'US',
'last_modified': '2020-07-15T15:11:23.000032',
'model_type': Model.ModelType(0).name,
'schema_labels': [],
'feature_columns': [],
'training_runs': ['1970-01-15T06:56:07+00:00']
}
}
result = bigquery.get_model_details('some_model_id')
self.assertEqual(expected, result)
def testGetDatasetDetailsFull(self):
client = Mock()
dataset = Mock(project='project_id',
dataset_id='dataset_id',
description='description of dataset',
labels={
'label_0': 'value_0',
'label_1': 'value_1'
},
created=datetime.datetime(2020,
7,
14,
13,
23,
45,
67,
tzinfo=None),
default_table_expiration_ms=17280000000,
location='US',
modified=datetime.datetime(2020,
7,
15,
15,
11,
23,
32,
tzinfo=None),
self_link='https://bigquery.googleapis.com/bigquery' + \
'/v2/projects/project_id/datasets/dataset_id')
client.get_dataset = Mock(return_value=dataset)
bigquery = BigQueryService(client)
expected = {
'details': {
'id':
'project_id.dataset_id',
'name':
'dataset_id',
'description':
'description of dataset',
'labels': ['label_0: value_0', 'label_1: value_1'],
'date_created':
'2020-07-14T13:23:45.000067',
'default_expiration':
17280000000,
'location':
'US',
'last_modified':
'2020-07-15T15:11:23.000032',
'project':
'project_id',
'link':
'https://bigquery.googleapis.com/bigquery' + \
'/v2/projects/project_id/datasets/dataset_id'
}
}
result = bigquery.get_dataset_details('some_dataset_id')
self.assertEqual(expected, result)
def testNestedTable(self):
# ensures records schema names are properly displayed and items
# within records are properly separated
client = Mock()
schema_field_0 = Mock(field_type='STRING', mode='NULLABLE')
schema_field_0.name = 'field_name_0'
schema_subfield = Mock(field_type='INTEGER', mode='NULLABLE')
schema_subfield.name = 'subfield'
schema_subfield_2 = Mock(field_type='DATETIME', mode='NULLABLE')
schema_subfield_2.name = 'other_subfield'
schema_field_1 = Mock(field_type='RECORD',
mode='NULLABLE',
fields=[schema_subfield, schema_subfield_2])
schema_field_1.name = 'field_name_1'
rows = MagicMock(schema=[schema_field_0, schema_field_1])
row_0 = [
'hello', {
'subfield':
1,
'other_subfield':
datetime.datetime(2020, 7, 14, 13, 23, 45, 67, tzinfo=None)
}
]
row_1 = ['goodbye', {'subfield': 2, 'other_subfield': None}]
row_2 = [None, None]
rows.__iter__.return_value = [row_0, row_1, row_2]
client.list_rows = MagicMock(return_value=rows)
bigquery = BigQueryService(client)
expected = {
'fields': [
'field_name_0', 'field_name_1.subfield',
'field_name_1.other_subfield'
],
'rows': [['hello', 1, '2020-07-14 13:23:45.000067 '],
['goodbye', 2, None], [None, None, None]]
}
result = bigquery.get_table_preview('some_table_id')
self.assertEqual(expected, result)
def testRepeatedTable(self):
# ensures that repeated fields are returned as strings, and that
# repeated record field name headers are not expanded
client = Mock()
schema_field_0 = Mock(field_type='STRING',
description='this field is a repeated string',
mode='REPEATED')
schema_field_0.name = 'field_name_0'
schema_subfield = Mock(field_type='INTEGER',
description='this field is an integer',
mode='NULLABLE')
schema_subfield.name = 'subfield'
schema_field_1 = Mock(field_type='RECORD',
description='this field is a repeated record',
mode='REPEATED',
fields=[schema_subfield])
schema_field_1.name = 'field_name_1'
rows = MagicMock(schema=[schema_field_0, schema_field_1])
row_0 = [['hello', 'hi'], [{'subfield': 1}]]
row_1 = [['goodbye', 'bye'], [{'subfield': 2}, {'subfield': 3}]]
row_2 = [[], []]
row_3 = [[], [{'subfield': None}]]
rows.__iter__.return_value = [row_0, row_1, row_2, row_3]
client.list_rows = MagicMock(return_value=rows)
bigquery = BigQueryService(client)
expected = {
'fields': ['field_name_0', 'field_name_1'],
'rows':
[['["hello", "hi"]', '[{"subfield": 1}]'],
['["goodbye", "bye"]', '[{"subfield": 2}, {"subfield": 3}]'],
['[]', '[]'], ['[]', '[{"subfield": null}]']]
}
result = bigquery.get_table_preview('some_table_id')
self.assertEqual(expected, result)
def testEmptyTable(self):
# same as nested table, but ensures
# that when all entries are None the header
# still displays properly.
client = Mock()
schema_field_0 = Mock(field_type='STRING', mode='NULLABLE')
schema_field_0.name = 'field_name_0'
schema_subfield = Mock(field_type='INTEGER', mode='NULLABLE')
schema_subfield.name = 'subfield'
schema_subfield_2 = Mock(field_type='DATETIME', mode='NULLABLE')
schema_subfield_2.name = 'other_subfield'
schema_field_1 = Mock(field_type='RECORD',
mode='NULLABLE',
fields=[schema_subfield, schema_subfield_2])
schema_field_1.name = 'field_name_1'
rows = MagicMock(schema=[schema_field_0, schema_field_1])
row_0 = [None, None]
rows.__iter__.return_value = [row_0]
client.list_rows = MagicMock(return_value=rows)
bigquery = BigQueryService(client)
expected = {
'fields': [
'field_name_0', 'field_name_1.subfield',
'field_name_1.other_subfield'
],
'rows': [[None, None, None]]
}
result = bigquery.get_table_preview('some_table_id')
self.assertEqual(expected, result)
def testGetTrainingRunDetails(self):
client = Mock()
options = [['data_split_column', 'column_name_1'],
['data_split_eval_fraction', 0.3], ['data_split_method', 1],
['distance_type',
1], ['early_stop', BoolValue(value=False)],
['initial_learn_rate', 0.1],
['input_label_columns', ['column1', 'column2']],
['kmeans_initialization_column', 'column_name_2'],
['kmeans_initialization_method', 1],
['l1_regularization',
DoubleValue(value=0.5)],
['l2_regularization',
DoubleValue(value=0.6)],
['label_class_weights', [0.2, 0.3]], ['learn_rate', 0.7],
['learn_rate_strategy', 1], ['loss_type', 1],
['max_iterations', 20],
['min_relative_progress',
DoubleValue(value=0.4)], ['model_uri', 'model.uri.string'],
['num_clusters', 7], ['optimization_strategy', 1],
['warm_start', BoolValue(value=True)]]
mocked_options = []
for option in options:
option_mock = Mock()
option_mock.name = option[0]
mocked_options.append([option_mock, option[1]])
training_options = Mock()
training_options.ListFields = Mock(return_value=mocked_options)
training_run = Mock(training_options=training_options,
results=['result', 'result', 'result'])
model = Mock(training_runs=[training_run])
client.get_model = Mock(return_value=model)
bigquery = BigQueryService(client)
expected = {
'details': {
'actual_iterations':
3,
'data_split_column':
'column_name_1',
'data_split_eval_fraction':
0.3,
'data_split_method':
Model.DataSplitMethod(1).name,
'distance_type':
Model.DistanceType(1).name,
'early_stop':
'False',
'initial_learn_rate':
0.1,
'input_label_columns':
"['column1', 'column2']",
'kmeans_initialization_column':
'column_name_2',
'kmeans_initialization_method':
Model.KmeansEnums.KmeansInitializationMethod(1).name,
'l1_regularization':
0.5,
'l2_regularization':
0.6,
'label_class_weights':
'[0.2, 0.3]',
'learn_rate':
0.7,
'learn_rate_strategy':
Model.LearnRateStrategy(1).name,
'loss_type':
Model.LossType(1).name,
'max_iterations':
20,
'min_relative_progress':
0.4,
'model_uri':
'model.uri.string',
'num_clusters':
7,
'optimization_strategy':
Model.OptimizationStrategy(1).name,
'warm_start':
'True'
}
}
result = bigquery.get_training_run_details('some_model_id', 0)
self.assertEqual(expected, result)
def testGetModelDetailsFull(self):
client = Mock()
label_col_0 = Mock()
label_col_0.name = 'schema_label_0'
label_col_0.type = Mock(type_kind=7)
label_col_1 = Mock()
label_col_1.name = 'schema_label_1'
label_col_1.type = Mock(type_kind=9)
feature_col_0 = Mock()
feature_col_0.name = 'feature_col_0'
feature_col_0.type = Mock(type_kind=8)
model = Mock(project='project_id',
dataset_id='dataset_id',
model_id='model_id',
description='description of model',
labels={
'label_0': 'value_0',
'label_1': 'value_1'
},
created=datetime.datetime(2020,
7,
14,
13,
23,
45,
67,
tzinfo=None),
expires=datetime.datetime(2021,
7,
14,
13,
23,
45,
67,
tzinfo=None),
location='US',
modified=datetime.datetime(2020,
7,
15,
15,
11,
23,
32,
tzinfo=None),
model_type=0,
label_columns=[label_col_0, label_col_1],
feature_columns=[feature_col_0],
training_runs=[
Mock(start_time=Mock(seconds=1234567)),
Mock(start_time=Mock(seconds=1234789))
])
client.get_model = Mock(return_value=model)
bigquery = BigQueryService(client)
expected = {
'details': {
'id':
'project_id.dataset_id.model_id',
'name':
'model_id',
'description':
'description of model',
'labels': ['label_0: value_0', 'label_1: value_1'],
'date_created':
'2020-07-14T13:23:45.000067',
'last_modified':
'2020-07-15T15:11:23.000032',
'expires':
'2021-07-14T13:23:45.000067',
'location':
'US',
'model_type':
Model.ModelType(0).name,
'schema_labels': [{
'name':
'schema_label_0',
'type':
SqlTypeNames[StandardSqlDataTypes(7).name].name
}, {
'name':
'schema_label_1',
'type':
SqlTypeNames[StandardSqlDataTypes(9).name].name
}],
'feature_columns': [{
'name':
'feature_col_0',
'type':
SqlTypeNames[StandardSqlDataTypes(8).name].name
}],
'training_runs':
['1970-01-15T06:56:07+00:00', '1970-01-15T06:59:49+00:00']
}
}
result = bigquery.get_model_details('some_model_id')
self.assertEqual(expected, result)
def testGetViewDetailsFull(self):
client = Mock()
schema_field_0 = Mock(field_type='STRING',
description='this field is a string',
mode='NULLABLE')
schema_field_0.name = 'field_name_0'
schema_field_1 = Mock(field_type='INTEGER',
description='this field is an integer',
mode='NULLABLE')
schema_field_1.name = 'field_name_1'
table = Mock(
project='project_id',
dataset_id='dataset_id',
table_id='view_id',
description='description of view',
labels={
'label_0': 'value_0',
'label_1': 'value_1'
},
created=datetime.datetime(2020, 7, 14, 13, 23, 45, 67, tzinfo=None),
expires=datetime.datetime(2021, 7, 14, 13, 23, 45, 67, tzinfo=None),
modified=datetime.datetime(2020, 7, 15, 15, 11, 23, 32, tzinfo=None),
self_link='https://bigquery.googleapis.com/bigquery/v2/' + \
'projects/project_id/datasets/dataset_id/view_id',
schema=[schema_field_0, schema_field_1],
view_query='SELECT * FROM `project_id.dataset_id.table_id LIMIT 200',
view_use_legacy_sql=False)
client.get_table = Mock(return_value=table)
bigquery = BigQueryService(client)
expected = {
'details': {
'id':
'project_id.dataset_id.view_id',
'name':
'view_id',
'description':
'description of view',
'labels': ['label_0: value_0', 'label_1: value_1'],
'date_created':
'2020-07-14T13:23:45.000067',
'expires':
'2021-07-14T13:23:45.000067',
'last_modified':
'2020-07-15T15:11:23.000032',
'project':
'project_id',
'dataset':
'dataset_id',
'link':
'https://bigquery.googleapis.com/bigquery' + \
'/v2/projects/project_id/datasets/dataset_id/view_id',
'schema': [{
'name': 'field_name_0',
'type': 'STRING',
'description': 'this field is a string',
'mode': 'NULLABLE'
}, {
'name': 'field_name_1',
'type': 'INTEGER',
'description': 'this field is an integer',
'mode': 'NULLABLE'
}],
'query':
'SELECT * FROM `project_id.dataset_id.table_id LIMIT 200',
'legacy_sql':
False
}
}
result = bigquery.get_view_details('some_view_id')
self.assertEqual(expected, result)
def testGetTableDetailsNestedSchema(self):
client = Mock()
schema_field_0 = Mock(field_type='STRING',
description='this field is a string and a child',
mode='NULLABLE')
schema_field_0.name = 'child'
schema_field_1 = Mock(field_type='RECORD',
description='this field is a record',
mode='NULLABLE',
fields=[schema_field_0])
schema_field_1.name = 'record'
table = Mock(project='project_id',
dataset_id='dataset_id',
table_id='table_id',
description='description of table',
labels={
'label_0': 'value_0',
'label_1': 'value_1'
},
created=datetime.datetime(2020,
7,
14,
13,
23,
45,
67,
tzinfo=None),
expires=datetime.datetime(2021,
7,
14,
13,
23,
45,
67,
tzinfo=None),
location='US',
modified=datetime.datetime(2020,
7,
15,
15,
11,
23,
32,
tzinfo=None),
self_link='https://bigquery.googleapis.com/bigquery' + \
'/v2/projects/project_id/datasets/dataset_id',
num_rows=123456,
num_bytes=2000000,
schema=[schema_field_1])
client.get_table = Mock(return_value=table)
bigquery = BigQueryService(client)
expected = {
'details': {
'id':
'project_id.dataset_id.table_id',
'name':
'table_id',
'description':
'description of table',
'labels': ['label_0: value_0', 'label_1: value_1'],
'date_created':
'2020-07-14T13:23:45.000067',
'expires':
'2021-07-14T13:23:45.000067',
'location':
'US',
'last_modified':
'2020-07-15T15:11:23.000032',
'project':
'project_id',
'dataset':
'dataset_id',
'link':
'https://bigquery.googleapis.com/bigquery' + \
'/v2/projects/project_id/datasets/dataset_id',
'num_rows':
123456,
'num_bytes':
2000000,
'schema': [{
'name': 'record',
'type': 'RECORD',
'description': 'this field is a record',
'mode': 'NULLABLE'
}, {
'name': 'record.child',
'type': 'STRING',
'description': 'this field is a string and a child',
'mode': 'NULLABLE'
}]
}
}
result = bigquery.get_table_details('some_table_id')
self.assertEqual(expected, result)
def testGetTableDetailsEmptyFields(self):
client = Mock()
table = Mock(project='project_id',
dataset_id='dataset_id',
table_id='table_id',
description=None,
labels={},
created=datetime.datetime(2020,
7,
14,
13,
23,
45,
67,
tzinfo=None),
expires=None,
location='US',
modified=datetime.datetime(2020,
7,
15,
15,
11,
23,
32,
tzinfo=None),
self_link='https://bigquery.googleapis.com/' + \
'bigquery/v2/projects/project_id/datasets/dataset_id',
num_rows=0,
num_bytes=0,
schema=[])
client.get_table = Mock(return_value=table)
bigquery = BigQueryService(client)
expected = {
'details': {
'id':
'project_id.dataset_id.table_id',
'name':
'table_id',
'description':
None,
'labels':
None,
'date_created':
'2020-07-14T13:23:45.000067',
'expires':
None,
'location':
'US',
'last_modified':
'2020-07-15T15:11:23.000032',
'project':
'project_id',
'dataset':
'dataset_id',
'link':
'https://bigquery.googleapis.com/' + \
'bigquery/v2/projects/project_id/datasets/dataset_id',
'num_rows':
0,
'num_bytes':
0,
'schema': []
}
}
result = bigquery.get_table_details('some_table_id')
self.assertEqual(expected, result)