mirror of
https://github.com/apache/superset.git
synced 2026-04-18 15:44:57 +00:00
refactor(tests): decouple unittests from integration tests (#15473)
* refactor move all tests to be under integration_tests package * refactor decouple unittests from integration tests - commands * add unit_tests package * fix celery_tests.py * fix wrong FIXTURES_DIR value
This commit is contained in:
ofekisr
337
tests/integration_tests/db_engine_specs/bigquery_tests.py
Normal file
337
tests/integration_tests/db_engine_specs/bigquery_tests.py
Normal file
@@ -0,0 +1,337 @@
|
||||
# Licensed to the Apache Software Foundation (ASF) under one
|
||||
# or more contributor license agreements. See the NOTICE file
|
||||
# distributed with this work for additional information
|
||||
# regarding copyright ownership. The ASF licenses this file
|
||||
# to you under the Apache License, Version 2.0 (the
|
||||
# "License"); you may not use this file except in compliance
|
||||
# with the License. You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing,
|
||||
# software distributed under the License is distributed on an
|
||||
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
|
||||
# KIND, either express or implied. See the License for the
|
||||
# specific language governing permissions and limitations
|
||||
# under the License.
|
||||
import sys
|
||||
import unittest.mock as mock
|
||||
|
||||
from pandas import DataFrame
|
||||
from sqlalchemy import column
|
||||
|
||||
from superset.db_engine_specs.base import BaseEngineSpec
|
||||
from superset.db_engine_specs.bigquery import BigQueryEngineSpec
|
||||
from superset.errors import ErrorLevel, SupersetError, SupersetErrorType
|
||||
from superset.sql_parse import Table
|
||||
from tests.integration_tests.db_engine_specs.base_tests import TestDbEngineSpec
|
||||
|
||||
|
||||
class TestBigQueryDbEngineSpec(TestDbEngineSpec):
|
||||
def test_bigquery_sqla_column_label(self):
|
||||
"""
|
||||
DB Eng Specs (bigquery): Test column label
|
||||
"""
|
||||
test_cases = {
|
||||
"Col": "Col",
|
||||
"SUM(x)": "SUM_x__5f110",
|
||||
"SUM[x]": "SUM_x__7ebe1",
|
||||
"12345_col": "_12345_col_8d390",
|
||||
}
|
||||
for original, expected in test_cases.items():
|
||||
actual = BigQueryEngineSpec.make_label_compatible(column(original).name)
|
||||
self.assertEqual(actual, expected)
|
||||
|
||||
def test_convert_dttm(self):
|
||||
"""
|
||||
DB Eng Specs (bigquery): Test conversion to date time
|
||||
"""
|
||||
dttm = self.get_dttm()
|
||||
test_cases = {
|
||||
"DATE": "CAST('2019-01-02' AS DATE)",
|
||||
"DATETIME": "CAST('2019-01-02T03:04:05.678900' AS DATETIME)",
|
||||
"TIMESTAMP": "CAST('2019-01-02T03:04:05.678900' AS TIMESTAMP)",
|
||||
"TIME": "CAST('03:04:05.678900' AS TIME)",
|
||||
"UNKNOWNTYPE": None,
|
||||
}
|
||||
|
||||
for target_type, expected in test_cases.items():
|
||||
actual = BigQueryEngineSpec.convert_dttm(target_type, dttm)
|
||||
self.assertEqual(actual, expected)
|
||||
|
||||
def test_timegrain_expressions(self):
|
||||
"""
|
||||
DB Eng Specs (bigquery): Test time grain expressions
|
||||
"""
|
||||
col = column("temporal")
|
||||
test_cases = {
|
||||
"DATE": "DATE_TRUNC(temporal, HOUR)",
|
||||
"TIME": "TIME_TRUNC(temporal, HOUR)",
|
||||
"DATETIME": "DATETIME_TRUNC(temporal, HOUR)",
|
||||
"TIMESTAMP": "TIMESTAMP_TRUNC(temporal, HOUR)",
|
||||
}
|
||||
for type_, expected in test_cases.items():
|
||||
actual = BigQueryEngineSpec.get_timestamp_expr(
|
||||
col=col, pdf=None, time_grain="PT1H", type_=type_
|
||||
)
|
||||
self.assertEqual(str(actual), expected)
|
||||
|
||||
def test_custom_minute_timegrain_expressions(self):
|
||||
"""
|
||||
DB Eng Specs (bigquery): Test time grain expressions
|
||||
"""
|
||||
col = column("temporal")
|
||||
test_cases = {
|
||||
"DATE": "CAST(TIMESTAMP_SECONDS("
|
||||
"5*60 * DIV(UNIX_SECONDS(CAST(temporal AS TIMESTAMP)), 5*60)"
|
||||
") AS DATE)",
|
||||
"DATETIME": "CAST(TIMESTAMP_SECONDS("
|
||||
"5*60 * DIV(UNIX_SECONDS(CAST(temporal AS TIMESTAMP)), 5*60)"
|
||||
") AS DATETIME)",
|
||||
"TIMESTAMP": "CAST(TIMESTAMP_SECONDS("
|
||||
"5*60 * DIV(UNIX_SECONDS(CAST(temporal AS TIMESTAMP)), 5*60)"
|
||||
") AS TIMESTAMP)",
|
||||
}
|
||||
for type_, expected in test_cases.items():
|
||||
actual = BigQueryEngineSpec.get_timestamp_expr(
|
||||
col=col, pdf=None, time_grain="PT5M", type_=type_
|
||||
)
|
||||
assert str(actual) == expected
|
||||
|
||||
def test_fetch_data(self):
|
||||
"""
|
||||
DB Eng Specs (bigquery): Test fetch data
|
||||
"""
|
||||
# Mock a google.cloud.bigquery.table.Row
|
||||
class Row(object):
|
||||
def __init__(self, value):
|
||||
self._value = value
|
||||
|
||||
def values(self):
|
||||
return self._value
|
||||
|
||||
data1 = [(1, "foo")]
|
||||
with mock.patch.object(BaseEngineSpec, "fetch_data", return_value=data1):
|
||||
result = BigQueryEngineSpec.fetch_data(None, 0)
|
||||
self.assertEqual(result, data1)
|
||||
|
||||
data2 = [Row(1), Row(2)]
|
||||
with mock.patch.object(BaseEngineSpec, "fetch_data", return_value=data2):
|
||||
result = BigQueryEngineSpec.fetch_data(None, 0)
|
||||
self.assertEqual(result, [1, 2])
|
||||
|
||||
def test_extra_table_metadata(self):
|
||||
"""
|
||||
DB Eng Specs (bigquery): Test extra table metadata
|
||||
"""
|
||||
database = mock.Mock()
|
||||
# Test no indexes
|
||||
database.get_indexes = mock.MagicMock(return_value=None)
|
||||
result = BigQueryEngineSpec.extra_table_metadata(
|
||||
database, "some_table", "some_schema"
|
||||
)
|
||||
self.assertEqual(result, {})
|
||||
|
||||
index_metadata = [
|
||||
{"name": "clustering", "column_names": ["c_col1", "c_col2", "c_col3"],},
|
||||
{"name": "partition", "column_names": ["p_col1", "p_col2", "p_col3"],},
|
||||
]
|
||||
expected_result = {
|
||||
"partitions": {"cols": [["p_col1", "p_col2", "p_col3"]]},
|
||||
"clustering": {"cols": [["c_col1", "c_col2", "c_col3"]]},
|
||||
}
|
||||
database.get_indexes = mock.MagicMock(return_value=index_metadata)
|
||||
result = BigQueryEngineSpec.extra_table_metadata(
|
||||
database, "some_table", "some_schema"
|
||||
)
|
||||
self.assertEqual(result, expected_result)
|
||||
|
||||
def test_normalize_indexes(self):
|
||||
"""
|
||||
DB Eng Specs (bigquery): Test extra table metadata
|
||||
"""
|
||||
indexes = [{"name": "partition", "column_names": [None], "unique": False}]
|
||||
normalized_idx = BigQueryEngineSpec.normalize_indexes(indexes)
|
||||
self.assertEqual(normalized_idx, [])
|
||||
|
||||
indexes = [{"name": "partition", "column_names": ["dttm"], "unique": False}]
|
||||
normalized_idx = BigQueryEngineSpec.normalize_indexes(indexes)
|
||||
self.assertEqual(normalized_idx, indexes)
|
||||
|
||||
indexes = [
|
||||
{"name": "partition", "column_names": ["dttm", None], "unique": False}
|
||||
]
|
||||
normalized_idx = BigQueryEngineSpec.normalize_indexes(indexes)
|
||||
self.assertEqual(
|
||||
normalized_idx,
|
||||
[{"name": "partition", "column_names": ["dttm"], "unique": False}],
|
||||
)
|
||||
|
||||
@mock.patch("superset.db_engine_specs.bigquery.BigQueryEngineSpec.get_engine")
|
||||
def test_df_to_sql(self, mock_get_engine):
|
||||
"""
|
||||
DB Eng Specs (bigquery): Test DataFrame to SQL contract
|
||||
"""
|
||||
# test missing google.oauth2 dependency
|
||||
sys.modules["pandas_gbq"] = mock.MagicMock()
|
||||
df = DataFrame()
|
||||
database = mock.MagicMock()
|
||||
self.assertRaisesRegexp(
|
||||
Exception,
|
||||
"Could not import libraries",
|
||||
BigQueryEngineSpec.df_to_sql,
|
||||
database=database,
|
||||
table=Table(table="name", schema="schema"),
|
||||
df=df,
|
||||
to_sql_kwargs={},
|
||||
)
|
||||
|
||||
invalid_kwargs = [
|
||||
{"name": "some_name"},
|
||||
{"schema": "some_schema"},
|
||||
{"con": "some_con"},
|
||||
{"name": "some_name", "con": "some_con"},
|
||||
{"name": "some_name", "schema": "some_schema"},
|
||||
{"con": "some_con", "schema": "some_schema"},
|
||||
]
|
||||
# Test check for missing schema.
|
||||
sys.modules["google.oauth2"] = mock.MagicMock()
|
||||
for invalid_kwarg in invalid_kwargs:
|
||||
self.assertRaisesRegexp(
|
||||
Exception,
|
||||
"The table schema must be defined",
|
||||
BigQueryEngineSpec.df_to_sql,
|
||||
database=database,
|
||||
table=Table(table="name"),
|
||||
df=df,
|
||||
to_sql_kwargs=invalid_kwarg,
|
||||
)
|
||||
|
||||
import pandas_gbq
|
||||
from google.oauth2 import service_account
|
||||
|
||||
pandas_gbq.to_gbq = mock.Mock()
|
||||
service_account.Credentials.from_service_account_info = mock.MagicMock(
|
||||
return_value="account_info"
|
||||
)
|
||||
|
||||
mock_get_engine.return_value.url.host = "google-host"
|
||||
mock_get_engine.return_value.dialect.credentials_info = "secrets"
|
||||
|
||||
BigQueryEngineSpec.df_to_sql(
|
||||
database=database,
|
||||
table=Table(table="name", schema="schema"),
|
||||
df=df,
|
||||
to_sql_kwargs={"if_exists": "extra_key"},
|
||||
)
|
||||
|
||||
pandas_gbq.to_gbq.assert_called_with(
|
||||
df,
|
||||
project_id="google-host",
|
||||
destination_table="schema.name",
|
||||
credentials="account_info",
|
||||
if_exists="extra_key",
|
||||
)
|
||||
|
||||
def test_extract_errors(self):
|
||||
msg = "403 POST https://bigquery.googleapis.com/bigquery/v2/projects/test-keel-310804/jobs?prettyPrint=false: Access Denied: Project User does not have bigquery.jobs.create permission in project profound-keel-310804"
|
||||
result = BigQueryEngineSpec.extract_errors(Exception(msg))
|
||||
assert result == [
|
||||
SupersetError(
|
||||
message="We were unable to connect to your database. Please confirm that your service account has the Viewer and Job User roles on the project.",
|
||||
error_type=SupersetErrorType.CONNECTION_DATABASE_PERMISSIONS_ERROR,
|
||||
level=ErrorLevel.ERROR,
|
||||
extra={
|
||||
"engine_name": "Google BigQuery",
|
||||
"issue_codes": [{"code": 1017, "message": "",}],
|
||||
},
|
||||
)
|
||||
]
|
||||
|
||||
msg = "bigquery error: 404 Not found: Dataset fakeDataset:bogusSchema was not found in location"
|
||||
result = BigQueryEngineSpec.extract_errors(Exception(msg))
|
||||
assert result == [
|
||||
SupersetError(
|
||||
message='The schema "bogusSchema" does not exist. A valid schema must be used to run this query.',
|
||||
error_type=SupersetErrorType.SCHEMA_DOES_NOT_EXIST_ERROR,
|
||||
level=ErrorLevel.ERROR,
|
||||
extra={
|
||||
"engine_name": "Google BigQuery",
|
||||
"issue_codes": [
|
||||
{
|
||||
"code": 1003,
|
||||
"message": "Issue 1003 - There is a syntax error in the SQL query. Perhaps there was a misspelling or a typo.",
|
||||
},
|
||||
{
|
||||
"code": 1004,
|
||||
"message": "Issue 1004 - The column was deleted or renamed in the database.",
|
||||
},
|
||||
],
|
||||
},
|
||||
)
|
||||
]
|
||||
|
||||
msg = 'Table name "badtable" missing dataset while no default dataset is set in the request'
|
||||
result = BigQueryEngineSpec.extract_errors(Exception(msg))
|
||||
assert result == [
|
||||
SupersetError(
|
||||
message='The table "badtable" does not exist. A valid table must be used to run this query.',
|
||||
error_type=SupersetErrorType.TABLE_DOES_NOT_EXIST_ERROR,
|
||||
level=ErrorLevel.ERROR,
|
||||
extra={
|
||||
"engine_name": "Google BigQuery",
|
||||
"issue_codes": [
|
||||
{
|
||||
"code": 1003,
|
||||
"message": "Issue 1003 - There is a syntax error in the SQL query. Perhaps there was a misspelling or a typo.",
|
||||
},
|
||||
{
|
||||
"code": 1005,
|
||||
"message": "Issue 1005 - The table was deleted or renamed in the database.",
|
||||
},
|
||||
],
|
||||
},
|
||||
)
|
||||
]
|
||||
|
||||
msg = "Unrecognized name: badColumn at [1:8]"
|
||||
result = BigQueryEngineSpec.extract_errors(Exception(msg))
|
||||
assert result == [
|
||||
SupersetError(
|
||||
message='We can\'t seem to resolve column "badColumn" at line 1:8.',
|
||||
error_type=SupersetErrorType.COLUMN_DOES_NOT_EXIST_ERROR,
|
||||
level=ErrorLevel.ERROR,
|
||||
extra={
|
||||
"engine_name": "Google BigQuery",
|
||||
"issue_codes": [
|
||||
{
|
||||
"code": 1003,
|
||||
"message": "Issue 1003 - There is a syntax error in the SQL query. Perhaps there was a misspelling or a typo.",
|
||||
},
|
||||
{
|
||||
"code": 1004,
|
||||
"message": "Issue 1004 - The column was deleted or renamed in the database.",
|
||||
},
|
||||
],
|
||||
},
|
||||
)
|
||||
]
|
||||
|
||||
msg = 'Syntax error: Expected end of input but got identifier "fromm"'
|
||||
result = BigQueryEngineSpec.extract_errors(Exception(msg))
|
||||
assert result == [
|
||||
SupersetError(
|
||||
message='Please check your query for syntax errors at or near "fromm". Then, try running your query again.',
|
||||
error_type=SupersetErrorType.SYNTAX_ERROR,
|
||||
level=ErrorLevel.ERROR,
|
||||
extra={
|
||||
"engine_name": "Google BigQuery",
|
||||
"issue_codes": [
|
||||
{
|
||||
"code": 1030,
|
||||
"message": "Issue 1030 - The query has a syntax error.",
|
||||
}
|
||||
],
|
||||
},
|
||||
)
|
||||
]
|
||||
Reference in New Issue
Block a user