def test_query_obj_throws_columns_and_metrics(self, super_query_obj):
datasource = self.get_datasource_mock()
form_data = {"all_columns": ["A", "B"], "metrics": ["x", "y"]}
super_query_obj.return_value = {}
test_viz = viz.TableViz(datasource, form_data)
with self.assertRaises(Exception):
test_viz.query_obj()
del form_data["metrics"]
form_data["groupby"] = ["B", "C"]
test_viz = viz.TableViz(datasource, form_data)
with self.assertRaises(Exception):
test_viz.query_obj()
def test_query_obj_throws_columns_and_metrics(self, super_query_obj):
datasource = Mock()
form_data = {
'all_columns': ['A', 'B'],
'metrics': ['x', 'y'],
}
super_query_obj.return_value = {}
test_viz = viz.TableViz(datasource, form_data)
with self.assertRaises(Exception):
test_viz.query_obj()
del form_data['metrics']
form_data['groupby'] = ['B', 'C']
test_viz = viz.TableViz(datasource, form_data)
with self.assertRaises(Exception):
test_viz.query_obj()
def test_adhoc_metric_with_sortby(self):
metrics = [
{
"expressionType": "SIMPLE",
"aggregate": "SUM",
"label": "sum_value",
"column": {"column_name": "value1", "type": "DOUBLE"},
}
]
form_data = {
"metrics": metrics,
"timeseries_limit_metric": {
"expressionType": "SIMPLE",
"aggregate": "SUM",
"label": "SUM(value1)",
"column": {"column_name": "value1", "type": "DOUBLE"},
},
"order_desc": False,
}
df = pd.DataFrame({"SUM(value1)": [15], "sum_value": [15]})
datasource = self.get_datasource_mock()
test_viz = viz.TableViz(datasource, form_data)
data = test_viz.get_data(df)
self.assertEqual(["sum_value", "SUM(value1)"], data["columns"])
def test_adhoc_filters_overwrite_legacy_filters(self):
form_data = {
"metrics": [
{
"expressionType": "SIMPLE",
"aggregate": "SUM",
"label": "SUM(value1)",
"column": {"column_name": "value1", "type": "DOUBLE"},
}
],
"adhoc_filters": [
{
"expressionType": "SIMPLE",
"clause": "WHERE",
"subject": "value2",
"operator": ">",
"comparator": "100",
},
{
"expressionType": "SQL",
"clause": "WHERE",
"sqlExpression": "value3 in ('North America')",
},
],
"having": "SUM(value1) > 5",
}
datasource = self.get_datasource_mock()
test_viz = viz.TableViz(datasource, form_data)
query_obj = test_viz.query_obj()
self.assertEqual(
[{"col": "value2", "val": "100", "op": ">"}], query_obj["filter"]
)
self.assertEqual([], query_obj["extras"]["having_druid"])
self.assertEqual("(value3 in ('North America'))", query_obj["extras"]["where"])
self.assertEqual("", query_obj["extras"]["having"])
def test_parse_adhoc_filters(self):
form_data = {
'metrics': [{
'expressionType': 'SIMPLE',
'aggregate': 'SUM',
'label': 'SUM(value1)',
'column': {
'column_name': 'value1',
'type': 'DOUBLE'
},
}],
'adhoc_filters': [
{
'expressionType': 'SIMPLE',
'clause': 'WHERE',
'subject': 'value2',
'operator': '>',
'comparator': '100',
},
{
'expressionType': 'SIMPLE',
'clause': 'HAVING',
'subject': 'SUM(value1)',
'operator': '<',
'comparator': '10',
},
{
'expressionType': 'SQL',
'clause': 'HAVING',
'sqlExpression': 'SUM(value1) > 5',
},
{
'expressionType': 'SQL',
'clause': 'WHERE',
'sqlExpression': 'value3 in (\'North America\')',
},
],
}
datasource = Mock()
test_viz = viz.TableViz(datasource, form_data)
query_obj = test_viz.query_obj()
self.assertEqual(
[{
'col': 'value2',
'val': '100',
'op': '>'
}],
query_obj['filter'],
)
self.assertEqual(
[{
'op': '<',
'val': '10',
'col': 'SUM(value1)'
}],
query_obj['extras']['having_druid'],
)
self.assertEqual('(value3 in (\'North America\'))',
query_obj['extras']['where'])
self.assertEqual('(SUM(value1) > 5)', query_obj['extras']['having'])
def test_legacy_filters_still_appear_without_adhoc_filters(self):
form_data = {
'metrics': [{
'expressionType': 'SIMPLE',
'aggregate': 'SUM',
'label': 'SUM(value1)',
'column': {'column_name': 'value1', 'type': 'DOUBLE'},
}],
'having': 'SUM(value1) > 5',
'where': 'value3 in (\'North America\')',
'filters': [{'col': 'value2', 'val': '100', 'op': '>'}],
'having_filters': [{'op': '<', 'val': '10', 'col': 'SUM(value1)'}],
}
datasource = Mock()
test_viz = viz.TableViz(datasource, form_data)
query_obj = test_viz.query_obj()
self.assertEqual(
[{'col': 'value2', 'val': '100', 'op': '>'}],
query_obj['filter'],
)
self.assertEqual(
[{'op': '<', 'val': '10', 'col': 'SUM(value1)'}],
query_obj['extras']['having_druid'],
)
self.assertEqual('value3 in (\'North America\')', query_obj['extras']['where'])
self.assertEqual('SUM(value1) > 5', query_obj['extras']['having'])
def test_query_obj_uses_sortby(self, super_query_obj):
datasource = self.get_datasource_mock()
form_data = {"timeseries_limit_metric": "__time__", "order_desc": False}
super_query_obj.return_value = {"metrics": ["colA", "colB"]}
test_viz = viz.TableViz(datasource, form_data)
query_obj = test_viz.query_obj()
self.assertEqual(["colA", "colB", "__time__"], query_obj["metrics"])
self.assertEqual([("__time__", True)], query_obj["orderby"])
def test_get_data_applies_percentage(self):
form_data = {
'percent_metrics': [{
'expressionType': 'SIMPLE',
'aggregate': 'SUM',
'label': 'SUM(value1)',
'column': {'column_name': 'value1', 'type': 'DOUBLE'},
}, 'avg__B'],
'metrics': [{
'expressionType': 'SIMPLE',
'aggregate': 'SUM',
'label': 'SUM(value1)',
'column': {'column_name': 'value1', 'type': 'DOUBLE'},
}, 'count', 'avg__C'],
}
datasource = self.get_datasource_mock()
raw = {}
raw['SUM(value1)'] = [15, 20, 25, 40]
raw['avg__B'] = [10, 20, 5, 15]
raw['avg__C'] = [11, 22, 33, 44]
raw['count'] = [6, 7, 8, 9]
raw['groupA'] = ['A', 'B', 'C', 'C']
raw['groupB'] = ['x', 'x', 'y', 'z']
df = pd.DataFrame(raw)
test_viz = viz.TableViz(datasource, form_data)
data = test_viz.get_data(df)
# Check method correctly transforms data and computes percents
self.assertEqual(set([
'groupA', 'groupB', 'count',
'SUM(value1)', 'avg__C',
'%SUM(value1)', '%avg__B',
]), set(data['columns']))
expected = [
{
'groupA': 'A', 'groupB': 'x',
'count': 6, 'SUM(value1)': 15, 'avg__C': 11,
'%SUM(value1)': 0.15, '%avg__B': 0.2,
},
{
'groupA': 'B', 'groupB': 'x',
'count': 7, 'SUM(value1)': 20, 'avg__C': 22,
'%SUM(value1)': 0.2, '%avg__B': 0.4,
},
{
'groupA': 'C', 'groupB': 'y',
'count': 8, 'SUM(value1)': 25, 'avg__C': 33,
'%SUM(value1)': 0.25, '%avg__B': 0.1,
},
{
'groupA': 'C', 'groupB': 'z',
'count': 9, 'SUM(value1)': 40, 'avg__C': 44,
'%SUM(value1)': 0.40, '%avg__B': 0.3,
},
]
self.assertEqual(expected, data['records'])
def test_raise_for_access_viz(self, mock_can_access_schema, mock_can_access):
test_viz = viz.TableViz(self.get_datasource_mock(), form_data={})
mock_can_access_schema.return_value = True
security_manager.raise_for_access(viz=test_viz)
mock_can_access.return_value = False
mock_can_access_schema.return_value = False
with self.assertRaises(SupersetSecurityException):
security_manager.raise_for_access(viz=test_viz)
def test_query_obj_uses_sortby(self, super_query_obj):
datasource = Mock()
form_data = {
'timeseries_limit_metric': '__time__',
'order_desc': False
}
super_query_obj.return_value = {'metrics': ['colA', 'colB']}
test_viz = viz.TableViz(datasource, form_data)
query_obj = test_viz.query_obj()
self.assertEqual(['colA', 'colB', '__time__'], query_obj['metrics'])
self.assertEqual([('__time__', True)], query_obj['orderby'])
def test_assert_viz_permission(self, mock_datasource_access):
test_viz = viz.TableViz(self.get_datasource_mock(), form_data={})
# Visualization with the "datasource_access" permission.
mock_datasource_access.return_value = True
security_manager.assert_viz_permission(test_viz)
# Visualization without the "datasource_access" permission.
mock_datasource_access.return_value = False
with self.assertRaises(SupersetSecurityException):
security_manager.assert_viz_permission(test_viz)
def test_query_obj_merges_percent_metrics(self, super_query_obj):
datasource = Mock()
form_data = {
'percent_metrics': ['sum__A', 'avg__B', 'max__Y'],
'metrics': ['sum__A', 'count', 'avg__C'],
}
test_viz = viz.TableViz(datasource, form_data)
f_query_obj = {'metrics': form_data['metrics']}
super_query_obj.return_value = f_query_obj
query_obj = test_viz.query_obj()
self.assertEqual(['sum__A', 'count', 'avg__C', 'avg__B', 'max__Y'],
query_obj['metrics'])
def test_query_obj_merges_percent_metrics(self, super_query_obj):
datasource = self.get_datasource_mock()
form_data = {
"percent_metrics": ["sum__A", "avg__B", "max__Y"],
"metrics": ["sum__A", "count", "avg__C"],
}
test_viz = viz.TableViz(datasource, form_data)
f_query_obj = {"metrics": form_data["metrics"]}
super_query_obj.return_value = f_query_obj
query_obj = test_viz.query_obj()
self.assertEqual(["sum__A", "count", "avg__C", "avg__B", "max__Y"],
query_obj["metrics"])
def test_query_obj_merges_all_columns(self, super_query_obj):
datasource = self.get_datasource_mock()
form_data = {
"all_columns": ["colA", "colB", "colC"],
"order_by_cols": ['["colA", "colB"]', '["colC"]'],
}
super_query_obj.return_value = {
"columns": ["colD", "colC"],
"groupby": ["colA", "colB"],
}
test_viz = viz.TableViz(datasource, form_data)
query_obj = test_viz.query_obj()
self.assertEqual(form_data["all_columns"], query_obj["columns"])
self.assertEqual([], query_obj["groupby"])
self.assertEqual([["colA", "colB"], ["colC"]], query_obj["orderby"])
def test_query_obj_merges_all_columns(self, super_query_obj):
datasource = Mock()
form_data = {
'all_columns': ['colA', 'colB', 'colC'],
'order_by_cols': ['["colA", "colB"]', '["colC"]'],
}
super_query_obj.return_value = {
'columns': ['colD', 'colC'],
'groupby': ['colA', 'colB'],
}
test_viz = viz.TableViz(datasource, form_data)
query_obj = test_viz.query_obj()
self.assertEqual(form_data['all_columns'], query_obj['columns'])
self.assertEqual([], query_obj['groupby'])
self.assertEqual([['colA', 'colB'], ['colC']], query_obj['orderby'])
def test_adhoc_filters_overwrite_legacy_filters(self):
form_data = {
'metrics': [{
'expressionType': 'SIMPLE',
'aggregate': 'SUM',
'label': 'SUM(value1)',
'column': {
'column_name': 'value1',
'type': 'DOUBLE'
},
}],
'adhoc_filters': [
{
'expressionType': 'SIMPLE',
'clause': 'WHERE',
'subject': 'value2',
'operator': '>',
'comparator': '100',
},
{
'expressionType': 'SQL',
'clause': 'WHERE',
'sqlExpression': "value3 in ('North America')",
},
],
'having':
'SUM(value1) > 5',
}
datasource = self.get_datasource_mock()
test_viz = viz.TableViz(datasource, form_data)
query_obj = test_viz.query_obj()
self.assertEqual(
[{
'col': 'value2',
'val': '100',
'op': '>'
}],
query_obj['filter'],
)
self.assertEqual(
[],
query_obj['extras']['having_druid'],
)
self.assertEqual("(value3 in ('North America'))",
query_obj['extras']['where'])
self.assertEqual('', query_obj['extras']['having'])
def test_get_data_applies_percentage(self):
form_data = {
'percent_metrics': ['sum__A', 'avg__B'],
'metrics': ['sum__A', 'count', 'avg__C'],
}
datasource = Mock()
raw = {}
raw['sum__A'] = [15, 20, 25, 40]
raw['avg__B'] = [10, 20, 5, 15]
raw['avg__C'] = [11, 22, 33, 44]
raw['count'] = [6, 7, 8, 9]
raw['groupA'] = ['A', 'B', 'C', 'C']
raw['groupB'] = ['x', 'x', 'y', 'z']
df = pd.DataFrame(raw)
test_viz = viz.TableViz(datasource, form_data)
data = test_viz.get_data(df)
# Check method correctly transforms data and computes percents
self.assertEqual(set([
'groupA', 'groupB', 'count',
'sum__A', 'avg__C',
'%sum__A', '%avg__B',
]), set(data['columns']))
expected = [
{
'groupA': 'A', 'groupB': 'x',
'count': 6, 'sum__A': 15, 'avg__C': 11,
'%sum__A': 0.15, '%avg__B': 0.2,
},
{
'groupA': 'B', 'groupB': 'x',
'count': 7, 'sum__A': 20, 'avg__C': 22,
'%sum__A': 0.2, '%avg__B': 0.4,
},
{
'groupA': 'C', 'groupB': 'y',
'count': 8, 'sum__A': 25, 'avg__C': 33,
'%sum__A': 0.25, '%avg__B': 0.1,
},
{
'groupA': 'C', 'groupB': 'z',
'count': 9, 'sum__A': 40, 'avg__C': 44,
'%sum__A': 0.40, '%avg__B': 0.3,
},
]
self.assertEqual(expected, data['records'])
def test_should_be_timeseries_raises_when_no_granularity(self):
datasource = Mock()
form_data = {'include_time': True}
test_viz = viz.TableViz(datasource, form_data)
with self.assertRaises(Exception):
test_viz.should_be_timeseries()
def test_get_data_applies_percentage(self):
form_data = {
"percent_metrics": [
{
"expressionType": "SIMPLE",
"aggregate": "SUM",
"label": "SUM(value1)",
"column": {"column_name": "value1", "type": "DOUBLE"},
},
"avg__B",
],
"metrics": [
{
"expressionType": "SIMPLE",
"aggregate": "SUM",
"label": "SUM(value1)",
"column": {"column_name": "value1", "type": "DOUBLE"},
},
"count",
"avg__C",
],
}
datasource = self.get_datasource_mock()
raw = {}
raw["SUM(value1)"] = [15, 20, 25, 40]
raw["avg__B"] = [10, 20, 5, 15]
raw["avg__C"] = [11, 22, 33, 44]
raw["count"] = [6, 7, 8, 9]
raw["groupA"] = ["A", "B", "C", "C"]
raw["groupB"] = ["x", "x", "y", "z"]
df = pd.DataFrame(raw)
test_viz = viz.TableViz(datasource, form_data)
data = test_viz.get_data(df)
# Check method correctly transforms data and computes percents
self.assertEqual(
set(
[
"groupA",
"groupB",
"count",
"SUM(value1)",
"avg__C",
"%SUM(value1)",
"%avg__B",
]
),
set(data["columns"]),
)
expected = [
{
"groupA": "A",
"groupB": "x",
"count": 6,
"SUM(value1)": 15,
"avg__C": 11,
"%SUM(value1)": 0.15,
"%avg__B": 0.2,
},
{
"groupA": "B",
"groupB": "x",
"count": 7,
"SUM(value1)": 20,
"avg__C": 22,
"%SUM(value1)": 0.2,
"%avg__B": 0.4,
},
{
"groupA": "C",
"groupB": "y",
"count": 8,
"SUM(value1)": 25,
"avg__C": 33,
"%SUM(value1)": 0.25,
"%avg__B": 0.1,
},
{
"groupA": "C",
"groupB": "z",
"count": 9,
"SUM(value1)": 40,
"avg__C": 44,
"%SUM(value1)": 0.40,
"%avg__B": 0.3,
},
]
self.assertEqual(expected, data["records"])
