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[bugfix] Fix ZeroDivisionError and get metrics label with percent metrics (#5026) 

* Fix percent_metrics ZeroDivisionError and can not get metrics with label issue

* convert iterator to list

* get percentage metrics with get_metric_label method

* Adding tests case for expression type metrics

* Simplify expression
This commit is contained in:
Yongjie Zhao 2018-05-21 00:10:57 +08:00 committed by Maxime Beauchemin
parent 5505c116ba
commit 9f66dae328
2 changed files with 29 additions and 15 deletions
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8
superset/viz.py
View File

@ -573,6 +573,7 @@ class TableViz(BaseViz):
# Sum up and compute percentages for all percent metrics
percent_metrics = fd.get('percent_metrics') or []
percent_metrics = [self.get_metric_label(m) for m in percent_metrics]
if len(percent_metrics):
percent_metrics = list(filter(lambda m: m in df, percent_metrics))
@ -581,15 +582,18 @@ class TableViz(BaseViz):
for m in percent_metrics
}
metric_percents = {
m: list(map(lambda a: a / metric_sums[m], df[m]))
m: list(map(
lambda a: None if metric_sums[m] == 0 else a / metric_sums[m], df[m]))
for m in percent_metrics
}
for m in percent_metrics:
m_name = '%' + m
df[m_name] = pd.Series(metric_percents[m], name=m_name)
# Remove metrics that are not in the main metrics list
metrics = fd.get('metrics', [])
metrics = [self.get_metric_label(m) for m in metrics]
for m in filter(
lambda m: m not in fd['metrics'] and m in df.columns,
lambda m: m not in metrics and m in df.columns,
percent_metrics,
):
del df[m]

36
tests/viz_tests.py
View File

@ -120,12 +120,22 @@ class BaseVizTestCase(unittest.TestCase):
class TableVizTestCase(unittest.TestCase):
def test_get_data_applies_percentage(self):
form_data = {
'percent_metrics': ['sum__A', 'avg__B'],
'metrics': ['sum__A', 'count', 'avg__C'],
'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 = Mock()
raw = {}
raw['sum__A'] = [15, 20, 25, 40]
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]
@ -137,29 +147,29 @@ class TableVizTestCase(unittest.TestCase):
# Check method correctly transforms data and computes percents
self.assertEqual(set([
'groupA', 'groupB', 'count',
'sum__A', 'avg__C',
'%sum__A', '%avg__B',
'SUM(value1)', 'avg__C',
'%SUM(value1)', '%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,
'count': 6, 'SUM(value1)': 15, 'avg__C': 11,
'%SUM(value1)': 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,
'count': 7, 'SUM(value1)': 20, 'avg__C': 22,
'%SUM(value1)': 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,
'count': 8, 'SUM(value1)': 25, 'avg__C': 33,
'%SUM(value1)': 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,
'count': 9, 'SUM(value1)': 40, 'avg__C': 44,
'%SUM(value1)': 0.40, '%avg__B': 0.3,
},
]
self.assertEqual(expected, data['records'])