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Posted to commits@superset.apache.org by ma...@apache.org on 2018/05/20 16:11:07 UTC
[incubator-superset] branch master updated: [bugfix] Fix
ZeroDivisionError and get metrics label with percent metrics (#5026)
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maximebeauchemin pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-superset.git
The following commit(s) were added to refs/heads/master by this push:
new 9f66dae [bugfix] Fix ZeroDivisionError and get metrics label with percent metrics (#5026)
9f66dae is described below
commit 9f66dae328b70b277bfc0e1f47c3f63aff541ae4
Author: Yongjie Zhao <yo...@gmail.com>
AuthorDate: Mon May 21 00:10:57 2018 +0800
[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
---
superset/viz.py | 8 ++++++--
tests/viz_tests.py | 36 +++++++++++++++++++++++-------------
2 files changed, 29 insertions(+), 15 deletions(-)
diff --git a/superset/viz.py b/superset/viz.py
index 38e5680..39d3411 100644
--- a/superset/viz.py
+++ b/superset/viz.py
@@ -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]
diff --git a/tests/viz_tests.py b/tests/viz_tests.py
index fb56581..30c37c8 100644
--- a/tests/viz_tests.py
+++ b/tests/viz_tests.py
@@ -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'])
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