[bugfix] Fix ZeroDivisionError and get metrics label with percent met…

…rics (apache#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

(cherry picked from commit 9f66dae)

superset/viz.py

@@ -535,6 +535,7 @@ def get_data(self, df):
 
         # 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))
@@ -543,15 +544,18 @@ def get_data(self, df):
                 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]

tests/viz_tests.py

@@ -120,12 +120,22 @@ def test_cache_timeout(self):
 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 @@ def test_get_data_applies_percentage(self):
         # 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'])