Refactoring: Renamed calculate_secondary_stats method to _calculate_secondary_stats.

(Redmine issue: #4321)

lib/hawat/blueprints/reports/__init__.py

@@ -311,7 +311,7 @@ class ShowView(HTMLViewMixin, SQLAlchemyViewMixin, HawatItemShowView):
         """
         if 'item' in self.response_context and self.response_context['item']:
             self.response_context.update(
-                statistics = mentat.stats.idea.calculate_secondary_stats(
+                statistics = mentat.stats.idea._calculate_secondary_stats(
                     self.response_context['item'].statistics
                 )
             )

lib/mentat/stats/idea.py

@@ -206,35 +206,6 @@ def truncate_evaluations(stats, top_threshold = 20):
             stats[key] = truncate_stats(stats[key], top_threshold)
     return stats
 
-def calculate_secondary_stats(stats):
-    """
-    Calculate secondary statistics (cnt, min, max, sum, avg) for every statistical
-    aggregation subkey.
-
-    :param dict stats: Structure containing single statistic category.
-    :return: Updated structure containing statistics.
-    :rtype: dict
-    """
-    # Calculate unique and recurring events.
-    if ST_SKEY_CNT_EVENTS in stats:
-        if ST_SKEY_CNT_RECURR in stats:
-            stats[ST_SKEY_CNT_UNIQUE] = stats[ST_SKEY_CNT_EVENTS] - stats[ST_SKEY_CNT_RECURR]
-        else:
-            stats[ST_SKEY_CNT_UNIQUE] = stats[ST_SKEY_CNT_EVENTS]
-            stats[ST_SKEY_CNT_RECURR] = 0
-
-    # Calculate secondary statistics.
-    for key in LIST_CALCSTAT_KEYS:
-        if key in stats:
-            stats['cnt_{}'.format(key)]  = len(stats[key])
-            stats['sum_{}'.format(key)]  = sum(stats[key].values())
-            stats['min_{}'.format(key)]  = min(stats[key].values())
-            stats['max_{}'.format(key)]  = max(stats[key].values())
-            stats['avg_{}'.format(key)]  = stats['sum_{}'.format(key)]/stats['cnt_{}'.format(key)]
-            stats['list_{}'.format(key)] = list(sorted(stats[key].keys()))
-
-    return stats
-
 
 #-------------------------------------------------------------------------------
 
@@ -271,7 +242,7 @@ def evaluate_events(events, stats = None):
         _include_event_to_stats(stats, event)
 
     # Calculate secondary statistics (cnt, min, max, sum, avg).
-    stats = calculate_secondary_stats(stats)
+    stats = _calculate_secondary_stats(stats)
 
     return stats
 
@@ -326,13 +297,13 @@ def evaluate_timeline_events(events, dt_from, dt_to, max_count, stats = None):
 
     # Calculate secondary statistics (cnt, min, max, sum, avg) and truncate result
     # to toplist of given size.
-    stats = calculate_secondary_stats(stats)
+    stats = _calculate_secondary_stats(stats)
     stats = truncate_stats(stats)
 
     # Calculate secondary statistics (cnt, min, max, sum, avg) and mask the result
     # to toplist of given size for all timeline time windows.
     for tl_stat in stats[ST_SKEY_TIMELINE]:
-        tl_stat[1] = calculate_secondary_stats(tl_stat[1])
+        tl_stat[1] = _calculate_secondary_stats(tl_stat[1])
         tl_stat[1] = truncate_stats_with_mask(tl_stat[1], stats)
 
     return stats
@@ -444,7 +415,7 @@ def aggregate_stat_groups(stats_list, result = None):
             )
 
     for grp_key in LIST_STAT_GROUPS:
-        result[grp_key] = calculate_secondary_stats(result[grp_key])
+        result[grp_key] = _calculate_secondary_stats(result[grp_key])
 
     return result
 
@@ -484,7 +455,7 @@ def aggregate_stats_reports(report_list, result = None):
             result
         )
 
-    result = calculate_secondary_stats(result)
+    result = _calculate_secondary_stats(result)
 
     return result
 
@@ -551,6 +522,35 @@ def _include_event_to_stats(stats, event, recurring = False):
             key = det
             _counter_inc(stats, ST_SKEY_DETECTORSWS, key)
 
+def _calculate_secondary_stats(stats):
+    """
+    Calculate secondary statistics (cnt, min, max, sum, avg) for every statistical
+    aggregation subkey.
+
+    :param dict stats: Structure containing single statistic category.
+    :return: Updated structure containing statistics.
+    :rtype: dict
+    """
+    # Calculate unique and recurring events.
+    if ST_SKEY_CNT_EVENTS in stats:
+        if ST_SKEY_CNT_RECURR in stats:
+            stats[ST_SKEY_CNT_UNIQUE] = stats[ST_SKEY_CNT_EVENTS] - stats[ST_SKEY_CNT_RECURR]
+        else:
+            stats[ST_SKEY_CNT_UNIQUE] = stats[ST_SKEY_CNT_EVENTS]
+            stats[ST_SKEY_CNT_RECURR] = 0
+
+    # Calculate secondary statistics.
+    for key in LIST_CALCSTAT_KEYS:
+        if key in stats:
+            stats['cnt_{}'.format(key)]  = len(stats[key])
+            stats['sum_{}'.format(key)]  = sum(stats[key].values())
+            stats['min_{}'.format(key)]  = min(stats[key].values())
+            stats['max_{}'.format(key)]  = max(stats[key].values())
+            stats['avg_{}'.format(key)]  = stats['sum_{}'.format(key)]/stats['cnt_{}'.format(key)]
+            stats['list_{}'.format(key)] = list(sorted(stats[key].keys()))
+
+    return stats
+
 def _make_toplist(stats, dict_key, top_threshold):
     """
     Produce only toplist of given statistical keys.