From 5f38bd20a170ec9cf554f78a10e08a17c1fc08c5 Mon Sep 17 00:00:00 2001
From: wuaho <wuaho@legu.cc>
Date: Wed, 13 Oct 2021 15:21:36 +0800
Subject: [PATCH] 1

---
 api/api_v1/endpoints/query.py | 17 +++++++++++++----
 models/behavior_analysis.py   | 27 ++++++++++++++++++---------
 2 files changed, 31 insertions(+), 13 deletions(-)

diff --git a/api/api_v1/endpoints/query.py b/api/api_v1/endpoints/query.py
index d5a4efb..b56e58f 100644
--- a/api/api_v1/endpoints/query.py
+++ b/api/api_v1/endpoints/query.py
@@ -740,6 +740,9 @@ async def scatter_model(
             for i, v in enumerate(quota_interval_arr[1:]):
                 resp['label'].append(f'[{quota_interval_arr[i]},{v})')
                 bins.append(v)
+        # 合计的
+        if res['time_particle'] == 'total':
+            df['date'] = '合计'
 
         # 这是整体的
         for key, tmp_df in df.groupby('date'):
@@ -747,10 +750,16 @@ async def scatter_model(
                             right=False).value_counts()
             bins_s.sort_index(inplace=True)
             total = int(bins_s.sum())
-            resp['list'][key.strftime('%Y-%m-%d')] = dict()
-            resp['list'][key.strftime('%Y-%m-%d')]['总体'] = {'n': bins_s.to_list(), 'total': total,
-                                                            'p': round(bins_s * 100 / total, 2).to_list(),
-                                                            'title': '总体'}
+            if res['time_particle'] == 'total':
+                resp['list']['合计'] = dict()
+                resp['list']['合计']['总体'] = {'n': bins_s.to_list(), 'total': total,
+                                            'p': round(bins_s * 100 / total, 2).to_list(),
+                                            'title': '总体'}
+            else:
+                resp['list'][key.strftime('%Y-%m-%d')] = dict()
+                resp['list'][key.strftime('%Y-%m-%d')]['总体'] = {'n': bins_s.to_list(), 'total': total,
+                                                                'p': round(bins_s * 100 / total, 2).to_list(),
+                                                                'title': '总体'}
         # 分组的
         if groupby:
             for key, tmp_df in df.groupby(['date', *groupby]):
diff --git a/models/behavior_analysis.py b/models/behavior_analysis.py
index 9d03395..fecd30e 100644
--- a/models/behavior_analysis.py
+++ b/models/behavior_analysis.py
@@ -625,10 +625,14 @@ ORDER BY level
             values_col = func.count(func.distinct(e_account_id_col)).label('values')
 
         if analysis in ['times', 'number_of_days', 'number_of_hours']:
-
-            qry = sa.select(event_date_col, *self.groupby, values_col) \
-                .where(and_(*where)) \
-                .group_by(event_date_col, *self.groupby)
+            if self.time_particle == 'total':
+                qry = sa.select( *self.groupby, values_col) \
+                    .where(and_(*where)) \
+                    .group_by( *self.groupby)
+            else:
+                qry = sa.select(event_date_col, *self.groupby, values_col) \
+                    .where(and_(*where)) \
+                    .group_by(event_date_col, *self.groupby)
 
             sql = str(qry.compile(compile_kwargs={"literal_binds": True}))
             print(sql)
@@ -644,11 +648,16 @@ ORDER BY level
             }
         elif event.get('quota'):
             event_attr_col = getattr(self.event_tbl.c, event['quota'])
-
-            qry = sa.select(event_date_col, e_account_id_col,
-                            settings.CK_FUNC[analysis](event_attr_col).label('values')) \
-                .where(and_(*where)) \
-                .group_by(event_date_col, *self.groupby, e_account_id_col)
+            if self.time_particle == 'total':
+                qry = sa.select( e_account_id_col,
+                                settings.CK_FUNC[analysis](event_attr_col).label('values')) \
+                    .where(and_(*where)) \
+                    .group_by( *self.groupby, e_account_id_col)
+            else:
+                qry = sa.select(event_date_col, e_account_id_col,
+                                settings.CK_FUNC[analysis](event_attr_col).label('values')) \
+                    .where(and_(*where)) \
+                    .group_by(event_date_col, *self.groupby, e_account_id_col)
             sql = str(qry.compile(compile_kwargs={"literal_binds": True}))
             print(sql)
             return {