parallel monthly ported to indexed db

py/main.py

@@ -141,7 +141,7 @@ def parallel_weekly():
 
     # Complex query to get each day of the week
     query = f'SELECT {sql_col_names} FROM {table_name} WHERE'
-    query += 'OR'.join('(Year=? AND Month=? AND Day=?)' for _ in range(len(weekdays)))
+    query += 'OR'.join(['(Year=? AND Month=? AND Day=?)'] * len(weekdays))
     query += ' GROUP BY Day;'
 
     # Break each date into three components then merge them all (in a flat list)
@@ -154,10 +154,8 @@ def parallel_weekly():
     sample = [["pos1", *[x*10+10 for x in range(len(col_names)-6)]]]
 
     myxs = {}
-    # group by day; take first of each group
-    #for k, g in itertools.groupby(res_all, lambda x: x[0]):
-    for i, data_point in enumerate(res_all):
-        #data_point = next(g)
+    # group by day; take first of each group    
+    for i, data_point in enumerate(res_all):        
         wd = list(weekdays.items())[i]
         point_id = f'{wd[1]} ({wd[0]})'
         myxs[point_id] = 'pos1'
@@ -187,22 +185,26 @@ def parallel_monthly():
     table_name, col_names = get_table_cols(hus, fam, typ)
     sql_col_names = ','.join(f'"{x}"' for x in col_names)
 
+    # Complex query to get each day separately
+    query = f'SELECT {sql_col_names} FROM {table_name} WHERE'
+    query += 'OR'.join(['(Year=? AND Month=? AND Day=?)'] * len(days))
+    query += ' GROUP BY Day;'
+
+    # Break each date into three components then merge them all (in a flat list)
+    params = [y for d in days for y in d.split('-')]
+
     conn = sqlite3.connect(DB_NAMES[hus])
-    query = f'SELECT {sql_col_names} FROM "{table_name}" WHERE "{date_col}" IN (?,?,?,?);'
-    print(query)
-    cur = conn.execute(query, days)
+    cur = conn.execute(query, params)
     res_all = cur.fetchall()
-    print(res_all)
 
-    sample = [["pos1", *[x*10+10 for x in range(len(col_names)-2)]]]
+    sample = [["pos1", *[x*10+10 for x in range(len(col_names)-6)]]]
 
     myxs = {}
-    # group by day; take first of each group
-    for k, g in itertools.groupby(res_all, lambda x: x[0]):
-        data_point = next(g)
-        point_id = f'{data_point[0]}'
+    # group by day; take first of each group    
+    for data_point in res_all:        
+        point_id = '-'.join(data_point[:3])
         myxs[point_id] = 'pos1'
-        data_point = [point_id, *data_point[2:]]
+        data_point = [point_id, *data_point[6:]]
         sample.append(data_point)
 
     return dict(sample=sample, myxs=myxs)