Fix lineup query filtering and syntax; ignore Python cache files

.gitignore

@@ -1,3 +1,5 @@
 
 .streamlit/secrets.toml
 secrets.toml
+__pycache__/
+*.pyc

database_queries.py

@@ -157,7 +157,7 @@ def init_DK_NFL_lineups(type_var, slate_var, prio_var, prio_mix, nfl_db_translat
                     raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
                 else:
                     cursor1 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).limit(math.ceil(lineup_num * (prio_mix / 100)))
-                    cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 1
+                    cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 100)))
                     raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
             else:
                 cursor = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort(prio_var, -1).limit(lineup_num)
@@ -198,7 +198,7 @@ def init_DK_NFL_lineups(type_var, slate_var, prio_var, prio_mix, nfl_db_translat
                     raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
                 else:
                     cursor1 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).limit(math.ceil(lineup_num * (prio_mix / 100)))
-                    cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 1
+                    cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 100)))
                     raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
             else:
                 cursor = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort(prio_var, -1).limit(lineup_num)
@@ -239,7 +239,7 @@ def init_DK_NFL_lineups(type_var, slate_var, prio_var, prio_mix, nfl_db_translat
                     raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
                 else:
                     cursor1 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).limit(math.ceil(lineup_num * (prio_mix / 100)))
-                    cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 1
+                    cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 100)))
                     raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
             else:
                 cursor = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort(prio_var, -1).limit(lineup_num)
@@ -326,7 +326,7 @@ def init_FD_NFL_lineups(type_var, slate_var, prio_var, prio_mix, nfl_db_translat
                     raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
                 else:
                     cursor1 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).limit(math.ceil(lineup_num * (prio_mix / 100)))
-                    cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 1
+                    cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 100)))
                     raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
             else:
                 cursor = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort(prio_var, -1).limit(lineup_num)
@@ -367,7 +367,7 @@ def init_FD_NFL_lineups(type_var, slate_var, prio_var, prio_mix, nfl_db_translat
                     raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
                 else:
                     cursor1 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).limit(math.ceil(lineup_num * (prio_mix / 100)))
-                    cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 1
+                    cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 100)))
                     raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
             else:
                 cursor = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort(prio_var, -1).limit(lineup_num)
@@ -408,7 +408,7 @@ def init_FD_NFL_lineups(type_var, slate_var, prio_var, prio_mix, nfl_db_translat
                     raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
                 else:
                     cursor1 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).limit(math.ceil(lineup_num * (prio_mix / 100)))
-                    cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 1
+                    cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 100)))
                     raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
             else:
                 cursor = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort(prio_var, -1).limit(lineup_num)
@@ -622,7 +622,7 @@ def init_DK_NBA_lineups(type_var, slate_var, prio_var, prio_mix, nba_db_translat
                     raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
                 else:
                     cursor1 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).limit(math.ceil(lineup_num * (prio_mix / 100)))
-                    cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 1
+                    cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 100)))
                     raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
             else:
                 cursor = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort(prio_var, -1).limit(lineup_num)
@@ -665,7 +665,7 @@ def init_DK_NBA_lineups(type_var, slate_var, prio_var, prio_mix, nba_db_translat
                     cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 100)))
                     raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
             else:
-                cursor = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}).sort(prio_var, -1).limit(lineup_num)
+                cursor = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort(prio_var, -1).limit(lineup_num)
                 raw_display = pd.DataFrame(list(cursor))
 
             raw_display = raw_display.drop_duplicates(subset=['PG', 'SG', 'SF', 'PF', 'C', 'G', 'F', 'FLEX'])
@@ -826,7 +826,7 @@ def init_FD_NBA_lineups(type_var, slate_var, prio_var, prio_mix, nba_db_translat
                     raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
                 else:
                     cursor1 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).limit(math.ceil(lineup_num * (prio_mix / 100)))
-                    cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 1
+                    cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 100)))
                     raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
             else:
                 cursor = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort(prio_var, -1).limit(lineup_num)
@@ -1578,7 +1578,7 @@ def init_FD_MLB_lineups(type_var, slate_var, prio_var, prio_mix, mlb_db_translat
                     raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
                 else:
                     cursor1 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).limit(math.ceil(lineup_num * (prio_mix / 100)))
-                    cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_
+                    cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 100)))
                     raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
             else:
                 cursor = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort(prio_var, -1).limit(lineup_num)
@@ -2248,7 +2248,7 @@ def init_DK_PGA_lineups(type_var, slate_var, prio_var, prio_mix, lineup_num, sal
                     raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
                 else:
                     cursor1 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).limit(math.ceil(lineup_num * (prio_mix / 100)))
-                    cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_
+                    cursor2 = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort('Own', -1).limit(math.ceil(lineup_num * ((100 - prio_mix) / 100)))
                     raw_display = pd.concat([pd.DataFrame(list(cursor1)), pd.DataFrame(list(cursor2))])
             else:
                 cursor = collection.find({'salary': {'$gte': salary_min, '$lte': salary_max}, 'Team_count': {'$gte': team_count_min if team_count_min is not None else 1, '$lte': team_count_max if team_count_max is not None else 999}}).sort(prio_var, -1).limit(lineup_num)