Refactor database collection names in Streamlit app for consistency across slate types, updating references for 'Late', 'Secondary', and 'Auxiliary' slates in both DK and FD lineups.

src/streamlit_app.py

@@ -202,12 +202,12 @@ def init_DK_lineups(type_var, slate_var):
             # Map names
             raw_display[dict_columns] = raw_display[dict_columns].apply(lambda x: x.map(names_dict))
         elif slate_var == 'Auxiliary':
-            collection = db['DK_NFL_Turbo_name_map']
+            collection = db['DK_NFL_Late_name_map']
             cursor = collection.find()
             raw_data = pd.DataFrame(list(cursor))
             names_dict = dict(zip(raw_data['key'], raw_data['value']))
             
-            collection = db['DK_NFL_Turbo_seed_frame']
+            collection = db['DK_NFL_Late_seed_frame']
             cursor = collection.find().limit(10000)
 
             raw_display = pd.DataFrame(list(cursor))
@@ -217,19 +217,19 @@ def init_DK_lineups(type_var, slate_var):
             raw_display[dict_columns] = raw_display[dict_columns].apply(lambda x: x.map(names_dict))
     elif type_var == 'Showdown':
         if slate_var == 'Main':
-            collection = db['DK_NFL_SD1_seed_frame']
+            collection = db['DK_NFL_SD_seed_frame']
             cursor = collection.find().limit(10000)
 
             raw_display = pd.DataFrame(list(cursor))
             raw_display = raw_display[['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
         elif slate_var == 'Secondary':
-            collection = db['DK_NFL_SD2_seed_frame']
+            collection = db['DK_NFL_Secondary_SD_seed_frame']
             cursor = collection.find().limit(10000)
 
             raw_display = pd.DataFrame(list(cursor))
             raw_display = raw_display[['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
         elif slate_var == 'Auxiliary':
-            collection = db['DK_NFL_SD3_seed_frame']
+            collection = db['DK_NFL_Auxiliary_SD_seed_frame']
             cursor = collection.find().limit(10000)
 
             raw_display = pd.DataFrame(list(cursor))
@@ -272,12 +272,12 @@ def init_FD_lineups(type_var, slate_var):
                 # Map names
                 raw_display[dict_columns] = raw_display[dict_columns].apply(lambda x: x.map(names_dict))
             elif slate_var == 'Auxiliary':
-                collection = db['FD_NFL_Turbo_name_map']
+                collection = db['FD_NFL_Late_name_map']
                 cursor = collection.find()
                 raw_data = pd.DataFrame(list(cursor))
                 names_dict = dict(zip(raw_data['key'], raw_data['value']))
 
-                collection = db['FD_NFL_Turbo_seed_frame']
+                collection = db['FD_NFL_Late_seed_frame']
                 cursor = collection.find().limit(10000)
             
                 raw_display = pd.DataFrame(list(cursor))
@@ -288,19 +288,19 @@ def init_FD_lineups(type_var, slate_var):
 
         elif type_var == 'Showdown':
             if slate_var == 'Main':
-                collection = db['FD_NFL_SD1_seed_frame']
+                collection = db['FD_NFL_SD_seed_frame']
                 cursor = collection.find().limit(10000)
 
                 raw_display = pd.DataFrame(list(cursor))
                 raw_display = raw_display[['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
             elif slate_var == 'Secondary':
-                collection = db['FD_NFL_SD2_seed_frame']
+                collection = db['FD_NFL_Secondary_SD_seed_frame']
                 cursor = collection.find().limit(10000)
 
                 raw_display = pd.DataFrame(list(cursor))
                 raw_display = raw_display[['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
             elif slate_var == 'Auxiliary':
-                collection = db['FD_NFL_SD3_seed_frame']
+                collection = db['FD_NFL_Auxiliary_SD_seed_frame']
                 cursor = collection.find().limit(10000)
             
                 raw_display = pd.DataFrame(list(cursor))