reverting player and team locks

src/streamlit_app.py

@@ -62,55 +62,14 @@ st.markdown("""
 </style>""", unsafe_allow_html=True)
 
 @st.cache_data(ttl = 600)
-def init_DK_seed_frames(sharp_split, player_lock_var1, team_lock_var1, player_remove_var1, team_remove_var1):
+def init_DK_seed_frames(sharp_split):
 
     collection = db['DK_NFL_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_seed_frame"] 
-    
-    # Build the query
-    query = {}
-    if player_lock_var1 != [] or team_lock_var1 != []:
-        # Build query to check if locked players exist in any position column
-        query_conditions = []
-        
-        if player_lock_var1:
-            position_columns = ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST']
-            player_conditions = []
-            for column in position_columns:
-                player_conditions.append({column: {'$in': player_lock_var1}})
-            query_conditions.append({'$or': player_conditions})
-        
-        if team_lock_var1:
-            query_conditions.append({'Team': {'$in': team_lock_var1}})
-        
-        if len(query_conditions) == 1:
-            query = query_conditions[0]
-        else:
-            query = {'$and': query_conditions}
-            
-    elif player_remove_var1 != [] or team_remove_var1 != []:
-        # Build query to exclude lineups containing removed players
-        query_conditions = []
-        
-        if player_remove_var1:
-            position_columns = ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST']
-            for column in position_columns:
-                query_conditions.append({column: {'$nin': player_remove_var1}})
-        
-        if team_remove_var1:
-            query_conditions.append({'Team': {'$nin': team_remove_var1}})
-        
-        if len(query_conditions) == 1:
-            query = query_conditions[0]
-        else:
-            query = {'$and': query_conditions}
-    
-    # Execute the query once
-    cursor = collection.find(query).limit(sharp_split)
+    cursor = collection.find().limit(sharp_split)
 
     raw_display = pd.DataFrame(list(cursor))
     raw_display = raw_display[['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
@@ -122,52 +81,13 @@ def init_DK_seed_frames(sharp_split, player_lock_var1, team_lock_var1, player_re
     return DK_seed
 
 @st.cache_data(ttl = 600)
-def init_DK_Secondary_seed_frames(sharp_split, player_lock_var1, team_lock_var1, player_remove_var1, team_remove_var1):  
+def init_DK_Secondary_seed_frames(sharp_split):  
 
     collection = db['DK_NFL_Secondary_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_Secondary_seed_frame"] 
-    if player_lock_var1 != [] or team_lock_var1 != []:
-        # Build query to check if locked players exist in any position column
-        player_conditions = []
-        if player_lock_var1:
-            position_columns = ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST']
-            for column in position_columns:
-                player_conditions.append({column: {'$in': player_lock_var1}})
-        
-        query_conditions = []
-        if player_conditions:
-            query_conditions.append({'$or': player_conditions})
-        if team_lock_var1:
-            query_conditions.append({'Team': {'$in': team_lock_var1}})
-        
-        if len(query_conditions) == 1:
-            collection = collection.find(query_conditions[0])
-        else:
-            collection = collection.find({'$and': query_conditions})
-    elif player_remove_var1 != [] or team_remove_var1 != []:
-        # Build query to exclude lineups containing removed players
-        exclusion_conditions = []
-        if player_remove_var1:
-            position_columns = ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST']
-            for column in position_columns:
-                exclusion_conditions.append({column: {'$nin': player_remove_var1}})
-        
-        query_conditions = []
-        if exclusion_conditions:
-            query_conditions.extend(exclusion_conditions)
-        if team_remove_var1:
-            query_conditions.append({'Team': {'$nin': team_remove_var1}})
-        
-        if len(query_conditions) == 1:
-            collection = collection.find(query_conditions[0])
-        else:
-            collection = collection.find({'$and': query_conditions})
-    else:
-        collection = collection.find()
     cursor = collection.find().limit(sharp_split)
 
     raw_display = pd.DataFrame(list(cursor))
@@ -180,7 +100,7 @@ def init_DK_Secondary_seed_frames(sharp_split, player_lock_var1, team_lock_var1,
     return DK_seed
 
 @st.cache_data(ttl = 599)
-def init_FD_seed_frames(sharp_split, player_lock_var1, team_lock_var1, player_remove_var1, team_remove_var1): 
+def init_FD_seed_frames(sharp_split): 
 
     collection = db['FD_NFL_name_map']
     cursor = collection.find()
@@ -188,44 +108,6 @@ def init_FD_seed_frames(sharp_split, player_lock_var1, team_lock_var1, player_re
     names_dict = dict(zip(raw_data['key'], raw_data['value']))
     
     collection = db["FD_NFL_seed_frame"] 
-    if player_lock_var1 != [] or team_lock_var1 != []:
-        # Build query to check if locked players exist in any position column
-        player_conditions = []
-        if player_lock_var1:
-            position_columns = ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST']
-            for column in position_columns:
-                player_conditions.append({column: {'$in': player_lock_var1}})
-        
-        query_conditions = []
-        if player_conditions:
-            query_conditions.append({'$or': player_conditions})
-        if team_lock_var1:
-            query_conditions.append({'Team': {'$in': team_lock_var1}})
-        
-        if len(query_conditions) == 1:
-            collection = collection.find(query_conditions[0])
-        else:
-            collection = collection.find({'$and': query_conditions})
-    elif player_remove_var1 != [] or team_remove_var1 != []:
-        # Build query to exclude lineups containing removed players
-        exclusion_conditions = []
-        if player_remove_var1:
-            position_columns = ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST']
-            for column in position_columns:
-                exclusion_conditions.append({column: {'$nin': player_remove_var1}})
-        
-        query_conditions = []
-        if exclusion_conditions:
-            query_conditions.extend(exclusion_conditions)
-        if team_remove_var1:
-            query_conditions.append({'Team': {'$nin': team_remove_var1}})
-        
-        if len(query_conditions) == 1:
-            collection = collection.find(query_conditions[0])
-        else:
-            collection = collection.find({'$and': query_conditions})
-    else:
-        collection = collection.find()
     cursor = collection.find().limit(sharp_split)
 
     raw_display = pd.DataFrame(list(cursor))
@@ -238,7 +120,7 @@ def init_FD_seed_frames(sharp_split, player_lock_var1, team_lock_var1, player_re
     return FD_seed
 
 @st.cache_data(ttl = 599)
-def init_FD_Secondary_seed_frames(sharp_split, player_lock_var1, team_lock_var1, player_remove_var1, team_remove_var1):  
+def init_FD_Secondary_seed_frames(sharp_split):  
 
     collection = db['FD_NFL_Secondary_name_map']
     cursor = collection.find()
@@ -246,44 +128,6 @@ def init_FD_Secondary_seed_frames(sharp_split, player_lock_var1, team_lock_var1,
     names_dict = dict(zip(raw_data['key'], raw_data['value']))
     
     collection = db["FD_NFL_Secondary_seed_frame"] 
-    if player_lock_var1 != [] or team_lock_var1 != []:
-        # Build query to check if locked players exist in any position column
-        player_conditions = []
-        if player_lock_var1:
-            position_columns = ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST']
-            for column in position_columns:
-                player_conditions.append({column: {'$in': player_lock_var1}})
-        
-        query_conditions = []
-        if player_conditions:
-            query_conditions.append({'$or': player_conditions})
-        if team_lock_var1:
-            query_conditions.append({'Team': {'$in': team_lock_var1}})
-        
-        if len(query_conditions) == 1:
-            collection = collection.find(query_conditions[0])
-        else:
-            collection = collection.find({'$and': query_conditions})
-    elif player_remove_var1 != [] or team_remove_var1 != []:
-        # Build query to exclude lineups containing removed players
-        exclusion_conditions = []
-        if player_remove_var1:
-            position_columns = ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST']
-            for column in position_columns:
-                exclusion_conditions.append({column: {'$nin': player_remove_var1}})
-        
-        query_conditions = []
-        if exclusion_conditions:
-            query_conditions.extend(exclusion_conditions)
-        if team_remove_var1:
-            query_conditions.append({'Team': {'$nin': team_remove_var1}})
-        
-        if len(query_conditions) == 1:
-            collection = collection.find(query_conditions[0])
-        else:
-            collection = collection.find({'$and': query_conditions})
-    else:
-        collection = collection.find()
     cursor = collection.find().limit(sharp_split)
 
     raw_display = pd.DataFrame(list(cursor))
@@ -373,8 +217,8 @@ if st.button("Load/Reset Data", key='reset2'):
     st.cache_data.clear()
     for key in st.session_state.keys():
         del st.session_state[key]
-    DK_seed = init_DK_seed_frames(10000, [], [], [], [])
-    FD_seed = init_FD_seed_frames(10000, [], [], [], [])
+    DK_seed = init_DK_seed_frames(10000)
+    FD_seed = init_FD_seed_frames(10000)
     dk_raw, fd_raw = init_baselines('Main Slate')
     dk_id_dict = dict(zip(dk_raw.Player, dk_raw.player_ID))
     fd_id_dict = dict(zip(fd_raw.Player, fd_raw.player_ID))
@@ -431,11 +275,11 @@ if selected_tab == "Contest Sims":
         if 'working_seed' not in st.session_state:
             if sim_site_var1 == 'Draftkings':
                 if sim_slate_var1 == 'Main Slate':
-                    st.session_state.working_seed = init_DK_seed_frames(sharp_split, player_lock_var1, team_lock_var1, player_remove_var1, team_remove_var1)
+                    st.session_state.working_seed = init_DK_seed_frames(sharp_split)
                     dk_raw, fd_raw = init_baselines('Main Slate')
                     dk_id_dict = dict(zip(dk_raw.Player, dk_raw.player_ID)) 
                 elif sim_slate_var1 == 'Secondary Slate':
-                    st.session_state.working_seed = init_DK_Secondary_seed_frames(sharp_split, player_lock_var1, team_lock_var1, player_remove_var1, team_remove_var1)
+                    st.session_state.working_seed = init_DK_Secondary_seed_frames(sharp_split)
                     dk_raw, fd_raw = init_baselines('Secondary Slate')
                     dk_id_dict = dict(zip(dk_raw.Player, dk_raw.player_ID)) 
                     
@@ -443,11 +287,11 @@ if selected_tab == "Contest Sims":
                 column_names = dk_columns
             elif sim_site_var1 == 'Fanduel':
                 if sim_slate_var1 == 'Main Slate':
-                    st.session_state.working_seed = init_FD_seed_frames(sharp_split, player_lock_var1, team_lock_var1, player_remove_var1, team_remove_var1)
+                    st.session_state.working_seed = init_FD_seed_frames(sharp_split)
                     dk_raw, fd_raw = init_baselines('Main Slate')
                     fd_id_dict = dict(zip(fd_raw.Player, fd_raw.player_ID))
                 elif sim_slate_var1 == 'Secondary Slate':
-                    st.session_state.working_seed = init_FD_Secondary_seed_frames(sharp_split, player_lock_var1, team_lock_var1, player_remove_var1, team_remove_var1)
+                    st.session_state.working_seed = init_FD_Secondary_seed_frames(sharp_split)
                     dk_raw, fd_raw = init_baselines('Secondary Slate')
                     fd_id_dict = dict(zip(fd_raw.Player, fd_raw.player_ID))
                     
@@ -873,8 +717,8 @@ if selected_tab == "Data Export":
               st.cache_data.clear()
               for key in st.session_state.keys():
                   del st.session_state[key]
-              DK_seed = init_DK_seed_frames(10000, [], [], [], [])
-              FD_seed = init_FD_seed_frames(10000, [], [], [], [])
+              DK_seed = init_DK_seed_frames(10000)
+              FD_seed = init_FD_seed_frames(10000)
               dk_raw, fd_raw = init_baselines('Main Slate')
               dk_id_dict = dict(zip(dk_raw.Player, dk_raw.player_ID))
               fd_id_dict = dict(zip(fd_raw.Player, fd_raw.player_ID))
@@ -923,10 +767,10 @@ if selected_tab == "Data Export":
                 elif 'working_seed' not in st.session_state:
                     if site_var1 == 'Draftkings':
                         if slate_var1 == 'Main Slate':
-                            st.session_state.working_seed = init_DK_seed_frames(sharp_split_var, [], [], [], [])
+                            st.session_state.working_seed = init_DK_seed_frames(sharp_split_var)
                             dk_id_dict = dict(zip(st.session_state.working_seed.Player, st.session_state.working_seed.player_ID))
                         elif slate_var1 == 'Secondary Slate':
-                            st.session_state.working_seed = init_DK_Secondary_seed_frames(sharp_split_var, [], [], [], [])
+                            st.session_state.working_seed = init_DK_Secondary_seed_frames(sharp_split_var)
                             dk_id_dict = dict(zip(st.session_state.working_seed.Player, st.session_state.working_seed.player_ID))
                             
                         raw_baselines = dk_raw
@@ -934,10 +778,10 @@ if selected_tab == "Data Export":
                 
                     elif site_var1 == 'Fanduel':
                         if slate_var1 == 'Main Slate':
-                            st.session_state.working_seed = init_FD_seed_frames(sharp_split_var, [], [], [], [])
+                            st.session_state.working_seed = init_FD_seed_frames(sharp_split_var)
                             fd_id_dict = dict(zip(st.session_state.working_seed.Player, st.session_state.working_seed.player_ID))
                         elif slate_var1 == 'Secondary Slate':
-                            st.session_state.working_seed = init_FD_Secondary_seed_frames(sharp_split_var, [], [], [], [])
+                            st.session_state.working_seed = init_FD_Secondary_seed_frames(sharp_split_var)
                             fd_id_dict = dict(zip(st.session_state.working_seed.Player, st.session_state.working_seed.player_ID))
                             
                         raw_baselines = fd_raw
@@ -963,12 +807,12 @@ if selected_tab == "Data Export":
                     st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:1000], columns=column_names)
                 elif 'working_seed' not in st.session_state:
                     if slate_var1 == 'Main Slate':
-                        st.session_state.working_seed = init_DK_seed_frames(sharp_split_var, [], [], [], [])
+                        st.session_state.working_seed = init_DK_seed_frames(sharp_split_var)
                         dk_id_dict = dict(zip(st.session_state.working_seed.Player, st.session_state.working_seed.player_ID))
                         dk_raw, fd_raw = init_baselines('Main Slate')
                         
                     elif slate_var1 == 'Secondary Slate':
-                        st.session_state.working_seed = init_DK_Secondary_seed_frames(sharp_split_var, [], [], [], [])
+                        st.session_state.working_seed = init_DK_Secondary_seed_frames(sharp_split_var)
                         dk_id_dict = dict(zip(st.session_state.working_seed.Player, st.session_state.working_seed.player_ID))
                         dk_raw, fd_raw = init_baselines('Secondary Slate')
                         
@@ -986,11 +830,11 @@ if selected_tab == "Data Export":
                     st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:1000], columns=column_names)
                 elif 'working_seed' not in st.session_state:
                     if slate_var1 == 'Main Slate':
-                        st.session_state.working_seed = init_FD_seed_frames(sharp_split_var, [], [], [], [])
+                        st.session_state.working_seed = init_FD_seed_frames(sharp_split_var)
                         fd_id_dict = dict(zip(st.session_state.working_seed.Player, st.session_state.working_seed.player_ID))
                         dk_raw, fd_raw = init_baselines('Main Slate')
                     elif slate_var1 == 'Secondary Slate':
-                        st.session_state.working_seed = init_FD_Secondary_seed_frames(sharp_split_var, [], [], [], [])
+                        st.session_state.working_seed = init_FD_Secondary_seed_frames(sharp_split_var)
                         fd_id_dict = dict(zip(st.session_state.working_seed.Player, st.session_state.working_seed.player_ID))
                         dk_raw, fd_raw = init_baselines('Secondary Slate')