Enhance DK and FD seed frame functions in Streamlit app to support player and team locking/removal. Updated function signatures and query logic to filter lineups based on user-defined constraints. Adjusted calls to these functions throughout the app for consistency.

src/streamlit_app.py

@@ -62,7 +62,7 @@ st.markdown("""
 </style>""", unsafe_allow_html=True)
 
 @st.cache_data(ttl = 600)
-def init_DK_seed_frames(sharp_split):
+def init_DK_seed_frames(sharp_split, player_lock_var1, team_lock_var1, player_remove_var1, team_remove_var1):
 
     collection = db['DK_NFL_name_map']
     cursor = collection.find()
@@ -70,6 +70,44 @@ def init_DK_seed_frames(sharp_split):
     names_dict = dict(zip(raw_data['key'], raw_data['value']))
     
     collection = db["DK_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))
@@ -82,7 +120,7 @@ def init_DK_seed_frames(sharp_split):
     return DK_seed
 
 @st.cache_data(ttl = 600)
-def init_DK_Secondary_seed_frames(sharp_split):  
+def init_DK_Secondary_seed_frames(sharp_split, player_lock_var1, team_lock_var1, player_remove_var1, team_remove_var1):  
 
     collection = db['DK_NFL_Secondary_name_map']
     cursor = collection.find()
@@ -90,6 +128,44 @@ def init_DK_Secondary_seed_frames(sharp_split):
     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))
@@ -102,7 +178,7 @@ def init_DK_Secondary_seed_frames(sharp_split):
     return DK_seed
 
 @st.cache_data(ttl = 599)
-def init_FD_seed_frames(sharp_split): 
+def init_FD_seed_frames(sharp_split, player_lock_var1, team_lock_var1, player_remove_var1, team_remove_var1): 
 
     collection = db['FD_NFL_name_map']
     cursor = collection.find()
@@ -110,6 +186,44 @@ def init_FD_seed_frames(sharp_split):
     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))
@@ -122,7 +236,7 @@ def init_FD_seed_frames(sharp_split):
     return FD_seed
 
 @st.cache_data(ttl = 599)
-def init_FD_Secondary_seed_frames(sharp_split):  
+def init_FD_Secondary_seed_frames(sharp_split, player_lock_var1, team_lock_var1, player_remove_var1, team_remove_var1):  
 
     collection = db['FD_NFL_Secondary_name_map']
     cursor = collection.find()
@@ -130,6 +244,44 @@ def init_FD_Secondary_seed_frames(sharp_split):
     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))
@@ -219,8 +371,8 @@ 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))
@@ -277,11 +429,11 @@ 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)
+                    st.session_state.working_seed = init_DK_seed_frames(sharp_split, player_lock_var1, team_lock_var1, player_remove_var1, team_remove_var1)
                     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)
+                    st.session_state.working_seed = init_DK_Secondary_seed_frames(sharp_split, player_lock_var1, team_lock_var1, player_remove_var1, team_remove_var1)
                     dk_raw, fd_raw = init_baselines('Secondary Slate')
                     dk_id_dict = dict(zip(dk_raw.Player, dk_raw.player_ID)) 
                     
@@ -289,11 +441,11 @@ 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)
+                    st.session_state.working_seed = init_FD_seed_frames(sharp_split, player_lock_var1, team_lock_var1, player_remove_var1, team_remove_var1)
                     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)
+                    st.session_state.working_seed = init_FD_Secondary_seed_frames(sharp_split, player_lock_var1, team_lock_var1, player_remove_var1, team_remove_var1)
                     dk_raw, fd_raw = init_baselines('Secondary Slate')
                     fd_id_dict = dict(zip(fd_raw.Player, fd_raw.player_ID))
                     
@@ -719,8 +871,8 @@ 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))
@@ -769,10 +921,10 @@ 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
@@ -780,10 +932,10 @@ 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
@@ -809,12 +961,12 @@ 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')
                         
@@ -832,11 +984,11 @@ 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')