Enhance app.py: Added auxiliary seed frame functions for Draftkings and Fanduel, updated data handling for secondary and auxiliary slates, and modified UI options for slate selection.

app.py

@@ -66,9 +66,31 @@ def init_DK_secondary_seed_frames(sharp_split):
         dict_columns = ['SP1', 'SP2', 'C', '1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3']
         # Map names
         raw_display[dict_columns] = raw_display[dict_columns].apply(lambda x: x.map(names_dict))
+        DK_seed = raw_display.to_numpy()
+
+        return DK_seed
+
+@st.cache_data(ttl = 60)
+def init_DK_auxiliary_seed_frames(sharp_split):  
         
-        # Remove any remaining NaN values
-        raw_display = raw_display.dropna()
+        collection = db['DK_MLB_turbo_name_map']
+        cursor = collection.find()
+        raw_data = pd.DataFrame(list(cursor))
+        names_dict = dict(zip(raw_data['key'], raw_data['value']))
+
+        # Get the valid players from the Range of Outcomes collection
+        collection = db["Player_Range_Of_Outcomes"]
+        cursor = collection.find({"Site": "Draftkings", "Slate": "turbo_slate"})
+        valid_players = set(pd.DataFrame(list(cursor))['Player'].unique())
+    
+        collection = db["DK_MLB_turbo_seed_frame"] 
+        cursor = collection.find().limit(sharp_split)
+    
+        raw_display = pd.DataFrame(list(cursor))
+        raw_display = raw_display[['SP1', 'SP2', 'C', '1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
+        dict_columns = ['SP1', 'SP2', 'C', '1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3']
+        # Map names
+        raw_display[dict_columns] = raw_display[dict_columns].apply(lambda x: x.map(names_dict))
         DK_seed = raw_display.to_numpy()
 
         return DK_seed
@@ -91,12 +113,9 @@ def init_FD_seed_frames(sharp_split):
     
         raw_display = pd.DataFrame(list(cursor))
         raw_display = raw_display[['P', 'C_1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3', 'UTIL', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
-        dict_columns = ['P', 'C_1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3']
+        dict_columns = ['P', 'C_1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3', 'UTIL']
         # Map names
         raw_display[dict_columns] = raw_display[dict_columns].apply(lambda x: x.map(names_dict))
-        
-        # Remove any remaining NaN values
-        raw_display = raw_display.dropna()
         FD_seed = raw_display.to_numpy()
 
         return FD_seed
@@ -119,12 +138,34 @@ def init_FD_secondary_seed_frames(sharp_split):
     
         raw_display = pd.DataFrame(list(cursor))
         raw_display = raw_display[['P', 'C_1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3', 'UTIL', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
-        dict_columns = ['P', 'C_1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3']
+        dict_columns = ['P', 'C_1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3', 'UTIL']
+        # Map names
+        raw_display[dict_columns] = raw_display[dict_columns].apply(lambda x: x.map(names_dict))
+        FD_seed = raw_display.to_numpy()
+
+        return FD_seed
+
+@st.cache_data(ttl = 60)
+def init_FD_auxiliary_seed_frames(sharp_split):  
+    
+        collection = db['FD_MLB_turbo_name_map']
+        cursor = collection.find()
+        raw_data = pd.DataFrame(list(cursor))
+        names_dict = dict(zip(raw_data['key'], raw_data['value']))
+
+        # Get the valid players from the Range of Outcomes collection
+        collection = db["Player_Range_Of_Outcomes"]
+        cursor = collection.find({"Site": "Fanduel", "Slate": "turbo_slate"})
+        valid_players = set(pd.DataFrame(list(cursor))['Player'].unique())
+    
+        collection = db["FD_MLB_turbo_seed_frame"] 
+        cursor = collection.find().limit(sharp_split)
+    
+        raw_display = pd.DataFrame(list(cursor))
+        raw_display = raw_display[['P', 'C_1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3', 'UTIL', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
+        dict_columns = ['P', 'C_1B', '2B', '3B', 'SS', 'OF1', 'OF2', 'OF3', 'UTIL']
         # Map names
         raw_display[dict_columns] = raw_display[dict_columns].apply(lambda x: x.map(names_dict))
-        
-        # Remove any remaining NaN values
-        raw_display = raw_display.dropna()
         FD_seed = raw_display.to_numpy()
 
         return FD_seed
@@ -164,9 +205,21 @@ def init_baselines():
     fd_secondary = fd_secondary_roo_raw.dropna(subset=['Median'])
     fd_secondary = fd_secondary.rename(columns={'Own%': 'Own'})
 
+    dk_auxiliary_roo_raw = load_display[load_display['Site'] == 'Draftkings']
+    dk_auxiliary_roo_raw = dk_auxiliary_roo_raw[dk_auxiliary_roo_raw['Slate'] == 'turbo_slate']
+    dk_auxiliary_roo_raw['STDev'] = dk_auxiliary_roo_raw['Median'] / 3
+    dk_auxiliary = dk_auxiliary_roo_raw.dropna(subset=['Median'])
+    dk_auxiliary = dk_auxiliary.rename(columns={'Own%': 'Own'})
+
+    fd_auxiliary_roo_raw = load_display[load_display['Site'] == 'Fanduel']
+    fd_auxiliary_roo_raw = fd_auxiliary_roo_raw[fd_auxiliary_roo_raw['Slate'] == 'turbo_slate']
+    fd_auxiliary_roo_raw['STDev'] = fd_auxiliary_roo_raw['Median'] / 3
+    fd_auxiliary = fd_auxiliary_roo_raw.dropna(subset=['Median'])
+    fd_auxiliary = fd_auxiliary.rename(columns={'Own%': 'Own'})
+
     teams_playing_count = len(dk_raw.Team.unique())
 
-    return dk_raw, fd_raw, dk_secondary, fd_secondary, teams_playing_count
+    return dk_raw, fd_raw, dk_secondary, fd_secondary, dk_auxiliary, fd_auxiliary, teams_playing_count
 
 @st.cache_data
 def validate_lineup_players(df, valid_players, player_columns):
@@ -247,7 +300,7 @@ def sim_contest(Sim_size, seed_frame, maps_dict, Contest_Size, teams_playing_cou
         
     return Sim_Winners
 
-dk_raw, fd_raw, dk_secondary, fd_secondary, teams_playing_count = init_baselines()
+dk_raw, fd_raw, dk_secondary, fd_secondary, dk_auxiliary, fd_auxiliary, teams_playing_count = init_baselines()
 dk_id_dict = dict(zip(dk_raw.Player, dk_raw.player_id))
 fd_id_dict = dict(zip(fd_raw.Player, fd_raw.player_id))
 
@@ -261,11 +314,11 @@ with tab1:
                   del st.session_state[key]
               DK_seed = init_DK_seed_frames(10000)
               FD_seed = init_FD_seed_frames(10000)
-              dk_raw, fd_raw, dk_secondary, fd_secondary, teams_playing_count = init_baselines()
+              dk_raw, fd_raw, dk_secondary, fd_secondary, dk_auxiliary, fd_auxiliary, teams_playing_count = init_baselines()
               dk_id_dict = dict(zip(dk_raw.Player, dk_raw.player_id))
               fd_id_dict = dict(zip(fd_raw.Player, fd_raw.player_id))
 
-        sim_slate_var1 = st.radio("Which data are you loading?", ('Main Slate', 'Other Main Slate'), key='sim_slate_var1')
+        sim_slate_var1 = st.radio("Which data are you loading?", ('Main Slate', 'Secondary Slate', 'Auxiliary Slate'), key='sim_slate_var1')
         sim_site_var1 = st.radio("What site are you working with?", ('Draftkings', 'Fanduel'), key='sim_site_var1')
             
         contest_var1 = st.selectbox("What contest size are you simulating?", ('Small', 'Medium', 'Large', 'Custom'))
@@ -334,12 +387,34 @@ with tab1:
                     dk_id_dict = dict(zip(dk_raw.Player, dk_raw.player_id))
                     raw_baselines = dk_raw
                     column_names = dk_columns
+                elif sim_slate_var1 == 'Secondary Slate':
+                    st.session_state.working_seed = init_DK_secondary_seed_frames(sharp_split)
+                    dk_id_dict = dict(zip(dk_secondary.Player, dk_secondary.player_id))
+                    raw_baselines = dk_secondary
+                    column_names = dk_columns
+                elif sim_slate_var1 == 'Auxiliary Slate':
+                    st.session_state.working_seed = init_DK_auxiliary_seed_frames(sharp_split)
+                    dk_id_dict = dict(zip(dk_auxiliary.Player, dk_auxiliary.player_id))
+                    raw_baselines = dk_auxiliary
+                    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)
                     fd_id_dict = dict(zip(fd_raw.Player, fd_raw.player_id))
                     raw_baselines = fd_raw
                     column_names = fd_columns
+                elif sim_slate_var1 == 'Secondary Slate':
+                    st.session_state.working_seed = init_FD_secondary_seed_frames(sharp_split)
+                    fd_id_dict = dict(zip(fd_secondary.Player, fd_secondary.player_id))
+                    raw_baselines = fd_secondary
+                    column_names = fd_columns
+                elif sim_slate_var1 == 'Auxiliary Slate':
+                    st.session_state.working_seed = init_FD_auxiliary_seed_frames(sharp_split)
+                    fd_id_dict = dict(zip(fd_auxiliary.Player, fd_auxiliary.player_id))
+                    raw_baselines = fd_auxiliary
+                    column_names = fd_columns
+                    
 
             st.session_state.maps_dict = {
                     'Projection_map':dict(zip(raw_baselines.Player,raw_baselines.Median)),
@@ -370,7 +445,7 @@ with tab1:
             
             # Data Copying
             st.session_state.Sim_Winner_Export = Sim_Winner_Frame.copy()
-            for col in st.session_state.Sim_Winner_Export.iloc[:, 0:9].columns:
+            for col in st.session_state.Sim_Winner_Export.iloc[:, 0:10].columns:
                 st.session_state.Sim_Winner_Export[col] = st.session_state.Sim_Winner_Export[col].map(dk_id_dict)
             st.session_state.Sim_Winner_Export = st.session_state.Sim_Winner_Export.drop_duplicates(subset=['Team', 'Secondary', 'salary', 'unique_id'])
             
@@ -598,7 +673,7 @@ with tab2:
                 dk_id_dict = dict(zip(dk_raw.Player, dk_raw.player_id))
                 fd_id_dict = dict(zip(fd_raw.Player, fd_raw.player_id))
                 
-        slate_var1 = st.radio("Which data are you loading?", ('Main Slate', 'Secondary Slate'))
+        slate_var1 = st.radio("Which data are you loading?", ('Main Slate', 'Secondary Slate', 'Auxiliary Slate'))
         site_var1 = st.radio("What site are you working with?", ('Draftkings', 'Fanduel'))
         sharp_split_var = st.number_input("How many lineups do you want?", value=10000, max_value=500000, min_value=10000, step=10000)
         lineup_num_var = st.number_input("How many lineups do you want to display?", min_value=1, max_value=500, value=10, step=1)
@@ -658,10 +733,17 @@ with tab2:
                         elif slate_var1 == 'Secondary Slate':
                             st.session_state.working_seed = init_DK_secondary_seed_frames(sharp_split_var)
 
-                            dk_id_dict = dict(zip(dk_raw.Player, dk_raw.player_id))
-                            raw_baselines = dk_raw
+                            dk_id_dict = dict(zip(dk_secondary.Player, dk_secondary.player_id))
+                            raw_baselines = dk_secondary
+                            column_names = dk_columns
+                        elif slate_var1 == 'Auxiliary Slate':
+                            st.session_state.working_seed = init_DK_auxiliary_seed_frames(sharp_split_var)
+
+                            dk_id_dict = dict(zip(dk_auxiliary.Player, dk_auxiliary.player_id))
+                            raw_baselines = dk_auxiliary
                             column_names = dk_columns
                 
+
                     elif site_var1 == 'Fanduel':
                         if slate_var1 == 'Main Slate':
                             st.session_state.working_seed = init_FD_seed_frames(sharp_split_var)
@@ -672,8 +754,14 @@ with tab2:
                         elif slate_var1 == 'Secondary Slate':
                             st.session_state.working_seed = init_FD_secondary_seed_frames(sharp_split_var)
 
-                            fd_id_dict = dict(zip(fd_raw.Player, fd_raw.player_id))
-                            raw_baselines = fd_raw
+                            fd_id_dict = dict(zip(fd_secondary.Player, fd_secondary.player_id))
+                            raw_baselines = fd_secondary
+                            column_names = fd_columns
+                        elif slate_var1 == 'Auxiliary Slate':
+                            st.session_state.working_seed = init_FD_auxiliary_seed_frames(sharp_split_var)
+
+                            fd_id_dict = dict(zip(fd_auxiliary.Player, fd_auxiliary.player_id))
+                            raw_baselines = fd_auxiliary
                             column_names = fd_columns
                     if site_var1 == 'Draftkings':
                         st.session_state.working_seed = st.session_state.working_seed[np.isin(st.session_state.working_seed[:, 12], team_var2)]
@@ -709,7 +797,19 @@ with tab2:
 
                     raw_baselines = dk_raw
                     column_names = dk_columns
-            
+                elif slate_var1 == 'Secondary Slate':
+                    st.session_state.working_seed = init_DK_secondary_seed_frames(sharp_split_var)
+
+                    dk_id_dict = dict(zip(dk_secondary.Player, dk_secondary.player_id))
+                    raw_baselines = dk_secondary
+                    column_names = dk_columns
+                elif slate_var1 == 'Auxiliary Slate':
+                    st.session_state.working_seed = init_DK_auxiliary_seed_frames(sharp_split_var)
+
+                    dk_id_dict = dict(zip(dk_auxiliary.Player, dk_auxiliary.player_id))
+                    raw_baselines = dk_auxiliary
+                    column_names = dk_columns
+
                 st.session_state.working_seed = st.session_state.working_seed[np.isin(st.session_state.working_seed[:, 12], team_var2)]
                 st.session_state.working_seed = st.session_state.working_seed[np.isin(st.session_state.working_seed[:, 13], stack_var2)]
                 st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:lineup_num_var], columns=column_names)
@@ -726,6 +826,18 @@ with tab2:
                     
                     raw_baselines = fd_raw
                     column_names = fd_columns
+                elif slate_var1 == 'Secondary Slate':
+                    st.session_state.working_seed = init_FD_secondary_seed_frames(sharp_split_var)
+
+                    fd_id_dict = dict(zip(fd_secondary.Player, fd_secondary.player_id))
+                    raw_baselines = fd_secondary
+                    column_names = fd_columns
+                elif slate_var1 == 'Auxiliary Slate':
+                    st.session_state.working_seed = init_FD_auxiliary_seed_frames(sharp_split_var)
+
+                    fd_id_dict = dict(zip(fd_auxiliary.Player, fd_auxiliary.player_id))
+                    raw_baselines = fd_auxiliary
+                    column_names = fd_columns
                 st.session_state.working_seed = st.session_state.working_seed[np.isin(st.session_state.working_seed[:, 11], team_var2)]
                 st.session_state.working_seed = st.session_state.working_seed[np.isin(st.session_state.working_seed[:, 12], stack_var2)]
                 st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:lineup_num_var], columns=column_names)