Adding showdown support

app.py

@@ -136,6 +136,14 @@ def grab_nfl_reg_salaries():
     records = records.rename(columns={'Display Name': 'Name', 'draftableId': 'ID', 'Position': 'Roster Position'})
     return records
 
+def grab_nfl_showdown_salaries():
+    collection = salaries_db["NFL_showdown_player_info"]
+    today_str = datetime.now().strftime("%Y%m%d")
+    records = pd.DataFrame(list(collection.find({'Contest Date': {'$gte': today_str}})))
+    records = records[['Display Name', 'draftableId', 'Position', 'Salary']]
+    records = records.rename(columns={'Display Name': 'Name', 'draftableId': 'ID', 'Position': 'Roster Position'})
+    return records
+
 def grab_nba_reg_salaries():
     collection = salaries_db["NBA_reg_player_info"]
     today_str = datetime.now().strftime("%Y%m%d")
@@ -144,6 +152,14 @@ def grab_nba_reg_salaries():
     records = records.rename(columns={'Display Name': 'Name', 'draftableId': 'ID', 'Position': 'Roster Position'})
     return records
 
+def grab_nba_showdown_salaries():
+    collection = salaries_db["NBA_showdown_player_info"]
+    today_str = datetime.now().strftime("%Y%m%d")
+    records = pd.DataFrame(list(collection.find({'Contest Date': {'$gte': today_str}})))
+    records = records[['Display Name', 'draftableId', 'Position', 'Salary']]
+    records = records.rename(columns={'Display Name': 'Name', 'draftableId': 'ID', 'Position': 'Roster Position'})
+    return records
+
 def grab_mlb_reg_salaries():
     collection = salaries_db["MLB_reg_player_info"]
     today_str = datetime.now().strftime("%Y%m%d")
@@ -152,6 +168,14 @@ def grab_mlb_reg_salaries():
     records = records.rename(columns={'Display Name': 'Name', 'draftableId': 'ID', 'Position': 'Roster Position'})
     return records
 
+def grab_mlb_showdown_salaries():
+    collection = salaries_db["MLB_showdown_player_info"]
+    today_str = datetime.now().strftime("%Y%m%d")
+    records = pd.DataFrame(list(collection.find({'Contest Date': {'$gte': today_str}})))
+    records = records[['Display Name', 'draftableId', 'Position', 'Salary']]
+    records = records.rename(columns={'Display Name': 'Name', 'draftableId': 'ID', 'Position': 'Roster Position'})
+    return records
+
 def grab_nhl_reg_salaries():
     collection = salaries_db["NHL_reg_player_info"]
     today_str = datetime.now().strftime("%Y%m%d")
@@ -160,6 +184,14 @@ def grab_nhl_reg_salaries():
     records = records.rename(columns={'Display Name': 'Name', 'draftableId': 'ID', 'Position': 'Roster Position'})
     return records
 
+def grab_nhl_showdown_salaries():
+    collection = salaries_db["NHL_showdown_player_info"]
+    today_str = datetime.now().strftime("%Y%m%d")
+    records = pd.DataFrame(list(collection.find({'Contest Date': {'$gte': today_str}})))
+    records = records[['Display Name', 'draftableId', 'Position', 'Salary']]
+    records = records.rename(columns={'Display Name': 'Name', 'draftableId': 'ID', 'Position': 'Roster Position'})
+    return records
+
 def define_dk_nfl_showdown_slates():
     collection = nfl_db["DK_SD_NFL_ROO"]
     cursor = collection.find()
@@ -251,7 +283,9 @@ except:
     nba_slate_name_lookup_fd = {}
 
 nfl_reg_salaries = grab_nfl_reg_salaries()
+nfl_showdown_salaries = grab_nfl_showdown_salaries()
 nba_reg_salaries = grab_nba_reg_salaries()
+nba_showdown_salaries = grab_nba_showdown_salaries()
 
 # Memory optimization helper functions
 def chunk_name_matching(portfolio_names, csv_names, chunk_size=1000):
@@ -693,9 +727,15 @@ if selected_tab == 'Data Load':
                 if 'csv_file' in st.session_state:
                     del st.session_state['csv_file']
                 if sport_var == 'NBA':
-                    st.session_state['csv_file'] = load_csv(nba_reg_salaries)
+                    if type_var == 'Classic':
+                        st.session_state['csv_file'] = load_csv(nba_reg_salaries)
+                    elif type_var == 'Showdown':
+                        st.session_state['csv_file'] = load_csv(nba_showdown_salaries)
                 elif sport_var == 'NFL':
-                    st.session_state['csv_file'] = load_csv(nfl_reg_salaries)
+                    if type_var == 'Classic':
+                        st.session_state['csv_file'] = load_csv(nfl_reg_salaries)
+                    elif type_var == 'Showdown':
+                        st.session_state['csv_file'] = load_csv(nfl_showdown_salaries)
                 st.session_state['pricing_loaded'] = True
                 
             try:
@@ -883,14 +923,26 @@ if selected_tab == 'Data Load':
                 if st.button("Load from Database"):
                     if sport_var == 'NBA':
                         if site_var == 'Draftkings':
-                            projections_file = init_nba_baselines(type_var, site_var, slate_var3)[0]
+                            if type_var == 'Classic':
+                                projections_file = init_nba_baselines(type_var, site_var, slate_var3)[0]
+                            elif type_var == 'Showdown':
+                                projections_file = init_nba_baselines(type_var, site_var, slate_var3)[2]
                         elif site_var == 'Fanduel':
-                            projections_file = init_nba_baselines(type_var, site_var, slate_var3)[1]
+                            if type_var == 'Classic':
+                                projections_file = init_nba_baselines(type_var, site_var, slate_var3)[1]
+                            elif type_var == 'Showdown':
+                                projections_file = init_nba_baselines(type_var, site_var, slate_var3)[3]
                     elif sport_var == 'NFL':
                         if site_var == 'Draftkings':
-                            projections_file = init_nfl_baselines(type_var, site_var, slate_var3)[0]
+                            if type_var == 'Classic':
+                                projections_file = init_nfl_baselines(type_var, site_var, slate_var3)[0]
+                            elif type_var == 'Showdown':
+                                projections_file = init_nfl_baselines(type_var, site_var, slate_var3)[2]
                         elif site_var == 'Fanduel':
-                            projections_file = init_nfl_baselines(type_var, site_var, slate_var3)[1]
+                            if type_var == 'Classic':
+                                projections_file = init_nfl_baselines(type_var, site_var, slate_var3)[1]
+                            elif type_var == 'Showdown':
+                                projections_file = init_nfl_baselines(type_var, site_var, slate_var3)[3]
                     st.session_state['db_projections_file'] = projections_file
                     st.session_state['projections_loaded'] = True
             if 'projections_df' in st.session_state:

database_queries.py

@@ -465,11 +465,11 @@ def init_nba_baselines(type_var: str, site_var: str, slate_var: str):
         fd_sd_roo_raw['player_ID'] = fd_sd_roo_raw['player_ID'].astype(str)
         fd_sd_roo_raw['player_ID'] = fd_sd_roo_raw['player_ID'].str.rsplit('-', n=1).str[0].astype(str)
 
-        dk_roo_raw = dk_roo_raw.drop(columns=['player_ID', 'slate', 'version', 'timestamp', 'site'])
-        fd_roo_raw = fd_roo_raw.drop(columns=['player_ID', 'slate', 'version', 'timestamp', 'site'])
+        dk_sd_roo_raw = dk_sd_roo_raw.drop(columns=['player_ID', 'slate', 'version', 'timestamp', 'site'])
+        fd_sd_roo_raw = fd_sd_roo_raw.drop(columns=['player_ID', 'slate', 'version', 'timestamp', 'site'])
 
-        dk_roo_raw = dk_roo_raw.rename(columns={'Player': 'player_names', 'Position': 'position', 'Team': 'team', 'Salary': 'salary', 'Median': 'median', 'Own': 'ownership', 'CPT_Own': 'captain ownership'})
-        fd_roo_raw = fd_roo_raw.rename(columns={'Player': 'player_names', 'Position': 'position', 'Team': 'team', 'Salary': 'salary', 'Median': 'median', 'Own': 'ownership', 'CPT_Own': 'captain ownership'})
+        dk_sd_roo_raw = dk_sd_roo_raw.rename(columns={'Player': 'player_names', 'Position': 'position', 'Team': 'team', 'Salary': 'salary', 'Median': 'median', 'Own': 'ownership', 'CPT_Own': 'captain ownership'})
+        fd_sd_roo_raw = fd_sd_roo_raw.rename(columns={'Player': 'player_names', 'Position': 'position', 'Team': 'team', 'Salary': 'salary', 'Median': 'median', 'Own': 'ownership', 'CPT_Own': 'captain ownership'})
 
         dk_roo_raw = None
         fd_roo_raw = None