Added lineups page

app.py

@@ -36,15 +36,22 @@ def init_conn():
           "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
           "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/gspread-connection%40sheets-api-connect-378620.iam.gserviceaccount.com"
         }
+
+        uri = st.secrets['mongo_uri']
+        client = pymongo.MongoClient(uri, retryWrites=True, serverSelectionTimeoutMS=500000)
+        db = client["NBA_DFS"]
      
         NBA_Data = st.secrets['NBA_Data']
 
         gc = gspread.service_account_from_dict(credentials)
         gc2 = gspread.service_account_from_dict(credentials2)
 
-        return gc, gc2, NBA_Data
+        return gc, gc2, db, NBA_Data
     
-gcservice_account, gcservice_account2, NBA_Data = init_conn()
+gcservice_account, gcservice_account2, db, NBA_Data = init_conn()
+
+dk_columns = ['PG', 'SG', 'SF', 'PF', 'C', 'G', 'F', 'FLEX', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']
+fd_columns = ['PG1', 'PG2', 'SG1', 'SG2', 'SF1', 'SF2', 'PF1', 'PF2', 'C1', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']
 
 @st.cache_data(ttl=300)
 def load_overall_stats():
@@ -102,10 +109,41 @@ def load_overall_stats():
 
     return dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, timestamp
 
+@st.cache_data(ttl = 300)
+def init_DK_lineups():  
+    
+        collection = db["DK_NBA_seed_frame"] 
+        cursor = collection.find()
+    
+        raw_display = pd.DataFrame(list(cursor))
+        raw_display = raw_display[['PG', 'SG', 'SF', 'PF', 'C', 'G', 'F', 'FLEX', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
+        DK_seed = raw_display.head(10000).to_numpy()
+
+        return DK_seed
+
+@st.cache_data(ttl = 300)
+def init_FD_lineups():  
+    
+        collection = db["FD_NBA_seed_frame"] 
+        cursor = collection.find()
+    
+        raw_display = pd.DataFrame(list(cursor))
+        raw_display = raw_display[['PG1', 'PG2', 'SG1', 'SG2', 'SF1', 'SF2', 'PF1', 'PF2', 'C1', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
+        FD_seed = raw_display.head(10000).to_numpy()
+
+        return FD_seed
+
 def convert_df_to_csv(df):
     return df.to_csv().encode('utf-8')
 
+@st.cache_data
+def convert_df(array):
+    array = pd.DataFrame(array, columns=column_names)
+    return array.to_csv().encode('utf-8')
+
 dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, timestamp = load_overall_stats()
+dk_lineups = init_DK_lineups()
+fd_lineups = init_FD_lineups()
 t_stamp = f"Last Update: " + str(timestamp) + f" CST"
 
 tab1, tab2 = st.tabs(['Range of Outcomes', 'Uploads and Info'])
@@ -117,11 +155,13 @@ with tab1:
     with col1:
         st.info(t_stamp)
         if st.button("Load/Reset Data", key='reset1'):
-              st.cache_data.clear()
-              dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, timestamp = load_overall_stats()
-              t_stamp = f"Last Update: " + str(timestamp) + f" CST"
-              for key in st.session_state.keys():
-                  del st.session_state[key]
+            st.cache_data.clear()
+            dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, timestamp = load_overall_stats()
+            dk_lineups = init_DK_lineups()
+            fd_lineups = init_FD_lineups()
+            t_stamp = f"Last Update: " + str(timestamp) + f" CST"
+            for key in st.session_state.keys():
+                del st.session_state[key]
         site_var2 = st.radio("What table would you like to display?", ('Draftkings', 'Fanduel'), key='site_var2')
         if site_var2 == 'Draftkings':
             site_baselines = roo_raw[roo_raw['site'] == 'Draftkings']
@@ -167,17 +207,69 @@ with tab1:
                     )
 
 with tab2:
-    st.info("The Projections file can have any columns in any order, but must contain columns explicitly named: 'Player', 'Salary', 'Position', 'Team', 'Opp', 'Minutes', 'Median', 'Own'.")
-    col1, col2 = st.columns([1, 5])
-
+    col1, col2 = st.columns([1, 7])
     with col1:
-        proj_file = st.file_uploader("Upload Projections File", key = 'proj_uploader')
-    
-        if proj_file is not None:
-                  try:
-                            proj_dataframe = pd.read_csv(proj_file)
-                  except:
-                            proj_dataframe = pd.read_excel(proj_file)
+        if st.button("Load/Reset Data", key='reset1'):
+            st.cache_data.clear()
+            dk_raw, fd_raw, dk_raw_sec, fd_raw_sec, roo_raw, timestamp = load_overall_stats()
+            dk_lineups = init_DK_lineups()
+            fd_lineups = init_FD_lineups()
+            t_stamp = f"Last Update: " + str(timestamp) + f" CST"
+            for key in st.session_state.keys():
+                del st.session_state[key]
+              
+        slate_var1 = st.radio("Which data are you loading?", ('Main Slate', 'Just the Main Slate'))
+        site_var1 = st.radio("What site are you working with?", ('Draftkings', 'Fanduel'))
+        if site_var1 == 'Draftkings':
+            raw_baselines = dk_raw
+            column_names = dk_columns
+            
+            player_var1 = st.radio("Do you want a frame with specific Players?", ('Full Slate', 'Specific Players'), key='player_var1')
+            if player_var1 == 'Specific Teams':
+                    player_var2 = st.multiselect('Which players do you want?', options = dk_raw['Player'].unique())
+            elif player_var1 == 'Full Slate':
+                    player_var2 = dk_raw.Player.values.tolist()
+                    
+        elif site_var1 == 'Fanduel':
+            raw_baselines = fd_raw
+            column_names = fd_columns
+            
+            player_var1 = st.radio("Do you want a frame with specific Players?", ('Full Slate', 'Specific Players'), key='player_var1')
+            if player_var1 == 'Specific Teams':
+                    player_var2 = st.multiselect('Which players do you want?', options = dk_raw['Player'].unique())
+            elif player_var1 == 'Full Slate':
+                    player_var2 = dk_raw.Player.values.tolist()
+        
+
+        if st.button("Prepare data export", key='data_export'):
+                data_export = st.session_state.working_seed.copy()
+                st.download_button(
+                    label="Export optimals set",
+                    data=convert_df(data_export),
+                    file_name='NBA_optimals_export.csv',
+                    mime='text/csv',
+                )
+            
     with col2:
-        if proj_file is not None:  
-                  st.dataframe(proj_dataframe.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True)
+        if st.button("Load Lineups", key='load_data'):
+            if site_var1 == 'Draftkings':
+                if 'working_seed' in st.session_state:
+                    st.session_state.working_seed = st.session_state.working_seed[np.isin(st.session_state.working_seed[:, 9], player_var2)]
+                    st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:151], columns=column_names)
+                elif 'working_seed' not in st.session_state:
+                    st.session_state.working_seed = dk_lineups.copy()
+                    st.session_state.working_seed = st.session_state.working_seed[np.isin(st.session_state.working_seed[:, 9], player_var2)]
+                    st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:151], columns=column_names)
+                
+            elif site_var1 == 'Fanduel':
+                if 'working_seed' in st.session_state:
+                    st.session_state.working_seed = st.session_state.working_seed[np.isin(st.session_state.working_seed[:, 10], player_var2)]
+                    st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:151], columns=column_names)
+                elif 'working_seed' not in st.session_state:
+                    st.session_state.working_seed = fd_lineups.copy()
+                    st.session_state.working_seed = st.session_state.working_seed[np.isin(st.session_state.working_seed[:, 10], player_var2)]
+                    st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:151], columns=column_names)
+                
+        with st.container():
+            if 'data_export_display' in st.session_state:
+                st.dataframe(st.session_state.data_export_display.style.format(precision=2), use_container_width = True)