adding all match outcomes

app.py

@@ -159,6 +159,14 @@ def calculate_max_bid_points(user_name):
     return max_bid_points
 
 
+def load_users(USERS_JSON):
+    try:
+        with open(USERS_JSON, 'r') as file:
+            return json.load(file)
+    except FileNotFoundError:
+        return {}
+
+
 def user_selection_and_prediction():
     users = list(load_data(USERS_JSON))
     user_name = st.selectbox("Select User", ["Select a user..."] + users)
@@ -203,7 +211,7 @@ def display_predictions():
 def display_leaderboard():
     if st.button("Show Leaderboard"):
         try:
-            users = load_data(USERS_JSON)  # Adjusted for the new load_data function
+            users = load_users(USERS_JSON)
             leaderboard = sorted(users.items(), key=lambda x: x[1], reverse=True)
             
             # Generate a list of dictionaries, each representing a row in the leaderboard
@@ -302,29 +310,38 @@ with st.expander("Leaderboard 🏆"):
 ############################# Admin Panel ##################################
 ADMIN_PASSPHRASE = "admin123"
 
-
-def load_predictions():
-    # loading predictions from 'predictions.csv'
-    try:
-        return load_data(PREDICTIONS_CSV)
-    except FileNotFoundError:
-        return pd.DataFrame(columns=['user_name', 'match_id', 'predicted_winner', 'predicted_motm', 'bid_points'])
-
-
 def save_users(users):
     with open(USERS_JSON, 'w') as file:
         json.dump(users, file, indent=4)
 
 
-def save_match_outcomes(outcomes):
+def save_match_outcomes(new_outcome):
+    # First, try to load the existing outcomes
+    try:
+        with open(OUTCOMES_JSON, 'r') as file:
+            outcomes = json.load(file)
+    except (FileNotFoundError, json.JSONDecodeError):
+        outcomes = []  # If there's an issue loading, start with an empty list
+
+    # Check if the match_id already exists in outcomes
+    match_index = next((index for (index, d) in enumerate(outcomes) if d["match_id"] == new_outcome["match_id"]), None)
+    
+    if match_index is not None:
+        # If match_id exists, update the existing entry
+        outcomes[match_index] = new_outcome
+    else:
+        # If match_id does not exist, append the new outcome
+        outcomes.append(new_outcome)
+
+    # Finally, save the updated outcomes back to the file
     with open(OUTCOMES_JSON, 'w') as file:
         json.dump(outcomes, file, indent=4)
 
 
 def update_leaderboard_and_outcomes(match_id, winning_team, man_of_the_match):
     outcomes = load_data(OUTCOMES_JSON)  # Load existing match outcomes
-    predictions = load_predictions()  # Load existing predictions
-    users = load_data(USERS_JSON)  # Load existing user points
+    predictions = load_predictions(PREDICTIONS_CSV)  # Load existing predictions
+    users = load_users(USERS_JSON)  # Load existing user points
 
     # Update match outcomes
     match_outcome = next((outcome for outcome in outcomes if outcome['match_id'] == match_id), None)

match_outcomes.json

@@ -1,3 +1,7 @@
 [
-    
+    {
+        "match_id": "20240323_3",
+        "winning_team": "KKR",
+        "man_of_the_match": "Andre Russell"
+    }
 ]

predictions.csv

@@ -11,3 +11,19 @@ Vinay,20240322_1,CSK,Rachin Ravindra,216
 Kichu,20240322_1,CSK,MS Dhoni,500
 Haaris,20240322_1,CSK,MS Dhoni,500
 Rakesh,20240322_1,CSK,MS Dhoni,500
+Megha,20240323_2,DC,Rishabh Pant,200
+Arpit,20240323_2,DC,David Warner,496
+Sahil,20240323_2,DC,Mitchell Marsh,250
+Sai,20240323_2,DC,Rishabh Pant,200
+Neha,20240323_2,DC,Rishabh Pant,500
+Ganesh,20240323_2,DC,Axar Patel,350
+Vinay,20240323_2,DC,David Warner,516
+Megha,20240323_3,KKR,Rinku Singh,200
+Arpit,20240323_3,KKR,Andre Russell,500
+Sahil,20240323_3,KKR,Phil Salt,350
+Sai,20240323_3,SRH,Pat Cummins,300
+Naveein,20240323_3,SRH,Travis Head,500
+Haaris,20240323_3,SRH,Travis Head,300
+Vaibhav,20240323_3,KKR,Mitchell Starc,300
+Neha,20240323_3,KKR,Rinku Singh,300
+Vinay,20240323_3,SRH,Pat Cummins,100

users.json

@@ -1,18 +1,18 @@
 {
     "Archana": 5000,
-    "Arpit": 5000,
-    "Ganesh": 5000,
-    "Haaris": 5000,
-    "Jay": 5000,
-    "Kichu": 5000,
-    "Megha": 5000,
-    "Naveein": 5000,
-    "Neha": 5000,
-    "Praveen": 5000,
-    "Rakesh": 5000,
-    "Sai": 5000,
-    "Sahil": 5000,
-    "Sunil": 5000,
-    "Vaibhav": 5000,
-    "Vinay": 5000
+    "Arpit": 9704,
+    "Ganesh": 6050,
+    "Haaris": 6500,
+    "Jay": 7000,
+    "Kichu": 7000,
+    "Megha": 5300,
+    "Naveein": 7300,
+    "Neha": 5900,
+    "Praveen": 8000,
+    "Rakesh": 7000,
+    "Sai": 4100,
+    "Sahil": 7750,
+    "Sunil": 4501,
+    "Vaibhav": 6600,
+    "Vinay": 5416
 }