testing app

Dockerfile

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+FROM python:3.9
+
+WORKDIR /app
+
+COPY requirements.txt requirements.txt
+RUN pip install -r requirements.txt
+
+COPY . .
+
+CMD ["streamlit", "run", "app.py"]

README copy.md

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+---
+title: DIS IPL Predictions
+emoji: 🦀
+colorFrom: red
+colorTo: pink
+sdk: streamlit
+sdk_version: 1.32.2
+app_file: app.py
+pinned: false
+license: apache-2.0
+---
+
+# DIS IPL Match Predictions App
+
+> "Predict, Compete, and Win 🏏 - Where Every Guess Counts! 🏆"
+
+Welcome to the DIS IPL Match Predictions App! This app allows you to predict the outcomes of IPL matches and compete with your colleagues to win exciting prizes.
+
+## Getting Started
+
+### Prerequisites
+
+- Python 3.x installed on your system
+- Git installed on your system
+- Pip package manager
+
+### Installation
+
+1. Clone this repository to your local machine using Git:
+
+   ```bash
+   git clone <repository_url>
+   ```
+
+2. Navigate to the cloned repository directory:
+
+   ```bash
+   cd ipl-match-predictions-app
+   ```
+
+3. Install the required Python dependencies using Pip:
+
+   ```bash
+   pip install -r requirements.txt
+   ```
+
+### Running The APP
+
+1. After installing the dependencies, you can run the Streamlit app using the following command:
+
+   ```bash
+   streamlit run app.py
+   ```
+
+2. The app will start running locally and open in your default web browser.
+
+Thanks

app.py

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+import base64
+import io
+import json
+import os
+import uuid
+from datetime import datetime
+
+import pandas as pd
+import pytz
+import requests
+import streamlit as st
+from huggingface_hub import CommitScheduler, HfApi
+
+# File paths as constants
+PREDICTIONS_CSV = 'dis_predictions.csv'
+PREDICTIONS_FOLDER = "ipl_predictions"  # Folder where JSON files are saved locally
+USERS_JSON = 'users.json'
+MATCHES_JSON = 'matches.json'
+OUTCOMES_JSON = 'match_outcomes.json'
+PLAYERS_JSON = 'players.json'
+image_path = 'ipl_image.png'
+
+
+# Initialize CommitScheduler
+scheduler = CommitScheduler(
+    repo_id="Jay-Rajput/DIS_IPL_Dataset",
+    repo_type="dataset",
+    folder_path="ipl_predictions",  # Local folder where predictions are saved temporarily
+    path_in_repo="predictions",  # Path in dataset repo where predictions will be saved
+    every=2,  # Push every 240 minutes (4 hours)
+)
+
+
+# Initialize CSV and JSON files if they don't exist
+def initialize_files():
+    # Initialize predictions CSV
+    try:
+        pd.read_csv(PREDICTIONS_CSV)
+    except FileNotFoundError:
+        df = pd.DataFrame(columns=['user_name', 'match_id', 'predicted_winner', 'predicted_motm', 'bid_points'])
+        df.to_csv(PREDICTIONS_CSV, index=False)
+
+
+def load_data(file_path):
+    """
+    Load data from a JSON or CSV file.
+    
+    Args:
+    file_path (str): The path to the file to load.
+    
+    Returns:
+    pd.DataFrame or dict: The loaded data.
+    """
+    try:
+        if file_path.endswith('.json'):
+            with open(file_path, 'r') as file:
+                return json.load(file)
+        elif file_path.endswith('.csv'):
+            return pd.read_csv(file_path)
+    except FileNotFoundError:
+        if file_path.endswith('.json'):
+            return {}
+        elif file_path.endswith('.csv'):
+            return pd.DataFrame()
+
+
+def get_base64_of_image(path):
+    with open(path, "rb") as image_file:
+        return base64.b64encode(image_file.read()).decode()
+
+
+# Get today's date in IST to load today's match
+def get_current_date_ist():
+    tz_IST = pytz.timezone('Asia/Kolkata')
+    datetime_ist = datetime.now(tz_IST)
+    return datetime_ist.strftime('%Y-%m-%d')
+
+
+# Function to get matches for today
+def get_today_matches():
+    today = get_current_date_ist()
+    matches = load_data(MATCHES_JSON)
+    today_matches = [match for match in matches if match['date'] == today]
+    return today_matches
+
+
+# Function to check if prediction submission is allowed
+def is_submission_allowed(match_id):
+    matches = load_data(MATCHES_JSON)  # This loads matches correctly with IST times
+
+    for match in matches:
+        if match["match_id"] == match_id:
+            # Parse the match start time in IST
+            tz_IST = pytz.timezone('Asia/Kolkata')
+            match_datetime_str = f'{match["date"]} {match["time"]}'
+            # The match time string is like "2024-03-21 7:30 PM"
+            match_datetime = datetime.strptime(match_datetime_str, "%Y-%m-%d %I:%M %p")
+            match_datetime = tz_IST.localize(match_datetime)  # Set the timezone to IST
+
+            # Get the current time in IST
+            current_datetime = datetime.now(tz_IST)
+
+            if current_datetime > match_datetime:
+                return False
+            else:
+                return True
+    return False  # If match_id not found, default to False
+
+
+def load_predictions(PREDICTIONS_CSV):
+    try:
+        return pd.read_csv(PREDICTIONS_CSV)
+    except FileNotFoundError:
+        return pd.DataFrame()
+
+
+# Submit prediction function
+def submit_prediction(
+        user_name,
+        match_id,
+        predicted_winner,
+        predicted_motm,
+        bid_points,
+        max_bid_points
+        ):
+
+    # Validation for user selection
+    if user_name == "Select a user...":
+        st.warning("Please select a valid user.")
+        return
+
+    # Check if prediction submission is allowed for the match
+    if not is_submission_allowed(match_id):
+        st.error("Prediction submission time has passed. Predictions can't be submitted after match start.")
+        return
+
+    if bid_points > max_bid_points:
+        st.error(f"Your bid points exceed the 20% limit of your total points. Maximum allowed bid points: {max_bid_points}")
+        return
+
+
+    # New: Generate a unique ID for this prediction
+    prediction_id = uuid.uuid4().hex
+    prediction_date = datetime.now().strftime('%Y-%m-%d')
+
+    prediction_data = {
+        'prediction_id': prediction_id,
+        'user_name': user_name,
+        'match_id': match_id,
+        'predicted_winner': predicted_winner,
+        'predicted_motm': predicted_motm,
+        'bid_points': bid_points,
+        'prediction_date': prediction_date  # Include the prediction date
+    }
+
+    # Save prediction to a local JSON file for CommitScheduler to handle
+    prediction_file_path = f"{PREDICTIONS_FOLDER}/prediction_{prediction_id}.json"
+    with open(prediction_file_path, 'w') as file:
+        json.dump(prediction_data, file)
+
+    st.success("Prediction submitted successfully!")
+
+
+def get_user_total_points(user_name):
+    users = load_data(USERS_JSON)
+    return users.get(user_name, 0)
+
+
+# Define the new function
+def calculate_max_bid_points(user_name):
+    total_points = get_user_total_points(user_name)
+    max_bid_points = int(total_points * 0.20)  # 20% of total points
+    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)
+
+    max_bid_points = None
+    if user_name != "Select a user...":
+        max_bid_points = calculate_max_bid_points(user_name)
+        st.write(f"Maximum bid points you can submit: {max_bid_points}")
+
+    matches = get_today_matches()
+    if matches:
+        match_choice = st.selectbox("Select Today's Match", matches, format_func=lambda match: f"{match['teams'][0]} vs {match['teams'][1]}")
+        match_id = match_choice['match_id']
+        teams = match_choice['teams']
+
+        predicted_winner = st.selectbox("Predicted Winner", teams)
+
+        player_list = load_data(PLAYERS_JSON)
+        predicted_motm = ""
+        if predicted_winner in player_list:
+            players = player_list[predicted_winner]
+            predicted_motm = st.selectbox("Predicted Man of the Match", players)
+
+        bid_points = st.number_input("Bid Points", min_value=1, value=100, format="%d")
+
+        if st.button("Submit Prediction"):
+            submit_prediction(user_name, match_id, predicted_winner, predicted_motm, bid_points, max_bid_points)
+    else:
+        st.write("No matches are scheduled for today.")
+
+
+def display_predictions():
+    if st.button("Show Predictions"):
+        all_predictions = []
+
+        # Check if the directory exists
+        if not os.path.exists(PREDICTIONS_FOLDER):
+            st.write("No predictions directory found.")
+            return
+
+        # List all JSON files in the directory
+        for filename in os.listdir(PREDICTIONS_FOLDER):
+            if filename.endswith('.json'):
+                file_path = os.path.join(PREDICTIONS_FOLDER, filename)
+                # Read each JSON file and append its contents to the list
+                with open(file_path, 'r') as file:
+                    prediction = json.load(file)
+                    all_predictions.append(prediction)
+
+        # Convert the list of dictionaries to a DataFrame
+        predictions_df = pd.DataFrame(all_predictions)
+
+        predictions_df['prediction_date'] = predictions_df.apply(lambda x: datetime.strptime(x['prediction_date'], '%Y-%m-%d'), axis=1)
+
+        # Filter for today's predictions
+        today_str = datetime.now().strftime('%Y-%m-%d')
+        todays_predictions = predictions_df[predictions_df['prediction_date'] == today_str]
+
+        # Remove the 'prediction_id' column if it exists
+        if 'prediction_id' in todays_predictions.columns:
+            todays_predictions = todays_predictions.drop(columns=['prediction_id', 'prediction_date'])
+
+        if not todays_predictions.empty:
+            st.dataframe(todays_predictions, hide_index=True)
+        else:
+            st.write("No predictions for today's matches yet.")
+
+
+def display_leaderboard():
+    if st.button("Show Leaderboard"):
+        try:
+            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
+            leaderboard_dicts = [{"Rank": rank+1, "User": user[0], "Points": user[1]} 
+                                 for rank, user in enumerate(leaderboard)]
+            
+            # Convert the list of dictionaries to a DataFrame
+            df_leaderboard = pd.DataFrame(leaderboard_dicts)
+            
+            st.dataframe(df_leaderboard, hide_index=True)
+        except FileNotFoundError:
+            st.write("Leaderboard data not available.")
+
+
+# Streamlit UI
+encoded_image = get_base64_of_image(image_path)
+custom_css = f"""
+<style>
+.header {{
+    font-size: 50px;
+    color: #FFD700; /* Gold */
+    text-shadow: -1px -1px 0 #000, 1px -1px 0 #000, -1px 1px 0 #000, 1px 1px 0 #000; /* Black text shadow */
+    text-align: center;
+    padding: 10px;
+    background-image: url('data:image/png;base64,{encoded_image}');
+    background-size: cover;
+}}
+</style>
+"""
+# Apply custom CSS
+st.markdown(custom_css, unsafe_allow_html=True)
+# Use the custom class in a div with your title
+st.markdown('<div class="header">DIS IPL Match Predictions</div>', unsafe_allow_html=True)
+
+st.write("🏆 Predict, Compete, and Win 🏏 - Where Every Guess Counts! 🏆")
+
+user_guide_content = """
+### 📘 User Guide
+
+#### Submitting Predictions
+- **Match Selection**: Choose the match you want to predict from today's available matches.
+- **Team and Player Prediction**: Select the team you predict will win and the "Man of the Match".
+- **Bid Points**: Enter the number of points you wish to bid on your prediction. Remember, the maximum you can bid is capped at 20% of your total points.
+
+#### Scoring System
+- **Winning Team Prediction**: Correct predictions earn you 1000 points, while incorrect predictions deduct 200 points.
+- **Man of the Match Prediction**: Correctly predicting the "Man of the Match" awards you 200 points. No penalty for incorrect guesses.
+- **Bonus Points**: An additional 200 points bonus is awarded for getting both the team and "Man of the Match" predictions right.
+
+#### Bid Point Constraints
+- You cannot bid more than 20% of your current total points.
+- Bid points will be doubled if your prediction is correct, and deducted if incorrect.
+
+#### Rules for Submission
+- Predictions must be submitted before the match starts.
+- Only one prediction per match is allowed.
+- Review your prediction carefully before submission, as it cannot be changed once submitted.
+"""
+
+# User Guide as an expander
+with st.expander("User Guide 📘"):
+    st.markdown(user_guide_content)
+
+with st.expander("Submit Prediction 📝"):
+    user_selection_and_prediction()
+
+with st.expander("Predictions 🔍"):
+    display_predictions()
+
+with st.expander("Leaderboard 🏆"):
+    display_leaderboard()
+
+
+############################# Admin Panel ##################################
+ADMIN_PASSPHRASE = "admin123"
+
+def save_users(users):
+    with open(USERS_JSON, 'w') as file:
+        json.dump(users, file, indent=4)
+
+
+def save_match_outcomes(outcomes):
+    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(PREDICTIONS_CSV)  # Load existing predictions
+    users = load_users(USERS_JSON)  # Load existing user points
+
+    # Directly update or add the match outcome
+    outcome_exists = False
+    for outcome in outcomes:
+        if outcome['match_id'] == match_id:
+            outcome.update({"winning_team": winning_team, "man_of_the_match": man_of_the_match})
+            outcome_exists = True
+            break
+    if not outcome_exists:
+        outcomes.append({"match_id": match_id, "winning_team": winning_team, "man_of_the_match": man_of_the_match})
+
+    # Update user points based on prediction accuracy
+    for _, prediction in predictions.iterrows():
+        if prediction['match_id'] == match_id:
+            user_name = prediction['user_name']
+            users[user_name] = users.get(user_name, 0)  # Initialize user points if not present
+
+            # Update points based on prediction accuracy
+            if prediction['predicted_winner'] == winning_team:
+                users[user_name] += 1000
+                users[user_name] += prediction['bid_points'] 
+                if prediction['predicted_motm'] == man_of_the_match:
+                    users[user_name] += 400  # Bonus for both correct predictions
+            else:
+                users[user_name] -= 200 + prediction['bid_points']  # Penalty for wrong team prediction
+
+    save_match_outcomes(outcomes)
+    save_users(users)
+
+
+with st.sidebar:
+    expander = st.expander("Admin Panel", expanded=False)
+    admin_pass = expander.text_input("Enter admin passphrase:", type="password", key="admin_pass")
+
+    if admin_pass == ADMIN_PASSPHRASE:
+        expander.success("Authenticated")
+        matches = get_today_matches()  # This function fetches today's matches
+
+        # If matches are available, let the admin select one
+        if matches:
+            match_selection = expander.selectbox("Select Match", matches, format_func=lambda match: f"{match['teams'][0]} vs {match['teams'][1]}", key="match_selection")
+            selected_match_id = match_selection['match_id']
+            teams = match_selection['teams']
+
+            # Let admin select the winning team
+            winning_team = expander.selectbox("Winning Team", teams, key="winning_team")
+
+            # Fetch and display players for the selected winning team
+            player_list = load_data(PLAYERS_JSON)
+            if winning_team in player_list:
+                players = player_list[winning_team]
+                man_of_the_match = expander.selectbox("Man of the Match", players, key="man_of_the_match")
+            else:
+                players = []
+                man_of_the_match = expander.text_input("Man of the Match (Type if not listed)", key="man_of_the_match_fallback")
+
+            if expander.button("Submit Match Outcome", key="submit_outcome"):
+                update_leaderboard_and_outcomes(selected_match_id, winning_team, man_of_the_match)
+                expander.success("Match outcome submitted and leaderboard updated!")
+        else:
+            expander.write("No matches are available for today.")
+    else:
+        if admin_pass:  # Show error only if something was typed
+            expander.error("Not authenticated")

dis_predictions.csv

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+user_name,match_id,predicted_winner,predicted_motm,bid_points
+Sunil,20240325_6,RCB,Glenn Maxwell,900
+Sahil,20240325_6,RCB,Virat Kohli,350
+Vinay,20240325_6,RCB,Faf du Plessis,200
+Megha,20240325_6,RCB,Virat Kohli,500
+Jay,20240325_6,RCB,Virat Kohli,200
+Sai,20240325_6,RCB,Glenn Maxwell,620
+Haaris,20240325_6,RCB,Virat Kohli,1200
+Naveein,20240325_6,RCB,Faf du Plessis,500
+Praveen,20240325_6,RCB,Faf du Plessis,1800
+Kishore,20240325_6,RCB,Glenn Maxwell,500

match_outcomes.json

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+[
+    {
+        "match_id": "20240322_1",
+        "winning_team": "CSK",
+        "man_of_the_match": "Mustafizur Rahman"
+    },
+    {
+        "match_id": "20240323_2",
+        "winning_team": "PBKS",
+        "man_of_the_match": "Sam Curran"
+    },
+    {
+        "match_id": "20240323_3",
+        "winning_team": "KKR",
+        "man_of_the_match": "Andre Russell"
+    },
+    {
+        "match_id": "20240324_4",
+        "winning_team": "RR",
+        "man_of_the_match": "Sanju Samson"
+    },
+    {
+        "match_id": "20240324_5",
+        "winning_team": "GT",
+        "man_of_the_match": "B Sai Sudharsan"
+    }
+]

matches.json

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+[
+    {
+        "match_id": "20240322_1",
+        "date": "2024-03-22",
+        "time": "7:30 PM",
+        "teams": ["CSK", "RCB"],
+        "venue": "Chennai"
+    },
+    {
+        "match_id": "20240323_2",
+        "date": "2024-03-23",
+        "time": "3:30 PM",
+        "teams": ["PBKS", "DC"],
+        "venue": "Mohali"
+    },
+    {
+        "match_id": "20240323_3",
+        "date": "2024-03-23",
+        "time": "7:30 PM",
+        "teams": ["KKR", "SRH"],
+        "venue": "Kolkata"
+    },
+    {
+        "match_id": "20240324_4",
+        "date": "2024-03-24",
+        "time": "3:30 PM",
+        "teams": ["RR", "LSG"],
+        "venue": "Jaipur"
+    },
+    {
+        "match_id": "20240324_5",
+        "date": "2024-03-24",
+        "time": "7:30 PM",
+        "teams": ["GT", "MI"],
+        "venue": "Ahmedabad"
+    },
+    {
+        "match_id": "20240325_6",
+        "date": "2024-03-25",
+        "time": "7:30 PM",
+        "teams": ["RCB", "PBKS"],
+        "venue": "Bengaluru"
+    },
+    {
+        "match_id": "20240326_7",
+        "date": "2024-03-26",
+        "time": "7:30 PM",
+        "teams": ["CSK", "GT"],
+        "venue": "Chennai"
+    },
+    {
+        "match_id": "20240327_8",
+        "date": "2024-03-27",
+        "time": "7:30 PM",
+        "teams": ["SRH", "MI"],
+        "venue": "Hyderabad"
+    },
+    {
+        "match_id": "20240328_9",
+        "date": "2024-03-28",
+        "time": "7:30 PM",
+        "teams": ["RR", "DC"],
+        "venue": "Jaipur"
+    },
+    {
+        "match_id": "20240329_10",
+        "date": "2024-03-29",
+        "time": "7:30 PM",
+        "teams": ["RCB", "KKR"],
+        "venue": "Bengaluru"
+    },
+    {
+        "match_id": "20240330_11",
+        "date": "2024-03-30",
+        "time": "7:30 PM",
+        "teams": ["LSG", "PBKS"],
+        "venue": "Lucknow"
+    },
+    {
+        "match_id": "20240331_12",
+        "date": "2024-03-31",
+        "time": "3:30 PM",
+        "teams": ["GT", "SRH"],
+        "venue": "Ahmedabad"
+    },
+    {
+        "match_id": "20240331_13",
+        "date": "2024-03-31",
+        "time": "7:30 PM",
+        "teams": ["DC", "CSK"],
+        "venue": "Visakhapatnam"
+    },
+    {
+        "match_id": "20240401_14",
+        "date": "2024-04-01",
+        "time": "7:30 PM",
+        "teams": ["MI", "RR"],
+        "venue": "Mumbai"
+    },
+    {
+        "match_id": "20240402_15",
+        "date": "2024-04-02",
+        "time": "7:30 PM",
+        "teams": ["RCB", "LSG"],
+        "venue": "Bengaluru"
+    },
+    {
+        "match_id": "20240403_16",
+        "date": "2024-04-03",
+        "time": "7:30 PM",
+        "teams": ["DC", "KKR"],
+        "venue": "Visakhapatnam"
+    },
+    {
+        "match_id": "20240404_17",
+        "date": "2024-04-04",
+        "time": "7:30 PM",
+        "teams": ["GT", "PBKS"],
+        "venue": "Ahmedabad"
+    },
+    {
+        "match_id": "20240405_18",
+        "date": "2024-04-05",
+        "time": "7:30 PM",
+        "teams": ["SRH", "CSK"],
+        "venue": "Hyderabad"
+    },
+    {
+        "match_id": "20240406_19",
+        "date": "2024-04-06",
+        "time": "7:30 PM",
+        "teams": ["RR", "RCB"],
+        "venue": "Jaipur"
+    },
+    {
+        "match_id": "20240407_20",
+        "date": "2024-04-07",
+        "time": "3:30 PM",
+        "teams": ["MI", "DC"],
+        "venue": "Mumbai"
+    },
+    {
+        "match_id": "20240407_21",
+        "date": "2024-04-07",
+        "time": "7:30 PM",
+        "teams": ["LSG", "GT"],
+        "venue": "Lucknow"
+    }
+]

players.json

@@ -0,0 +1,273 @@
+{
+    "CSK": [
+      "MS Dhoni",
+      "Devon Conway",
+      "Ruturaj Gaikwad",
+      "Ajinkya Rahane",
+      "Shaik Rasheed",
+      "Ravindra Jadeja",
+      "Mitchell Santner",
+      "Moeen Ali",
+      "Shivam Dube",
+      "Nishant Sindhu",
+      "Ajay Mandal",
+      "Rajvardhan Hangargekar",
+      "Deepak Chahar",
+      "Maheesh Theekshana",
+      "Mukesh Chowdhary",
+      "Prashant Solanki",
+      "Simarjeet Singh",
+      "Tushar Deshpande",
+      "Matheesha Pathirana",
+      "Rachin Ravindra",
+      "Shardul Thakur",
+      "Daryl Mitchell",
+      "Sameer Rizvi",
+      "Mustafizur Rahman",
+      "Avanish Rao Aravelly"
+    ],
+    "DC": [
+      "Rishabh Pant",
+      "David Warner",
+      "Prithvi Shaw",
+      "Yash Dhull",
+      "Abishek Porel",
+      "Axar Patel",
+      "Lalit Yadav",
+      "Mitchell Marsh",
+      "Pravin Dubey",
+      "Vicky Ostwal",
+      "Anrich Nortje",
+      "Kuldeep Yadav",
+      "Lungi Ngidi",
+      "Khaleel Ahmed",
+      "Ishant Sharma",
+      "Mukesh Kumar",
+      "Harry Brook",
+      "Tristan Stubbs",
+      "Ricky Bhui",
+      "Kumar Kushagra",
+      "Rasikh Dar",
+      "Jhye Richardson",
+      "Sumit Kumar",
+      "Shai Hope",
+      "Swastik Chhikara",
+      "Jake Fraser-McGurk"
+    ],
+    "GT": [
+      "David Miller",
+      "Shubman Gill",
+      "Matthew Wade",
+      "Wriddhiman Saha",
+      "Kane Williamson",
+      "Abhinav Manohar",
+      "B Sai Sudharsan",
+      "Darshan Nalkande",
+      "Vijay Shankar",
+      "Jayant Yadav",
+      "Rahul Tewatia",
+      "Mohammed Shami",
+      "Noor Ahmad",
+      "R Sai Kishore",
+      "Rashid Khan",
+      "Josh Little",
+      "Mohit Sharma",
+      "Azmatullah Omarzai",
+      "Umesh Yadav",
+      "Shahrukh Khan",
+      "Sushant Mishra",
+      "Kartik Tyagi",
+      "Manav Suthar",
+      "Spencer Johnson",
+      "Robin Minz"
+    ],
+    "KKR": [
+      "Nitish Rana",
+      "Rinku Singh",
+      "Rahmanullah Gurbaz",
+      "Shreyas Iyer",
+      "Jason Roy",
+      "Anukul Roy",
+      "Andre Russell",
+      "Venkatesh Iyer",
+      "Suyash Sharma",
+      "Harshit Rana",
+      "Sunil Narine",
+      "Vaibhav Arora",
+      "Varun Chakravarthy",
+      "KS Bharat",
+      "Chetan Sakariya",
+      "Mitchell Starc",
+      "Angkrish Raghuvanshi",
+      "Ramandeep Singh",
+      "Sherfane Rutherford",
+      "Manish Pandey",
+      "Mujeeb Ur Rahman",
+      "Gus Atkinson",
+      "Sakib Hussain",
+      "Dushmantha Chameera",
+      "Phil Salt"
+    ],
+    "LSG": [
+        "KL Rahul",
+        "Quinton de Kock",
+        "Nicholas Pooran",
+        "Ayush Badoni",
+        "Deepak Hooda",
+        "K Gowtham",
+        "Krunal Pandya",
+        "Kyle Mayers",
+        "Marcus Stoinis",
+        "Prerak Mankad",
+        "Yudhvir Singh",
+        "Mark Wood",
+        "Mayank Yadav",
+        "Mohsin Khan",
+        "Ravi Bishnoi",
+        "Yash Thakur",
+        "Amit Mishra",
+        "Naveen-ul-Haq",
+        "Devdutt Padikkal",
+        "Shivam Mavi",
+        "Arshin Kulkarni",
+        "M. Siddharth",
+        "Ashton Turner",
+        "David Willey",
+        "Arshad Khan"
+    ],
+    "MI": [
+        "Rohit Sharma",
+        "Dewald Brevis",
+        "Suryakumar Yadav",
+        "Ishan Kishan",
+        "Tilak Varma",
+        "Tim David",
+        "Vishnu Vinod",
+        "Arjun Tendulkar",
+        "Shams Mulani",
+        "Nehal Wadhera",
+        "Jasprit Bumrah",
+        "Kumar Kartikeya",
+        "Piyush Chawla",
+        "Akash Madhwal",
+        "Jason Behrendorff",
+        "Romario Shepherd",
+        "Hardik Pandya",
+        "Gerald Coetzee",
+        "Dilshan Madushanka",
+        "Shreyas Gopal",
+        "Nuwan Thushara",
+        "Naman Dhir",
+        "Anshul Kamboj",
+        "Mohammad Nabi",
+        "Shivalik Sharma",
+        "Luke Wood"
+    ],
+    "PBKS": [
+        "Shikhar Dhawan",
+        "Jitesh Sharma",
+        "Jonny Bairstow",
+        "Prabhsimran Singh",
+        "Liam Livingstone",
+        "Matthew Short",
+        "Harpreet Bhatia",
+        "Atharva Taide",
+        "Rishi Dhawan",
+        "Sam Curran",
+        "Sikandar Raza",
+        "Shivam Singh",
+        "Harpreet Brar",
+        "Arshdeep Singh",
+        "Kagiso Rabada",
+        "Nathan Ellis",
+        "Rahul Chahar",
+        "Gurnoor Brar",
+        "Vidwath Kaverappa",
+        "Harshal Patel",
+        "Chris Woakes",
+        "Ashutosh Sharma",
+        "Vishwanath Pratap Singh",
+        "Shashank Singh",
+        "Tanay Thyagarajan",
+        "Prince Choudhary",
+        "Rilee Rossouw"
+    ],
+    "RR": [
+        "Sanju Samson",
+        "Jos Buttler",
+        "Shimron Hetmyer",
+        "Yashasvi Jaiswal",
+        "Dhruv Jurel",
+        "Riyan Parag",
+        "Donovan Ferreira",
+        "Kunal Rathore",
+        "R Ashwin",
+        "Kuldeep Sen",
+        "Navdeep Saini",
+        "Sandeep Sharma",
+        "Trent Boult",
+        "Yuzvendra Chahal",
+        "Adam Zampa",
+        "Prasidh Krishna",
+        "Avesh Khan",
+        "Rovman Powell",
+        "Shubham Dubey",
+        "Tom Kohler-Cadmore",
+        "Abid Mushtaq",
+        "Nandre Burger"
+    ],
+    "RCB": [
+        "Faf du Plessis",
+        "Glenn Maxwell",
+        "Virat Kohli",
+        "Rajat Patidar",
+        "Anuj Rawat",
+        "Dinesh Karthik",
+        "Suyash Prabhudessai",
+        "Will Jacks",
+        "Mahipal Lomror",
+        "Karn Sharma",
+        "Manoj Bhandage",
+        "Mayank Dagar",
+        "Vyshak Vijaykumar",
+        "Akash Deep",
+        "Mohammed Siraj",
+        "Reece Topley",
+        "Himanshu Sharma",
+        "Rajan Kumar",
+        "Cameron Green",
+        "Alzarri Joseph",
+        "Yash Dayal",
+        "Lockie Ferguson",
+        "Tom Curran",
+        "Swapnil Singh",
+        "Saurav Chauhan"
+    ],
+    "SRH": [
+        "Abdul Samad",
+        "Aiden Markram",
+        "Rahul Tripathi",
+        "Glenn Phillips",
+        "Mayank Agarwal",
+        "Heinrich Klaasen",
+        "Anmolpreet Singh",
+        "Upendra Yadav",
+        "Nitish Kumar Reddy",
+        "Abhishek Sharma",
+        "Marco Jansen",
+        "Washington Sundar",
+        "Sanvir Singh",
+        "Bhuvneshwar Kumar",
+        "Fazalhaq Farooqi",
+        "T Natarajan",
+        "Umran Malik",
+        "Mayank Markande",
+        "Shahbaz Ahmed",
+        "Travis Head",
+        "Wanindu Hasaranga",
+        "Pat Cummins",
+        "Jaydev Unadkat",
+        "Akash Singh",
+        "Jhathavedh Subramanyan"
+    ]
+}  

predictions.csv

@@ -0,0 +1,33 @@
+user_name,match_id,predicted_winner,predicted_motm,bid_points
+Sahil,20240322_1,CSK,Ruturaj Gaikwad,250
+Naveein,20240322_1,CSK,Rachin Ravindra,1000
+Ganesh,20240322_1,CSK,Ruturaj Gaikwad,300
+Jay,20240322_1,CSK,Ruturaj Gaikwad,500
+Megha,20240322_1,RCB,Virat Kohli,500
+Arpit,20240322_1,CSK,Ravindra Jadeja,1000
+Sunil,20240322_1,RCB,Virat Kohli,299
+Praveen,20240322_1,CSK,Ravindra Jadeja,1000
+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,500
+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
+Sunil,20240325_6,RCB,Glenn Maxwell,900
+Sahil,20240325_6,RCB,Virat Kohli,350
+Vinay,20240325_6,RCB,Faf du Plessis,200
+Megha,20240325_6,RCB,Virat Kohli,500

requirements.txt

@@ -0,0 +1,5 @@
+huggingface_hub
+pandas
+pytz
+requests
+streamlit

users.json

@@ -0,0 +1,17 @@
+{
+    "Arpit": 11300,
+    "Ganesh": 5750,
+    "Haaris": 6000,
+    "Jay": 6500,
+    "Kishore": 5700,
+    "Megha": 5900,
+    "Naveein": 6300,
+    "Neha": 5600,
+    "Praveen": 9000,
+    "Rakesh": 6500,
+    "Sai": 3100,
+    "Sahil": 6600,
+    "Sunil": 4501,
+    "Vaibhav": 5600,
+    "Vinay": 5300
+}