app.py

import pandas as pd
import streamlit as st
import gspread
from google.oauth2.service_account import Credentials
import ast
import requests
import pandas as pd
import boto3
from datetime import datetime
import json
# Define the scope
start = False
starting_position = []
tradeHistory_positions = []


s3 = boto3.resource(
    service_name = 's3',
    region_name = 'ap-south-1',
    aws_access_key_id = 'AKIA3TD2SOLYZML62HJR',
    aws_secret_access_key ='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'
)

obj = s3.Bucket('usdsmcoinmdata').Object('copyLeaderboard_trade_history.csv').get()
df = pd.read_csv(obj['Body'],index_col=False)

df2 = pd.read_csv('df.csv')

def convert_str_to_list_or_keep(value):
    if isinstance(value, str):
        try:
            return ast.literal_eval(value)
        except (SyntaxError, ValueError):
            return value
    else:
        return value

df = df.apply(lambda col: col.map(convert_str_to_list_or_keep))
df2 = df2.apply(lambda col: col.map(convert_str_to_list_or_keep))





df['positionClosed'] = False

print(df)

uid_input = int(st.text_input("Enter U_IDs to filter"))

option = st.radio("Choose an option:", ["Show Position History", "Show Live Positions"])

if df is not None and uid_input:

    if option == "Show Position History":
        st.title("Position History Viewer")
        # Display starting positions with clickable rows
        st.header("Starting Positions")
        
        filtered_df = df[df['U_IDs'] == uid_input].copy() 
        print("filtered df",filtered_df)

        if not filtered_df.empty:
            trade_list = filtered_df['trade_history'].iloc[0]
        else:
            st.write("No data found for the provided U_ID.")


        unique_lists = []

        def get_amounts_from_positions_and_closed_trades(data):
                    print("revheeeeeeeeeeeeeeeegfeggggggggggggg")
                    print('data',data)
            

                    # Check if 'Modified' key exists and extract amounts
                    if 'Modified' in data:
                        modified_positions = data['Modified']
                        print("reeeeeegggggggggggggg33")
                        print(modified_positions)
                        print(type(modified_positions))
                        # modified_positions = modified_positions[0]
                        if isinstance(modified_positions, dict) and 'amount' in modified_positions:
                                    print("reafffffffff000000000")
                                    amount = modified_positions.get('amount')
                                    if isinstance(amount, (int, float)):  # Check if amount is a number
                                        amounts =amount
                    # Check if 'ClosedTrades' key exists and extract amounts
                    if 'ClosedTrades' in data:
                        closed_trades = data['ClosedTrades']
                        closed_trades =closed_trades[0]
                        if isinstance(closed_trades, dict) and 'amount' in closed_trades:
                                    amount = closed_trades.get('amount')
                                    if isinstance(amount, (int, float)):  # Check if amount is a number
                                        amounts = amount

                    return amounts
                
        def get_symbols_from_positions_and_closed_trades(data):
                        

                        # Check if 'Modified' key exists and extract symbols
                        if 'Modified' in data:
                            modified_positions = data['Modified']
                            # modified_positions =modified_positions
                            if isinstance(modified_positions, dict) and 'symbol' in modified_positions:
                                        symbol = modified_positions['symbol']

                        # Check if 'ClosedTrades' key exists and extract symbols
                        if 'ClosedTrades' in data:
                            closed_trades = data['ClosedTrades']
                            closed_trades =closed_trades[0]
                            if isinstance(closed_trades, dict) and 'symbol' in closed_trades:
                                        symbol = closed_trades['symbol']

                        return symbol

        for i in range(len(trade_list)):

            
            if trade_list[i]=="none":
                continue

            if not trade_list:  # Check if the trade_list is empty
                st.header("No data found, this may not be in the leaderboard")

            if start ==False:
                st.subheader(f"Data is from {datetime.now()}")
                start =True
            foundCLosed = False
            changeInAmount = 0
            
            if 'symbol' in trade_list[i]:
                symbol = trade_list[i]['symbol']
                side  ="buy" if float(trade_list[i]['amount'])>0 else "sell"
                amount = trade_list[i]['amount']
                symbol = trade_list[i]['symbol']     
                trade_list[i]['side'] =side
                trade_list[i]['changeInAmount'] = changeInAmount
                trade_list[i]['i'] = i
                unique_lists.append({"position":trade_list[i]})
                trade_list[i] = "none"
                

            else:    
                if 'positions' in trade_list[i]:
                    reached = False
                    # Collect necessary data first before modifying the dictionary
                    for k, v in list(trade_list[i].items()):  # Convert to a list to avoid modifying during iteration
                        for entry in v:
                            if 'NewPosition' in entry:
                                new_position = entry.get('NewPosition', {})
                                # Extract symbol and amount
                                symbol = new_position.get('symbol')
                                amount = new_position.get('amount')
                                # if start==False:
                                #     start_time = new_position.get('updateTime')
                                #     year = start_time[0]
                                #     month = start_time[1]
                                #     day = start_time[2]
                                #     hour =start_time[3]
                                #     minute =start_time[4]
                                #     seconds = start_time[5]
                                #     dt = datetime(year, month, day, hour, minute, seconds)
                                #     human_readable_format = dt.strftime('%B %d, %Y, %I:%M:%S %p')     
                                #     st.subheader(f"Data from {human_readable_format}")
                                #     start=True 
                                # if start==False:
                                #     
                                #     start =True
                                side = "buy" if amount > 0 else "sell"
                                new_position['side'] = side
                                new_position['changeInAmount'] = changeInAmount
                                new_position['i'] = i
                                # Update the entry with the modified 'NewPosition'
                                entry['NewPosition'] = new_position
                                
                                # Append the updated trade_list[i] to unique_lists
                                unique_lists.append(trade_list[i])

                                reached = True

                    # Now safely modify the dictionary after iteration is complete
                    if reached:
                        trade_list[i] = "none"

                    # Now safely modify the dictionary after iteration is complete
                                

            for j in range(i+1, len(trade_list)):
                if trade_list[j] == "none":
                    continue

                if 'positions' in trade_list[j] and isinstance(trade_list[j]['positions'], list):
                    for position in trade_list[j]['positions']:
                        # Check if 'Modified' is in the position and is a dict
                        if 'Modified' in position and isinstance(position['Modified'], dict):
                            
                            # if start==False:
                            #         for k,v in position.items():
                            #             start_time = v['updateTime']
                                    
                            #         year = start_time[0]
                            #         month = start_time[1]
                            #         day = start_time[2]
                            #         hour =start_time[3]
                            #         minute =start_time[4]
                            #         seconds = start_time[5]
                            #         dt = datetime(year, month, day, hour, minute, seconds)
                            #         human_readable_format = dt.strftime('%d-%m-%Y %H:%M:%S')   
                            #         st.subheader(f"Data from {human_readable_format}")
                            #         start=True 
                            modified_amount = get_amounts_from_positions_and_closed_trades(position)
                            modified_symbol = get_symbols_from_positions_and_closed_trades(position)

                            if modified_amount > 0:
                                modified_side = "buy"
                            else:
                                modified_side = "sell"
                            
                            if symbol == modified_symbol and side == modified_side:
                                if start ==False:
                                    st.header(f"Data is from {datetime.now}")
                                    start =True
                                position['Modified']['side'] = modified_side
                                position['Modified']['changeInAmount'] = float(amount) - modified_amount if modified_amount < 0 else modified_amount - float(amount)
                                position['Modified']['i'] = i
                                amount = modified_amount
                                unique_lists.append(trade_list[j])
                                trade_list[j] = "none"
                        
                        # Check if 'ClosedTrades' is in the position and is a tuple
                        if 'ClosedTrades' in position and isinstance(position['ClosedTrades'], tuple):
                            if start ==False:
                                    st.header(f"Data is from {datetime.now}")
                                    start =True
                            foundCLosed = False
                            closed_trades_tuple = position['ClosedTrades']
                            closed_trades_dict = {
                                'trade_info': closed_trades_tuple[0],
                                'side': closed_trades_tuple[1]
                            }
                            
                            closed_amount = get_amounts_from_positions_and_closed_trades(position)
                            closed_symbol = get_symbols_from_positions_and_closed_trades(position)

                            if closed_amount > 0:
                                closed_side = "buy"
                            else:
                                closed_side = "sell"

                            if symbol == closed_symbol and side == closed_side:
                                # if start==False:
                                #     for k,v in position.items():
                                #         start_time = v['updateTime']
                                #     start =True
                                
                                closed_trades_dict['side'] = closed_side
                                trade_info = closed_trades_dict['trade_info']
                                trade_info['changeInAmount'] = float(amount) - closed_amount if closed_amount < 0 else closed_amount - float(amount)
                                amount = closed_amount
                                closed_trades_dict['trade_info']['i'] = i  # Store index 'i' inside 'ClosedTrades'
                                closed_trades_dict['trade_info']['closed'] = True
                                
                                # Append the updated trade_list[j] to unique_lists
                                unique_lists.append(trade_list[j])
                                trade_list[j] = "none"
                                foundCLosed = True
                                break

                        # Break the inner loop if a closed trade was found
                if foundCLosed:
                            break        


                                                
                            
            for k in range(len(unique_lists)):
                data = unique_lists[k]
                            

                if k ==0: 
                    
                    
                    if 'positions' in data:
                        if isinstance(data['positions'], list):
                            for a in data['positions']:
                                if 'NewPosition' in a:
                                    
                                    position_data = a['NewPosition']
                                    starting_position.append(position_data)
                                    tradeHistory_positions.append(position_data)
                                    

                    else:
                        if 'position' in data:
                            position_data =data['position']
                            starting_position.append(position_data)
                            tradeHistory_positions.append(position_data)

                        
                
                if 'positions' in data:
                    if isinstance(data['positions'],list):
                        for a in data['positions']:
                                if 'ClosedTrades' in a:
                                    position_data = a['ClosedTrades'][0]
                                    tradeHistory_positions.append(position_data)



                if 'positions' in data:
                    if isinstance(data['positions'],list):
                        for a in data['positions']:
                                if 'Modified' in a:
                                    position_data = a['Modified']
                                    tradeHistory_positions.append(position_data)


                

            unique_lists =[]

    elif option == "Show Live Positions":
        filtered_df2 = df2[df2['U_IDs'] == uid_input]

        if not filtered_df2.empty:

            positions_list = filtered_df2['Positions'].iloc[0]  # Extract the first match

            # Convert the list of dictionaries to a DataFrame
            if isinstance(positions_list, list) and positions_list:
                positions_df = pd.DataFrame(positions_list)
                st.subheader("Live Positions")
                st.dataframe(positions_df)
            else:
                st.write("No live positions data available for the given U_ID.")


        
        # data3 = sheet3.get_all_values()
        # headers3 = data3.pop(0)
        # df3 = pd.DataFrame(data3, columns=headers3)
        # filtered_df3 = df3[df3['U_IDs'] == uid_input]
        # st.subheader("Performace")
        # st.dataframe(filtered_df3)
        
            
    
    def show_position_history(selected_position):
        st.header(f"History for {selected_position}")
        
        # Filter trade history for the selected position
        position_history = [pos for pos in tradeHistory_positions if pos['i'] == selected_position]


        
        if position_history:
            df_history = pd.DataFrame(position_history)

            df_history['changeInAmount'] = pd.to_numeric(df_history['changeInAmount'], errors='coerce')
            df_history['markPrice'] = pd.to_numeric(df_history['markPrice'], errors='coerce')
            df_history['entryPrice'] = pd.to_numeric(df_history['entryPrice'], errors='coerce')

            df_history['amount'] = pd.to_numeric(df_history['amount'],errors='coerce')

# Replace NaN with 0 or handle as required
            df_history.fillna(0, inplace=True)
            
            # Update the global timestamp with the last update from history
            columns_to_check = [
    'symbol', 'side', 'amount', 'changeInAmount', 'markPrice',
    'entryPrice', 'pnl', 'roe', 'leverage', 'updateTime',
    'tradeType', 'stopLossPrice', 'takeProfitPrice', 'weightedScoreRatio'
]

# Adding missing columns with None as default
            for column in columns_to_check:
                if column not in df_history.columns:
                    df_history[column] = None
            
            # Create a transformed DataFrame for display
            df_transformed = pd.DataFrame({
    'Pair/Asset': df_history['symbol'],
    'is long': df_history['side'],
    'Current size after change': df_history['amount'],
    'Change in size in Asset': df_history['changeInAmount'],
    'Change in size in USDT': df_history['changeInAmount'] * -(df_history['markPrice']),
    'Entry price': df_history['entryPrice'],
    'Exit price': df_history['markPrice'],
    'pnl in usdt': df_history['pnl'],
    'pnl in %': df_history['roe'],
    'Leverage': df_history['leverage'],
    # 'updatedTime': df_history['updateTime'],
    'Trade Type': df_history['tradeType'],  # New field
    'Stop Loss Price': df_history['stopLossPrice'],  # New field
    'Take Profit Price': df_history['takeProfitPrice'],  # New field
    'Weighted Score Ratio': df_history['weightedScoreRatio'],  # New field
    # 'Transaction Value in USDT': df_history['amount'] * df_history['markPrice'],  # New calculation
    'Profit/Loss Ratio': (df_history['markPrice'] - df_history['entryPrice']) / df_history['entryPrice']  # New calculation
})
            
            if 'closed' in df_history.columns:
                df_transformed['Position closed'] = df_history['closed']
            
            st.dataframe(df_transformed)
            
            # Add the update timestamp to the transformed DataFrame
            
        else:
            st.write("No history found for this position.")

    def lastUpdated(selected_position):
        position_history = [pos for pos in tradeHistory_positions if pos['i'] == selected_position]
        return  position_history[-1]['updateTime']
    
    def isClosed(selected_position):
    # Filter trade history for the selected position
        position_history = [pos for pos in tradeHistory_positions if pos['i'] == selected_position]
        
        # Check if there are any records for the selected position
        if not position_history:
            return False
        
        # Get the most recent entry for the selected position
        last_entry = position_history[-1]
        
        # Check if the 'closed' key exists and if it indicates the position is closed
        return last_entry.get('closed', False)


         

    def main():
        df_starting = pd.DataFrame(starting_position)
        
        for index, row in df_starting.iterrows():
            side = True if float(row['amount']) > 0 else False
            is_closed = isClosed(row['i'])
            
            # Generate a unique key for the button
            button_key = f"position_{row['i']}"
            
            # Display a button for each trade position
            if st.button(
                f"{row['symbol']} : Long: {side}, Entry Price: {row['entryPrice']}, "
                f"Market Price: {row['markPrice']}, Amount: {row['amount']}, "
                f"Leverage: {row['leverage']}, isClosed: {is_closed}",
                key=button_key
            ):
                show_position_history(row['i'])

    if __name__ == "__main__":
        main()