app.py

import pandas as pd
import streamlit as st
import gspread
from google.oauth2.service_account import Credentials
import ast
import requests
from datetime import datetime
import json
# Define the scope
start = False
starting_position = []
tradeHistory_positions = []
scopes = ["https://www.googleapis.com/auth/spreadsheets"]

# Service account credentials as a dictionary
service_account_info = {            
     "type": "service_account",
    "project_id": "primetrade-433011",
    "private_key_id": "8bdab2f373343c045c8712c27e34f858132675df",
    "private_key": "-----BEGIN PRIVATE KEY-----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\nn6WFbBEenJv8p5vZQi0NhHg=\n-----END PRIVATE KEY-----\n",
    "client_email": "myapi-994@primetrade-433011.iam.gserviceaccount.com",
    "client_id": "104595139129046465243",
    "auth_uri": "https://accounts.google.com/o/oauth2/auth",
    "token_uri": "https://oauth2.googleapis.com/token",
    "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
    "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/myapi-994%40primetrade-433011.iam.gserviceaccount.com",
    "universe_domain": "googleapis.com"          
    # Add your service account credentials here
}
cookie_str = "p20t=web.740861259.532251DB15AFA4E2C9D5A7A4AA7EB97E" #cookie_str get by logging into binance
csrft = "4f341a1a0b78bfb7ddb0bfc9b093ec06"
trade_type= "PERPETUAL" # perpetual or delivery
# Authenticate using the service account info
creds = Credentials.from_service_account_info(service_account_info, scopes=scopes)
client = gspread.authorize(creds)

# The ID of the Google Sheet (found in the URL of the sheet)
sheet_id = "1I_PuAeWTaRC4OhS5BA5gv0XQCA17VlIjpA1MvOlzVA8"

# Open the Google Sheet by sheet ID
workbook = client.open_by_key(sheet_id)

# Select the specific sheet in the workbook
sheet = workbook.worksheet("okxHistory")
sheet2 = workbook.worksheet("okxLeaderBoard")
sheet3 = workbook.worksheet("Performance")

# Extract the data from the Google Sheet into a pandas DataFrame
data = sheet.get_all_values()
data2 = sheet2.get_all_values()

headers = data.pop(0)
headers2 = data2.pop(0)
df = pd.DataFrame(data, columns=headers)
df2 = pd.DataFrame(data2,columns=headers2)





def combine_chunks(df):
    combined_rows = []
    
    # Group by U_IDs
    grouped = df.groupby('U_IDs')
    
    for uid, group in grouped:
        # Combine chunks for each UID
    
        trade_history_combined = ''.join(group['trade_history'].tolist())
        
        # Create a DataFrame for the combined row
        combined_row = pd.DataFrame({
            'U_IDs': [uid],
            'trade_history': [trade_history_combined]
        })
        
        combined_rows.append(combined_row)
    
    # Concatenate all combined rows into a single DataFrame
    combined_df = pd.concat(combined_rows, ignore_index=True)
    
    return combined_df

df = df.fillna(value=pd.NA)
df = df.where(pd.notnull(df), None)
df2 = df2.fillna(value=pd.NA)
df2 = df2.where(pd.notnull(df2), None)


df = combine_chunks(df)
# df2 = combine_chunks(df2)

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

uid_input = 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() 

        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):
            

                    # Check if 'Modified' key exists and extract amounts
                    if 'Modified' in data:
                        modified_positions = data['Modified']
                        # modified_positions = modified_positions[0]
                        if isinstance(modified_positions, dict) and 'amount' in modified_positions:
                                    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 trade_list[i]['amount']>0 else "sell"
                amount = trade_list[i]['usdAmount']
                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('usdAmount')
                                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'] = amount - modified_amount if modified_amount < 0 else modified_amount - 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'] = amount - closed_amount if closed_amount < 0 else closed_amount - 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)
            
            # Update the global timestamp with the last update from history
            
            
            # 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['usdAmount'],
                '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']
            })
            
            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 row['usdAmount'] > 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['usdAmount']}, "
                f"Leverage: {row['leverage']}, TradeTakenAt: {row['updateTime']}, "
                f"lastUpdated: {lastUpdated(row['i'])}, isClosed: {is_closed}",
                key=button_key
            ):
                show_position_history(row['i'])

    if __name__ == "__main__":
        main()