Create app.py

app.py

@@ -0,0 +1,454 @@
+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()