Update app.py

app.py

@@ -4,28 +4,58 @@ import gspread
 from google.oauth2.service_account import Credentials
 import ast
 import requests
-import pandas as pd
-import boto3
 from datetime import datetime
+import boto3
 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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'
+    aws_secret_access_key ='mfk4Z48kAAivsIiCAqklP/+7v9iY6MxKMo3Rm1zD'   
 )
 
-obj = s3.Bucket('usdsmcoinmdata').Object('copyLeaderboard_trade_history.csv').get()
-df = pd.read_csv(obj['Body'],index_col=False)
+bucket_name = 'usdsmcoinmdata'
+
+# File mapping for options
+file_mapping = {
+    "usdm": "usdm_trade_history.csv",
+    "coinm": "coinm_trade_history.csv",
+    "copyLeaderboard": "copyLeaderboard_trade_history.csv"
+}
+
+# Streamlit App
+st.title("Trade History Viewer")
+
+# Dropdown to select the trade history
+option = st.selectbox("Choose the trade history to display:", list(file_mapping.keys()))
+
+
+# Fetch and display the corresponding trade history
+if option:
+    file_key = file_mapping[option]
+    try:
+        # Fetch the file from S3
+        obj = s3.Bucket(bucket_name).Object(file_key).get()
+        
+        # Read the CSV into a DataFrame
+        df = pd.read_csv(obj['Body'], index_col=False)
+        
+        # Display the DataFrame in Streamlit
+        st.write(f"Displaying data for: **{option}**")
+    except Exception as e:
+        st.error(f"Error fetching the file: {str(e)}")
+
+
+
 
 df2 = pd.read_csv('df.csv')
 
+
 def convert_str_to_list_or_keep(value):
     if isinstance(value, str):
         try:
@@ -38,27 +68,26 @@ def convert_str_to_list_or_keep(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)
+if option =="copyLeaderboard":
+    uid_input = int(st.text_input("Enter U_IDs to filter"))
 
-uid_input = int(st.text_input("Enter U_IDs to filter"))
+else:
+        uid_input = str.upper(st.text_input("Enter U_IDs to filter"))
 
-option = st.radio("Choose an option:", ["Show Position History", "Show Live Positions"])
+
+option2 = st.radio("Choose an option:", ["Show Position History", "Show Live Positions"])
 
 if df is not None and uid_input:
 
-    if option == "Show Position History":
+    if option2 == "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]
@@ -69,19 +98,13 @@ if df is not None and uid_input:
         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
@@ -132,7 +155,7 @@ if df is not None and uid_input:
             
             if 'symbol' in trade_list[i]:
                 symbol = trade_list[i]['symbol']
-                side  ="buy" if float(trade_list[i]['amount'])>0 else "sell"
+                side  ="buy" if trade_list[i]['amount']>0 else "sell"
                 amount = trade_list[i]['amount']
                 symbol = trade_list[i]['symbol']     
                 trade_list[i]['side'] =side
@@ -153,18 +176,19 @@ if df is not None and uid_input:
                                 # 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 option != "copyLeaderBoard":
+                                    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
@@ -195,21 +219,21 @@ if df is not None and uid_input:
                     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 
+                            if option!="copyLeaderboard":
+                                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)
 
@@ -223,7 +247,7 @@ if df is not None and uid_input:
                                     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']['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])
@@ -250,14 +274,15 @@ if df is not None and uid_input:
                                 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
+                                if option!= "copyLeaderboard":
+                                    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)
+                                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
@@ -321,7 +346,7 @@ if df is not None and uid_input:
 
             unique_lists =[]
 
-    elif option == "Show Live Positions":
+    elif option2 == "Show Live Positions":
         filtered_df2 = df2[df2['U_IDs'] == uid_input]
 
         if not filtered_df2.empty:
@@ -358,14 +383,16 @@ if df is not None and uid_input:
         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')
+            if option =="copyLeaderboard":
+                  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')
+                  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)
+    # 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 = [
@@ -391,12 +418,12 @@ if df is not None and uid_input:
     'pnl in usdt': df_history['pnl'],
     'pnl in %': df_history['roe'],
     'Leverage': df_history['leverage'],
-    # 'updatedTime': df_history['updateTime'],
+    '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
+    '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
 })
             
@@ -411,7 +438,7 @@ if df is not None and uid_input:
             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]
+        position_history = [pos for pos in tradeHistory_positions  if pos['i'] == selected_position]
         return  position_history[-1]['updateTime']
     
     def isClosed(selected_position):
@@ -435,20 +462,31 @@ if df is not None and uid_input:
         df_starting = pd.DataFrame(starting_position)
         
         for index, row in df_starting.iterrows():
-            side = True if float(row['amount']) > 0 else False
+            side = True if 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(
+            if option == "copyLeaderboard":
+                 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}",
+                f"Leverage: {row['leverage']}, "
+                f" isClosed: {is_closed}",
                 key=button_key
-            ):
-                show_position_history(row['i'])
+                ):
+                    show_position_history(row['i'])
+            else:
+                if st.button(
+                    f"{row['symbol']} : Long: {side}, Entry Price: {row['entryPrice']}, "
+                    f"Market Price: {row['markPrice']}, Amount: {row['amount']}, "
+                    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()