Update app.py

app.py

@@ -5,96 +5,55 @@ from google.oauth2.service_account import Credentials
 import ast
 import requests
 from datetime import datetime
+import boto3
 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": "[email protected]",
-    "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'
-
-options = ["Select an option", "usdmHistory", "coinmHistory", "copyLeaderBoard"]
-
-# Dropdown menu to select the sheet
-selected_sheet = st.selectbox("Select a worksheet:", options)
-
-# Ensure a valid selection is made
-if selected_sheet != "Select an option":
-    sheet = workbook.worksheet(selected_sheet)
-    st.write(f"Selected sheet: {selected_sheet}")
-else:
-    st.write("Please select a worksheet.")
-
 
-# Extract the data from the Google Sheet into a pandas DataFrame
-data = sheet.get_all_values()
+s3 = boto3.resource(
+    service_name = 's3',
+    region_name = 'ap-south-1',
+    aws_access_key_id = 'AKIA3TD2SOLYZML62HJR',
+    aws_secret_access_key ='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'
+)
 
-headers = data.pop(0)
-df = pd.DataFrame(data, columns=headers)
+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")
 
-sheet3 = workbook.worksheet("Performance")
+# Dropdown to select the trade history
+option = st.selectbox("Choose the trade history to display:", list(file_mapping.keys()))
 
-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())
+# 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()
         
-        # Create a DataFrame for the combined row
-        combined_row = pd.DataFrame({
-            'U_IDs': [uid],
-            'trade_history': [trade_history_combined]
-        })
+        # Read the CSV into a DataFrame
+        df = pd.read_csv(obj['Body'], index_col=False)
         
-        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
+        # 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)}")
+
+
 
-df = df.fillna(value=pd.NA)
-df = df.where(pd.notnull(df), None)
 
+df2 = pd.read_csv('df.csv')
 
-df = combine_chunks(df)
-# df2 = combine_chunks(df2)
 
 def convert_str_to_list_or_keep(value):
     if isinstance(value, str):
@@ -106,13 +65,11 @@ def convert_str_to_list_or_keep(value):
         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
 
-if selected_sheet == "copyLeaderBoard":
-    uid_input = int(st.text_input("Enter U_IDs to filter"))
-else:
-    uid_input = str.upper(st.text_input("Enter U_IDs to filter"))
+uid_input = str.upper(st.text_input("Enter U_IDs to filter"))
 
 option = st.radio("Choose an option:", ["Show Position History", "Show Live Positions"])
 
@@ -125,6 +82,7 @@ if df is not None and uid_input:
         
 
         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]
@@ -192,10 +150,7 @@ if df is not None and uid_input:
             
             if 'symbol' in trade_list[i]:
                 symbol = trade_list[i]['symbol']
-                if selected_sheet == "copyLeaderBoard":
-                    side  ="buy" if float(trade_list[i]['amount'])>0 else "sell"
-                else:
-                    side  ="buy" if 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
@@ -216,19 +171,18 @@ if df is not None and uid_input:
                                 # Extract symbol and amount
                                 symbol = new_position.get('symbol')
                                 amount = new_position.get('amount')
-                                if selected_sheet != "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_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
@@ -259,21 +213,21 @@ 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 selected_sheet != "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 
+                            
+                            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)
 
@@ -287,10 +241,7 @@ if df is not None and uid_input:
                                     st.header(f"Data is from {datetime.now}")
                                     start =True
                                 position['Modified']['side'] = modified_side
-                                if selected_sheet =="copyLeaderBoard":
-                                    position['Modified']['changeInAmount'] = float(amount) - modified_amount if modified_amount < 0 else modified_amount - float(amount)
-                                else:
-                                    position['Modified']['changeInAmount'] = amount - modified_amount if modified_amount < 0 else modified_amount - 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])
@@ -317,19 +268,14 @@ if df is not None and uid_input:
                                 closed_side = "sell"
 
                             if symbol == closed_symbol and side == closed_side:
-                                if selected_sheet != "copyLeaderBoard":
-                                    if start==False:
-                                        for k,v in position.items():
-                                            start_time = v['updateTime']
-                                        start =True
+                                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']
-                                if selected_sheet =="copyLeaderBoard":
-                                    trade_info['changeInAmount'] = float(amount) - closed_amount if closed_amount < 0 else closed_amount - float(amount)
-                                else:
-
-                                    trade_info['changeInAmount'] = amount - closed_amount if closed_amount < 0 else closed_amount - 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
@@ -394,27 +340,28 @@ if df is not None and uid_input:
             unique_lists =[]
 
     elif option == "Show Live Positions":
+        filtered_df2 = df2[df2['U_IDs'] == uid_input]
 
-        # if not filtered_df2.empty:
+        if not filtered_df2.empty:
 
-        #     positions_list = filtered_df2['Positions'].iloc[0]  # Extract the first match
+            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.")
+            # 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)
+        # 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)
         
             
     
@@ -428,46 +375,40 @@ if df is not None and uid_input:
         
         if position_history:
             df_history = pd.DataFrame(position_history)
-
-            if selected_sheet == "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['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
-            if selected_sheet != "copyLeaderBoard":
-                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']
-                })
-            else:
-                 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'],
-                    'Leverage': df_history['leverage'],
-                })
-                 
+            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']
             
@@ -503,34 +444,21 @@ if df is not None and uid_input:
         df_starting = pd.DataFrame(starting_position)
         
         for index, row in df_starting.iterrows():
-            if selected_sheet =="copyLeaderBoard":
-                  side = True if float(row['amount']) > 0 else False
-            else:
-                 side = True if 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 selected_sheet != "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']}, TradeTakenAt: {row['updateTime']}, "
-                    f"lastUpdated: {lastUpdated(row['i'])}, isClosed: {is_closed}",
-                    key=button_key
-                ):
-                    show_position_history(row['i'])
-
-            else:
-                if st.button(
+            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']}, TradeTakenAt: {row['updateTime']}, "
+                f"lastUpdated: {lastUpdated(row['i'])}, isClosed: {is_closed}",
                 key=button_key
-                ):
-                    show_position_history(row['i'])
+            ):
+                show_position_history(row['i'])
 
     if __name__ == "__main__":
-        main()
+        main()