import streamlit as st import plotly.graph_objects as go from datetime import datetime import pytz from trading.journal import ( create_trades_table, get_open_trades, get_trade_history, add_trade, update_trade, delete_trade, TradeEntry, get_open_trades_summary, get_current_prices, generate_position_id, get_position_summary, get_latest_portfolio_value, update_portfolio_value ) def calculate_position_performance(trades): """Calculate performance metrics for a group of trades""" total_bought = 0 total_cost = 0 total_sold = 0 total_proceeds = 0 for trade in trades: try: shares = float(trade['shares']) # Handle buy orders if ('direction' not in trade or not trade['direction'] or trade.get('direction', '').lower() == 'buy'): if trade.get('entry_price'): price = float(trade['entry_price']) total_bought += shares total_cost += shares * price # Handle sell orders elif trade.get('direction', '').lower() == 'sell' or trade.get('exit_price'): price = float(trade.get('exit_price') or trade.get('entry_price')) total_sold += shares total_proceeds += shares * price print(f"Processing trade: Direction={trade.get('direction')}, " f"Shares={shares}, Price={price}") # Debug except (ValueError, TypeError) as e: print(f"Error processing trade: {e}") continue print(f"Performance calculation results:") # Debug print(f"Total bought: {total_bought} shares at total cost: ${total_cost}") # Debug print(f"Total sold: {total_sold} shares with total proceeds: ${total_proceeds}") # Debug # Avoid division by zero if total_bought == 0: return { 'total_bought': 0, 'total_sold': 0, 'avg_entry': 0, 'avg_exit': 0, 'realized_pl': 0, 'remaining_shares': 0 } avg_entry = total_cost / total_bought if total_bought > 0 else 0 avg_exit = total_proceeds / total_sold if total_sold > 0 else 0 realized_pl = total_proceeds - (total_sold / total_bought * total_cost) if total_sold > 0 else 0 remaining_shares = total_bought - total_sold return { 'total_bought': total_bought, 'total_sold': total_sold, 'avg_entry': avg_entry, 'avg_exit': avg_exit, 'realized_pl': realized_pl, 'remaining_shares': remaining_shares } def format_datetime(dt): """Format datetime for display""" if dt: return dt.strftime('%Y-%m-%d %H:%M') return '' def plot_trade_history(trades): """Create a P/L chart using Plotly""" if not trades: return None # Prepare data dates = [] pnl = [] cumulative_pnl = 0 for trade in trades: # Skip trades without numeric exit prices if not trade['exit_price'] or not isinstance(trade['exit_price'], (int, float)): continue try: # Convert prices to float if they're strings and are numeric exit_price = float(trade['exit_price']) entry_price = float(trade['entry_price']) shares = float(trade['shares']) trade_pnl = (exit_price - entry_price) * shares cumulative_pnl += trade_pnl dates.append(trade['exit_date']) pnl.append(cumulative_pnl) except (ValueError, TypeError): # Skip trades where conversion to float fails continue if not dates: return None # Create figure fig = go.Figure() fig.add_trace( go.Scatter(x=dates, y=pnl, mode='lines+markers', name='Cumulative P/L', line=dict(color='blue'), hovertemplate='Date: %{x}
P/L: $%{y:.2f}') ) fig.update_layout( title='Cumulative Profit/Loss Over Time', xaxis_title='Date', yaxis_title='Cumulative P/L ($)', hovermode='x unified' ) return fig def trading_journal_page(): st.header("Trading Journal") print("\n=== Starting Trading Journal Page ===") # Debug # Tabs for different journal functions tab1, tab2, tab3, tab4 = st.tabs(["Open Positions", "Add Trade", "Update Trade", "Trade History"]) with tab1: st.subheader("Open Positions") print("\n--- Fetching Open Positions ---") # Debug open_trades = get_open_trades() print(f"Retrieved {len(open_trades) if open_trades else 0} open trades") # Debug print(f"Open trades {open_trades}") # Debug open_summary = get_open_trades_summary() print(f"Retrieved {len(open_summary) if open_summary else 0} position summaries") # Debug print(f"Open summary {open_summary}") # Debug if open_summary: # Get current prices unique_tickers = list(set(summary['ticker'] for summary in open_summary)) print(f"Fetching prices for tickers: {unique_tickers}") # Debug current_prices = get_current_prices(unique_tickers) print(f"Retrieved current prices: {current_prices}") # Debug total_portfolio_value = 0 total_paper_pl = 0 for summary in open_summary: print(f"\nProcessing summary for {summary['ticker']}") # Debug with st.expander(f"{summary['ticker']} Summary"): ticker = summary['ticker'] avg_entry = summary['avg_entry_price'] current_price = current_prices.get(ticker) total_shares = summary['total_shares'] position_value = avg_entry * total_shares print(f"Position details for {ticker}:") # Debug print(f"- Shares: {total_shares}") # Debug print(f"- Avg Entry: {avg_entry}") # Debug print(f"- Current Price: {current_price}") # Debug print(f"- Position Value: {position_value}") # Debug col1, col2 = st.columns(2) with col1: st.metric("Total Shares", f"{total_shares:,}") st.metric("Average Entry", f"${avg_entry:.2f}") st.metric("Position Value", f"${position_value:.2f}") with col2: if current_price: current_value = current_price * total_shares paper_pl = (current_price - avg_entry) * total_shares pl_percentage = (paper_pl / position_value) * 100 st.metric("Current Price", f"${current_price:.2f}") st.metric("Paper P/L", f"${paper_pl:.2f}", f"{pl_percentage:.2f}%") total_portfolio_value += current_value total_paper_pl += paper_pl if total_portfolio_value > 0: st.markdown("---") st.subheader("Portfolio Summary") col1, col2 = st.columns(2) with col1: st.metric("Total Portfolio Value", f"${total_portfolio_value:.2f}") with col2: st.metric("Total P/L", f"${total_paper_pl:.2f}", f"{(total_paper_pl / (total_portfolio_value - total_paper_pl)) * 100:.2f}%") with tab2: st.subheader("Add New Trade") print("\n--- Add Trade Tab ---") # Debug ticker = st.text_input("Ticker Symbol").upper() print(f"Ticker entered: {ticker}") # Debug # Add direction selection direction = st.selectbox( "Direction", ["Buy", "Sell"], key="trade_direction" ) print(f"Direction selected: {direction}") # Debug if ticker: print(f"\nProcessing ticker {ticker}") # Debug existing_positions = get_position_summary(ticker) print(f"Found existing positions: {existing_positions}") # Debug # Handle position selection based on direction if direction == "Buy": if existing_positions: print(f"Processing existing positions for {ticker}") # Debug st.write(f"Existing {ticker} Positions:") for pos in existing_positions: print(f"Position details: {pos}") # Debug st.write(f"Position ID: {pos['position_id']}") st.write(f"Total Shares: {pos['total_shares']}") st.write(f"Average Entry: ${pos['avg_entry_price']:.2f}") add_to_existing = st.checkbox("Add to existing position") print(f"Add to existing selected: {add_to_existing}") # Debug if add_to_existing: position_id = st.selectbox( "Select Position ID", options=[pos['position_id'] for pos in existing_positions], key="position_select" ) print(f"Selected position ID: {position_id}") # Debug else: position_id = None print("Creating new position") # Debug else: position_id = None print("No existing positions found, creating new position") # Debug else: # Sell if not existing_positions: st.error("No existing positions found for this ticker") st.stop() position_id = st.selectbox( "Select Position to Exit", options=[pos['position_id'] for pos in existing_positions], key="position_select" ) # Get entry date/time entry_date = st.date_input("Entry Date") entry_time_str = st.text_input("Entry Time (HH:MM)", "09:30") try: entry_time = datetime.strptime(entry_time_str, "%H:%M").time() entry_datetime = datetime.combine(entry_date, entry_time) entry_datetime = pytz.timezone('US/Pacific').localize(entry_datetime) except ValueError: st.error("Please enter time in HH:MM format (e.g. 09:30)") st.stop() # Generate position_id if needed if position_id is None: position_id = generate_position_id(ticker, entry_datetime) col1, col2 = st.columns(2) with col1: shares = st.number_input("Number of Shares", min_value=1, step=1) if direction == "Buy": entry_price = st.number_input("Entry Price", min_value=0.01, step=0.01) else: entry_price = st.number_input("Exit Price", min_value=0.01, step=0.01) with col2: if direction == "Buy": target_price = st.number_input("Target Price", min_value=0.01, step=0.01) stop_loss = st.number_input("Stop Loss", min_value=0.01, step=0.01) strategy = st.text_input("Strategy") else: exit_reason = st.text_area("Exit Reason", key="exit_reason") order_type = st.selectbox("Order Type", ["Market", "Limit"], key="add_trade_order_type") if direction == "Buy": followed_rules = st.checkbox("Followed Trading Rules") entry_reason = st.text_area("Entry Reason", key="add_trade_reason") notes = st.text_area("Notes", key="add_trade_notes") if st.button("Add Trade"): try: print("\n--- Processing Add Trade ---") # Debug entry_datetime = datetime.combine(entry_date, entry_time) entry_datetime = pytz.timezone('US/Pacific').localize(entry_datetime) print(f"Entry datetime: {entry_datetime}") # Debug trade = TradeEntry( ticker=ticker, entry_date=entry_datetime, shares=shares, entry_price=entry_price, target_price=target_price if direction == "Buy" else None, stop_loss=stop_loss if direction == "Buy" else None, strategy=strategy if direction == "Buy" else None, order_type=order_type, position_id=position_id, followed_rules=followed_rules if direction == "Buy" else None, entry_reason=entry_reason if direction == "Buy" else None, exit_reason=exit_reason if direction == "Sell" else None, notes=notes, direction=direction.lower() ) print(f"Trade object created: {trade.__dict__}") # Debug add_trade(trade) print("Trade added successfully") # Debug st.success("Trade added successfully!") st.query_params(rerun=True) except Exception as e: print(f"Error adding trade: {str(e)}") # Debug st.error(f"Error adding trade: {str(e)}") with tab3: st.subheader("Update Trade") print("\n--- Update Trade Tab ---") # Debug open_trades = get_open_trades() print(f"Retrieved {len(open_trades) if open_trades else 0} trades for update tab") # Debug print(f"Update tab trades {open_trades}") # Debug if open_trades: trade_id = st.selectbox( "Select Trade to Update", options=[t['id'] for t in open_trades], format_func=lambda x: f"{next(t['ticker'] for t in open_trades if t['id'] == x)} - {x}", key="trade_select" ) trade = next(t for t in open_trades if t['id'] == trade_id) print(f"\nSelected trade for update: {trade}") # Debug col1, col2 = st.columns(2) with col1: new_shares = st.number_input("Shares", value=trade['shares'] if trade['shares'] is not None else 0) new_entry = st.number_input("Entry Price", value=float(trade['entry_price']) if trade['entry_price'] is not None else 0.0) new_target = st.number_input("Target Price", value=float(trade['target_price']) if trade['target_price'] is not None else 0.0) with col2: new_stop = st.number_input("Stop Loss", value=float(trade['stop_loss']) if trade['stop_loss'] is not None else 0.0) new_strategy = st.text_input("Strategy", value=trade['strategy']) new_order_type = st.selectbox("Order Type", ["Market", "Limit"], index=0 if trade['order_type'] == "Market" else 1, key="update_trade_order_type") # Add date and time fields entry_date = st.date_input( "Entry Date", value=trade['entry_date'].date(), key="update_entry_date" ) entry_time_str = st.text_input( "Entry Time (HH:MM)", value=trade['entry_date'].strftime("%H:%M"), key="update_entry_time" ) try: entry_time = datetime.strptime(entry_time_str, "%H:%M").time() except ValueError: st.error("Please enter time in HH:MM format (e.g. 09:30)") st.stop() new_notes = st.text_area("Notes", value=trade['notes'] if trade['notes'] else "", key="update_trade_notes") if st.button("Update Trade"): try: # Combine date and time into datetime entry_datetime = datetime.combine(entry_date, entry_time) entry_datetime = pytz.timezone('US/Pacific').localize(entry_datetime) updates = { 'entry_date': entry_datetime, 'shares': new_shares, 'entry_price': new_entry, 'target_price': new_target, 'stop_loss': new_stop, 'strategy': new_strategy, 'order_type': new_order_type, 'notes': new_notes } print("\n--- Processing Trade Update ---") # Debug print(f"Update data being sent: {updates}") # Debug update_trade(trade_id, updates) print("Trade update completed") # Debug st.success("Trade updated successfully!") print("Clearing session state and triggering rerun") # Debug # Clear session state for key in st.session_state.keys(): del st.session_state[key] st.rerun() except Exception as e: st.error(f"Error updating trade: {str(e)}") else: st.info("No open trades to update") with tab4: st.subheader("Trade History") history = get_trade_history() if history: # Group trades by position_id positions = {} for trade in history: if trade['position_id'] not in positions: positions[trade['position_id']] = [] positions[trade['position_id']].append(trade) # Add P/L chart fig = plot_trade_history(history) if fig: st.plotly_chart(fig, use_container_width=True) # Display trades grouped by position for position_id, trades in positions.items(): # Sort trades chronologically trades.sort(key=lambda x: x['entry_date']) first_trade = trades[0] # Calculate position performance performance = calculate_position_performance(trades) with st.expander(f"{first_trade['ticker']} - Position {position_id}"): # Show position summary col1, col2, col3 = st.columns(3) with col1: st.metric("Total Shares Bought", f"{int(performance['total_bought']):,}") st.metric("Avg Entry", f"${performance['avg_entry']:.2f}") with col2: st.metric("Total Shares Sold", f"{int(performance['total_sold']):,}") st.metric("Avg Exit", f"${performance['avg_exit']:.2f}") with col3: st.metric("Remaining Shares", f"{int(performance['remaining_shares']):,}") st.metric("Realized P/L", f"${performance['realized_pl']:.2f}", f"{(performance['realized_pl'] / (performance['total_sold'] * performance['avg_entry']) * 100):.2f}%" if performance['total_sold'] > 0 else None) st.markdown("---") # Show buy trades st.subheader("Buy Orders") for trade in trades: # Infer direction if not set if 'direction' not in trade or not trade['direction']: is_buy = trade.get('exit_price') is None else: is_buy = trade.get('direction', '').lower() == 'buy' if is_buy: col1, col2, col3 = st.columns(3) with col1: st.text(f"Date: {format_datetime(trade['entry_date'])}") st.text(f"Shares: {trade['shares']}") with col2: st.text(f"Price: ${float(trade['entry_price']):.2f}") st.text(f"Order: {trade['order_type']}") with col3: if trade.get('target_price'): st.text(f"Target: ${float(trade['target_price']):.2f}") if trade.get('stop_loss'): st.text(f"Stop: ${float(trade['stop_loss']):.2f}") if trade.get('entry_reason'): st.text(f"Reason: {trade['entry_reason']}") st.markdown("---") # Show sell trades st.subheader("Sell Orders") for trade in trades: # Check for sell orders is_sell = (trade.get('direction', '').lower() == 'sell' or trade.get('exit_price') is not None) if is_sell: col1, col2 = st.columns(2) with col1: st.text(f"Date: {format_datetime(trade.get('exit_date') or trade.get('entry_date'))}") st.text(f"Shares: {trade['shares']}") with col2: # Use exit_price for sells, fallback to entry_price price = float(trade.get('exit_price') or trade.get('entry_price')) st.text(f"Price: ${price:.2f}") st.text(f"Order: {trade['order_type']}") if trade.get('exit_reason'): st.text(f"Reason: {trade['exit_reason']}") st.markdown("---") else: st.info("No trade history found")