import streamlit as st
import pandas as pd
from datetime import datetime
import pytz
from db.db_connection import create_client
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
)
from trading.trading_plan import (
delete_trading_plan,
TradingPlan, PlanStatus, Timeframe, MarketFocus, TradeFrequency,
create_trading_plan_table, save_trading_plan, get_trading_plan,
get_all_trading_plans, update_trading_plan, get_plan_trades,
link_trades_to_plan, calculate_plan_metrics, unlink_trades_from_plan
)
from trading.position_calculator import PositionCalculator
from pages.rules.strategy_guide_page import strategy_guide_page
from screener.scanner_controller import run_technical_scanner
from screener.canslim_controller import run_canslim_screener
from trading.portfolio import Portfolio, Position
from trading.position_calculator import PositionCalculator
import plotly.graph_objects as go
from plotly.subplots import make_subplots
def init_session_state():
"""Initialize session state variables"""
if 'page' not in st.session_state:
st.session_state.page = 'Trading Journal'
def load_scanner_reports():
"""Load and return available scanner reports"""
import os
import pandas as pd
from datetime import datetime
reports = []
reports_dir = "reports"
if os.path.exists(reports_dir):
for file in os.listdir(reports_dir):
if file.endswith(".csv"):
file_path = os.path.join(reports_dir, file)
# Get file creation time
created = datetime.fromtimestamp(os.path.getctime(file_path))
reports.append({
'name': file,
'path': file_path,
'created': created
})
# Sort by creation time, newest first
return sorted(reports, key=lambda x: x['created'], reverse=True)
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:
if trade['exit_price']:
trade_pnl = (trade['exit_price'] - trade['entry_price']) * trade['shares']
cumulative_pnl += trade_pnl
dates.append(trade['exit_date'])
pnl.append(cumulative_pnl)
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")
# 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")
open_trades = get_open_trades()
open_summary = get_open_trades_summary()
if open_summary:
# Get current prices
unique_tickers = list(set(summary['ticker'] for summary in open_summary))
current_prices = get_current_prices(unique_tickers)
total_portfolio_value = 0
total_paper_pl = 0
for summary in open_summary:
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
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")
ticker = st.text_input("Ticker Symbol").upper()
# Add direction selection
direction = st.selectbox(
"Direction",
["Buy", "Sell"],
key="trade_direction"
)
if ticker:
# Show existing positions for this ticker
existing_positions = get_position_summary(ticker)
if existing_positions:
st.write(f"Existing {ticker} Positions:")
for pos in existing_positions:
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}")
if direction == "Sell":
position_id = st.selectbox(
"Select Position to Exit",
options=[pos['position_id'] for pos in existing_positions],
key="position_select"
)
else: # Buy
add_to_existing = st.checkbox("Add to existing position")
if add_to_existing:
position_id = st.selectbox(
"Select Position ID",
options=[pos['position_id'] for pos in existing_positions],
key="position_select"
)
else:
position_id = generate_position_id(ticker)
else:
if direction == "Sell":
st.error("No existing positions found for this ticker")
st.stop()
position_id = generate_position_id(ticker)
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")
entry_date = st.date_input("Entry Date")
entry_time = st.time_input("Entry Time")
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:
entry_datetime = datetime.combine(entry_date, entry_time)
entry_datetime = pytz.timezone('US/Pacific').localize(entry_datetime)
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()
)
add_trade(trade)
st.success("Trade added successfully!")
st.query_params(rerun=True)
except Exception as e:
st.error(f"Error adding trade: {str(e)}")
with tab3:
st.subheader("Update Trade")
open_trades = get_open_trades()
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)
col1, col2 = st.columns(2)
with col1:
new_shares = st.number_input("Shares", value=trade['shares'])
new_entry = st.number_input("Entry Price", value=float(trade['entry_price']))
new_target = st.number_input("Target Price", value=float(trade['target_price']))
with col2:
new_stop = st.number_input("Stop Loss", value=float(trade['stop_loss']))
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 = st.time_input(
"Entry Time",
value=trade['entry_date'].time(),
key="update_entry_time"
)
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
}
update_trade(trade_id, updates)
st.success("Trade updated successfully!")
st.query_params(rerun=True)
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:
# Add P/L chart
fig = plot_trade_history(history)
if fig:
st.plotly_chart(fig, use_container_width=True)
for trade in history:
with st.expander(f"{trade['ticker']} - {format_datetime(trade['entry_date'])}"):
profit_loss = (trade['exit_price'] - trade['entry_price']) * trade['shares'] if trade['exit_price'] else None
col1, col2 = st.columns(2)
with col1:
st.metric("Entry Price", f"${trade['entry_price']:.2f}")
st.metric("Shares", trade['shares'])
if profit_loss:
st.metric("P/L", f"${profit_loss:.2f}")
with col2:
if trade['exit_price']:
st.metric("Exit Price", f"${trade['exit_price']:.2f}")
st.metric("Exit Date", format_datetime(trade['exit_date']))
st.text(f"Strategy: {trade['strategy']}")
if trade['notes']:
st.text(f"Notes: {trade['notes']}")
else:
st.info("No trade history found")
def technical_scanner_page():
st.header("Technical Scanner")
# Create tabs for scanner and reports
scanner_tab, reports_tab = st.tabs(["Run Scanner", "View Reports"])
with scanner_tab:
scanner_type = st.selectbox(
"Select Scanner",
["SunnyBands", "ATR-EMA", "ATR-EMA v2"],
key="tech_scanner_type"
)
# Add interval selection
interval = st.selectbox(
"Select Time Interval",
["Daily", "5 minute", "15 minute", "30 minute", "1 hour"],
key="interval_select"
)
# Convert interval to format expected by scanner
interval_map = {
"Daily": "1d",
"5 minute": "5m",
"15 minute": "15m",
"30 minute": "30m",
"1 hour": "1h"
}
selected_interval = interval_map[interval]
# Date range selection
date_col1, date_col2 = st.columns(2)
with date_col1:
start_date = st.date_input("Start Date")
with date_col2:
end_date = st.date_input("End Date")
col1, col2 = st.columns(2)
with col1:
min_price = st.number_input("Minimum Price", value=5.0, step=0.1)
max_price = st.number_input("Maximum Price", value=100.0, step=0.1)
with col2:
min_volume = st.number_input("Minimum Volume", value=500000, step=100000)
portfolio_size = st.number_input("Portfolio Size", value=100000.0, step=1000.0)
if st.button("Run Scanner"):
with st.spinner("Running scanner..."):
try:
signals = run_technical_scanner(
scanner_choice=scanner_type.lower().replace(" ", "_"),
start_date=start_date.strftime("%Y-%m-%d"),
end_date=end_date.strftime("%Y-%m-%d"),
min_price=min_price,
max_price=max_price,
min_volume=min_volume,
portfolio_size=portfolio_size,
interval=selected_interval
)
if signals:
st.success(f"Found {len(signals)} signals")
for signal in signals:
with st.expander(f"{signal['ticker']} - ${signal['entry_price']:.2f}"):
col1, col2 = st.columns(2)
with col1:
st.metric("Entry Price", f"${signal['entry_price']:.2f}")
st.metric("Target", f"${signal['target_price']:.2f}")
st.metric("Stop Loss", f"${signal['stop_loss']:.2f}")
with col2:
st.metric("Shares", signal['shares'])
st.metric("Position Size", f"${signal['position_size']:.2f}")
st.metric("Risk Amount", f"${abs(signal['risk_amount']):.2f}")
else:
st.info("No signals found")
except Exception as e:
st.error(f"Error running scanner: {str(e)}")
with reports_tab:
st.subheader("Scanner Reports")
reports = load_scanner_reports()
if reports:
# Create a selectbox to choose the report
selected_report = st.selectbox(
"Select Report",
options=reports,
format_func=lambda x: f"{x['name']} ({x['created'].strftime('%Y-%m-%d %H:%M')})",
key="tech_scanner_report"
)
if selected_report:
try:
# Load and display the CSV
df = pd.read_csv(selected_report['path'])
# Add download button
st.download_button(
label="Download Report",
data=df.to_csv(index=False),
file_name=selected_report['name'],
mime='text/csv'
)
# Display the dataframe
st.dataframe(df)
except Exception as e:
st.error(f"Error loading report: {str(e)}")
else:
st.info("No scanner reports found")
def canslim_screener_page():
st.header("CANSLIM Screener")
# Create tabs for scanner and reports
scanner_tab, reports_tab = st.tabs(["Run Scanner", "View Reports"])
with scanner_tab:
# Date range selection
col1, col2 = st.columns(2)
with col1:
start_date = st.date_input("Start Date")
with col2:
end_date = st.date_input("End Date")
# CANSLIM criteria selection
st.subheader("Select Screening Criteria")
c_criteria = st.expander("Current Quarterly Earnings (C)")
with c_criteria:
eps_threshold = st.slider("EPS Growth Threshold (%)", 0, 100, 25)
sales_threshold = st.slider("Sales Growth Threshold (%)", 0, 100, 25)
roe_threshold = st.slider("ROE Threshold (%)", 0, 50, 17)
a_criteria = st.expander("Annual Earnings Growth (A)")
with a_criteria:
annual_eps_threshold = st.slider("Annual EPS Growth Threshold (%)", 0, 100, 25)
l_criteria = st.expander("Industry Leadership (L)")
with l_criteria:
use_l = st.checkbox("Check Industry Leadership", value=True)
l_threshold = st.slider("Industry Leadership Score Threshold", 0.0, 1.0, 0.7)
i_criteria = st.expander("Institutional Sponsorship (I)")
with i_criteria:
use_i = st.checkbox("Check Institutional Sponsorship", value=True)
i_threshold = st.slider("Institutional Sponsorship Score Threshold", 0.0, 1.0, 0.7)
if st.button("Run CANSLIM Screener"):
with st.spinner("Running CANSLIM screener..."):
try:
# Prepare selected screeners dictionary
selected_screeners = {
"C": {
"EPS_Score": eps_threshold / 100,
"Sales_Score": sales_threshold / 100,
"ROE_Score": roe_threshold / 100
},
"A": {
"Annual_EPS_Score": annual_eps_threshold / 100
}
}
if use_l:
selected_screeners["L"] = {"L_Score": l_threshold}
if use_i:
selected_screeners["I"] = {"I_Score": i_threshold}
# Convert dates to strings for the screener
start_str = start_date.strftime("%Y-%m-%d")
end_str = end_date.strftime("%Y-%m-%d")
# Run the screener
st.session_state.screener_params = {
"start_date": start_str,
"end_date": end_str,
"selected_screeners": selected_screeners
}
# Modify run_canslim_screener to accept parameters
run_canslim_screener()
st.success("Screening complete! Check the Reports tab for results.")
except Exception as e:
st.error(f"Error running CANSLIM screener: {str(e)}")
with reports_tab:
st.subheader("CANSLIM Reports")
# Use the same report loading function but look in a CANSLIM-specific directory
reports = load_scanner_reports() # You might want to modify this to look in a CANSLIM directory
if reports:
# Create a selectbox to choose the report
selected_report = st.selectbox(
"Select Report",
options=reports,
format_func=lambda x: f"{x['name']} ({x['created'].strftime('%Y-%m-%d %H:%M')})",
key="canslim_scanner_report"
)
if selected_report:
try:
# Load and display the CSV
df = pd.read_csv(selected_report['path'])
# Add download button
st.download_button(
label="Download Report",
data=df.to_csv(index=False),
file_name=selected_report['name'],
mime='text/csv'
)
# Display the dataframe
st.dataframe(df)
except Exception as e:
st.error(f"Error loading report: {str(e)}")
else:
st.info("No CANSLIM reports found")
def trading_system_page():
st.header("Trading System")
# Create tabs
calc_tab, portfolio_tab, value_tab = st.tabs(["Position Calculator", "Portfolio Management", "Portfolio Value"])
with calc_tab:
st.subheader("Position Calculator")
# Get latest portfolio value for default account size
portfolio_data = get_latest_portfolio_value()
default_account_size = portfolio_data['total_value'] if portfolio_data else 100000.0
col1, col2 = st.columns(2)
with col1:
account_size = st.number_input("Account Size ($)",
min_value=0.0,
value=default_account_size,
step=1000.0)
risk_percentage = st.number_input("Risk Percentage (%)",
min_value=0.1,
max_value=100.0,
value=1.0,
step=0.1)
stop_loss_percentage = st.number_input("Stop Loss Percentage (%)",
min_value=0.1,
max_value=100.0,
value=7.0,
step=0.1)
with col2:
entry_price = st.number_input("Entry Price ($)", min_value=0.01, step=0.01)
target_price = st.number_input("Target Price ($)", min_value=0.01, step=0.01)
if st.button("Calculate Position"):
try:
calculator = PositionCalculator(
account_size=account_size,
risk_percentage=risk_percentage,
stop_loss_percentage=stop_loss_percentage
)
position = calculator.calculate_position_size(entry_price, target_price)
col1, col2 = st.columns(2)
with col1:
st.metric("Number of Shares", f"{position['shares']:,}")
st.metric("Position Value", f"${position['position_value']:,.2f}")
st.metric("Risk Amount", f"${position['risk_amount']:,.2f}")
with col2:
st.metric("Stop Loss Price", f"${position['stop_loss']:.2f}")
st.metric("Potential Loss", f"${position['potential_loss']:,.2f}")
if 'potential_profit' in position:
st.metric("Potential Profit", f"${position['potential_profit']:,.2f}")
st.metric("Risk/Reward Ratio", f"{position['risk_reward_ratio']:.2f}")
except Exception as e:
st.error(f"Error calculating position: {str(e)}")
with portfolio_tab:
st.subheader("Portfolio Management")
# Initialize portfolio if not in session state
if 'portfolio' not in st.session_state:
st.session_state.portfolio = Portfolio()
# Load existing open trades into portfolio
open_trades = get_open_trades()
for trade in open_trades:
position = Position(
symbol=trade['ticker'],
entry_date=trade['entry_date'],
entry_price=trade['entry_price'],
shares=trade['shares'],
stop_loss=trade['stop_loss'],
target_price=trade['target_price']
)
st.session_state.portfolio.add_position(position)
# Add position form
with st.expander("Add New Position"):
col1, col2 = st.columns(2)
with col1:
symbol = st.text_input("Symbol").upper()
shares = st.number_input("Number of Shares", min_value=1, step=1)
entry_price = st.number_input("Entry Price ($)", min_value=0.01, step=0.01, key="port_entry_price")
with col2:
target_price = st.number_input("Target Price ($)", min_value=0.01, step=0.01, key="port_target_price")
stop_loss = st.number_input("Stop Loss ($)", min_value=0.01, step=0.01)
if st.button("Add Position"):
try:
position = Position(
symbol=symbol,
entry_date=datetime.now(),
entry_price=entry_price,
shares=shares,
stop_loss=stop_loss,
target_price=target_price
)
st.session_state.portfolio.add_position(position)
st.success(f"Added position: {symbol}")
except Exception as e:
st.error(f"Error adding position: {str(e)}")
# Display current portfolio
positions = st.session_state.portfolio.get_position_summary()
if positions:
st.subheader("Current Positions")
# Add a counter to make unique keys
for i, pos in enumerate(positions):
with st.expander(f"{pos['symbol']} Position - {format_datetime(pos['entry_date'])}"):
col1, col2 = st.columns(2)
with col1:
st.metric("Entry Price", f"${pos['entry_price']:.2f}")
st.metric("Shares", pos['shares'])
st.metric("Current Value", f"${pos['current_value']:.2f}")
with col2:
st.metric("Stop Loss", f"${pos['stop_loss']:.2f}")
st.metric("Target", f"${pos['target_price']:.2f}")
st.metric("Risk/Reward", f"{pos['risk_reward_ratio']:.2f}")
if st.button(f"Remove {pos['symbol']}", key=f"remove_{pos['symbol']}_{i}"):
st.session_state.portfolio.remove_position(pos['symbol'])
st.rerun()
else:
st.info("No positions in portfolio")
with value_tab:
st.subheader("Portfolio Value Management")
# Get latest portfolio value
portfolio_data = get_latest_portfolio_value()
if portfolio_data:
st.metric("Current Portfolio Value", f"${portfolio_data['total_value']:,.2f}")
st.metric("Cash Balance", f"${portfolio_data['cash_balance']:,.2f}")
st.text(f"Last Updated: {portfolio_data['date']}")
else:
st.info("No portfolio value data found")
# Update portfolio value form
with st.expander("Update Portfolio Value"):
new_value = st.number_input("New Portfolio Value ($)", min_value=0.0, step=100.0)
new_cash = st.number_input("New Cash Balance ($)", min_value=0.0, step=100.0)
notes = st.text_area("Notes (optional)", key="portfolio_value_notes")
if st.button("Update Values"):
try:
update_portfolio_value(new_value, new_cash, notes)
st.success("Portfolio value updated successfully!")
st.set_query_params(rerun=True)
except Exception as e:
st.error(f"Error updating portfolio value: {str(e)}")
def trading_plan_page():
st.header("Trading Plans")
# Create tabs for different plan operations
list_tab, add_tab, edit_tab = st.tabs(["View Plans", "Add Plan", "Edit Plan"])
with list_tab:
st.subheader("Trading Plans")
plans = get_all_trading_plans()
if plans:
for plan in plans:
with st.expander(f"{plan.plan_name} ({plan.status.value})"):
col1, col2 = st.columns(2)
with col1:
st.markdown("### Basic Information")
st.write(f"**Plan Name:** {plan.plan_name}")
st.write(f"**Status:** {plan.status.value}")
st.write(f"**Author:** {plan.plan_author}")
st.write(f"**Version:** {plan.strategy_version}")
st.write(f"**Created:** {plan.created_at}")
st.write(f"**Updated:** {plan.updated_at}")
st.markdown("### Market Details")
st.write(f"**Timeframe:** {plan.timeframe.value}")
st.write(f"**Market:** {plan.market_focus.value}")
st.write(f"**Frequency:** {plan.trade_frequency.value}")
if plan.sector_focus:
st.write(f"**Sector Focus:** {plan.sector_focus}")
with col2:
st.markdown("### Risk Parameters")
st.write(f"**Stop Loss:** {plan.stop_loss}%")
st.write(f"**Profit Target:** {plan.profit_target}%")
st.write(f"**Risk/Reward Ratio:** {plan.risk_reward_ratio}")
st.write(f"**Position Size:** {plan.position_sizing}%")
st.write(f"**Risk per Trade:** {plan.total_risk_per_trade}%")
st.write(f"**Max Portfolio Risk:** {plan.max_portfolio_risk}%")
st.write(f"**Max Drawdown:** {plan.maximum_drawdown}%")
st.write(f"**Max Trades/Day:** {plan.max_trades_per_day}")
st.write(f"**Max Trades/Week:** {plan.max_trades_per_week}")
st.markdown("### Performance Metrics")
if any([plan.win_rate, plan.average_return_per_trade, plan.profit_factor]):
col3, col4 = st.columns(2)
with col3:
if plan.win_rate:
st.write(f"**Win Rate:** {plan.win_rate}%")
if plan.average_return_per_trade:
st.write(f"**Avg Return/Trade:** {plan.average_return_per_trade}%")
with col4:
if plan.profit_factor:
st.write(f"**Profit Factor:** {plan.profit_factor}")
# Add Linked Trades section
st.markdown("### Linked Trades")
plan_trades = get_plan_trades(plan.id)
if plan_trades:
total_pl = 0
winning_trades = 0
total_trades = len(plan_trades)
# Display trade statistics first
st.markdown("#### Trade Statistics")
col1, col2 = st.columns(2)
with col1:
st.write(f"**Total Trades:** {total_trades}")
st.write(f"**Winning Trades:** {winning_trades}")
if total_trades > 0:
st.write(f"**Win Rate:** {(winning_trades/total_trades)*100:.2f}%")
with col2:
st.write(f"**Total P/L:** ${total_pl:.2f}")
if total_trades > 0:
st.write(f"**Average P/L per Trade:** ${total_pl/total_trades:.2f}")
# Display trades in a table format instead of nested expanders
st.markdown("#### Individual Trades")
for trade in plan_trades:
st.markdown("---")
cols = st.columns(3)
with cols[0]:
st.write(f"**{trade['ticker']} - {trade['entry_date']}**")
st.write(f"**Direction:** {trade['direction']}")
if trade['strategy']:
st.write(f"**Strategy:** {trade['strategy']}")
with cols[1]:
st.write(f"**Entry:** ${trade['entry_price']:.2f}")
st.write(f"**Shares:** {trade['shares']}")
with cols[2]:
if trade['exit_price']:
pl = (trade['exit_price'] - trade['entry_price']) * trade['shares']
total_pl += pl
if pl > 0:
winning_trades += 1
st.write(f"**Exit:** ${trade['exit_price']:.2f}")
st.write(f"**P/L:** ${pl:.2f}")
st.write(f"**Exit Date:** {trade['exit_date']}")
else:
st.write("**Status:** Open")
else:
st.info("No trades linked to this plan")
st.markdown("### Strategy Details")
st.write("**Entry Criteria:**")
st.write(plan.entry_criteria)
st.write("**Exit Criteria:**")
st.write(plan.exit_criteria)
st.write("**Entry Confirmation:**")
st.write(plan.entry_confirmation)
st.write("**Market Conditions:**")
st.write(plan.market_conditions)
st.write("**Technical Indicators:**")
st.write(plan.indicators_used)
st.markdown("### Risk Management")
st.write("**Drawdown Adjustments:**")
st.write(plan.adjustments_for_drawdown)
st.write("**Risk Controls:**")
st.write(plan.risk_controls)
if plan.fundamental_criteria:
st.markdown("### Fundamental Analysis")
st.write(plan.fundamental_criteria)
if plan.options_strategy_details:
st.markdown("### Options Strategy")
st.write(plan.options_strategy_details)
if plan.improvements_needed:
st.markdown("### Areas for Improvement")
st.write(plan.improvements_needed)
if plan.trade_review_notes:
st.markdown("### Trade Review Notes")
st.write(plan.trade_review_notes)
if plan.future_testing_ideas:
st.markdown("### Future Testing Ideas")
st.write(plan.future_testing_ideas)
if plan.historical_backtest_results:
st.markdown("### Historical Backtest Results")
st.write(plan.historical_backtest_results)
if plan.real_trade_performance:
st.markdown("### Real Trading Performance")
st.write(plan.real_trade_performance)
else:
st.info("No trading plans found")
with add_tab:
st.subheader("Create New Trading Plan")
# Basic Info
col1, col2 = st.columns(2)
with col1:
plan_name = st.text_input("Plan Name", key="add_plan_name")
status = st.selectbox("Status", [s.value for s in PlanStatus], key="add_status")
timeframe = st.selectbox("Timeframe", [t.value for t in Timeframe], key="add_timeframe")
market_focus = st.selectbox("Market Focus", [m.value for m in MarketFocus], key="add_market_focus")
with col2:
trade_frequency = st.selectbox("Trade Frequency", [f.value for f in TradeFrequency], key="add_trade_frequency")
plan_author = st.text_input("Author", key="add_plan_author")
strategy_version = st.number_input("Version", min_value=1, value=1, key="add_strategy_version")
# Risk Parameters
st.subheader("Risk Parameters")
col1, col2 = st.columns(2)
with col1:
stop_loss = st.number_input("Stop Loss %", min_value=0.1, value=7.0, key="add_stop_loss")
profit_target = st.number_input("Profit Target %", min_value=0.1, value=21.0, key="add_profit_target")
risk_reward_ratio = profit_target / stop_loss if stop_loss > 0 else 0
st.write(f"Risk:Reward Ratio: {risk_reward_ratio:.2f}")
with col2:
position_sizing = st.number_input("Position Size %", min_value=0.1, value=5.0, key="add_position_sizing")
total_risk_per_trade = st.number_input("Risk per Trade %", min_value=0.1, value=1.0, key="add_total_risk_per_trade")
max_portfolio_risk = st.number_input("Max Portfolio Risk %", min_value=0.1, value=5.0, key="add_max_portfolio_risk")
# Trade Rules
st.subheader("Trade Rules")
col1, col2 = st.columns(2)
with col1:
max_trades_per_day = st.number_input("Max Trades per Day", min_value=1, value=3, key="add_max_trades_per_day")
max_trades_per_week = st.number_input("Max Trades per Week", min_value=1, value=15, key="add_max_trades_per_week")
maximum_drawdown = st.number_input("Maximum Drawdown %", min_value=0.1, value=20.0, key="add_maximum_drawdown")
# Strategy Details
st.subheader("Strategy Details")
entry_criteria = st.text_area("Entry Criteria", key="add_entry_criteria")
exit_criteria = st.text_area("Exit Criteria", key="add_exit_criteria")
entry_confirmation = st.text_area("Entry Confirmation", key="add_entry_confirmation")
market_conditions = st.text_area("Market Conditions", key="add_market_conditions")
indicators_used = st.text_area("Technical Indicators", key="add_indicators_used")
# Risk Management
st.subheader("Risk Management")
adjustments_for_drawdown = st.text_area("Drawdown Adjustments", key="add_adjustments_for_drawdown")
risk_controls = st.text_area("Risk Controls", key="add_risk_controls")
# Optional Fields
st.subheader("Additional Information")
col1, col2 = st.columns(2)
with col1:
sector_focus = st.text_input("Sector Focus (optional)", key="add_sector_focus")
fundamental_criteria = st.text_area("Fundamental Criteria (optional)", key="add_fundamental_criteria")
with col2:
options_strategy_details = st.text_area("Options Strategy Details (optional)", key="add_options_strategy_details")
improvements_needed = st.text_area("Improvements Needed (optional)", key="add_improvements_needed")
if st.button("Create Trading Plan", key="create_plan_button"):
try:
plan = TradingPlan(
plan_name=plan_name,
status=PlanStatus(status),
timeframe=Timeframe(timeframe),
market_focus=MarketFocus(market_focus),
trade_frequency=TradeFrequency(trade_frequency),
entry_criteria=entry_criteria,
exit_criteria=exit_criteria,
stop_loss=stop_loss,
profit_target=profit_target,
risk_reward_ratio=risk_reward_ratio,
entry_confirmation=entry_confirmation,
position_sizing=position_sizing,
maximum_drawdown=maximum_drawdown,
max_trades_per_day=max_trades_per_day,
max_trades_per_week=max_trades_per_week,
total_risk_per_trade=total_risk_per_trade,
max_portfolio_risk=max_portfolio_risk,
adjustments_for_drawdown=adjustments_for_drawdown,
risk_controls=risk_controls,
market_conditions=market_conditions,
indicators_used=indicators_used,
plan_author=plan_author,
strategy_version=strategy_version,
sector_focus=sector_focus,
fundamental_criteria=fundamental_criteria,
options_strategy_details=options_strategy_details,
improvements_needed=improvements_needed
)
save_trading_plan(plan)
st.success("Trading plan created successfully!")
st.query_params.update(rerun=True)
except Exception as e:
st.error(f"Error creating trading plan: {str(e)}")
with edit_tab:
st.subheader("Edit Trading Plan")
plans = get_all_trading_plans()
if plans:
selected_plan_id = st.selectbox(
"Select Plan to Edit",
options=[plan.id for plan in plans],
format_func=lambda x: next(p.plan_name for p in plans if p.id == x),
key="edit_plan_select"
)
if selected_plan_id:
plan = get_trading_plan(selected_plan_id)
if plan:
# Basic Info
col1, col2 = st.columns(2)
with col1:
plan_name = st.text_input("Plan Name", value=plan.plan_name, key="edit_plan_name")
status = st.selectbox("Status", [s.value for s in PlanStatus], index=[s.value for s in PlanStatus].index(plan.status.value), key="edit_status")
timeframe = st.selectbox("Timeframe", [t.value for t in Timeframe], index=[t.value for t in Timeframe].index(plan.timeframe.value), key="edit_timeframe")
market_focus = st.selectbox("Market Focus", [m.value for m in MarketFocus], index=[m.value for m in MarketFocus].index(plan.market_focus.value), key="edit_market_focus")
with col2:
trade_frequency = st.selectbox("Trade Frequency", [f.value for f in TradeFrequency], index=[f.value for f in TradeFrequency].index(plan.trade_frequency.value), key="edit_trade_frequency")
plan_author = st.text_input("Author", value=plan.plan_author, key="edit_plan_author")
strategy_version = st.number_input("Version", min_value=1, value=plan.strategy_version, key="edit_strategy_version")
# Risk Parameters
st.subheader("Risk Parameters")
col1, col2 = st.columns(2)
with col1:
stop_loss = st.number_input("Stop Loss %", min_value=0.1, value=plan.stop_loss, key="edit_stop_loss")
profit_target = st.number_input("Profit Target %", min_value=0.1, value=plan.profit_target, key="edit_profit_target")
risk_reward_ratio = profit_target / stop_loss if stop_loss > 0 else 0
st.write(f"Risk:Reward Ratio: {risk_reward_ratio:.2f}")
with col2:
position_sizing = st.number_input("Position Size %", min_value=0.1, value=plan.position_sizing, key="edit_position_sizing")
total_risk_per_trade = st.number_input("Risk per Trade %", min_value=0.1, value=plan.total_risk_per_trade, key="edit_total_risk_per_trade")
max_portfolio_risk = st.number_input("Max Portfolio Risk %", min_value=0.1, value=plan.max_portfolio_risk, key="edit_max_portfolio_risk")
# Trade Rules
st.subheader("Trade Rules")
col1, col2 = st.columns(2)
with col1:
max_trades_per_day = st.number_input("Max Trades per Day", min_value=1, value=plan.max_trades_per_day, key="edit_max_trades_per_day")
max_trades_per_week = st.number_input("Max Trades per Week", min_value=1, value=plan.max_trades_per_week, key="edit_max_trades_per_week")
maximum_drawdown = st.number_input("Maximum Drawdown %", min_value=0.1, value=plan.maximum_drawdown, key="edit_maximum_drawdown")
# Strategy Details
st.subheader("Strategy Details")
entry_criteria = st.text_area("Entry Criteria", value=plan.entry_criteria, key="edit_entry_criteria")
exit_criteria = st.text_area("Exit Criteria", value=plan.exit_criteria, key="edit_exit_criteria")
entry_confirmation = st.text_area("Entry Confirmation", value=plan.entry_confirmation, key="edit_entry_confirmation")
market_conditions = st.text_area("Market Conditions", value=plan.market_conditions, key="edit_market_conditions")
indicators_used = st.text_area("Technical Indicators", value=plan.indicators_used, key="edit_indicators_used")
# Risk Management
st.subheader("Risk Management")
adjustments_for_drawdown = st.text_area("Drawdown Adjustments", value=plan.adjustments_for_drawdown, key="edit_adjustments_for_drawdown")
risk_controls = st.text_area("Risk Controls", value=plan.risk_controls, key="edit_risk_controls")
# Optional Fields
st.subheader("Additional Information")
col1, col2 = st.columns(2)
with col1:
sector_focus = st.text_input("Sector Focus (optional)", value=plan.sector_focus, key="edit_sector_focus")
fundamental_criteria = st.text_area("Fundamental Criteria (optional)", value=plan.fundamental_criteria, key="edit_fundamental_criteria")
with col2:
options_strategy_details = st.text_area("Options Strategy Details (optional)", value=plan.options_strategy_details, key="edit_options_strategy_details")
improvements_needed = st.text_area("Improvements Needed (optional)", value=plan.improvements_needed, key="edit_improvements_needed")
if st.button("Update Plan", key="update_plan_button"):
try:
# Update the plan with new values
plan.plan_name = plan_name
plan.status = PlanStatus(status)
plan.timeframe = Timeframe(timeframe)
plan.market_focus = MarketFocus(market_focus)
plan.trade_frequency = TradeFrequency(trade_frequency)
plan.plan_author = plan_author
plan.strategy_version = strategy_version
plan.stop_loss = stop_loss
plan.profit_target = profit_target
plan.position_sizing = position_sizing
plan.total_risk_per_trade = total_risk_per_trade
plan.max_portfolio_risk = max_portfolio_risk
plan.max_trades_per_day = max_trades_per_day
plan.max_trades_per_week = max_trades_per_week
plan.maximum_drawdown = maximum_drawdown
plan.entry_criteria = entry_criteria
plan.exit_criteria = exit_criteria
plan.entry_confirmation = entry_confirmation
plan.market_conditions = market_conditions
plan.indicators_used = indicators_used
plan.adjustments_for_drawdown = adjustments_for_drawdown
plan.risk_controls = risk_controls
plan.sector_focus = sector_focus
plan.fundamental_criteria = fundamental_criteria
plan.options_strategy_details = options_strategy_details
plan.improvements_needed = improvements_needed
update_trading_plan(plan)
st.success("Plan updated successfully!")
st.query_params.update(rerun=True)
except Exception as e:
st.error(f"Error updating plan: {str(e)}")
# Delete button (at the same level as the update button)
if st.button("Delete Plan", key="delete_plan_button"):
try:
delete_trading_plan(plan.id)
st.success("Plan deleted successfully!")
st.query_params.update(rerun=True)
except Exception as e:
st.error(f"Error deleting plan: {str(e)}")
# Add Trade Management section
st.subheader("Trade Management")
# Get current trades for this plan
plan_trades = get_plan_trades(plan.id)
# Display current trades
if plan_trades:
st.write("Current Trades:")
for trade in plan_trades:
with st.expander(f"{trade['ticker']} - {trade['entry_date']}"):
col1, col2 = st.columns(2)
with col1:
st.write(f"Entry: ${trade['entry_price']:.2f}")
st.write(f"Shares: {trade['shares']}")
with col2:
if trade['exit_price']:
pl = (trade['exit_price'] - trade['entry_price']) * trade['shares']
st.write(f"Exit: ${trade['exit_price']:.2f}")
st.write(f"P/L: ${pl:.2f}")
# Add unlink button for each trade
if st.button("Unlink Trade", key=f"unlink_trade_{trade['id']}"):
try:
# Update the single trade
query = """
ALTER TABLE stock_db.trades
UPDATE plan_id = NULL
WHERE id = %(trade_id)s
"""
with create_client() as client:
client.command(query, {'trade_id': trade['id']})
# Recalculate metrics
metrics = calculate_plan_metrics(plan.id)
plan.win_rate = metrics['win_rate']
plan.average_return_per_trade = metrics['average_return']
plan.profit_factor = metrics['profit_factor']
update_trading_plan(plan)
st.success(f"Trade unlinked successfully!")
st.query_params.update(rerun=True)
except Exception as e:
st.error(f"Error unlinking trade: {str(e)}")
# Add button to unlink all trades
if st.button("Unlink All Trades", key=f"unlink_all_trades_{plan.id}"):
try:
if unlink_trades_from_plan(plan.id):
# Reset metrics
plan.win_rate = None
plan.average_return_per_trade = None
plan.profit_factor = None
update_trading_plan(plan)
st.success("All trades unlinked successfully!")
st.query_params.update(rerun=True)
else:
st.error("Error unlinking trades")
except Exception as e:
st.error(f"Error unlinking trades: {str(e)}")
# Get available trades
with create_client() as client:
query = """
SELECT
id,
ticker,
entry_date,
entry_price,
shares,
exit_price,
exit_date,
direction,
strategy,
CASE
WHEN exit_price IS NOT NULL
THEN (exit_price - entry_price) * shares
ELSE NULL
END as profit_loss
FROM stock_db.trades
WHERE plan_id IS NULL
ORDER BY entry_date DESC
"""
result = client.query(query)
available_trades = [dict(zip(
['id', 'ticker', 'entry_date', 'entry_price', 'shares',
'exit_price', 'exit_date', 'direction', 'strategy', 'profit_loss'],
row
)) for row in result.result_rows]
if available_trades:
st.write("Link Existing Trades:")
selected_trades = st.multiselect(
"Select trades to link to this plan",
options=[t['id'] for t in available_trades],
format_func=lambda x: next(
f"{t['ticker']} - {t['entry_date']} - ${t['entry_price']:.2f} "
f"({t['direction']}) - {t['strategy']} "
f"{'[Closed]' if t['exit_price'] else '[Open]'} "
f"{'P/L: $' + format(t['profit_loss'], '.2f') if t['profit_loss'] is not None else ''}"
for t in available_trades if t['id'] == x
),
key=f"link_trades_{plan.id}"
)
if selected_trades and st.button("Link Selected Trades", key=f"link_trades_button_{plan.id}"):
if link_trades_to_plan(plan.id, selected_trades):
st.success("Trades linked successfully!")
# Calculate and update metrics
metrics = calculate_plan_metrics(plan.id)
plan.win_rate = metrics['win_rate']
plan.average_return_per_trade = metrics['average_return']
plan.profit_factor = metrics['profit_factor']
update_trading_plan(plan)
st.query_params.update(rerun=True)
else:
st.error("Error linking trades")
else:
st.info("No plans available to edit")
def main():
st.set_page_config(page_title="Trading System", layout="wide")
init_session_state()
# Sidebar navigation
st.sidebar.title("Navigation")
st.session_state.page = st.sidebar.radio(
"Go to",
["Strategy Guide", "Trading Journal", "Technical Scanner", "CANSLIM Screener", "Trading System", "Trading Plans"]
)
# Create necessary tables
create_trades_table()
create_trading_plan_table()
# Display selected page
if st.session_state.page == "Strategy Guide":
strategy_guide_page()
elif st.session_state.page == "Trading Journal":
trading_journal_page()
elif st.session_state.page == "Technical Scanner":
technical_scanner_page()
elif st.session_state.page == "CANSLIM Screener":
canslim_screener_page()
elif st.session_state.page == "Trading System":
trading_system_page()
elif st.session_state.page == "Trading Plans":
trading_plan_page()
if __name__ == "__main__":
main()