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import pandas as pd
import streamlit as st
import os
import random
from bokeh.io import output_file, save
from bokeh.plotting import figure
from streamlit.components import v1 as components
from indicators import SMC
from utils import fetch, run_strategy
def use_file_for_bokeh(chart: figure, chart_height=1067):
# Function used to replace st.boken_chart, because streamlit doesn't support bokeh v3
file_name = f'bokeh_graph_{random.getrandbits(8)}.html'
output_file(file_name)
save(chart)
with open(file_name, 'r', encoding='utf-8') as f:
html = f.read()
os.remove(file_name)
components.html(html, height=chart_height)
st.bokeh_chart = use_file_for_bokeh
def algorithmic_trading_dashboard():
# Load data
symbols = pd.read_csv('data/Ticker_List_NSE_India.csv')
limits = pd.read_csv('data/yahoo_limits.csv')
# Dropdown options
period_list = ['1d', '5d', '1mo', '3mo', '6mo', '1y', '2y', '5y', '10y', 'ytd', 'max']
st.markdown(
"""
# Algorithmic Trading Dashboard
## Run Strategy
"""
)
# Input fields on the main page
# Select stock
stock = st.selectbox("Select Company", symbols['NAME OF COMPANY'].unique(), index=None)
c1, c2 = st.columns(2)
with c1:
# Select interval
interval = st.selectbox("Select Interval", limits['interval'].tolist(), index=3)
with c2:
# Update period options based on interval
limit = limits[limits['interval'] == interval]['limit'].values[0]
idx = period_list.index(limit)
period_options = period_list[:idx + 1] + ['max']
period = st.selectbox("Select Period", period_options, index=3)
c1, c2 = st.columns(2)
with c1:
# Select strategy
strategy = st.selectbox("Select Strategy", ['Order Block', 'Order Block with EMA', 'Structure trading'], index=2)
with c2:
# Swing High/Low window size
swing_hl = st.number_input("Swing High/Low Window Size", min_value=1, value=10)
# EMA parameters if "Order Block with EMA" is selected
if strategy == "Order Block with EMA":
c1, c2, c3 = st.columns(3)
with c1:
ema1 = st.number_input("Fast EMA Length", min_value=1, value=9)
with c2:
ema2 = st.number_input("Slow EMA Length", min_value=1, value=21)
with c3:
cross_close = st.checkbox("Close trade on EMA crossover", value=False)
else:
ema1, ema2, cross_close = None, None, None
# Button to run the analysis
if st.button("Run"):
# Fetch ticker data
ticker = symbols[symbols['NAME OF COMPANY'] == stock]['YahooEquiv'].values[0]
data = fetch(ticker, period, interval)
# Generate signal plot based on strategy
if strategy == "Order Block" or strategy == "Order Block with EMA":
signal_plot = (
SMC(data=data, swing_hl_window_sz=swing_hl)
.plot(order_blocks=True, swing_hl=True, show=False)
.update_layout(title=dict(text=ticker))
)
else:
signal_plot = (
SMC(data=data, swing_hl_window_sz=swing_hl)
.plot(swing_hl_v2=True, structure=True, show=False)
.update_layout(title=dict(text=ticker))
)
# Generate backtest plot
# if strategy == "Order Block":
# backtest_plot = smc_plot_backtest(data, 'test.html', swing_hl)
# elif strategy == "Order Block with EMA":
# backtest_plot = smc_ema_plot_backtest(data, 'test.html', ema1, ema2, cross_close)
# elif strategy == "Structure trading":
# backtest_plot = smc_structure_plot_backtest(data, 'test.html', swing_hl)
backtest_results = run_strategy(ticker, strategy, period, interval, swing_hl=swing_hl, ema1=ema1, ema2=ema2, cross_close=cross_close)
# Display plots
st.write("### Signal Plot")
st.plotly_chart(signal_plot, width=1200)
st.write('### Backtest Results')
cols = ['stock', 'Start', 'End', 'Return [%]', 'Equity Final [$]', 'Buy & Hold Return [%]', '# Trades',
'Win Rate [%]', 'Best Trade [%]', 'Worst Trade [%]', 'Avg. Trade [%]']
st.dataframe(backtest_results, hide_index=True, column_order=cols)
st.write("### Backtest Plot")
plot = backtest_results['plot']
components.html(plot[0], height=1067)
algorithmic_trading_dashboard() |