import sys # sys.path.append(r"D:\code\algotrading\backtesting") import streamlit as st import pandas as pd import time from streamlit.components import v1 as components from utils import complete_test def complete_backtest(): st.markdown( """ # Algorithmic Trading Dashboard ## Evaluate Strategy """ ) limits = pd.read_csv('data/yahoo_limits.csv') period_list = ['1d', '5d', '1mo', '3mo', '6mo', '1y', '2y', '5y', '10y', 'ytd', 'max'] 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) 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) # 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 multiprocess = st.checkbox("Multiprocess", value=True) # Button to run the analysis if st.button("Run"): start = time.time() st.session_state.results = complete_test(strategy, period, interval, multiprocess, swing_hl=swing_hl, ema1=ema1, ema2=ema2, cross_close=cross_close) # st.write(f"Analysis finished in {time.strftime("%Hh%Mm%Ss", time.gmtime(time.time()-start))}") st.success(f"Analysis finished in {round(time.time()-start, 2)} seconds") if "results" in st.session_state: st.write("⬇️ Select a row in index column to get detailed information of the respective stock run.") cols = ['stock', 'Start', 'End', 'Return [%]', 'Equity Final [$]', 'Buy & Hold Return [%]', '# Trades', 'Win Rate [%]', 'Best Trade [%]', 'Worst Trade [%]', 'Avg. Trade [%]'] df = st.dataframe(st.session_state.results, hide_index=True, column_order=cols, on_select="rerun", selection_mode="single-row") df.selection.rows = 1 if df.selection.rows: row = df.selection.rows plot = st.session_state.results['plot'].values[row] components.html(plot[0], height=1067) complete_backtest()