Delete pages

pages/complete_backtest.py

@@ -1,55 +0,0 @@
-import streamlit as st
-import pandas as pd
-from streamlit.components import v1 as components
-from utils import complete_test
-
-def complete_backtest():
-    st.title("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
-
-    # Button to run the analysis
-    if st.button("Run"):
-        st.session_state.results = complete_test(strategy, period, interval, swing_hl=swing_hl, ema1=ema1, ema2=ema2, cross_close=cross_close)
-
-    if "results" in st.session_state:
-        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")
-        if df.selection.rows:
-            row = df.selection.rows
-            plot = st.session_state.results['plot'].values[row]
-            components.html(plot[0], height=1067)
-
-complete_backtest()

pages/dashboard.py

@@ -1,106 +0,0 @@
-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, smc_plot_backtest, smc_ema_plot_backtest, smc_structure_plot_backtest
-
-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']
-
-    # Input fields on the main page
-    st.title("Algorithmic Trading Dashboard")
-
-    # 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)
-
-    # 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)
-
-        # Display plots
-        st.write("### Signal Plot")
-        st.plotly_chart(signal_plot, width=1200)
-
-        st.write("### Backtesting Plot")
-        st.bokeh_chart(backtest_plot)
-
-algorithmic_trading_dashboard()