Synced repo using 'sync_with_huggingface' Github Action

app.py

@@ -1,11 +1,15 @@
 import streamlit as st
 
-st.set_page_config(page_title="Algorithmic Trading Dashboard", layout="wide", initial_sidebar_state="auto",
-                       menu_items=None, page_icon=":chart_with_upwards_trend:")
+def app():
+    st.set_page_config(page_title="Algorithmic Trading Dashboard", layout="wide", initial_sidebar_state="auto",
+                           menu_items=None, page_icon=":chart_with_upwards_trend:")
 
-dashboard = st.Page("pages/dashboard.py", title="Dashboard")
-complete_test = st.Page("pages/complete_backtest.py", title="Nifty50 Test")
+    single_test = st.Page("page/single_backtest.py", title="Run Strategy")
+    complete_test = st.Page("page/complete_backtest.py", title="Evaluate Strategy")
 
-pg = st.navigation([dashboard, complete_test])
+    pg = st.navigation({'Algorithmic Trading Dashboard':[single_test, complete_test]})
 
-pg.run()
+    pg.run()
+
+if __name__ == "__main__":
+    app()

page/complete_backtest.py

@@ -0,0 +1,71 @@
+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()

page/single_backtest.py

@@ -0,0 +1,112 @@
+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']
+
+    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)
+
+    # 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()

utils.py

@@ -2,7 +2,11 @@ import yfinance as yf
 from backtesting import Backtest
 import pandas as pd
 import random
+import os
 
+from multiprocessing import Pool
+from itertools import repeat
+import time
 from strategies import SMC_test, SMC_ema, SMCStructure
 
 def fetch(symbol, period, interval):
@@ -25,24 +29,59 @@ def smc_structure_plot_backtest(data, filename, swing_hl, **kwargs):
     bt.run(swing_window=swing_hl)
     return bt.plot(filename=filename, open_browser=False)
 
-def smc_backtest(data, swing_hl, **kwargs):
+def smc_backtest(data, filename, swing_hl, **kwargs):
     bt = Backtest(data, SMC_test, **kwargs)
     results = bt.run(swing_window=swing_hl)
-    bt.plot(filename='bokeh_graph.html', open_browser=False)
+    bt.plot(filename=filename, open_browser=False)
     return results
 
-def smc_ema_backtest(data, ema1, ema2, closecross, **kwargs):
+def smc_ema_backtest(data, filename, ema1, ema2, closecross, **kwargs):
     bt = Backtest(data, SMC_ema, **kwargs)
     results = bt.run(ema1=ema1, ema2=ema2, close_on_crossover=closecross)
-    bt.plot(filename='bokeh_graph.html', open_browser=False)
+    bt.plot(filename=filename, open_browser=False)
     return results
 
-def smc_structure_backtest(data, swing_hl, **kwargs):
+def smc_structure_backtest(data, filename, swing_hl, **kwargs):
     bt = Backtest(data, SMCStructure, **kwargs)
     results = bt.run(swing_window=swing_hl)
-    bt.plot(filename='bokeh_graph.html', open_browser=False)
+    bt.plot(filename=filename, open_browser=False)
     return results
 
+def run_strategy(ticker_symbol, strategy, period, interval, kwargs):
+    # Fetching ohlc of random ticker_symbol.
+    data = fetch(ticker_symbol, period, interval)
+
+    filename = f'{ticker_symbol}.html'
+
+    if strategy == "Order Block":
+        backtest_results = smc_backtest(data, filename, kwargs['swing_hl'])
+    elif strategy == "Order Block with EMA":
+        backtest_results = smc_ema_backtest(data, filename, kwargs['ema1'], kwargs['ema2'], kwargs['cross_close'])
+    elif strategy == "Structure trading":
+        backtest_results = smc_structure_backtest(data, filename, kwargs['swing_hl'])
+    else:
+        raise Exception('Strategy not found')
+
+    with open(filename, 'r', encoding='utf-8') as f:
+        plot = f.read()
+
+    os.remove(filename)
+
+    # Converting pd.Series to pd.Dataframe
+    backtest_results = backtest_results.to_frame().transpose()
+
+    backtest_results['stock'] = ticker_symbol
+    backtest_results['plot'] = plot
+
+    # Reordering columns.
+    # cols = df.columns.tolist()
+    # cols = cols[-1:] + cols[:-1]
+    cols = ['stock', 'Start', 'End', 'Return [%]', 'Equity Final [$]', 'Buy & Hold Return [%]', '# Trades',
+            'Win Rate [%]', 'Best Trade [%]', 'Worst Trade [%]', 'Avg. Trade [%]', 'plot']
+    backtest_results = backtest_results[cols]
+
+    return backtest_results
+
 def random_test(strategy: str, period: str, interval: str, no_of_stocks: int = 5, **kwargs):
     nifty50 = pd.read_csv("data/ind_nifty50list.csv")
     ticker_list = pd.read_csv("data/Ticker_List_NSE_India.csv")
@@ -89,52 +128,25 @@ def random_test(strategy: str, period: str, interval: str, no_of_stocks: int = 5
 
     return df
 
-def complete_test(strategy: str, period: str, interval: str, **kwargs):
+def complete_test(strategy: str, period: str, interval: str, multiprocess=True, **kwargs):
     nifty50 = pd.read_csv("data/ind_nifty50list.csv")
     ticker_list = pd.read_csv("data/Ticker_List_NSE_India.csv")
 
     # Merging nifty50 and ticker_list dataframes to get 'YahooEquiv' column.
     nifty50 = nifty50.merge(ticker_list, "inner", left_on=['Symbol'], right_on=['SYMBOL'])
 
-    df = pd.DataFrame()
-
-    for i in range(len(nifty50)):
-    # for i in range(5):
+    if multiprocess:
+        with Pool() as p:
+            result = p.starmap(run_strategy, zip(nifty50['YahooEquiv'].values, repeat(strategy), repeat(period), repeat(interval), repeat(kwargs)))
+    else:
+        result = [run_strategy(nifty50['YahooEquiv'].values[i], strategy, period, interval, kwargs) for i in range(len(nifty50))]
 
-        # Fetching ohlc of random ticker_symbol.
-        ticker_symbol = nifty50['YahooEquiv'].values[i]
-        data = fetch(ticker_symbol, period, interval)
-
-        if strategy == "Order Block":
-            backtest_results = smc_backtest(data, kwargs['swing_hl'])
-        elif strategy == "Order Block with EMA":
-            backtest_results = smc_ema_backtest(data, kwargs['ema1'], kwargs['ema2'], kwargs['cross_close'])
-        elif strategy == "Structure trading":
-            backtest_results = smc_structure_backtest(data, kwargs['swing_hl'])
-        else:
-            raise Exception('Strategy not found')
-
-        with open("bokeh_graph.html", 'r', encoding='utf-8') as f:
-            plot = f.read()
-
-        # Converting pd.Series to pd.Dataframe
-        backtest_results = backtest_results.to_frame().transpose()
-
-        backtest_results['stock'] = ticker_symbol
-        backtest_results['plot'] = plot
-
-        # Reordering columns.
-        # cols = df.columns.tolist()
-        # cols = cols[-1:] + cols[:-1]
-        cols = ['stock', 'Start', 'End', 'Return [%]', 'Equity Final [$]', 'Buy & Hold Return [%]', '# Trades', 'Win Rate [%]', 'Best Trade [%]', 'Worst Trade [%]', 'Avg. Trade [%]', 'plot']
-        backtest_results = backtest_results[cols]
-
-        df = pd.concat([df, backtest_results])
+    df = pd.concat(result)
 
     df['plot'] = df['plot'].astype(str)
     df = df.sort_values(by=['Return [%]'], ascending=False)
 
-    return df
+    return df.reset_index().drop(columns=['index'])
 
 
 if __name__ == "__main__":
@@ -143,5 +155,5 @@ if __name__ == "__main__":
     # df = yf.download('RELIANCE.NS', period='1yr', interval='15m')
 
     rt = complete_test("Order Block", '1mo', '15m', swing_hl=20)
-    rt.to_excel('test/all_testing_1.xlsx', index=False)
+    rt.to_excel('test/all_testing_2.xlsx', index=False)
     print(rt)