Synced repo using 'sync_with_huggingface' Github Action

page/complete_backtest.py

@@ -15,6 +15,8 @@ def complete_backtest():
         """
     )
 
+    st.info("Strategy runs on most of the Nifty50 stocks",  icon="ℹ️")
+
     limits = pd.read_csv('data/yahoo_limits.csv')
     period_list = ['1d', '5d', '1mo', '3mo', '6mo', '1y', '2y', '5y', '10y', 'ytd', 'max']
 
@@ -35,7 +37,7 @@ def complete_backtest():
         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)
+        period = st.selectbox("Select Period", period_options, index=2)
 
     # EMA parameters if "Order Block with EMA" is selected
     if strategy == "Order Block with EMA":

utils.py

@@ -58,7 +58,7 @@ def run_strategy(ticker_symbol, strategy, period, interval, kwargs):
 
         if len(data) == 0:
             if i < retries - 1:
-                print(f"Attempt{i+1}: {ticker_symbol} ohlc is empty")
+                print(f"Attempt{i + 1}: {ticker_symbol} ohlc is empty")
             else:
                 raise Exception(f"{ticker_symbol} ohlc is empty")
         else:
@@ -95,65 +95,6 @@ def run_strategy(ticker_symbol, strategy, period, interval, kwargs):
 
     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")
-
-    # Merging nifty50 and ticker_list dataframes to get 'YahooEquiv' column.
-    nifty50 = nifty50.merge(ticker_list, "inner", left_on=['Symbol'], right_on=['SYMBOL'])
-
-    # Generating random indices between 0 and len(nifty50).
-    random_indices = random.sample(range(0, len(nifty50)), no_of_stocks)
-
-    df = pd.DataFrame()
-
-    for i in random_indices:
-        # Fetching ohlc of random ticker_symbol.
-        ticker_symbol = nifty50['YahooEquiv'].values[i]
-        retries = 3
-        for i in range(retries):
-            try:
-                data = fetch(ticker_symbol, period, interval)
-            except:
-                raise Exception(f"{ticker_symbol} data fetch failed")
-    
-            if len(data) == 0:
-                raise Exception(f"{ticker_symbol} ohlc is empty")
-            else:
-                break
-        
-        try:
-            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')
-        except:
-            raise Exception(f"{ticker_symbol} strategy run failed")
-
-        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
-
-        # 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 [%]']
-        backtest_results = backtest_results[cols]
-
-        df = pd.concat([df, backtest_results])
-
-    df = df.sort_values(by=['Return [%]'], ascending=False)
-
-    return df
-
 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")