Refactor backtesting logic and introduce new components

- Replaced TrendDetectorSimple with a new Backtest class for improved backtesting functionality.
- Integrated argparse for configuration file input, allowing dynamic parameter setting.
- Added MarketFees and Supertrends classes to handle fee calculations and trend detection, respectively.
- Removed deprecated main_debug.py and trend_detector_simple.py files to streamline the codebase.
- Enhanced process_timeframe_data to utilize the new Backtest class for executing trades and calculating results.
- Updated Storage class to support writing backtest results with metadata.

cycles/utils/apply_taxes_to_file.py

@@ -1,23 +0,0 @@
-import sys
-import os
-sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-from taxes import Taxes
-
-if __name__ == "__main__":
-    if len(sys.argv) < 2:
-        print("Usage: python apply_taxes_to_file.py <input_csv> [profit_col]")
-        sys.exit(1)
-
-    input_csv = sys.argv[1]
-    profit_col = sys.argv[2] if len(sys.argv) > 2 else 'final_usd'
-
-    if not os.path.isfile(input_csv):
-        print(f"File not found: {input_csv}")
-        sys.exit(1)
-
-    base, ext = os.path.splitext(input_csv)
-    output_csv = f"{base}_taxed.csv"
-
-    taxes = Taxes()  # Default 20% tax rate
-    taxes.add_taxes_to_results_csv(input_csv, output_csv, profit_col=profit_col)
-    print(f"Taxed file saved as: {output_csv}")

cycles/utils/storage.py

@@ -169,15 +169,19 @@ class Storage:
                 filtered_row = {k: v for k, v in row.items() if k in fieldnames}
                 writer.writerow(filtered_row)
     
-    def write_results_combined(self, filename, fieldnames, rows):
+    def write_backtest_results(self, filename, fieldnames, rows, metadata_lines=None):
         """Write a combined results to a CSV file
         Args:
             filename: filename to write to
             fieldnames: list of fieldnames
             rows: list of rows
+            metadata_lines: optional list of strings to write as header comments
         """
         fname = os.path.join(self.results_dir, filename)
         with open(fname, "w", newline="") as csvfile:
+            if metadata_lines:
+                for line in metadata_lines:
+                    csvfile.write(f"{line}\n")
             writer = csv.DictWriter(csvfile, fieldnames=fieldnames, delimiter='\t')
             writer.writeheader()
             for row in rows: