partial progress commit:

added terminal tabulate-output
added yet non-working csv output using pandas

freqtrade/commands/arguments.py

@@ -116,10 +116,11 @@ NO_CONF_REQURIED = ["convert-data", "convert-trade-data", "download-data", "list
 
 NO_CONF_ALLOWED = ["create-userdir", "list-exchanges", "new-strategy"]
 
-ARGS_STRATEGY_UPDATER = ["strategy_list"]
+ARGS_STRATEGY_UPDATER = ["strategy_list", "strategy_path", "recursive_strategy_search"]
 
 ARGS_BACKTEST_LOOKAHEAD_BIAS_CHECKER = ARGS_BACKTEST + ["minimum_trade_amount",
-                                                        "targeted_trade_amount"]
+                                                        "targeted_trade_amount",
+                                                        "overwrite_existing_exportfilename_content"]
 
 
 # + ["target_trades", "minimum_trades",
@@ -458,13 +459,14 @@ class Arguments:
                                                           'files to the current version',
                                                      parents=[_common_parser])
         strategy_updater_cmd.set_defaults(func=start_strategy_update)
-        self._build_args(optionlist=ARGS_STRATEGY_UPDATER, parser=strategy_updater_cmd)
+        self._build_args(optionlist=ARGS_STRATEGY_UPDATER,
+                         parser=strategy_updater_cmd)
 
         # Add backtest lookahead bias checker subcommand
         backtest_lookahead_bias_checker_cmd = \
             subparsers.add_parser('backtest-lookahead-bias-checker',
                                   help="checks for potential look ahead bias",
-                                  parents=[_common_parser])
+                                  parents=[_common_parser, _strategy_parser])
         backtest_lookahead_bias_checker_cmd.set_defaults(func=start_backtest_lookahead_bias_checker)
 
         self._build_args(optionlist=ARGS_BACKTEST_LOOKAHEAD_BIAS_CHECKER,

freqtrade/commands/cli_options.py

@@ -688,5 +688,10 @@ AVAILABLE_CLI_OPTIONS = {
         type=check_int_positive,
         metavar='INT',
         default=20,
+    ),
+    "overwrite_existing_exportfilename_content": Arg(
+        '--overwrite-existing-exportfilename-content',
+        help='overwrites existing contents if existent with exportfilename given',
+        action='store_true'
     )
 }

freqtrade/commands/strategy_utils_commands.py

@@ -4,6 +4,9 @@ import time
 from pathlib import Path
 from typing import Any, Dict
 
+import pandas as pd
+from tabulate import tabulate
+
 from freqtrade.configuration import setup_utils_configuration
 from freqtrade.enums import RunMode
 from freqtrade.resolvers import StrategyResolver
@@ -76,7 +79,6 @@ def start_backtest_lookahead_bias_checker(args: Dict[str, Any]) -> None:
         config, enum_failed=False, recursive=config.get('recursive_strategy_search', False))
 
     bias_checker_instances = []
-
     filtered_strategy_objs = []
     if 'strategy_list' in args and args['strategy_list'] is not None:
         for args_strategy in args['strategy_list']:
@@ -87,28 +89,82 @@ def start_backtest_lookahead_bias_checker(args: Dict[str, Any]) -> None:
                     break
 
         for filtered_strategy_obj in filtered_strategy_objs:
-            bias_checker_instances = initialize_single_lookahead_bias_checker(
-                filtered_strategy_obj, config, args)
+            bias_checker_instances.append(
+                initialize_single_lookahead_bias_checker(filtered_strategy_obj, config, args))
     else:
         processed_locations = set()
         for strategy_obj in strategy_objs:
             if strategy_obj['location'] not in processed_locations:
                 processed_locations.add(strategy_obj['location'])
-                bias_checker_instances = initialize_single_lookahead_bias_checker(
-                    strategy_obj, config, args)
-    create_result_list(bias_checker_instances)
+                bias_checker_instances.append(
+                    initialize_single_lookahead_bias_checker(strategy_obj, config, args))
+    text_table_bias_checker_instances(bias_checker_instances)
+    export_to_csv(args, bias_checker_instances)
 
 
-def create_result_list(bias_checker_instances):
-    pass
+def text_table_bias_checker_instances(bias_checker_instances):
+    headers = ['strategy', 'has_bias',
+               'total_signals', 'biased_entry_signals', 'biased_exit_signals', 'biased_indicators']
+    data = []
+    for current_instance in bias_checker_instances:
+        data.append(
+            [current_instance.strategy_obj['name'],
+             current_instance.current_analysis.has_bias,
+             current_instance.current_analysis.total_signals,
+             current_instance.current_analysis.false_entry_signals,
+             current_instance.current_analysis.false_exit_signals,
+             ", ".join(current_instance.current_analysis.false_indicators)]
+        )
+    table = tabulate(data, headers=headers, tablefmt="orgtbl")
+    print(table)
+
+
+def export_to_csv(args, bias_checker_instances):
+    def add_or_update_row(df, row_data):
+        strategy_col_name = 'strategy'
+        if row_data[strategy_col_name] in df[strategy_col_name].values:
+            # create temporary dataframe with a single row
+            # and use that to replace the previous data in there.
+            index = (df.index[df[strategy_col_name] ==
+                              row_data[strategy_col_name]][0])
+            df.loc[index] = pd.Series(row_data, index='strategy')
+
+        else:
+            df = df.concat(row_data, ignore_index=True)
+        return df
+
+    csv_df = None
+
+    if not Path.exists(args['exportfilename']):
+        # If the file doesn't exist, create a new DataFrame from scratch
+        csv_df = pd.DataFrame(columns=['filename', 'strategy', 'has_bias',
+                                       'total_signals',
+                                       'biased_entry_signals', 'biased_exit_signals',
+                                       'biased_indicators'],
+                              index='filename')
+    else:
+        # Read CSV file into a pandas dataframe
+        csv_df = pd.read_csv(args['exportfilename'])
+
+    for inst in bias_checker_instances:
+        new_row_data = {'filename': inst.strategy_obj['location'].parts[-1],
+                        'strategy': inst.strategy_obj['name'],
+                        'has_bias': inst.current_analysis.has_bias,
+                        'total_signals': inst.current_analysis.total_signals,
+                        'biased_entry_signals': inst.current_analysis.false_entry_signals,
+                        'biased_exit_signals': inst.current_analysis.false_exit_signals,
+                        'biased_indicators': ", ".join(inst.current_analysis.false_indicators)}
+        csv_df = add_or_update_row(csv_df, new_row_data)
+    if len(bias_checker_instances) > 0:
+        print(f"saving {args['exportfilename']}")
+        csv_df.to_csv(args['exportfilename'])
 
 
 def initialize_single_lookahead_bias_checker(strategy_obj, config, args):
-    # try:
     print(f"Bias test of {Path(strategy_obj['location']).name} started.")
-    instance_backtest_lookahead_bias_checker = BacktestLookaheadBiasChecker()
     start = time.perf_counter()
-    current_instance = instance_backtest_lookahead_bias_checker.start(config, strategy_obj, args)
+    current_instance = BacktestLookaheadBiasChecker()
+    current_instance.start(config, strategy_obj, args)
     elapsed = time.perf_counter() - start
     print(f"checking look ahead bias via backtests of {Path(strategy_obj['location']).name} "
           f"took {elapsed:.1f} seconds.")

freqtrade/strategy/backtest_lookahead_bias_checker.py

@@ -2,7 +2,7 @@ import copy
 from copy import deepcopy
 from datetime import datetime, timedelta, timezone
 
-import pandas
+from pandas import DataFrame
 
 from freqtrade.configuration import TimeRange
 from freqtrade.data.history import get_timerange
@@ -10,33 +10,37 @@ from freqtrade.exchange import timeframe_to_minutes
 from freqtrade.optimize.backtesting import Backtesting
 
 
+class VarHolder:
+    timerange: TimeRange
+    data: DataFrame
+    indicators: DataFrame
+    result: DataFrame
+    compared: DataFrame
+    from_dt: datetime
+    to_dt: datetime
+    compared_dt: datetime
+
+
+class Analysis:
+    def __init__(self):
+        self.total_signals = 0
+        self.false_entry_signals = 0
+        self.false_exit_signals = 0
+        self.false_indicators = []
+        self.has_bias = False
+
+    total_signals: int
+    false_entry_signals: int
+    false_exit_signals: int
+
+    false_indicators: list
+    has_bias: bool
+
+
 class BacktestLookaheadBiasChecker:
-    class VarHolder:
-        timerange: TimeRange
-        data: pandas.DataFrame
-        indicators: pandas.DataFrame
-        result: pandas.DataFrame
-        compared: pandas.DataFrame
-        from_dt: datetime
-        to_dt: datetime
-        compared_dt: datetime
-
-    class Analysis:
-        def __init__(self):
-            self.total_signals = 0
-            self.false_entry_signals = 0
-            self.false_exit_signals = 0
-            self.false_indicators = []
-            self.has_bias = False
-
-        total_signals: int
-        false_entry_signals: int
-        false_exit_signals: int
-
-        false_indicators: list
-        has_bias: bool
 
     def __init__(self):
+        self.exportfilename = None
         self.strategy_obj = None
         self.current_analysis = None
         self.local_config = None
@@ -44,7 +48,6 @@ class BacktestLookaheadBiasChecker:
         self.entry_varHolder = None
         self.exit_varHolder = None
         self.backtesting = None
-        self.current_analysis = None
         self.minimum_trade_amount = None
         self.targeted_trade_amount = None
 
@@ -124,9 +127,12 @@ class BacktestLookaheadBiasChecker:
         prepare_data_config['timerange'] = (str(self.dt_to_timestamp(varHolder.from_dt)) + "-" +
                                             str(self.dt_to_timestamp(varHolder.to_dt)))
         prepare_data_config['pairs'] = pairs_to_load
+
         self.backtesting = Backtesting(prepare_data_config)
         self.backtesting._set_strategy(self.backtesting.strategylist[0])
         varHolder.data, varHolder.timerange = self.backtesting.load_bt_data()
+        self.backtesting.load_bt_data_detail()
+
         varHolder.indicators = self.backtesting.strategy.advise_all_indicators(varHolder.data)
         varHolder.result = self.get_result(self.backtesting, varHolder.indicators)
 
@@ -139,12 +145,14 @@ class BacktestLookaheadBiasChecker:
         # and not worry about another strategy to check after.
         self.local_config = deepcopy(config)
         self.local_config['strategy_list'] = [strategy_obj['name']]
-        self.current_analysis = BacktestLookaheadBiasChecker.Analysis()
+        self.current_analysis = Analysis()
         self.minimum_trade_amount = args['minimum_trade_amount']
         self.targeted_trade_amount = args['targeted_trade_amount']
+        self.exportfilename = args['exportfilename']
+        self.strategy_obj = strategy_obj
 
         # first make a single backtest
-        self.full_varHolder = BacktestLookaheadBiasChecker.VarHolder()
+        self.full_varHolder = VarHolder()
 
         # define datetime in human-readable format
         parsed_timerange = TimeRange.parse_timerange(config['timerange'])
@@ -182,8 +190,8 @@ class BacktestLookaheadBiasChecker:
 
             self.current_analysis.total_signals += 1
 
-            self.entry_varHolder = BacktestLookaheadBiasChecker.VarHolder()
-            self.exit_varHolder = BacktestLookaheadBiasChecker.VarHolder()
+            self.entry_varHolder = VarHolder()
+            self.exit_varHolder = VarHolder()
 
             self.entry_varHolder.from_dt = self.full_varHolder.from_dt
             self.entry_varHolder.compared_dt = result_row['open_date']