freqtrade_origin/freqtrade/optimize/lookahead_analysis_helpers.py

import logging
import time
from pathlib import Path
from typing import Any, Dict, List

import pandas as pd

from freqtrade.constants import Config
from freqtrade.exceptions import OperationalException
from freqtrade.optimize.lookahead_analysis import LookaheadAnalysis
from freqtrade.resolvers import StrategyResolver


logger = logging.getLogger(__name__)


class LookaheadAnalysisSubFunctions:

    @staticmethod
    def text_table_lookahead_analysis_instances(
            config: Dict[str, Any],
            lookahead_instances: List[LookaheadAnalysis]):
        headers = ['filename', 'strategy', 'has_bias', 'total_signals',
                   'biased_entry_signals', 'biased_exit_signals', 'biased_indicators']
        data = []
        for inst in lookahead_instances:
            if config['minimum_trade_amount'] > inst.current_analysis.total_signals:
                data.append(
                    [
                        inst.strategy_obj['location'].parts[-1],
                        inst.strategy_obj['name'],
                        "too few trades caught "
                        f"({inst.current_analysis.total_signals}/{config['minimum_trade_amount']})."
                        f"Test failed."
                    ]
                )
            elif inst.failed_bias_check:
                data.append(
                    [
                        inst.strategy_obj['location'].parts[-1],
                        inst.strategy_obj['name'],
                        'error while checking'
                    ]
                )
            else:
                data.append(
                    [
                        inst.strategy_obj['location'].parts[-1],
                        inst.strategy_obj['name'],
                        inst.current_analysis.has_bias,
                        inst.current_analysis.total_signals,
                        inst.current_analysis.false_entry_signals,
                        inst.current_analysis.false_exit_signals,
                        ", ".join(inst.current_analysis.false_indicators)
                    ]
                )
        from tabulate import tabulate
        table = tabulate(data, headers=headers, tablefmt="orgtbl")
        print(table)
        return table, headers, data

    @staticmethod
    def export_to_csv(config: Dict[str, Any], lookahead_analysis: List[LookaheadAnalysis]):
        def add_or_update_row(df, row_data):
            if (
                    (df['filename'] == row_data['filename']) &
                    (df['strategy'] == row_data['strategy'])
            ).any():
                # Update existing row
                pd_series = pd.DataFrame([row_data])
                df.loc[
                    (df['filename'] == row_data['filename']) &
                    (df['strategy'] == row_data['strategy'])
                    ] = pd_series
            else:
                # Add new row
                df = pd.concat([df, pd.DataFrame([row_data], columns=df.columns)])

            return df

        if Path(config['lookahead_analysis_exportfilename']).exists():
            # Read CSV file into a pandas dataframe
            csv_df = pd.read_csv(config['lookahead_analysis_exportfilename'])
        else:
            # Create a new empty DataFrame with the desired column names and set the index
            csv_df = pd.DataFrame(columns=[
                'filename', 'strategy', 'has_bias', 'total_signals',
                'biased_entry_signals', 'biased_exit_signals', 'biased_indicators'
            ],
                index=None)

        for inst in lookahead_analysis:
            # only update if
            if (inst.current_analysis.total_signals > config['minimum_trade_amount']
                    and inst.failed_bias_check is not True):
                new_row_data = {'filename': inst.strategy_obj['location'].parts[-1],
                                'strategy': inst.strategy_obj['name'],
                                'has_bias': inst.current_analysis.has_bias,
                                'total_signals':
                                    int(inst.current_analysis.total_signals),
                                'biased_entry_signals':
                                    int(inst.current_analysis.false_entry_signals),
                                'biased_exit_signals':
                                    int(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)

        # Fill NaN values with a default value (e.g., 0)
        csv_df['total_signals'] = csv_df['total_signals'].fillna(0)
        csv_df['biased_entry_signals'] = csv_df['biased_entry_signals'].fillna(0)
        csv_df['biased_exit_signals'] = csv_df['biased_exit_signals'].fillna(0)

        # Convert columns to integers
        csv_df['total_signals'] = csv_df['total_signals'].astype(int)
        csv_df['biased_entry_signals'] = csv_df['biased_entry_signals'].astype(int)
        csv_df['biased_exit_signals'] = csv_df['biased_exit_signals'].astype(int)

        logger.info(f"saving {config['lookahead_analysis_exportfilename']}")
        csv_df.to_csv(config['lookahead_analysis_exportfilename'], index=False)

    @staticmethod
    def calculate_config_overrides(config: Config):
        if config['targeted_trade_amount'] < config['minimum_trade_amount']:
            # this combo doesn't make any sense.
            raise OperationalException(
                "Targeted trade amount can't be smaller than minimum trade amount."
            )
        if len(config['pairs']) > config['max_open_trades']:
            logger.info('Max_open_trades were less than amount of pairs. '
                        'Set max_open_trades to amount of pairs just to avoid false positives.')
            config['max_open_trades'] = len(config['pairs'])

        min_dry_run_wallet = 1000000000
        if config['dry_run_wallet'] < min_dry_run_wallet:
            logger.info('Dry run wallet was not set to 1 billion, pushing it up there '
                        'just to avoid false positives')
            config['dry_run_wallet'] = min_dry_run_wallet

        if 'timerange' not in config:
            # setting a timerange is enforced here
            raise OperationalException(
                "Please set a timerange. "
                "Usually a few months are enough depending on your needs and strategy."
            )
        # fix stake_amount to 10k.
        # in a combination with a wallet size of 1 billion it should always be able to trade
        # no matter if they use custom_stake_amount as a small percentage of wallet size
        # or fixate custom_stake_amount to a certain value.
        logger.info('fixing stake_amount to 10k')
        config['stake_amount'] = 10000

        # enforce cache to be 'none', shift it to 'none' if not already
        # (since the default value is 'day')
        if config.get('backtest_cache') is None:
            config['backtest_cache'] = 'none'
        elif config['backtest_cache'] != 'none':
            logger.info(f"backtest_cache = "
                        f"{config['backtest_cache']} detected. "
                        f"Inside lookahead-analysis it is enforced to be 'none'. "
                        f"Changed it to 'none'")
            config['backtest_cache'] = 'none'
        return config

    @staticmethod
    def initialize_single_lookahead_analysis(config: Config, strategy_obj: Dict[str, Any]):

        logger.info(f"Bias test of {Path(strategy_obj['location']).name} started.")
        start = time.perf_counter()
        current_instance = LookaheadAnalysis(config, strategy_obj)
        current_instance.start()
        elapsed = time.perf_counter() - start
        logger.info(f"Checking look ahead bias via backtests "
                    f"of {Path(strategy_obj['location']).name} "
                    f"took {elapsed:.0f} seconds.")
        return current_instance

    @staticmethod
    def start(config: Config):
        config = LookaheadAnalysisSubFunctions.calculate_config_overrides(config)

        strategy_objs = StrategyResolver.search_all_objects(
            config, enum_failed=False, recursive=config.get('recursive_strategy_search', False))

        lookaheadAnalysis_instances = []

        # unify --strategy and --strategy_list to one list
        if not (strategy_list := config.get('strategy_list', [])):
            if config.get('strategy') is None:
                raise OperationalException(
                    "No Strategy specified. Please specify a strategy via --strategy or "
                    "--strategy_list"
                )
            strategy_list = [config['strategy']]

        # check if strategies can be properly loaded, only check them if they can be.
        for strat in strategy_list:
            for strategy_obj in strategy_objs:
                if strategy_obj['name'] == strat and strategy_obj not in strategy_list:
                    lookaheadAnalysis_instances.append(
                        LookaheadAnalysisSubFunctions.initialize_single_lookahead_analysis(
                            config, strategy_obj))
                    break

        # report the results
        if lookaheadAnalysis_instances:
            LookaheadAnalysisSubFunctions.text_table_lookahead_analysis_instances(
                config, lookaheadAnalysis_instances)
            if config.get('lookahead_analysis_exportfilename') is not None:
                LookaheadAnalysisSubFunctions.export_to_csv(config, lookaheadAnalysis_instances)
        else:
            logger.error("There were no strategies specified neither through "
                         "--strategy nor through "
                         "--strategy_list "
                         "or timeframe was not specified.")