default settings to trigger low, take stop
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creslinux
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@ -101,7 +101,7 @@ class Backtesting(object):
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self.debug_vector = False # Debug vector calcs
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self.debug_timing_main_loop = False # print overall timing per pair - works in Backtest and Backslap
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self.backslap_show_trades = True # prints trades in addition to summary report
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self.backslap_show_trades = False # prints trades in addition to summary report
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self.backslap_save_trades = True # saves trades as a pretty table to backslap.txt
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self.stop_stops: int = 9999 # stop back testing any pair with this many stops, set to 999999 to not hit
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@ -414,33 +414,35 @@ class Backtesting(object):
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if debug:
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from pandas import set_option
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set_option('display.max_rows', 5000)
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set_option('display.max_columns', 10)
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set_option('display.max_columns', 20)
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pd.set_option('display.width', 1000)
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pd.set_option('max_colwidth', 40)
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pd.set_option('precision', 12)
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bslap_results_df['trade_duration'] = bslap_results_df['close_time'] - bslap_results_df['open_time']
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# if debug:
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# print(bslap_results_df[['open_time', 'close_time', 'trade_duration']])
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## Spends, Takes, Profit, Absolute Profit
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print(bslap_results_df)
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# Buy Price
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bslap_results_df['buy_sum'] = stake * bslap_results_df['open_rate']
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bslap_results_df['buy_fee'] = bslap_results_df['buy_sum'] * open_fee
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bslap_results_df['buy_spend'] = bslap_results_df['buy_sum'] + bslap_results_df['buy_fee']
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bslap_results_df['buy_vol'] = stake / bslap_results_df['open_rate'] # How many target are we buying
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bslap_results_df['buy_fee'] = stake * open_fee
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bslap_results_df['buy_spend'] = stake + bslap_results_df['buy_fee'] # How much we're spending
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# Sell price
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bslap_results_df['sell_sum'] = stake * bslap_results_df['close_rate']
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bslap_results_df['sell_fee'] = bslap_results_df['sell_sum'] * close_fee
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bslap_results_df['sell_sum'] = bslap_results_df['buy_vol'] * bslap_results_df['close_rate']
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bslap_results_df['sell_fee'] = bslap_results_df['sell_sum'] * close_fee
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bslap_results_df['sell_take'] = bslap_results_df['sell_sum'] - bslap_results_df['sell_fee']
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# profit_percent
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bslap_results_df['profit_percent'] = bslap_results_df['sell_take'] / bslap_results_df['buy_spend'] - 1
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bslap_results_df['profit_percent'] = (bslap_results_df['sell_take'] - bslap_results_df['buy_spend']) \
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/ bslap_results_df['buy_spend']
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# Absolute profit
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bslap_results_df['profit_abs'] = bslap_results_df['sell_take'] - bslap_results_df['buy_spend']
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if debug:
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print("\n")
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print(bslap_results_df[
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['buy_sum', 'buy_fee', 'buy_spend', 'sell_sum','sell_fee', 'sell_take', 'profit_percent', 'profit_abs', 'exit_type']])
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['buy_vol', 'buy_fee', 'buy_spend', 'sell_sum','sell_fee', 'sell_take', 'profit_percent', 'profit_abs', 'exit_type']])
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return bslap_results_df
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@ -458,6 +460,8 @@ class Backtesting(object):
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stop_stops i
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"""
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debug = self.debug
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# Timers, to be called if in debug
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def s():
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st = timeit.default_timer()
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@ -486,7 +490,8 @@ class Backtesting(object):
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if stop_stops_count >= stop_stops: # if maximum number of stops allowed in a pair is hit, exit loop
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t_open_ind = -1 # -1 ends the loop
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print("Max stop limit ", stop_stops, "reached. Moving to next pair")
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if debug:
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print("Max stop limit ", stop_stops, "reached. Moving to next pair")
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return t_open_ind
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@ -1026,6 +1031,8 @@ class Backtesting(object):
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timerange = Arguments.parse_timerange(None if self.config.get(
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'timerange') is None else str(self.config.get('timerange')))
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ld_files = self.s()
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data = optimize.load_data(
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self.config['datadir'],
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pairs=pairs,
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@ -1046,6 +1053,8 @@ class Backtesting(object):
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max_open_trades = 0
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preprocessed = self.tickerdata_to_dataframe(data)
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t_t = self.f(ld_files)
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print("Load from json to file to df in mem took", t_t)
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# Print timeframe
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min_date, max_date = self.get_timeframe(preprocessed)
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@ -1110,18 +1119,16 @@ class Backtesting(object):
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results
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)
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)
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## TODO. Catch open trades for this report.
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# logger.info(
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# '\n=============================================== '
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# 'LEFT OPEN TRADES REPORT'
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# ' ===============================================\n'
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# '%s',
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# self._generate_text_table(
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# data,
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# results.loc[results.open_at_end]
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# )
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# )
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logger.info(
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'\n=============================================== '
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'LEFT OPEN TRADES REPORT'
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' ===============================================\n'
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'%s',
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self._generate_text_table(
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data,
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results.loc[results.open_at_end]
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)
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)
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def setup_configuration(args: Namespace) -> Dict[str, Any]:
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