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Added Show trades option

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If true, prints trades ordered by date after summary.
Useful for spotting trends.
This commit is contained in:
creslinux 2018-07-16 17:06:06 +00:00
parent 99d16e82c0
commit ec1960530b
1 changed files with 19 additions and 6 deletions
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25
freqtrade/optimize/backtesting.py
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@ -94,12 +94,14 @@ class Backtesting(object):
self.np_sto: int = self.np_close # stops_triggered_on - Should be low, FT uses close self.np_sto: int = self.np_close # stops_triggered_on - Should be low, FT uses close
self.np_sco: int = self.np_close # stops_calculated_on - Should be stop, FT uses close self.np_sco: int = self.np_close # stops_calculated_on - Should be stop, FT uses close
self.use_backslap = True # Enable backslap - if false Orginal code is executed. self.use_backslap = True # Enable backslap - if false Orginal code is executed.
self.debug = False # Main debug enable, very print heavy, enable 2 loops recommended self.debug = False # Main debug enable, very print heavy, enable 2 loops recommended
self.debug_timing = False # Stages within Backslap self.debug_timing = False # Stages within Backslap
self.debug_2loops = False # Limit each pair to two loops, useful when debugging self.debug_2loops = False # Limit each pair to two loops, useful when debugging
self.debug_vector = True # Debug vector calcs self.debug_vector = False # Debug vector calcs
self.debug_timing_main_loop = True # print overall timing per pair - works in Backtest and Backslap self.debug_timing_main_loop = False # print overall timing per pair - works in Backtest and Backslap
self.backslap_show_trades = True #prints trades in addition to summary report, also saves to backslap.txt
@staticmethod @staticmethod
@ -1053,6 +1055,17 @@ class Backtesting(object):
results results
) )
) )
if self.backslap_show_trades:
TradesFrame = results.filter(['open_time', 'pair', 'exit_type', 'profit_percent', 'profit_abs',
'buy_spend', 'sell_take', 'trade_duration', 'close_time'], axis=1)
def to_fwf(df, fname):
content = tabulate(df.values.tolist(), list(df.columns), floatfmt=".8f", tablefmt='psql')
print(content)
open(fname, "w").write(content)
DataFrame.to_fwf = to_fwf(TradesFrame, "backslap.txt")
else: else:
logger.info( logger.info(
'\n================================================= ' '\n================================================= '