def harmony_search(
func,
bounds: np.ndarray,
n_harmonies: int,
hm_considering_rate: float,
bandwidth: float,
pitch_adjusting_rate: float,
iters: int,
starting_xs: [np.ndarray] = [],
post_processing_func = None):
# hm == harmony memory
n_harmonies = max(n_harmonies, len(starting_xs))
seen = set()
hm = numpyize([[np.random.uniform(bounds[0][i], bounds[1][i]) for i in range(len(bounds[0]))] for _ in range(n_harmonies)])
for i in range(len(starting_xs)):
assert len(starting_xs[i]) == len(bounds[0])
harmony = np.array(starting_xs[i])
for z in range(len(bounds[0])):
harmony[z] = max(bounds[0][z], min(bounds[1][z], harmony[z]))
tpl = tuple(harmony)
if tpl not in seen:
hm[i] = harmony
seen.add(tpl)
print('evaluating initial harmonies...')
hm_evals = numpyize([func(h) for h in hm])
print('best harmony')
print(round_values(denumpyize(hm[hm_evals.argmin()]), 5), f'{hm_evals.min():.8f}')
if post_processing_func is not None:
post_processing_func(hm[hm_evals.argmin()])
print('starting search...')
worst_eval_i = hm_evals.argmax()
for itr in range(iters):
new_harmony = np.zeros(len(bounds[0]))
for note_i in range(len(bounds[0])):
if np.random.random() < hm_considering_rate:
new_note = hm[np.random.randint(0, len(hm))][note_i]
if np.random.random() < pitch_adjusting_rate:
new_note = new_note + bandwidth * (np.random.random() - 0.5) * abs(bounds[0][note_i] - bounds[1][note_i])
new_note = max(bounds[0][note_i], min(bounds[1][note_i], new_note))
else:
new_note = np.random.uniform(bounds[0][note_i], bounds[1][note_i])
new_harmony[note_i] = new_note
h_eval = func(new_harmony)
if h_eval < hm_evals[worst_eval_i]:
hm[worst_eval_i] = new_harmony
hm_evals[worst_eval_i] = h_eval
worst_eval_i = hm_evals.argmax()
print('improved harmony')
print(round_values(denumpyize(new_harmony), 5), f'{h_eval:.8f}')
print('best harmony')
print(round_values(denumpyize(hm[hm_evals.argmin()]), 5), f'{hm_evals.min():.8f}')
print('iteration', itr, 'of', iters)
if post_processing_func is not None:
post_processing_func(hm[hm_evals.argmin()])
return hm[hm_evals.argmin()]
def process(self, result):
score, analysis, config = result
score = -score
best_score = self.all_backtest_analyses[0][0] if self.all_backtest_analyses else 9e9
analysis['score'] = score
idx = bisect([e[0] for e in self.all_backtest_analyses], score)
self.all_backtest_analyses.insert(idx, (score, analysis))
to_dump = denumpyize({**analysis, **pack_config(config)})
f"{len(self.all_backtest_analyses): <5}"
table = PrettyTable()
table.field_names = ['adg', 'bkr_dist', 'eqbal_ratio', 'shrp', 'hrs_no_fills',
'hrs_no_fills_ss', 'mean_hrs_btwn_fills', 'n_slices', 'score']
for elm in self.all_backtest_analyses[:20] + [(score, analysis)]:
row = [round_dynamic(e, 6)
for e in [elm[1]['average_daily_gain'],
elm[1]['closest_bkr'],
elm[1]['lowest_eqbal_ratio'],
elm[1]['sharpe_ratio'],
elm[1]['max_hrs_no_fills'],
elm[1]['max_hrs_no_fills_same_side'],
elm[1]['mean_hrs_between_fills'],
elm[1]['completed_slices'],
elm[1]['score']]]
table.add_row(row)
output = table.get_string(border=True, padding_width=1)
print(f'\n\n{len(self.all_backtest_analyses)}')
print(output)
with open(config['optimize_dirpath'] + 'results.txt', 'a') as f:
f.write(json.dumps(to_dump) + '\n')
if score < best_score:
dump_live_config(to_dump, config['optimize_dirpath'] + 'current_best.json')
return score
def backtest_single_wrap(config_: dict):
config = config_.copy()
exchange_name = config['exchange'] + ('_spot' if config['market_type'] == 'spot' else '')
cache_filepath = f"backtests/{exchange_name}/{config['symbol']}/caches/"
ticks_filepath = cache_filepath + f"{config['start_date']}_{config['end_date']}_ticks_cache.npy"
mss = json.load(open(cache_filepath + 'market_specific_settings.json'))
ticks = np.load(ticks_filepath)
config.update(mss)
try:
fills, stats = backtest(config, ticks)
fdf, sdf, analysis = analyze_fills(fills, stats, config)
pa_closeness_long = analysis['pa_closeness_mean_long']
pa_closeness_shrt = analysis['pa_closeness_mean_shrt']
adg = analysis['average_daily_gain']
print(f"backtested {config['symbol']: <12} pa closeness long {pa_closeness_long:.6f} "
f"pa closeness shrt {pa_closeness_shrt:.6f} adg {adg:.6f}")
except Exception as e:
print(f'error with {config["symbol"]} {e}')
print('config')
traceback.print_exc()
adg = 0.0
pa_closeness_long = pa_closeness_shrt = 100.0
with open(make_get_filepath('tmp/harmony_search_errors.txt'), 'a') as f:
f.write(json.dumps([time(), 'error', str(e), denumpyize(config)]) + '\n')
return (pa_closeness_long, pa_closeness_shrt, adg)
async def main() -> None:
parser = argparse.ArgumentParser(prog='passivbot',
description='run passivbot')
parser.add_argument('user',
type=str,
help='user/account_name defined in api-keys.json')
parser.add_argument('symbol', type=str, help='symbol to trade')
parser.add_argument('live_config_path',
type=str,
help='live config to use')
parser.add_argument(
'-m',
'--market_type',
type=str,
required=False,
dest='market_type',
default=None,
help=
'specify whether spot or futures (default), overriding value from backtest config'
)
parser.add_argument('-gs',
'--graceful_stop',
action='store_true',
help='if true, disable long and short')
parser.add_argument(
"-lw",
"--long_wallet_exposure_limit",
"--long-wallet-exposure-limit",
type=float,
required=False,
dest="long_wallet_exposure_limit",
default=None,
help=
"specify long wallet exposure limit, overriding value from live config",
)
parser.add_argument(
"-sw",
"--short_wallet_exposure_limit",
"--short-wallet-exposure-limit",
type=float,
required=False,
dest="short_wallet_exposure_limit",
default=None,
help=
"specify short wallet exposure limit, overriding value from live config",
)
parser.add_argument(
"-sm",
"--short_mode",
"--short-mode",
type=str,
required=False,
dest="short_mode",
default=None,
help=
"specify one of following short modes: [n (normal), m (manual), gs (graceful_stop), p (panic), t (tp_only)]"
)
parser.add_argument(
"-lm",
"--long_mode",
"--long-mode",
type=str,
required=False,
dest="long_mode",
default=None,
help=
"specify one of following long modes: [n (normal), m (manual), gs (graceful_stop), p (panic), t (tp_only)]"
)
parser.add_argument('-ab',
'--assigned_balance',
type=float,
required=False,
dest='assigned_balance',
default=None,
help='add assigned_balance to live config')
args = parser.parse_args()
try:
accounts = json.load(open('api-keys.json'))
except Exception as e:
print(e, 'failed to load api-keys.json file')
return
try:
account = accounts[args.user]
except Exception as e:
print('unrecognized account name', args.user, e)
return
try:
config = load_live_config(args.live_config_path)
except Exception as e:
print(e, 'failed to load config', args.live_config_path)
return
config['user'] = args.user
config['exchange'] = account['exchange']
config['symbol'] = args.symbol
config['live_config_path'] = args.live_config_path
config[
'market_type'] = args.market_type if args.market_type is not None else 'futures'
if args.assigned_balance is not None:
print(f'\nassigned balance set to {args.assigned_balance}\n')
config['assigned_balance'] = args.assigned_balance
if args.long_mode is not None:
if args.long_mode in ['gs', 'graceful_stop', 'graceful-stop']:
print(
'\n\nlong graceful stop enabled; will not make new entries once existing positions are closed\n'
)
config['long']['enabled'] = config['do_long'] = False
elif args.long_mode in ['m', 'manual']:
print(
'\n\nlong manual mode enabled; will neither cancel nor create long orders'
)
config['long_mode'] = 'manual'
elif args.long_mode in ['n', 'normal']:
print('\n\nlong normal mode')
config['long']['enabled'] = config['do_long'] = True
elif args.long_mode in ['p', 'panic']:
print('\nlong panic mode enabled')
config['long_mode'] = 'panic'
config['long']['enabled'] = config['do_long'] = False
elif args.long_mode.lower() in ['t', 'tp_only', 'tp-only']:
print('\nlong tp only mode enabled')
config['long_mode'] = 'tp_only'
if args.short_mode is not None:
if args.short_mode in ['gs', 'graceful_stop', 'graceful-stop']:
print(
'\n\nshrt graceful stop enabled; will not make new entries once existing positions are closed\n'
)
config['shrt']['enabled'] = config['do_shrt'] = False
elif args.short_mode in ['m', 'manual']:
print(
'\n\nshrt manual mode enabled; will neither cancel nor create shrt orders'
)
config['shrt_mode'] = 'manual'
elif args.short_mode in ['n', 'normal']:
print('\n\nshrt normal mode')
config['shrt']['enabled'] = config['do_shrt'] = True
elif args.short_mode in ['p', 'panic']:
print('\nshort panic mode enabled')
config['shrt_mode'] = 'panic'
config['shrt']['enabled'] = config['do_shrt'] = False
elif args.short_mode.lower() in ['t', 'tp_only', 'tp-only']:
print('\nshort tp only mode enabled')
config['shrt_mode'] = 'tp_only'
if args.graceful_stop:
print(
'\n\ngraceful stop enabled for both long and short; will not make new entries once existing positions are closed\n'
)
config['long']['enabled'] = config['do_long'] = False
config['shrt']['enabled'] = config['do_shrt'] = False
if args.long_wallet_exposure_limit is not None:
print(
f"overriding long wallet exposure limit ({config['long']['pbr_limit']}) "
f"with new value: {args.long_wallet_exposure_limit}")
config["long"]["pbr_limit"] = args.long_wallet_exposure_limit
if args.short_wallet_exposure_limit is not None:
print(
f"overriding short wallet exposure limit ({config['shrt']['pbr_limit']}) "
f"with new value: {args.short_wallet_exposure_limit}")
config["shrt"]["pbr_limit"] = args.short_wallet_exposure_limit
if 'spot' in config['market_type']:
config = spotify_config(config)
if account['exchange'] == 'binance':
if 'spot' in config['market_type']:
from procedures import create_binance_bot_spot
bot = await create_binance_bot_spot(config)
else:
from procedures import create_binance_bot
bot = await create_binance_bot(config)
elif account['exchange'] == 'bybit':
from procedures import create_bybit_bot
bot = await create_bybit_bot(config)
else:
raise Exception('unknown exchange', account['exchange'])
print('using config')
pprint.pprint(denumpyize(config))
signal.signal(signal.SIGINT, bot.stop)
signal.signal(signal.SIGTERM, bot.stop)
await start_bot(bot)
await bot.session.close()
def backtest_wrap(config_: dict, ticks_caches: dict):
"""
loads historical data from disk, runs backtest and returns relevant metrics
"""
config = {
**{
"long": deepcopy(config_["long"]),
"short": deepcopy(config_["short"])
},
**{
k: config_[k]
for k in [
"starting_balance",
"latency_simulation_ms",
"symbol",
"market_type",
"config_no",
]
},
**{k: v
for k, v in config_["market_specific_settings"].items()},
}
if config["symbol"] in ticks_caches:
ticks = ticks_caches[config["symbol"]]
else:
ticks = np.load(config_["ticks_cache_fname"])
try:
fills_long, fills_short, stats = backtest(config, ticks)
longs, shorts, sdf, analysis = analyze_fills(fills_long, fills_short,
stats, config)
pa_distance_mean_long = analysis["pa_distance_mean_long"]
pa_distance_mean_short = analysis["pa_distance_mean_short"]
PAD_std_long = analysis["pa_distance_std_long"]
PAD_std_short = analysis["pa_distance_std_short"]
adg_long = analysis["adg_long"]
adg_short = analysis["adg_short"]
adg_DGstd_ratio_long = analysis["adg_DGstd_ratio_long"]
adg_DGstd_ratio_short = analysis["adg_DGstd_ratio_short"]
"""
with open("logs/debug_harmonysearch.txt", "a") as f:
f.write(json.dumps({"config": denumpyize(config), "analysis": analysis}) + "\n")
"""
logging.debug(
f"backtested {config['symbol']: <12} pa distance long {pa_distance_mean_long:.6f} "
+
f"pa distance short {pa_distance_mean_short:.6f} adg long {adg_long:.6f} "
+ f"adg short {adg_short:.6f} std long {PAD_std_long:.5f} " +
f"std short {PAD_std_short:.5f}")
except Exception as e:
logging.error(f'error with {config["symbol"]} {e}')
logging.error("config")
traceback.print_exc()
adg_long = adg_short = adg_DGstd_ratio_long = adg_DGstd_ratio_short = 0.0
pa_distance_mean_long = pa_distance_mean_short = PAD_std_long = PAD_std_short = 100.0
with open(make_get_filepath("tmp/harmony_search_errors.txt"),
"a") as f:
f.write(
json.dumps([time(), "error",
str(e),
denumpyize(config)]) + "\n")
return {
"pa_distance_mean_long": pa_distance_mean_long,
"pa_distance_mean_short": pa_distance_mean_short,
"adg_DGstd_ratio_long": adg_DGstd_ratio_long,
"adg_DGstd_ratio_short": adg_DGstd_ratio_short,
"pa_distance_std_long": PAD_std_long,
"pa_distance_std_short": PAD_std_short,
"adg_long": adg_long,
"adg_short": adg_short,
}
if args.long_wallet_exposure_limit is not None:
print(
f"overriding long wallet exposure limit ({config['long']['pbr_limit']}) "
f"with new value: {args.long_wallet_exposure_limit}"
)
config["long"]["pbr_limit"] = args.long_wallet_exposure_limit
if args.short_wallet_exposure_limit is not None:
print(
f"overriding short wallet exposure limit ({config['shrt']['pbr_limit']}) "
f"with new value: {args.short_wallet_exposure_limit}"
)
config["shrt"]["pbr_limit"] = args.short_wallet_exposure_limit
if 'spot' in config['market_type']:
live_config = spotify_config(live_config)
downloader = Downloader(config)
print()
for k in (keys := ['exchange', 'spot', 'symbol', 'market_type', 'config_type', 'starting_balance', 'start_date', 'end_date',
'latency_simulation_ms']):
if k in config:
print(f"{k: <{max(map(len, keys)) + 2}} {config[k]}")
print()
data = await downloader.get_sampled_ticks()
config['n_days'] = round_((data[-1][0] - data[0][0]) / (1000 * 60 * 60 * 24), 0.1)
pprint.pprint(denumpyize(live_config))
plot_wrap(config, data)
if __name__ == '__main__':
asyncio.run(main())
async def main():
parser = argparse.ArgumentParser(
prog="Backtest", description="Backtest given passivbot config.")
parser.add_argument("live_config_path",
type=str,
help="path to live config to test")
parser = add_argparse_args(parser)
parser.add_argument(
"-lw",
"--long_wallet_exposure_limit",
"--long-wallet-exposure-limit",
type=float,
required=False,
dest="long_wallet_exposure_limit",
default=None,
help=
"specify long wallet exposure limit, overriding value from live config",
)
parser.add_argument(
"-sw",
"--short_wallet_exposure_limit",
"--short-wallet-exposure-limit",
type=float,
required=False,
dest="short_wallet_exposure_limit",
default=None,
help=
"specify short wallet exposure limit, overriding value from live config",
)
parser.add_argument(
"-le",
"--long_enabled",
"--long-enabled",
type=str,
required=False,
dest="long_enabled",
default=None,
help="specify long enabled [y/n], overriding value from live config",
)
parser.add_argument(
"-se",
"--short_enabled",
"--short-enabled",
type=str,
required=False,
dest="short_enabled",
default=None,
help="specify short enabled [y/n], overriding value from live config",
)
parser.add_argument(
"-np",
"--n_parts",
"--n-parts",
type=int,
required=False,
dest="n_parts",
default=None,
help="set n backtest slices to plot",
)
parser.add_argument(
"-oh",
"--ohlcv",
help="use 1m ohlcv instead of 1s ticks",
action="store_true",
)
args = parser.parse_args()
if args.symbol is None:
tmp_cfg = load_hjson_config(args.backtest_config_path)
symbols = (tmp_cfg["symbol"] if type(tmp_cfg["symbol"]) == list else
tmp_cfg["symbol"].split(","))
else:
symbols = args.symbol.split(",")
for symbol in symbols:
args = parser.parse_args()
args.symbol = symbol
config = await prepare_backtest_config(args)
config["n_parts"] = args.n_parts
live_config = load_live_config(args.live_config_path)
config.update(live_config)
if args.long_wallet_exposure_limit is not None:
print(
f"overriding long wallet exposure limit ({config['long']['wallet_exposure_limit']}) "
f"with new value: {args.long_wallet_exposure_limit}")
config["long"][
"wallet_exposure_limit"] = args.long_wallet_exposure_limit
if args.short_wallet_exposure_limit is not None:
print(
f"overriding short wallet exposure limit ({config['short']['wallet_exposure_limit']}) "
f"with new value: {args.short_wallet_exposure_limit}")
config["short"][
"wallet_exposure_limit"] = args.short_wallet_exposure_limit
if args.long_enabled is not None:
config["long"]["enabled"] = "y" in args.long_enabled.lower()
if args.short_enabled is not None:
config["short"]["enabled"] = "y" in args.short_enabled.lower()
if "spot" in config["market_type"]:
live_config = spotify_config(live_config)
config["ohlcv"] = args.ohlcv
print()
for k in (keys := [
"exchange",
"spot",
"symbol",
"market_type",
"passivbot_mode",
"config_type",
"starting_balance",
"start_date",
"end_date",
"latency_simulation_ms",
"base_dir",
]):
if k in config:
print(f"{k: <{max(map(len, keys)) + 2}} {config[k]}")
print()
if config["ohlcv"]:
data = load_hlc_cache(
symbol,
config["start_date"],
config["end_date"],
base_dir=config["base_dir"],
spot=config["spot"],
)
else:
downloader = Downloader(config)
data = await downloader.get_sampled_ticks()
config["n_days"] = round_(
(data[-1][0] - data[0][0]) / (1000 * 60 * 60 * 24), 0.1)
pprint.pprint(denumpyize(live_config))
plot_wrap(config, data)
def dump_plots(result: dict, fdf: pd.DataFrame, sdf: pd.DataFrame, df: pd.DataFrame):
init(autoreset=True)
plt.rcParams['figure.figsize'] = [29, 18]
pd.set_option('precision', 10)
table = PrettyTable(["Metric", "Value"])
table.align['Metric'] = 'l'
table.align['Value'] = 'l'
table.title = 'Summary'
table.add_row(['Exchange', result['exchange'] if 'exchange' in result else 'unknown'])
table.add_row(['Market type', result['market_type'] if 'market_type' in result else 'unknown'])
table.add_row(['Symbol', result['symbol'] if 'symbol' in result else 'unknown'])
table.add_row(['No. days', round_dynamic(result['result']['n_days'], 6)])
table.add_row(['Starting balance', round_dynamic(result['result']['starting_balance'], 6)])
profit_color = Fore.RED if result['result']['final_balance'] < result['result']['starting_balance'] else Fore.RESET
table.add_row(['Final balance', f"{profit_color}{round_dynamic(result['result']['final_balance'], 6)}{Fore.RESET}"])
table.add_row(['Final equity', f"{profit_color}{round_dynamic(result['result']['final_equity'], 6)}{Fore.RESET}"])
table.add_row(['Net PNL + fees', f"{profit_color}{round_dynamic(result['result']['net_pnl_plus_fees'], 6)}{Fore.RESET}"])
table.add_row(['Total gain percentage', f"{profit_color}{round_dynamic(result['result']['gain'] * 100, 4)}%{Fore.RESET}"])
table.add_row(['Average daily gain percentage', f"{profit_color}{round_dynamic((result['result']['average_daily_gain']) * 100, 3)}%{Fore.RESET}"])
table.add_row(['Adjusted daily gain', f"{profit_color}{round_dynamic(result['result']['adjusted_daily_gain'], 6)}{Fore.RESET}"])
bankruptcy_color = Fore.RED if result['result']['closest_bkr'] < 0.4 else Fore.YELLOW if result['result']['closest_bkr'] < 0.8 else Fore.RESET
table.add_row(['Closest bankruptcy percentage', f"{bankruptcy_color}{round_dynamic(result['result']['closest_bkr'] * 100, 4)}%{Fore.RESET}"])
table.add_row([' ', ' '])
table.add_row(['Profit sum', f"{profit_color}{round_dynamic(result['result']['profit_sum'], 6)}{Fore.RESET}"])
table.add_row(['Loss sum', f"{Fore.RED}{round_dynamic(result['result']['loss_sum'], 6)}{Fore.RESET}"])
table.add_row(['Fee sum', round_dynamic(result['result']['fee_sum'], 6)])
table.add_row(['Lowest equity/balance ratio', round_dynamic(result['result']['eqbal_ratio_min'], 6)])
table.add_row(['Biggest psize', round_dynamic(result['result']['biggest_psize'], 6)])
table.add_row(['Price action distance mean long', round_dynamic(result['result']['pa_closeness_mean_long'], 6)])
table.add_row(['Price action distance median long', round_dynamic(result['result']['pa_closeness_median_long'], 6)])
table.add_row(['Price action distance max long', round_dynamic(result['result']['pa_closeness_max_long'], 6)])
table.add_row(['Price action distance mean short', round_dynamic(result['result']['pa_closeness_mean_shrt'], 6)])
table.add_row(['Price action distance median short', round_dynamic(result['result']['pa_closeness_median_shrt'], 6)])
table.add_row(['Price action distance max short', round_dynamic(result['result']['pa_closeness_max_shrt'], 6)])
table.add_row(['Average n fills per day', round_dynamic(result['result']['avg_fills_per_day'], 6)])
table.add_row([' ', ' '])
table.add_row(['No. fills', round_dynamic(result['result']['n_fills'], 6)])
table.add_row(['No. entries', round_dynamic(result['result']['n_entries'], 6)])
table.add_row(['No. closes', round_dynamic(result['result']['n_closes'], 6)])
table.add_row(['No. initial entries', round_dynamic(result['result']['n_ientries'], 6)])
table.add_row(['No. reentries', round_dynamic(result['result']['n_rentries'], 6)])
table.add_row([' ', ' '])
table.add_row(['Mean hours between fills', round_dynamic(result['result']['hrs_stuck_avg_long'], 6)])
table.add_row(['Max hours no fills (same side)', round_dynamic(result['result']['hrs_stuck_max_long'], 6)])
table.add_row(['Max hours no fills', round_dynamic(result['result']['hrs_stuck_max_long'], 6)])
longs = fdf[fdf.type.str.contains('long')]
shrts = fdf[fdf.type.str.contains('shrt')]
if result['long']['enabled']:
table.add_row([' ', ' '])
table.add_row(['Long', result['long']['enabled']])
table.add_row(["No. inital entries", len(longs[longs.type.str.contains('ientry')])])
table.add_row(["No. reentries", len(longs[longs.type.str.contains('rentry')])])
table.add_row(["No. normal closes", len(longs[longs.type.str.contains('nclose')])])
table.add_row(['Mean hours stuck (long)', round_dynamic(result['result']['hrs_stuck_avg_long'], 6)])
table.add_row(['Max hours stuck (long)', round_dynamic(result['result']['hrs_stuck_max_long'], 6)])
profit_color = Fore.RED if longs.pnl.sum() < 0 else Fore.RESET
table.add_row(["PNL sum", f"{profit_color}{longs.pnl.sum()}{Fore.RESET}"])
if result['shrt']['enabled']:
table.add_row([' ', ' '])
table.add_row(['Short', result['shrt']['enabled']])
table.add_row(["No. inital entries", len(shrts[shrts.type.str.contains('ientry')])])
table.add_row(["No. reentries", len(shrts[shrts.type.str.contains('rentry')])])
table.add_row(["No. normal closes", len(shrts[shrts.type.str.contains('nclose')])])
table.add_row(['Mean hours stuck (shrt)', round_dynamic(result['result']['hrs_stuck_avg_shrt'], 6)])
table.add_row(['Max hours stuck (shrt)', round_dynamic(result['result']['hrs_stuck_max_shrt'], 6)])
profit_color = Fore.RED if shrts.pnl.sum() < 0 else Fore.RESET
table.add_row(["PNL sum", f"{profit_color}{shrts.pnl.sum()}{Fore.RESET}"])
dump_live_config(result, result['plots_dirpath'] + 'live_config.json')
json.dump(denumpyize(result), open(result['plots_dirpath'] + 'result.json', 'w'), indent=4)
print('writing backtest_result.txt...\n')
with open(f"{result['plots_dirpath']}backtest_result.txt", 'w') as f:
output = table.get_string(border=True, padding_width=1)
print(output)
f.write(re.sub('\033\\[([0-9]+)(;[0-9]+)*m', '', output))
print('\nplotting balance and equity...')
plt.clf()
sdf.balance.plot()
sdf.equity.plot(title="Balance and equity", xlabel="Time", ylabel="Balance")
plt.savefig(f"{result['plots_dirpath']}balance_and_equity_sampled.png")
plt.clf()
longs.pnl.cumsum().plot(title="PNL cumulated sum - Long", xlabel="Time", ylabel="PNL")
plt.savefig(f"{result['plots_dirpath']}pnl_cumsum_long.png")
plt.clf()
shrts.pnl.cumsum().plot(title="PNL cumulated sum - Short", xlabel="Time", ylabel="PNL")
plt.savefig(f"{result['plots_dirpath']}pnl_cumsum_shrt.png")
adg = (sdf.equity / sdf.equity.iloc[0]) ** (1 / ((sdf.timestamp - sdf.timestamp.iloc[0]) / (1000 * 60 * 60 * 24)))
plt.clf()
adg.plot(title="Average daily gain", xlabel="Time", ylabel="Average daily gain")
plt.savefig(f"{result['plots_dirpath']}adg.png")
print('plotting backtest whole and in chunks...')
n_parts = max(3, int(round_up(result['n_days'] / 14, 1.0)))
for z in range(n_parts):
start_ = z / n_parts
end_ = (z + 1) / n_parts
print(f'{z} of {n_parts} {start_ * 100:.2f}% to {end_ * 100:.2f}%')
fig = plot_fills(df, fdf.iloc[int(len(fdf) * start_):int(len(fdf) * end_)], bkr_thr=0.1, title=f'Fills {z+1} of {n_parts}')
if fig is not None:
fig.savefig(f"{result['plots_dirpath']}backtest_{z + 1}of{n_parts}.png")
else:
print('no fills...')
fig = plot_fills(df, fdf, bkr_thr=0.1, plot_whole_df=True, title='Overview Fills')
fig.savefig(f"{result['plots_dirpath']}whole_backtest.png")
print('plotting pos sizes...')
plt.clf()
longs.psize.plot()
shrts.psize.plot(title="Position size in terms of contracts", xlabel="Time", ylabel="Position size")
plt.savefig(f"{result['plots_dirpath']}psizes_plot.png")
def dump_plots(
result: dict,
longs: pd.DataFrame,
shorts: pd.DataFrame,
sdf: pd.DataFrame,
df: pd.DataFrame,
n_parts: int = None,
):
init(autoreset=True)
plt.rcParams["figure.figsize"] = [29, 18]
try:
pd.set_option("display.precision", 10)
except Exception as e:
print("error setting pandas precision", e)
table = PrettyTable(["Metric", "Value"])
table.align["Metric"] = "l"
table.align["Value"] = "l"
table.title = "Summary"
table.add_row([
"Exchange", result["exchange"] if "exchange" in result else "unknown"
])
table.add_row([
"Market type",
result["market_type"] if "market_type" in result else "unknown"
])
table.add_row(
["Symbol", result["symbol"] if "symbol" in result else "unknown"])
table.add_row(["No. days", round_dynamic(result["result"]["n_days"], 6)])
table.add_row([
"Starting balance",
round_dynamic(result["result"]["starting_balance"], 6)
])
for side in ["long", "short"]:
if result[side]["enabled"]:
table.add_row([" ", " "])
table.add_row([side.capitalize(), result[side]["enabled"]])
adg_per_exp = result["result"][f"adg_{side}"] / result[side][
"wallet_exposure_limit"]
table.add_row([
"ADG per exposure", f"{round_dynamic(adg_per_exp * 100, 3)}%"
])
profit_color = (
Fore.RED if result["result"][f"final_balance_{side}"] <
result["result"]["starting_balance"] else Fore.RESET)
table.add_row([
"Final balance",
f"{profit_color}{round_dynamic(result['result'][f'final_balance_{side}'], 6)}{Fore.RESET}",
])
table.add_row([
"Final equity",
f"{profit_color}{round_dynamic(result['result'][f'final_equity_{side}'], 6)}{Fore.RESET}",
])
table.add_row([
"Net PNL + fees",
f"{profit_color}{round_dynamic(result['result'][f'net_pnl_plus_fees_{side}'], 6)}{Fore.RESET}",
])
table.add_row([
"Total gain",
f"{profit_color}{round_dynamic(result['result'][f'gain_{side}'] * 100, 4)}%{Fore.RESET}",
])
table.add_row([
"Average daily gain",
f"{profit_color}{round_dynamic((result['result'][f'adg_{side}']) * 100, 3)}%{Fore.RESET}",
])
gain_per_exp = result["result"][f"gain_{side}"] / result[side][
"wallet_exposure_limit"]
table.add_row([
"Gain per exposure", f"{round_dynamic(gain_per_exp * 100, 3)}%"
])
table.add_row([
"DG mean std ratio",
f"{round_dynamic(result['result'][f'adg_DGstd_ratio_{side}'], 4)}",
])
table.add_row([
f"Price action distance mean",
round_dynamic(result["result"][f"pa_distance_mean_{side}"], 6),
])
table.add_row([
f"Price action distance std",
round_dynamic(result["result"][f"pa_distance_std_{side}"], 6),
])
table.add_row([
f"Price action distance max",
round_dynamic(result["result"][f"pa_distance_max_{side}"], 6),
])
table.add_row([
"Closest bankruptcy",
f'{round_dynamic(result["result"][f"closest_bkr_{side}"] * 100, 4)}%',
])
table.add_row([
"Lowest equity/balance ratio",
f'{round_dynamic(result["result"][f"eqbal_ratio_min_{side}"], 4)}',
])
table.add_row(["No. fills", result["result"][f"n_fills_{side}"]])
table.add_row(
["No. entries", result["result"][f"n_entries_{side}"]])
table.add_row(["No. closes", result["result"][f"n_closes_{side}"]])
table.add_row([
"No. initial entries", result["result"][f"n_ientries_{side}"]
])
table.add_row(
["No. reentries", result["result"][f"n_rentries_{side}"]])
table.add_row([
"No. unstuck entries",
result["result"][f"n_unstuck_entries_{side}"]
])
table.add_row([
"No. unstuck closes",
result["result"][f"n_unstuck_closes_{side}"]
])
table.add_row([
"No. normal closes",
result["result"][f"n_normal_closes_{side}"]
])
table.add_row([
"Average n fills per day",
round_dynamic(result["result"][f"avg_fills_per_day_{side}"],
3),
])
table.add_row([
"Mean hours stuck",
round_dynamic(result["result"][f"hrs_stuck_avg_{side}"], 6),
])
table.add_row([
"Max hours stuck",
round_dynamic(result["result"][f"hrs_stuck_max_{side}"], 6),
])
profit_color = Fore.RED if result["result"][
f"pnl_sum_{side}"] < 0 else Fore.RESET
table.add_row([
"PNL sum",
f"{profit_color}{round_dynamic(result['result'][f'pnl_sum_{side}'], 4)}{Fore.RESET}",
])
table.add_row([
"Profit sum",
round_dynamic(result["result"][f"profit_sum_{side}"], 4)
])
table.add_row([
"Loss sum",
round_dynamic(result["result"][f"loss_sum_{side}"], 4)
])
table.add_row([
"Fee sum",
round_dynamic(result["result"][f"fee_sum_{side}"], 4)
])
table.add_row([
"Biggest pos size", result["result"][f"biggest_psize_{side}"]
])
table.add_row([
"Biggest pos cost",
round_dynamic(result["result"][f"biggest_psize_quote_{side}"],
4),
])
table.add_row([
"Volume quote",
round_dynamic(result["result"][f"volume_quote_{side}"], 6)
])
dump_live_config(result, result["plots_dirpath"] + "live_config.json")
json.dump(denumpyize(result),
open(result["plots_dirpath"] + "result.json", "w"),
indent=4)
print("writing backtest_result.txt...\n")
with open(f"{result['plots_dirpath']}backtest_result.txt", "w") as f:
output = table.get_string(border=True, padding_width=1)
print(output)
f.write(re.sub("\033\\[([0-9]+)(;[0-9]+)*m", "", output))
n_parts = n_parts if n_parts is not None else max(
3, int(round_up(result["n_days"] / 14, 1.0)))
for side, fdf in [("long", longs), ("short", shorts)]:
if result[side]["enabled"]:
plt.clf()
fig = plot_fills(df,
fdf,
plot_whole_df=True,
title=f"Overview Fills {side.capitalize()}")
fig.savefig(f"{result['plots_dirpath']}whole_backtest_{side}.png")
print(f"\nplotting balance and equity {side}...")
plt.clf()
sdf[f"balance_{side}"].plot()
sdf[f"equity_{side}"].plot(
title=f"Balance and equity {side.capitalize()}",
xlabel="Time",
ylabel="Balance")
plt.savefig(
f"{result['plots_dirpath']}balance_and_equity_sampled_{side}.png"
)
for z in range(n_parts):
start_ = z / n_parts
end_ = (z + 1) / n_parts
print(
f"{side} {z} of {n_parts} {start_ * 100:.2f}% to {end_ * 100:.2f}%"
)
fig = plot_fills(
df,
fdf.iloc[int(len(fdf) * start_):int(len(fdf) * end_)],
title=f"Fills {side} {z+1} of {n_parts}",
)
if fig is not None:
fig.savefig(
f"{result['plots_dirpath']}backtest_{side}{z + 1}of{n_parts}.png"
)
else:
print(f"no {side} fills...")
print(f"plotting {side} initial entry band")
spans_multiplier = 60 / ((df.index[1] - df.index[0]) / 1000)
spans = [
result[side]["ema_span_0"] * spans_multiplier,
((result[side]["ema_span_0"] * result[side]["ema_span_1"])**
0.5) * spans_multiplier,
result[side]["ema_span_1"] * spans_multiplier,
]
emas = pd.DataFrame({
str(span): df.iloc[::100].price.ewm(span=max(1.0, span / 100),
adjust=False).mean()
for span in spans
})
ema_band_lower = emas.min(axis=1)
ema_band_upper = emas.max(axis=1)
if side == "long":
ientry_band = ema_band_lower * (
1 - result[side]["initial_eprice_ema_dist"])
else:
ientry_band = ema_band_upper * (
1 + result[side]["initial_eprice_ema_dist"])
plt.clf()
df.price.iloc[::100].plot(
style="y-", title=f"{side.capitalize()} Initial Entry Band")
ientry_band.plot(style=f"{('b' if side == 'long' else 'r')}-.")
plt.savefig(
f"{result['plots_dirpath']}initial_entry_band_{side}.png")
if result[side]["auto_unstuck_wallet_exposure_threshold"] != 0.0:
print(f"plotting {side} unstucking bands...")
unstucking_band_lower = ema_band_lower * (
1 - result[side]["auto_unstuck_ema_dist"])
unstucking_band_upper = ema_band_upper * (
1 + result[side]["auto_unstuck_ema_dist"])
plt.clf()
df.price.iloc[::100].plot(
style="y-",
title=f"{side.capitalize()} Auto Unstucking Bands")
unstucking_band_lower.plot(style="b-.")
unstucking_band_upper.plot(style="r-.")
plt.savefig(
f"{result['plots_dirpath']}auto_unstuck_bands_{side}.png")
print("plotting pos sizes...")
plt.clf()
sdf[["psize_long", "psize_short"]].plot(
title="Position size in terms of contracts",
xlabel="Time",
ylabel="Position size",
)
plt.savefig(f"{result['plots_dirpath']}psizes_plot.png")
async def main() -> None:
parser = argparse.ArgumentParser(prog="passivbot",
description="run passivbot")
parser.add_argument("user",
type=str,
help="user/account_name defined in api-keys.json")
parser.add_argument("symbol", type=str, help="symbol to trade")
parser.add_argument("live_config_path",
type=str,
help="live config to use")
parser.add_argument(
"-m",
"--market_type",
type=str,
required=False,
dest="market_type",
default=None,
help=
"specify whether spot or futures (default), overriding value from backtest config",
)
parser.add_argument(
"-gs",
"--graceful_stop",
action="store_true",
help="if true, disable long and short",
)
parser.add_argument(
"-lw",
"--long_wallet_exposure_limit",
"--long-wallet-exposure-limit",
type=float,
required=False,
dest="long_wallet_exposure_limit",
default=None,
help=
"specify long wallet exposure limit, overriding value from live config",
)
parser.add_argument(
"-sw",
"--short_wallet_exposure_limit",
"--short-wallet-exposure-limit",
type=float,
required=False,
dest="short_wallet_exposure_limit",
default=None,
help=
"specify short wallet exposure limit, overriding value from live config",
)
parser.add_argument(
"-sm",
"--short_mode",
"--short-mode",
type=str,
required=False,
dest="short_mode",
default=None,
help=
"specify one of following short modes: [n (normal), m (manual), gs (graceful_stop), p (panic), t (tp_only)]",
)
parser.add_argument(
"-lm",
"--long_mode",
"--long-mode",
type=str,
required=False,
dest="long_mode",
default=None,
help=
"specify one of following long modes: [n (normal), m (manual), gs (graceful_stop), p (panic), t (tp_only)]",
)
parser.add_argument(
"-ab",
"--assigned_balance",
type=float,
required=False,
dest="assigned_balance",
default=None,
help="add assigned_balance to live config",
)
args = parser.parse_args()
try:
accounts = json.load(open("api-keys.json"))
except Exception as e:
print(e, "failed to load api-keys.json file")
return
try:
account = accounts[args.user]
except Exception as e:
print("unrecognized account name", args.user, e)
return
try:
config = load_live_config(args.live_config_path)
except Exception as e:
print(e, "failed to load config", args.live_config_path)
return
config["user"] = args.user
config["exchange"] = account["exchange"]
config["symbol"] = args.symbol
config[
"market_type"] = args.market_type if args.market_type is not None else "futures"
config["passivbot_mode"] = determine_passivbot_mode(config)
if args.assigned_balance is not None:
print(f"\nassigned balance set to {args.assigned_balance}\n")
config["assigned_balance"] = args.assigned_balance
if args.long_mode is None:
if not config["long"]["enabled"]:
config["long_mode"] = "manual"
else:
if args.long_mode in ["gs", "graceful_stop", "graceful-stop"]:
print(
"\n\nlong graceful stop enabled; will not make new entries once existing positions are closed\n"
)
config["long"]["enabled"] = config["do_long"] = False
elif args.long_mode in ["m", "manual"]:
print(
"\n\nlong manual mode enabled; will neither cancel nor create long orders"
)
config["long_mode"] = "manual"
elif args.long_mode in ["n", "normal"]:
print("\n\nlong normal mode")
config["long"]["enabled"] = config["do_long"] = True
elif args.long_mode in ["p", "panic"]:
print("\nlong panic mode enabled")
config["long_mode"] = "panic"
config["long"]["enabled"] = config["do_long"] = False
elif args.long_mode.lower() in ["t", "tp_only", "tp-only"]:
print("\nlong tp only mode enabled")
config["long_mode"] = "tp_only"
if args.short_mode is None:
if not config["short"]["enabled"]:
config["short_mode"] = "manual"
else:
if args.short_mode in ["gs", "graceful_stop", "graceful-stop"]:
print(
"\n\nshort graceful stop enabled; will not make new entries once existing positions are closed\n"
)
config["short"]["enabled"] = config["do_short"] = False
elif args.short_mode in ["m", "manual"]:
print(
"\n\nshort manual mode enabled; will neither cancel nor create short orders"
)
config["short_mode"] = "manual"
elif args.short_mode in ["n", "normal"]:
print("\n\nshort normal mode")
config["short"]["enabled"] = config["do_short"] = True
elif args.short_mode in ["p", "panic"]:
print("\nshort panic mode enabled")
config["short_mode"] = "panic"
config["short"]["enabled"] = config["do_short"] = False
elif args.short_mode.lower() in ["t", "tp_only", "tp-only"]:
print("\nshort tp only mode enabled")
config["short_mode"] = "tp_only"
if args.graceful_stop:
print(
"\n\ngraceful stop enabled for both long and short; will not make new entries once existing positions are closed\n"
)
config["long"]["enabled"] = config["do_long"] = False
config["short"]["enabled"] = config["do_short"] = False
config["long_mode"] = None
config["short_mode"] = None
if args.long_wallet_exposure_limit is not None:
print(
f"overriding long wallet exposure limit ({config['long']['wallet_exposure_limit']}) "
f"with new value: {args.long_wallet_exposure_limit}")
config["long"][
"wallet_exposure_limit"] = args.long_wallet_exposure_limit
if args.short_wallet_exposure_limit is not None:
print(
f"overriding short wallet exposure limit ({config['short']['wallet_exposure_limit']}) "
f"with new value: {args.short_wallet_exposure_limit}")
config["short"][
"wallet_exposure_limit"] = args.short_wallet_exposure_limit
if "spot" in config["market_type"]:
config = spotify_config(config)
if account["exchange"] == "binance":
if "spot" in config["market_type"]:
from procedures import create_binance_bot_spot
bot = await create_binance_bot_spot(config)
else:
from procedures import create_binance_bot
bot = await create_binance_bot(config)
elif account["exchange"] == "binance_us":
from procedures import create_binance_bot_spot
bot = await create_binance_bot_spot(config)
elif account["exchange"] == "bybit":
from procedures import create_bybit_bot
bot = await create_bybit_bot(config)
else:
raise Exception("unknown exchange", account["exchange"])
print("using config")
pprint.pprint(denumpyize(config))
signal.signal(signal.SIGINT, bot.stop)
signal.signal(signal.SIGTERM, bot.stop)
await start_bot(bot)
await bot.session.close()
