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refactor config handling

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This commit is contained in:
Saleh Mir
2021-10-26 12:37:28 +02:00
parent e7b7d28b91
commit cbd510b4c8
3 changed files with 36 additions and 27 deletions
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33
jesse/config.py
View File

@@ -256,20 +256,26 @@ config = {
}
def set_config(c) -> None:
def set_config(conf: dict) -> None:
global config
if 'logging' in c:
config['env']['logging'] = c['logging']
# optimization mode only
if jh.is_optimizing():
# ratio
config['env']['optimization']['ratio'] = conf['ratio']
# exchange info (only one because the optimize mode supports only one trading route at the moment)
config['env']['optimization']['exchange'] = conf['exchange']
# warm_up_candles
config['env']['optimization']['warmup_candles_num'] = int(conf['warm_up_candles'])
if 'warm_up_candles' in c:
config['env']['data']['warmup_candles_num'] = int(c['warm_up_candles'])
if 'optimization' in c:
config['env']['optimization'] = c['optimization']
if 'exchanges' in c:
for key, e in c['exchanges'].items():
# backtest and live
if jh.is_backtesting() or jh.is_live():
# warm_up_candles
config['env']['data']['warmup_candles_num'] = int(conf['warm_up_candles'])
# logs
config['env']['logging'] = conf['logging']
# exchanges
for key, e in conf['exchanges'].items():
config['env']['exchanges'][e['name']] = {
'fee': float(e['fee']),
'type': 'futures',
@@ -285,8 +291,9 @@ def set_config(c) -> None:
],
}
if 'notifications' in c:
config['env']['notifications'] = c['notifications']
# live mode only
if jh.is_live():
config['env']['notifications'] = conf['notifications']
# TODO: must become a config value later when we go after multi account support?
config['env']['identifier'] = 'main'

2
jesse/modes/optimize_mode/Genetics.py
View File

@@ -117,7 +117,7 @@ class Optimizer(ABC):
w = Process(
target=get_and_add_fitness_to_the_bucket,
args=(
dna_bucket, router.formatted_routes, router.formatted_extra_routes,
dna_bucket, jh.get_config('env.optimization'), router.formatted_routes, router.formatted_extra_routes,
self.strategy_hp, dna, self.training_candles, self.testing_candles,
self.optimal_total
)

28
jesse/modes/optimize_mode/fitness.py
View File

@@ -6,23 +6,23 @@ import traceback
import os
def _formatted_inputs_for_isolated_backtest():
# TODO: make config dynamically
def _formatted_inputs_for_isolated_backtest(user_config, routes):
formatted_config = {
'starting_balance': 5_000,
'fee': 0.001,
'futures_leverage': 3,
'futures_leverage_mode': 'cross',
'exchange': 'Binance',
'settlement_currency': 'USDT',
'warm_up_candles': 100
'starting_balance': user_config['exchange']['balance'],
'fee': user_config['exchange']['fee'],
'futures_leverage': user_config['exchange']['futures_leverage'],
'futures_leverage_mode': user_config['exchange']['futures_leverage_mode'],
'exchange': routes[0]['exchange'],
'settlement_currency': jh.quote_asset(routes[0]['symbol']),
'warm_up_candles': user_config['warmup_candles_num']
}
return formatted_config
def get_fitness(
routes: list, extra_routes: list, strategy_hp, dna: str, training_candles, testing_candles, optimal_total
optimization_config: dict, routes: list, extra_routes: list, strategy_hp, dna: str, training_candles,
testing_candles, optimal_total
) -> tuple:
"""
Notice that this function is likely to be executed inside workers, hence its inputs must
@@ -32,7 +32,7 @@ def get_fitness(
# run backtest simulation
training_data_metrics = isolated_backtest(
_formatted_inputs_for_isolated_backtest(),
_formatted_inputs_for_isolated_backtest(optimization_config, routes),
routes,
extra_routes,
training_candles,
@@ -108,7 +108,8 @@ def get_fitness(
def get_and_add_fitness_to_the_bucket(
dna_bucket, routes: list, extra_routes: list, strategy_hp, dna, training_candles, testing_candles, optimal_total
dna_bucket, optimization_config, routes: list, extra_routes: list, strategy_hp, dna, training_candles,
testing_candles, optimal_total
) -> None:
"""
Calculates the fitness ands adds the result into the dna_bucket (which is the object passed among workers)
@@ -117,7 +118,8 @@ def get_and_add_fitness_to_the_bucket(
# check if the DNA is already in the list
if all(dna_tuple[0] != dna for dna_tuple in dna_bucket):
fitness_score, fitness_log_training, fitness_log_testing = get_fitness(
routes, extra_routes, strategy_hp, dna, training_candles, testing_candles, optimal_total
optimization_config, routes, extra_routes, strategy_hp, dna, training_candles, testing_candles,
optimal_total
)
dna_bucket.append((dna, fitness_score, fitness_log_training, fitness_log_testing))
else: