Merge branch 'freqtrade:develop' into develop

This commit is contained in:
lolong
2022-10-23 10:09:08 +02:00
committed by GitHub
44 changed files with 561 additions and 178 deletions

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@@ -16,6 +16,6 @@ if 'dev' in __version__:
from pathlib import Path
versionfile = Path('./freqtrade_commit')
if versionfile.is_file():
__version__ = f"docker-{versionfile.read_text()[:8]}"
__version__ = f"docker-{__version__}-{versionfile.read_text()[:8]}"
except Exception:
pass

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@@ -15,9 +15,9 @@ from freqtrade.commands.db_commands import start_convert_db
from freqtrade.commands.deploy_commands import (start_create_userdir, start_install_ui,
start_new_strategy)
from freqtrade.commands.hyperopt_commands import start_hyperopt_list, start_hyperopt_show
from freqtrade.commands.list_commands import (start_list_exchanges, start_list_markets,
start_list_strategies, start_list_timeframes,
start_show_trades)
from freqtrade.commands.list_commands import (start_list_exchanges, start_list_freqAI_models,
start_list_markets, start_list_strategies,
start_list_timeframes, start_show_trades)
from freqtrade.commands.optimize_commands import (start_backtesting, start_backtesting_show,
start_edge, start_hyperopt)
from freqtrade.commands.pairlist_commands import start_test_pairlist

View File

@@ -41,6 +41,8 @@ ARGS_EDGE = ARGS_COMMON_OPTIMIZE + ["stoploss_range"]
ARGS_LIST_STRATEGIES = ["strategy_path", "print_one_column", "print_colorized",
"recursive_strategy_search"]
ARGS_LIST_FREQAIMODELS = ["freqaimodel_path", "print_one_column", "print_colorized"]
ARGS_LIST_HYPEROPTS = ["hyperopt_path", "print_one_column", "print_colorized"]
ARGS_BACKTEST_SHOW = ["exportfilename", "backtest_show_pair_list"]
@@ -106,8 +108,8 @@ ARGS_ANALYZE_ENTRIES_EXITS = ["exportfilename", "analysis_groups", "enter_reason
"exit_reason_list", "indicator_list"]
NO_CONF_REQURIED = ["convert-data", "convert-trade-data", "download-data", "list-timeframes",
"list-markets", "list-pairs", "list-strategies", "list-data",
"hyperopt-list", "hyperopt-show", "backtest-filter",
"list-markets", "list-pairs", "list-strategies", "list-freqaimodels",
"list-data", "hyperopt-list", "hyperopt-show", "backtest-filter",
"plot-dataframe", "plot-profit", "show-trades", "trades-to-ohlcv"]
NO_CONF_ALLOWED = ["create-userdir", "list-exchanges", "new-strategy"]
@@ -192,10 +194,11 @@ class Arguments:
start_create_userdir, start_download_data, start_edge,
start_hyperopt, start_hyperopt_list, start_hyperopt_show,
start_install_ui, start_list_data, start_list_exchanges,
start_list_markets, start_list_strategies,
start_list_timeframes, start_new_config, start_new_strategy,
start_plot_dataframe, start_plot_profit, start_show_trades,
start_test_pairlist, start_trading, start_webserver)
start_list_freqAI_models, start_list_markets,
start_list_strategies, start_list_timeframes,
start_new_config, start_new_strategy, start_plot_dataframe,
start_plot_profit, start_show_trades, start_test_pairlist,
start_trading, start_webserver)
subparsers = self.parser.add_subparsers(dest='command',
# Use custom message when no subhandler is added
@@ -362,6 +365,15 @@ class Arguments:
list_strategies_cmd.set_defaults(func=start_list_strategies)
self._build_args(optionlist=ARGS_LIST_STRATEGIES, parser=list_strategies_cmd)
# Add list-freqAI Models subcommand
list_freqaimodels_cmd = subparsers.add_parser(
'list-freqaimodels',
help='Print available freqAI models.',
parents=[_common_parser],
)
list_freqaimodels_cmd.set_defaults(func=start_list_freqAI_models)
self._build_args(optionlist=ARGS_LIST_FREQAIMODELS, parser=list_freqaimodels_cmd)
# Add list-timeframes subcommand
list_timeframes_cmd = subparsers.add_parser(
'list-timeframes',

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@@ -90,6 +90,21 @@ def start_list_strategies(args: Dict[str, Any]) -> None:
_print_objs_tabular(strategy_objs, config.get('print_colorized', False))
def start_list_freqAI_models(args: Dict[str, Any]) -> None:
"""
Print files with FreqAI models custom classes available in the directory
"""
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
from freqtrade.resolvers.freqaimodel_resolver import FreqaiModelResolver
model_objs = FreqaiModelResolver.search_all_objects(config, not args['print_one_column'])
# Sort alphabetically
model_objs = sorted(model_objs, key=lambda x: x['name'])
if args['print_one_column']:
print('\n'.join([s['name'] for s in model_objs]))
else:
_print_objs_tabular(model_objs, config.get('print_colorized', False))
def start_list_timeframes(args: Dict[str, Any]) -> None:
"""
Print timeframes available on Exchange

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@@ -410,11 +410,13 @@ class Exchange:
else:
return DataFrame()
def get_contract_size(self, pair: str) -> float:
def get_contract_size(self, pair: str) -> Optional[float]:
if self.trading_mode == TradingMode.FUTURES:
market = self.markets[pair]
market = self.markets.get(pair, {})
contract_size: float = 1.0
if market['contractSize'] is not None:
if not market:
return None
if market.get('contractSize') is not None:
# ccxt has contractSize in markets as string
contract_size = float(market['contractSize'])
return contract_size
@@ -1934,6 +1936,7 @@ class Exchange:
candle_limit = self.ohlcv_candle_limit(timeframe, self._config['candle_type_def'])
# Age out old candles
ohlcv_df = ohlcv_df.tail(candle_limit + self._startup_candle_count)
ohlcv_df = ohlcv_df.reset_index(drop=True)
self._klines[(pair, timeframe, c_type)] = ohlcv_df
else:
self._klines[(pair, timeframe, c_type)] = ohlcv_df

View File

@@ -51,7 +51,7 @@ class BaseClassifierModel(IFreqaiModel):
f"{end_date} --------------------")
# split data into train/test data.
data_dictionary = dk.make_train_test_datasets(features_filtered, labels_filtered)
if not self.freqai_info.get("fit_live_predictions", 0) or not self.live:
if not self.freqai_info.get("fit_live_predictions_candles", 0) or not self.live:
dk.fit_labels()
# normalize all data based on train_dataset only
data_dictionary = dk.normalize_data(data_dictionary)

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@@ -50,7 +50,7 @@ class BaseRegressionModel(IFreqaiModel):
f"{end_date} --------------------")
# split data into train/test data.
data_dictionary = dk.make_train_test_datasets(features_filtered, labels_filtered)
if not self.freqai_info.get("fit_live_predictions", 0) or not self.live:
if not self.freqai_info.get("fit_live_predictions_candles", 0) or not self.live:
dk.fit_labels()
# normalize all data based on train_dataset only
data_dictionary = dk.normalize_data(data_dictionary)

View File

@@ -47,7 +47,7 @@ class BaseTensorFlowModel(IFreqaiModel):
f"{end_date} --------------------")
# split data into train/test data.
data_dictionary = dk.make_train_test_datasets(features_filtered, labels_filtered)
if not self.freqai_info.get("fit_live_predictions", 0) or not self.live:
if not self.freqai_info.get("fit_live_predictions_candles", 0) or not self.live:
dk.fit_labels()
# normalize all data based on train_dataset only
data_dictionary = dk.normalize_data(data_dictionary)

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@@ -971,6 +971,9 @@ class FreqaiDataKitchen:
append_df[f"{label}_mean"] = self.data["labels_mean"][label]
append_df[f"{label}_std"] = self.data["labels_std"][label]
for extra_col in self.data["extra_returns_per_train"]:
append_df["{extra_col}"] = self.data["extra_returns_per_train"][extra_col]
append_df["do_predict"] = do_predict
if self.freqai_config["feature_parameters"].get("DI_threshold", 0) > 0:
append_df["DI_values"] = self.DI_values

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@@ -1,4 +1,5 @@
import logging
import sys
from pathlib import Path
from typing import Any, Dict
@@ -48,6 +49,7 @@ class CatboostClassifier(BaseClassifierModel):
init_model = self.get_init_model(dk.pair)
cbr.fit(X=train_data, eval_set=test_data, init_model=init_model)
cbr.fit(X=train_data, eval_set=test_data, init_model=init_model,
log_cout=sys.stdout, log_cerr=sys.stderr)
return cbr

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@@ -1,4 +1,5 @@
import logging
import sys
from pathlib import Path
from typing import Any, Dict
@@ -47,6 +48,7 @@ class CatboostRegressor(BaseRegressionModel):
**self.model_training_parameters,
)
model.fit(X=train_data, eval_set=test_data, init_model=init_model)
model.fit(X=train_data, eval_set=test_data, init_model=init_model,
log_cout=sys.stdout, log_cerr=sys.stderr)
return model

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@@ -1,4 +1,5 @@
import logging
import sys
from pathlib import Path
from typing import Any, Dict
@@ -58,8 +59,10 @@ class CatboostRegressorMultiTarget(BaseRegressionModel):
fit_params = []
for i in range(len(eval_sets)):
fit_params.append(
{'eval_set': eval_sets[i], 'init_model': init_models[i]})
fit_params.append({
'eval_set': eval_sets[i], 'init_model': init_models[i],
'log_cout': sys.stdout, 'log_cerr': sys.stderr,
})
model = FreqaiMultiOutputRegressor(estimator=cbr)
thread_training = self.freqai_info.get('multitarget_parallel_training', False)

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@@ -1471,12 +1471,13 @@ class FreqtradeBot(LoggingMixin):
)
return cancelled
def _safe_exit_amount(self, pair: str, amount: float) -> float:
def _safe_exit_amount(self, trade: Trade, pair: str, amount: float) -> float:
"""
Get sellable amount.
Should be trade.amount - but will fall back to the available amount if necessary.
This should cover cases where get_real_amount() was not able to update the amount
for whatever reason.
:param trade: Trade we're working with
:param pair: Pair we're trying to sell
:param amount: amount we expect to be available
:return: amount to sell
@@ -1495,6 +1496,7 @@ class FreqtradeBot(LoggingMixin):
return amount
elif wallet_amount > amount * 0.98:
logger.info(f"{pair} - Falling back to wallet-amount {wallet_amount} -> {amount}.")
trade.amount = wallet_amount
return wallet_amount
else:
raise DependencyException(
@@ -1553,7 +1555,7 @@ class FreqtradeBot(LoggingMixin):
# Emergency sells (default to market!)
order_type = self.strategy.order_types.get("emergency_exit", "market")
amount = self._safe_exit_amount(trade.pair, sub_trade_amt or trade.amount)
amount = self._safe_exit_amount(trade, trade.pair, sub_trade_amt or trade.amount)
time_in_force = self.strategy.order_time_in_force['exit']
if (exit_check.exit_type != ExitType.LIQUIDATION
@@ -1828,7 +1830,7 @@ class FreqtradeBot(LoggingMixin):
never in base currency.
"""
self.wallets.update()
amount_ = amount
amount_ = trade.amount
if order_obj.ft_order_side == trade.exit_side or order_obj.ft_order_side == 'stoploss':
# check against remaining amount!
amount_ = trade.amount - amount

View File

@@ -151,6 +151,8 @@ class Backtesting:
self.trading_mode: TradingMode = config.get('trading_mode', TradingMode.SPOT)
# strategies which define "can_short=True" will fail to load in Spot mode.
self._can_short = self.trading_mode != TradingMode.SPOT
self._position_stacking: bool = self.config.get('position_stacking', False)
self.enable_protections: bool = self.config.get('enable_protections', False)
self.init_backtest()
@@ -924,7 +926,7 @@ class Backtesting:
Handling of left open trades at the end of backtesting
"""
for pair in open_trades.keys():
for trade in open_trades[pair]:
for trade in list(open_trades[pair]):
if trade.open_order_id and trade.nr_of_successful_entries == 0:
# Ignore trade if entry-order did not fill yet
continue
@@ -959,9 +961,8 @@ class Backtesting:
return 'short'
return None
def run_protections(
self, enable_protections, pair: str, current_time: datetime, side: LongShort):
if enable_protections:
def run_protections(self, pair: str, current_time: datetime, side: LongShort):
if self.enable_protections:
self.protections.stop_per_pair(pair, current_time, side)
self.protections.global_stop(current_time, side)
@@ -1067,10 +1068,78 @@ class Backtesting:
return None
return row
def backtest(self, processed: Dict, # noqa: max-complexity: 13
def backtest_loop(
self, row: Tuple, pair: str, current_time: datetime, end_date: datetime,
max_open_trades: int, open_trade_count_start: int) -> int:
"""
NOTE: This method is used by Hyperopt at each iteration. Please keep it optimized.
Backtesting processing for one candle/pair.
"""
for t in list(LocalTrade.bt_trades_open_pp[pair]):
# 1. Manage currently open orders of active trades
if self.manage_open_orders(t, current_time, row):
# Close trade
open_trade_count_start -= 1
LocalTrade.remove_bt_trade(t)
self.wallets.update()
# 2. Process entries.
# without positionstacking, we can only have one open trade per pair.
# max_open_trades must be respected
# don't open on the last row
trade_dir = self.check_for_trade_entry(row)
if (
(self._position_stacking or len(LocalTrade.bt_trades_open_pp[pair]) == 0)
and self.trade_slot_available(max_open_trades, open_trade_count_start)
and current_time != end_date
and trade_dir is not None
and not PairLocks.is_pair_locked(pair, row[DATE_IDX], trade_dir)
):
trade = self._enter_trade(pair, row, trade_dir)
if trade:
# TODO: hacky workaround to avoid opening > max_open_trades
# This emulates previous behavior - not sure if this is correct
# Prevents entering if the trade-slot was freed in this candle
open_trade_count_start += 1
# logger.debug(f"{pair} - Emulate creation of new trade: {trade}.")
LocalTrade.add_bt_trade(trade)
self.wallets.update()
for trade in list(LocalTrade.bt_trades_open_pp[pair]):
# 3. Process entry orders.
order = trade.select_order(trade.entry_side, is_open=True)
if order and self._get_order_filled(order.price, row):
order.close_bt_order(current_time, trade)
trade.open_order_id = None
self.wallets.update()
# 4. Create exit orders (if any)
if not trade.open_order_id:
self._get_exit_trade_entry(trade, row) # Place exit order if necessary
# 5. Process exit orders.
order = trade.select_order(trade.exit_side, is_open=True)
if order and self._get_order_filled(order.price, row):
order.close_bt_order(current_time, trade)
trade.open_order_id = None
sub_trade = order.safe_amount_after_fee != trade.amount
if sub_trade:
order.close_bt_order(current_time, trade)
trade.recalc_trade_from_orders()
else:
trade.close_date = current_time
trade.close(order.price, show_msg=False)
# logger.debug(f"{pair} - Backtesting exit {trade}")
LocalTrade.close_bt_trade(trade)
self.wallets.update()
self.run_protections(pair, current_time, trade.trade_direction)
return open_trade_count_start
def backtest(self, processed: Dict,
start_date: datetime, end_date: datetime,
max_open_trades: int = 0, position_stacking: bool = False,
enable_protections: bool = False) -> Dict[str, Any]:
max_open_trades: int = 0) -> Dict[str, Any]:
"""
Implement backtesting functionality
@@ -1083,11 +1152,9 @@ class Backtesting:
:param start_date: backtesting timerange start datetime
:param end_date: backtesting timerange end datetime
:param max_open_trades: maximum number of concurrent trades, <= 0 means unlimited
:param position_stacking: do we allow position stacking?
:param enable_protections: Should protections be enabled?
:return: DataFrame with trades (results of backtesting)
"""
self.prepare_backtest(enable_protections)
self.prepare_backtest(self.enable_protections)
# Ensure wallets are uptodate (important for --strategy-list)
self.wallets.update()
# Use dict of lists with data for performance
@@ -1098,15 +1165,12 @@ class Backtesting:
indexes: Dict = defaultdict(int)
current_time = start_date + timedelta(minutes=self.timeframe_min)
open_trades: Dict[str, List[LocalTrade]] = defaultdict(list)
open_trade_count = 0
self.progress.init_step(BacktestState.BACKTEST, int(
(end_date - start_date) / timedelta(minutes=self.timeframe_min)))
# Loop timerange and get candle for each pair at that point in time
while current_time <= end_date:
open_trade_count_start = open_trade_count
open_trade_count_start = LocalTrade.bt_open_open_trade_count
self.check_abort()
for i, pair in enumerate(data):
row_index = indexes[pair]
@@ -1118,78 +1182,14 @@ class Backtesting:
indexes[pair] = row_index
self.dataprovider._set_dataframe_max_index(row_index)
for t in list(open_trades[pair]):
# 1. Manage currently open orders of active trades
if self.manage_open_orders(t, current_time, row):
# Close trade
open_trade_count -= 1
open_trade_count_start -= 1
open_trades[pair].remove(t)
LocalTrade.remove_bt_trade(t)
self.wallets.update()
# 2. Process entries.
# without positionstacking, we can only have one open trade per pair.
# max_open_trades must be respected
# don't open on the last row
trade_dir = self.check_for_trade_entry(row)
if (
(position_stacking or len(open_trades[pair]) == 0)
and self.trade_slot_available(max_open_trades, open_trade_count_start)
and current_time != end_date
and trade_dir is not None
and not PairLocks.is_pair_locked(pair, row[DATE_IDX], trade_dir)
):
trade = self._enter_trade(pair, row, trade_dir)
if trade:
# TODO: hacky workaround to avoid opening > max_open_trades
# This emulates previous behavior - not sure if this is correct
# Prevents entering if the trade-slot was freed in this candle
open_trade_count_start += 1
open_trade_count += 1
# logger.debug(f"{pair} - Emulate creation of new trade: {trade}.")
open_trades[pair].append(trade)
LocalTrade.add_bt_trade(trade)
self.wallets.update()
for trade in list(open_trades[pair]):
# 3. Process entry orders.
order = trade.select_order(trade.entry_side, is_open=True)
if order and self._get_order_filled(order.price, row):
order.close_bt_order(current_time, trade)
trade.open_order_id = None
self.wallets.update()
# 4. Create exit orders (if any)
if not trade.open_order_id:
self._get_exit_trade_entry(trade, row) # Place exit order if necessary
# 5. Process exit orders.
order = trade.select_order(trade.exit_side, is_open=True)
if order and self._get_order_filled(order.price, row):
order.close_bt_order(current_time, trade)
trade.open_order_id = None
sub_trade = order.safe_amount_after_fee != trade.amount
if sub_trade:
order.close_bt_order(current_time, trade)
trade.recalc_trade_from_orders()
else:
trade.close_date = current_time
trade.close(order.price, show_msg=False)
# logger.debug(f"{pair} - Backtesting exit {trade}")
open_trade_count -= 1
open_trades[pair].remove(trade)
LocalTrade.close_bt_trade(trade)
self.wallets.update()
self.run_protections(
enable_protections, pair, current_time, trade.trade_direction)
open_trade_count_start = self.backtest_loop(
row, pair, current_time, end_date, max_open_trades, open_trade_count_start)
# Move time one configured time_interval ahead.
self.progress.increment()
current_time += timedelta(minutes=self.timeframe_min)
self.handle_left_open(open_trades, data=data)
self.handle_left_open(LocalTrade.bt_trades_open_pp, data=data)
self.wallets.update()
results = trade_list_to_dataframe(LocalTrade.trades)
@@ -1245,8 +1245,6 @@ class Backtesting:
start_date=min_date,
end_date=max_date,
max_open_trades=max_open_trades,
position_stacking=self.config.get('position_stacking', False),
enable_protections=self.config.get('enable_protections', False),
)
backtest_end_time = datetime.now(timezone.utc)
results.update({

View File

@@ -122,7 +122,6 @@ class Hyperopt:
else:
logger.debug('Ignoring max_open_trades (--disable-max-market-positions was used) ...')
self.max_open_trades = 0
self.position_stacking = self.config.get('position_stacking', False)
if HyperoptTools.has_space(self.config, 'sell'):
# Make sure use_exit_signal is enabled
@@ -258,6 +257,7 @@ class Hyperopt:
logger.debug("Hyperopt has 'protection' space")
# Enable Protections if protection space is selected.
self.config['enable_protections'] = True
self.backtesting.enable_protections = True
self.protection_space = self.custom_hyperopt.protection_space()
if HyperoptTools.has_space(self.config, 'buy'):
@@ -339,8 +339,6 @@ class Hyperopt:
start_date=self.min_date,
end_date=self.max_date,
max_open_trades=self.max_open_trades,
position_stacking=self.position_stacking,
enable_protections=self.config.get('enable_protections', False),
)
backtest_end_time = datetime.now(timezone.utc)
bt_results.update({

View File

@@ -2,6 +2,7 @@
This module contains the class to persist trades into SQLite
"""
import logging
from collections import defaultdict
from datetime import datetime, timedelta, timezone
from math import isclose
from typing import Any, Dict, List, Optional
@@ -255,6 +256,9 @@ class LocalTrade():
# Trades container for backtesting
trades: List['LocalTrade'] = []
trades_open: List['LocalTrade'] = []
# Copy of trades_open - but indexed by pair
bt_trades_open_pp: Dict[str, List['LocalTrade']] = defaultdict(list)
bt_open_open_trade_count: int = 0
total_profit: float = 0
realized_profit: float = 0
@@ -538,6 +542,8 @@ class LocalTrade():
"""
LocalTrade.trades = []
LocalTrade.trades_open = []
LocalTrade.bt_trades_open_pp = defaultdict(list)
LocalTrade.bt_open_open_trade_count = 0
LocalTrade.total_profit = 0
def adjust_min_max_rates(self, current_price: float, current_price_low: float) -> None:
@@ -1067,6 +1073,8 @@ class LocalTrade():
@staticmethod
def close_bt_trade(trade):
LocalTrade.trades_open.remove(trade)
LocalTrade.bt_trades_open_pp[trade.pair].remove(trade)
LocalTrade.bt_open_open_trade_count -= 1
LocalTrade.trades.append(trade)
LocalTrade.total_profit += trade.close_profit_abs
@@ -1074,12 +1082,16 @@ class LocalTrade():
def add_bt_trade(trade):
if trade.is_open:
LocalTrade.trades_open.append(trade)
LocalTrade.bt_trades_open_pp[trade.pair].append(trade)
LocalTrade.bt_open_open_trade_count += 1
else:
LocalTrade.trades.append(trade)
@staticmethod
def remove_bt_trade(trade):
LocalTrade.trades_open.remove(trade)
LocalTrade.bt_trades_open_pp[trade.pair].remove(trade)
LocalTrade.bt_open_open_trade_count -= 1
@staticmethod
def get_open_trades() -> List[Any]:
@@ -1096,7 +1108,7 @@ class LocalTrade():
if Trade.use_db:
return Trade.query.filter(Trade.is_open.is_(True)).count()
else:
return len(LocalTrade.trades_open)
return LocalTrade.bt_open_open_trade_count
@staticmethod
def stoploss_reinitialization(desired_stoploss):
@@ -1508,3 +1520,87 @@ class Trade(_DECL_BASE, LocalTrade):
Order.status == 'closed'
).scalar()
return trading_volume
@staticmethod
def from_json(json_str: str) -> 'Trade':
"""
Create a Trade instance from a json string.
Used for debugging purposes - please keep.
:param json_str: json string to parse
:return: Trade instance
"""
import rapidjson
data = rapidjson.loads(json_str)
trade = Trade(
id=data["trade_id"],
pair=data["pair"],
base_currency=data["base_currency"],
stake_currency=data["quote_currency"],
is_open=data["is_open"],
exchange=data["exchange"],
amount=data["amount"],
amount_requested=data["amount_requested"],
stake_amount=data["stake_amount"],
strategy=data["strategy"],
enter_tag=data["enter_tag"],
timeframe=data["timeframe"],
fee_open=data["fee_open"],
fee_open_cost=data["fee_open_cost"],
fee_open_currency=data["fee_open_currency"],
fee_close=data["fee_close"],
fee_close_cost=data["fee_close_cost"],
fee_close_currency=data["fee_close_currency"],
open_date=datetime.fromtimestamp(data["open_timestamp"] // 1000, tz=timezone.utc),
open_rate=data["open_rate"],
open_rate_requested=data["open_rate_requested"],
open_trade_value=data["open_trade_value"],
close_date=(datetime.fromtimestamp(data["close_timestamp"] // 1000, tz=timezone.utc)
if data["close_timestamp"] else None),
realized_profit=data["realized_profit"],
close_rate=data["close_rate"],
close_rate_requested=data["close_rate_requested"],
close_profit=data["close_profit"],
close_profit_abs=data["close_profit_abs"],
exit_reason=data["exit_reason"],
exit_order_status=data["exit_order_status"],
stop_loss=data["stop_loss_abs"],
stop_loss_pct=data["stop_loss_ratio"],
stoploss_order_id=data["stoploss_order_id"],
stoploss_last_update=(datetime.fromtimestamp(data["stoploss_last_update"] // 1000,
tz=timezone.utc) if data["stoploss_last_update"] else None),
initial_stop_loss=data["initial_stop_loss_abs"],
initial_stop_loss_pct=data["initial_stop_loss_ratio"],
min_rate=data["min_rate"],
max_rate=data["max_rate"],
leverage=data["leverage"],
interest_rate=data["interest_rate"],
liquidation_price=data["liquidation_price"],
is_short=data["is_short"],
trading_mode=data["trading_mode"],
funding_fees=data["funding_fees"],
open_order_id=data["open_order_id"],
)
for order in data["orders"]:
order_obj = Order(
amount=order["amount"],
ft_order_side=order["ft_order_side"],
ft_pair=order["pair"],
ft_is_open=order["is_open"],
order_id=order["order_id"],
status=order["status"],
average=order["average"],
cost=order["cost"],
filled=order["filled"],
order_date=datetime.strptime(order["order_date"], DATETIME_PRINT_FORMAT),
order_filled_date=(datetime.fromtimestamp(
order["order_filled_timestamp"] // 1000, tz=timezone.utc)
if order["order_filled_timestamp"] else None),
order_type=order["order_type"],
price=order["price"],
remaining=order["remaining"],
)
trade.orders.append(order_obj)
return trade

View File

@@ -26,6 +26,7 @@ class FreqaiModelResolver(IResolver):
initial_search_path = (
Path(__file__).parent.parent.joinpath("freqai/prediction_models").resolve()
)
extra_path = "freqaimodel_path"
@staticmethod
def load_freqaimodel(config: Config) -> IFreqaiModel:
@@ -50,7 +51,6 @@ class FreqaiModelResolver(IResolver):
freqaimodel_name,
config,
kwargs={"config": config},
extra_dir=config.get("freqaimodel_path"),
)
return freqaimodel

View File

@@ -42,6 +42,8 @@ class IResolver:
object_type_str: str
user_subdir: Optional[str] = None
initial_search_path: Optional[Path]
# Optional config setting containing a path (strategy_path, freqaimodel_path)
extra_path: Optional[str] = None
@classmethod
def build_search_paths(cls, config: Config, user_subdir: Optional[str] = None,
@@ -58,6 +60,9 @@ class IResolver:
for dir in extra_dirs:
abs_paths.insert(0, Path(dir).resolve())
if cls.extra_path and (extra := config.get(cls.extra_path)):
abs_paths.insert(0, Path(extra).resolve())
return abs_paths
@classmethod

View File

@@ -30,6 +30,7 @@ class StrategyResolver(IResolver):
object_type_str = "Strategy"
user_subdir = USERPATH_STRATEGIES
initial_search_path = None
extra_path = "strategy_path"
@staticmethod
def load_strategy(config: Config = None) -> IStrategy:
@@ -268,14 +269,6 @@ class StrategyResolver(IResolver):
"or contains Python code errors."
)
@classmethod
def build_search_paths(cls, config: Config, user_subdir: Optional[str] = None,
extra_dirs: List[str] = []) -> List[Path]:
if 'strategy_path' in config and config['strategy_path'] not in extra_dirs:
extra_dirs = [config['strategy_path']] + extra_dirs
return super().build_search_paths(config, user_subdir, extra_dirs)
def warn_deprecated_setting(strategy: IStrategy, old: str, new: str, error=False):
if hasattr(strategy, old):

View File

@@ -89,6 +89,7 @@ async def api_start_backtest(bt_settings: BacktestRequest, background_tasks: Bac
lastconfig['enable_protections'] = btconfig.get('enable_protections')
lastconfig['dry_run_wallet'] = btconfig.get('dry_run_wallet')
ApiServer._bt.enable_protections = btconfig.get('enable_protections', False)
ApiServer._bt.strategylist = [strat]
ApiServer._bt.results = {}
ApiServer._bt.load_prior_backtest()

View File

@@ -1,3 +1,4 @@
import asyncio
import logging
from typing import Any, Dict
@@ -89,6 +90,8 @@ async def _process_consumer_request(
for _, message in analyzed_df.items():
response = WSAnalyzedDFMessage(data=message)
await channel.send(response.dict(exclude_none=True))
# Throttle the messages to 50/s
await asyncio.sleep(0.02)
@router.websocket("/message/ws")

View File

@@ -198,6 +198,10 @@ class ApiServer(RPCHandler):
logger.debug(f"Found message of type: {message.get('type')}")
# Broadcast it
await self._ws_channel_manager.broadcast(message)
# Limit messages per sec.
# Could cause problems with queue size if too low, and
# problems with network traffik if too high.
await asyncio.sleep(0.001)
except asyncio.CancelledError:
pass

View File

@@ -1085,9 +1085,7 @@ class IStrategy(ABC, HyperStrategyMixin):
else:
logger.warning("CustomStoploss function did not return valid stoploss")
sl_lower_long = (trade.stop_loss < (low or current_rate) and not trade.is_short)
sl_higher_short = (trade.stop_loss > (high or current_rate) and trade.is_short)
if self.trailing_stop and (sl_lower_long or sl_higher_short):
if self.trailing_stop and dir_correct:
# trailing stoploss handling
sl_offset = self.trailing_stop_positive_offset
@@ -1101,7 +1099,7 @@ class IStrategy(ABC, HyperStrategyMixin):
if self.trailing_stop_positive is not None and bound_profit > sl_offset:
stop_loss_value = self.trailing_stop_positive
logger.debug(f"{trade.pair} - Using positive stoploss: {stop_loss_value} "
f"offset: {sl_offset:.4g} profit: {current_profit:.2%}")
f"offset: {sl_offset:.4g} profit: {bound_profit:.2%}")
trade.adjust_stop_loss(bound or current_rate, stop_loss_value)