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Merge branch 'develop' into pr/mkavinkumar1/6545

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This commit is contained in:
Matthias
2022-05-26 19:51:36 +02:00
parent b5f6f919b6 682daa4e94
commit 192bc868a7
67 changed files with 9040 additions and 8305 deletions
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4
freqtrade/commands/db_commands.py
View File

@@ -19,9 +19,9 @@ def start_convert_db(args: Dict[str, Any]) -> None:
config = setup_utils_configuration(args, RunMode.UTIL_NO_EXCHANGE)
init_db(config['db_url'], False)
init_db(config['db_url'])
session_target = Trade._session
init_db(config['db_url_from'], False)
init_db(config['db_url_from'])
logger.info("Starting db migration.")
trade_count = 0

2
freqtrade/commands/list_commands.py
View File

@@ -212,7 +212,7 @@ def start_show_trades(args: Dict[str, Any]) -> None:
raise OperationalException("--db-url is required for this command.")
logger.info(f'Using DB: "{parse_db_uri_for_logging(config["db_url"])}"')
init_db(config['db_url'], clean_open_orders=False)
init_db(config['db_url'])
tfilter = []
if config.get('trade_ids'):

2
freqtrade/configuration/check_exchange.py
View File

@@ -27,7 +27,7 @@ def check_exchange(config: Dict[str, Any], check_for_bad: bool = True) -> bool:
return True
logger.info("Checking exchange...")
exchange = config.get('exchange', {}).get('name').lower()
exchange = config.get('exchange', {}).get('name', '').lower()
if not exchange:
raise OperationalException(
f'This command requires a configured exchange. You should either use '

5
freqtrade/configuration/configuration.py
View File

@@ -490,7 +490,8 @@ class Configuration:
if not pairs_file.exists():
raise OperationalException(f'No pairs file found with path "{pairs_file}".')
config['pairs'] = load_file(pairs_file)
config['pairs'].sort()
if isinstance(config['pairs'], list):
config['pairs'].sort()
return
if 'config' in self.args and self.args['config']:
@@ -501,5 +502,5 @@ class Configuration:
pairs_file = config['datadir'] / 'pairs.json'
if pairs_file.exists():
config['pairs'] = load_file(pairs_file)
if 'pairs' in config:
if 'pairs' in config and isinstance(config['pairs'], list):
config['pairs'].sort()

2
freqtrade/configuration/deprecated_settings.py
View File

@@ -113,7 +113,7 @@ def process_temporary_deprecated_settings(config: Dict[str, Any]) -> None:
process_removed_setting(config, 'experimental', 'ignore_roi_if_buy_signal',
None, 'ignore_roi_if_entry_signal')
process_removed_setting(config, 'ask_strategy', 'use_sell_signal', None, 'exit_sell_signal')
process_removed_setting(config, 'ask_strategy', 'use_sell_signal', None, 'use_exit_signal')
process_removed_setting(config, 'ask_strategy', 'sell_profit_only', None, 'exit_profit_only')
process_removed_setting(config, 'ask_strategy', 'sell_profit_offset',
None, 'exit_profit_offset')

2
freqtrade/configuration/directory_operations.py
View File

@@ -15,7 +15,7 @@ def create_datadir(config: Dict[str, Any], datadir: Optional[str] = None) -> Pat
folder = Path(datadir) if datadir else Path(f"{config['user_data_dir']}/data")
if not datadir:
# set datadir
exchange_name = config.get('exchange', {}).get('name').lower()
exchange_name = config.get('exchange', {}).get('name', '').lower()
folder = folder.joinpath(exchange_name)
if not folder.is_dir():

4
freqtrade/constants.py
View File

@@ -302,12 +302,12 @@ CONF_SCHEMA = {
'exit_fill': {
'type': 'string',
'enum': TELEGRAM_SETTING_OPTIONS,
'default': 'off'
'default': 'on'
},
'protection_trigger': {
'type': 'string',
'enum': TELEGRAM_SETTING_OPTIONS,
'default': 'off'
'default': 'on'
},
'protection_trigger_global': {
'type': 'string',

2
freqtrade/data/btanalysis.py
View File

@@ -353,7 +353,7 @@ def load_trades_from_db(db_url: str, strategy: Optional[str] = None) -> pd.DataF
Can also serve as protection to load the correct result.
:return: Dataframe containing Trades
"""
init_db(db_url, clean_open_orders=False)
init_db(db_url)
filters = []
if strategy:

8
freqtrade/data/history/history_utils.py
View File

@@ -68,7 +68,8 @@ def load_data(datadir: Path,
startup_candles: int = 0,
fail_without_data: bool = False,
data_format: str = 'json',
candle_type: CandleType = CandleType.SPOT
candle_type: CandleType = CandleType.SPOT,
user_futures_funding_rate: int = None,
) -> Dict[str, DataFrame]:
"""
Load ohlcv history data for a list of pairs.
@@ -100,6 +101,10 @@ def load_data(datadir: Path,
)
if not hist.empty:
result[pair] = hist
else:
if candle_type is CandleType.FUNDING_RATE and user_futures_funding_rate is not None:
logger.warn(f"{pair} using user specified [{user_futures_funding_rate}]")
result[pair] = DataFrame(columns=["open", "close", "high", "low", "volume"])
if fail_without_data and not result:
raise OperationalException("No data found. Terminating.")
@@ -277,6 +282,7 @@ def refresh_backtest_ohlcv_data(exchange: Exchange, pairs: List[str], timeframes
pairs_not_available = []
data_handler = get_datahandler(datadir, data_format)
candle_type = CandleType.get_default(trading_mode)
process = ''
for idx, pair in enumerate(pairs, start=1):
if pair not in exchange.markets:
pairs_not_available.append(pair)

6
freqtrade/enums/exitchecktuple.py
View File

@@ -15,3 +15,9 @@ class ExitCheckTuple:
@property
def exit_flag(self):
return self.exit_type != ExitType.NONE
def __eq__(self, other):
return self.exit_type == other.exit_type and self.exit_reason == other.exit_reason
def __repr__(self):
return f"ExitCheckTuple({self.exit_type}, {self.exit_reason})"

4
freqtrade/exchange/binance.py
View File

@@ -57,7 +57,7 @@ class Binance(Exchange):
(side == "buy" and stop_loss < float(order['info']['stopPrice']))
)
def get_tickers(self, symbols: List[str] = None, cached: bool = False) -> Dict:
def get_tickers(self, symbols: Optional[List[str]] = None, cached: bool = False) -> Dict:
tickers = super().get_tickers(symbols=symbols, cached=cached)
if self.trading_mode == TradingMode.FUTURES:
# Binance's future result has no bid/ask values.
@@ -95,7 +95,7 @@ class Binance(Exchange):
async def _async_get_historic_ohlcv(self, pair: str, timeframe: str,
since_ms: int, candle_type: CandleType,
is_new_pair: bool = False, raise_: bool = False,
until_ms: int = None
until_ms: Optional[int] = None
) -> Tuple[str, str, str, List]:
"""
Overwrite to introduce "fast new pair" functionality by detecting the pair's listing date

15935
freqtrade/exchange/binance_leverage_tiers.json
View File

File diff suppressed because it is too large Load Diff

29
freqtrade/exchange/common.py
View File

@@ -2,6 +2,7 @@ import asyncio
import logging
import time
from functools import wraps
from typing import Any, Callable, Optional, TypeVar, cast, overload
from freqtrade.exceptions import DDosProtection, RetryableOrderError, TemporaryError
from freqtrade.mixins import LoggingMixin
@@ -11,6 +12,14 @@ logger = logging.getLogger(__name__)
__logging_mixin = None
def _reset_logging_mixin():
"""
Reset global logging mixin - used in tests only.
"""
global __logging_mixin
__logging_mixin = LoggingMixin(logger)
def _get_logging_mixin():
# Logging-mixin to cache kucoin responses
# Only to be used in retrier
@@ -133,8 +142,22 @@ def retrier_async(f):
return wrapper
def retrier(_func=None, retries=API_RETRY_COUNT):
def decorator(f):
F = TypeVar('F', bound=Callable[..., Any])
# Type shenanigans
@overload
def retrier(_func: F) -> F:
...
@overload
def retrier(*, retries=API_RETRY_COUNT) -> Callable[[F], F]:
...
def retrier(_func: Optional[F] = None, *, retries=API_RETRY_COUNT):
def decorator(f: F) -> F:
@wraps(f)
def wrapper(*args, **kwargs):
count = kwargs.pop('count', retries)
@@ -155,7 +178,7 @@ def retrier(_func=None, retries=API_RETRY_COUNT):
else:
logger.warning(msg + 'Giving up.')
raise ex
return wrapper
return cast(F, wrapper)
# Support both @retrier and @retrier(retries=2) syntax
if _func is None:
return decorator

59
freqtrade/exchange/exchange.py
View File

@@ -92,8 +92,8 @@ class Exchange:
it does basic validation whether the specified exchange and pairs are valid.
:return: None
"""
self._api: ccxt.Exchange = None
self._api_async: ccxt_async.Exchange = None
self._api: ccxt.Exchange
self._api_async: ccxt_async.Exchange
self._markets: Dict = {}
self._trading_fees: Dict[str, Any] = {}
self._leverage_tiers: Dict[str, List[Dict]] = {}
@@ -291,7 +291,7 @@ class Exchange:
return self._markets
@property
def precisionMode(self) -> str:
def precisionMode(self) -> int:
"""exchange ccxt precisionMode"""
return self._api.precisionMode
@@ -322,7 +322,7 @@ class Exchange:
return int(self._ft_has.get('ohlcv_candle_limit_per_timeframe', {}).get(
timeframe, self._ft_has.get('ohlcv_candle_limit')))
def get_markets(self, base_currencies: List[str] = None, quote_currencies: List[str] = None,
def get_markets(self, base_currencies: List[str] = [], quote_currencies: List[str] = [],
spot_only: bool = False, margin_only: bool = False, futures_only: bool = False,
tradable_only: bool = True,
active_only: bool = False) -> Dict[str, Any]:
@@ -953,6 +953,12 @@ class Exchange:
order = self.check_dry_limit_order_filled(order)
return order
except KeyError as e:
from freqtrade.persistence import Order
order = Order.order_by_id(order_id)
if order:
ccxt_order = order.to_ccxt_object()
self._dry_run_open_orders[order_id] = ccxt_order
return ccxt_order
# Gracefully handle errors with dry-run orders.
raise InvalidOrderException(
f'Tried to get an invalid dry-run-order (id: {order_id}). Message: {e}') from e
@@ -1158,7 +1164,7 @@ class Exchange:
raise OperationalException(e) from e
@retrier(retries=API_FETCH_ORDER_RETRY_COUNT)
def fetch_order(self, order_id: str, pair: str, params={}) -> Dict:
def fetch_order(self, order_id: str, pair: str, params: Dict = {}) -> Dict:
if self._config['dry_run']:
return self.fetch_dry_run_order(order_id)
try:
@@ -1180,8 +1186,8 @@ class Exchange:
except ccxt.BaseError as e:
raise OperationalException(e) from e
# Assign method to fetch_stoploss_order to allow easy overriding in other classes
fetch_stoploss_order = fetch_order
def fetch_stoploss_order(self, order_id: str, pair: str, params: Dict = {}) -> Dict:
return self.fetch_order(order_id, pair, params)
def fetch_order_or_stoploss_order(self, order_id: str, pair: str,
stoploss_order: bool = False) -> Dict:
@@ -1206,7 +1212,7 @@ class Exchange:
and order.get('filled') == 0.0)
@retrier
def cancel_order(self, order_id: str, pair: str, params={}) -> Dict:
def cancel_order(self, order_id: str, pair: str, params: Dict = {}) -> Dict:
if self._config['dry_run']:
try:
order = self.fetch_dry_run_order(order_id)
@@ -1232,8 +1238,8 @@ class Exchange:
except ccxt.BaseError as e:
raise OperationalException(e) from e
# Assign method to cancel_stoploss_order to allow easy overriding in other classes
cancel_stoploss_order = cancel_order
def cancel_stoploss_order(self, order_id: str, pair: str, params: Dict = {}) -> Dict:
return self.cancel_order(order_id, pair, params)
def is_cancel_order_result_suitable(self, corder) -> bool:
if not isinstance(corder, dict):
@@ -1345,7 +1351,7 @@ class Exchange:
raise OperationalException(e) from e
@retrier
def fetch_bids_asks(self, symbols: List[str] = None, cached: bool = False) -> Dict:
def fetch_bids_asks(self, symbols: Optional[List[str]] = None, cached: bool = False) -> Dict:
"""
:param cached: Allow cached result
:return: fetch_tickers result
@@ -1373,7 +1379,7 @@ class Exchange:
raise OperationalException(e) from e
@retrier
def get_tickers(self, symbols: List[str] = None, cached: bool = False) -> Dict:
def get_tickers(self, symbols: Optional[List[str]] = None, cached: bool = False) -> Dict:
"""
:param cached: Allow cached result
:return: fetch_tickers result
@@ -1744,7 +1750,7 @@ class Exchange:
async def _async_get_historic_ohlcv(self, pair: str, timeframe: str,
since_ms: int, candle_type: CandleType,
is_new_pair: bool = False, raise_: bool = False,
until_ms: int = None
until_ms: Optional[int] = None
) -> Tuple[str, str, str, List]:
"""
Download historic ohlcv
@@ -1805,7 +1811,7 @@ class Exchange:
def refresh_latest_ohlcv(self, pair_list: ListPairsWithTimeframes, *,
since_ms: Optional[int] = None, cache: bool = True,
drop_incomplete: bool = None
drop_incomplete: Optional[bool] = None
) -> Dict[PairWithTimeframe, DataFrame]:
"""
Refresh in-memory OHLCV asynchronously and set `_klines` with the result
@@ -2445,14 +2451,35 @@ class Exchange:
)
@staticmethod
def combine_funding_and_mark(funding_rates: DataFrame, mark_rates: DataFrame) -> DataFrame:
def combine_funding_and_mark(funding_rates: DataFrame, mark_rates: DataFrame,
futures_funding_rate: Optional[int] = None) -> DataFrame:
"""
Combine funding-rates and mark-rates dataframes
:param funding_rates: Dataframe containing Funding rates (Type FUNDING_RATE)
:param mark_rates: Dataframe containing Mark rates (Type mark_ohlcv_price)
:param futures_funding_rate: Fake funding rate to use if funding_rates are not available
"""
if futures_funding_rate is None:
return mark_rates.merge(
funding_rates, on='date', how="inner", suffixes=["_mark", "_fund"])
else:
if len(funding_rates) == 0:
# No funding rate candles - full fillup with fallback variable
mark_rates['open_fund'] = futures_funding_rate
return mark_rates.rename(
columns={'open': 'open_mark',
'close': 'close_mark',
'high': 'high_mark',
'low': 'low_mark',
'volume': 'volume_mark'})
return funding_rates.merge(mark_rates, on='date', how="inner", suffixes=["_fund", "_mark"])
else:
# Fill up missing funding_rate candles with fallback value
combined = mark_rates.merge(
funding_rates, on='date', how="outer", suffixes=["_mark", "_fund"]
)
combined['open_fund'] = combined['open_fund'].fillna(futures_funding_rate)
return combined
def calculate_funding_fees(
self,

4
freqtrade/exchange/ftx.py
View File

@@ -104,7 +104,7 @@ class Ftx(Exchange):
raise OperationalException(e) from e
@retrier(retries=API_FETCH_ORDER_RETRY_COUNT)
def fetch_stoploss_order(self, order_id: str, pair: str) -> Dict:
def fetch_stoploss_order(self, order_id: str, pair: str, params: Dict = {}) -> Dict:
if self._config['dry_run']:
return self.fetch_dry_run_order(order_id)
@@ -145,7 +145,7 @@ class Ftx(Exchange):
raise OperationalException(e) from e
@retrier
def cancel_stoploss_order(self, order_id: str, pair: str) -> Dict:
def cancel_stoploss_order(self, order_id: str, pair: str, params: Dict = {}) -> Dict:
if self._config['dry_run']:
return {}
try:

4
freqtrade/exchange/gateio.py
View File

@@ -71,14 +71,14 @@ class Gateio(Exchange):
}
return trades
def fetch_stoploss_order(self, order_id: str, pair: str, params={}) -> Dict:
def fetch_stoploss_order(self, order_id: str, pair: str, params: Dict = {}) -> Dict:
return self.fetch_order(
order_id=order_id,
pair=pair,
params={'stop': True}
)
def cancel_stoploss_order(self, order_id: str, pair: str, params={}) -> Dict:
def cancel_stoploss_order(self, order_id: str, pair: str, params: Dict = {}) -> Dict:
return self.cancel_order(
order_id=order_id,
pair=pair,

2
freqtrade/exchange/kraken.py
View File

@@ -45,7 +45,7 @@ class Kraken(Exchange):
return (parent_check and
market.get('darkpool', False) is False)
def get_tickers(self, symbols: List[str] = None, cached: bool = False) -> Dict:
def get_tickers(self, symbols: Optional[List[str]] = None, cached: bool = False) -> Dict:
# Only fetch tickers for current stake currency
# Otherwise the request for kraken becomes too large.
symbols = list(self.get_markets(quote_currencies=[self._config['stake_currency']]))

30
freqtrade/freqtradebot.py
View File

@@ -68,7 +68,7 @@ class FreqtradeBot(LoggingMixin):
self.exchange = ExchangeResolver.load_exchange(self.config['exchange']['name'], self.config)
init_db(self.config.get('db_url', None), clean_open_orders=self.config['dry_run'])
init_db(self.config.get('db_url', None))
self.wallets = Wallets(self.config, self.exchange)
@@ -124,7 +124,7 @@ class FreqtradeBot(LoggingMixin):
self._schedule.every().day.at(t).do(update)
self.last_process = datetime(1970, 1, 1, tzinfo=timezone.utc)
self.strategy.bot_start()
self.strategy.ft_bot_start()
def notify_status(self, msg: str) -> None:
"""
@@ -300,7 +300,8 @@ class FreqtradeBot(LoggingMixin):
fo = self.exchange.fetch_order_or_stoploss_order(order.order_id, order.ft_pair,
order.ft_order_side == 'stoploss')
self.update_trade_state(order.trade, order.order_id, fo)
self.update_trade_state(order.trade, order.order_id, fo,
stoploss_order=(order.ft_order_side == 'stoploss'))
except ExchangeError as e:
@@ -1043,7 +1044,7 @@ class FreqtradeBot(LoggingMixin):
# Lock pair for one candle to prevent immediate rebuys
self.strategy.lock_pair(trade.pair, datetime.now(timezone.utc),
reason='Auto lock')
self._notify_exit(trade, "stoploss")
self._notify_exit(trade, "stoploss", True)
return True
if trade.open_order_id or not trade.is_open:
@@ -1130,7 +1131,7 @@ class FreqtradeBot(LoggingMixin):
"""
Check and execute trade exit
"""
should_exit: ExitCheckTuple = self.strategy.should_exit(
exits: List[ExitCheckTuple] = self.strategy.should_exit(
trade,
exit_rate,
datetime.now(timezone.utc),
@@ -1138,12 +1139,13 @@ class FreqtradeBot(LoggingMixin):
exit_=exit_,
force_stoploss=self.edge.stoploss(trade.pair) if self.edge else 0
)
if should_exit.exit_flag:
logger.info(f'Exit for {trade.pair} detected. Reason: {should_exit.exit_type}'
f'Tag: {exit_tag if exit_tag is not None else "None"}')
self.execute_trade_exit(trade, exit_rate, should_exit, exit_tag=exit_tag)
return True
for should_exit in exits:
if should_exit.exit_flag:
logger.info(f'Exit for {trade.pair} detected. Reason: {should_exit.exit_type}'
f'{f" Tag: {exit_tag}" if exit_tag is not None else ""}')
exited = self.execute_trade_exit(trade, exit_rate, should_exit, exit_tag=exit_tag)
if exited:
return True
return False
def manage_open_orders(self) -> None:
@@ -1433,7 +1435,7 @@ class FreqtradeBot(LoggingMixin):
:param trade: Trade instance
:param limit: limit rate for the sell order
:param exit_check: CheckTuple with signal and reason
:return: True if it succeeds (supported) False (not supported)
:return: True if it succeeds False
"""
trade.funding_fees = self.exchange.get_funding_fees(
pair=trade.pair,
@@ -1481,7 +1483,7 @@ class FreqtradeBot(LoggingMixin):
time_in_force=time_in_force, exit_reason=exit_reason,
sell_reason=exit_reason, # sellreason -> compatibility
current_time=datetime.now(timezone.utc)):
logger.info(f"User requested abortion of exiting {trade.pair}")
logger.info(f"User requested abortion of {trade.pair} exit.")
return False
try:
@@ -1708,7 +1710,7 @@ class FreqtradeBot(LoggingMixin):
if send_msg and not stoploss_order and not trade.open_order_id:
self._notify_exit(trade, '', True, sub_trade=sub_trade, order=order_obj)
self.handle_protections(trade.pair, trade.trade_direction)
elif send_msg and not trade.open_order_id:
elif send_msg and not trade.open_order_id and not stoploss_order:
# Enter fill
self._notify_enter(trade, order_obj, fill=True, sub_trade=sub_trade)

47
freqtrade/optimize/backtesting.py
View File

@@ -187,7 +187,7 @@ class Backtesting:
# since a "perfect" stoploss-exit is assumed anyway
# And the regular "stoploss" function would not apply to that case
self.strategy.order_types['stoploss_on_exchange'] = False
self.strategy.bot_start()
self.strategy.ft_bot_start()
def _load_protections(self, strategy: IStrategy):
if self.config.get('enable_protections', False):
@@ -275,8 +275,12 @@ class Backtesting:
if pair not in self.exchange._leverage_tiers:
unavailable_pairs.append(pair)
continue
self.futures_data[pair] = funding_rates_dict[pair].merge(
mark_rates_dict[pair], on='date', how="inner", suffixes=["_fund", "_mark"])
self.futures_data[pair] = self.exchange.combine_funding_and_mark(
funding_rates=funding_rates_dict[pair],
mark_rates=mark_rates_dict[pair],
futures_funding_rate=self.config.get('futures_funding_rate', None),
)
if unavailable_pairs:
raise OperationalException(
@@ -497,7 +501,8 @@ class Backtesting:
stake_available = self.wallets.get_available_stake_amount()
stake_amount = strategy_safe_wrapper(self.strategy.adjust_trade_position,
default_retval=None)(
trade=trade, current_time=row[DATE_IDX].to_pydatetime(), current_rate=current_rate,
trade=trade, # type: ignore[arg-type]
current_time=row[DATE_IDX].to_pydatetime(), current_rate=current_rate,
current_profit=current_profit, min_stake=min_stake,
max_stake=min(max_stake, stake_available),
current_entry_rate=current_rate, current_exit_rate=current_rate,
@@ -540,15 +545,23 @@ class Backtesting:
if check_adjust_entry:
trade = self._get_adjust_trade_entry_for_candle(trade, row)
exit_candle_time: datetime = row[DATE_IDX].to_pydatetime()
enter = row[SHORT_IDX] if trade.is_short else row[LONG_IDX]
exit_sig = row[ESHORT_IDX] if trade.is_short else row[ELONG_IDX]
exit_ = self.strategy.should_exit(
trade, row[OPEN_IDX], exit_candle_time, # type: ignore
exits = self.strategy.should_exit(
trade, row[OPEN_IDX], row[DATE_IDX].to_pydatetime(), # type: ignore
enter=enter, exit_=exit_sig,
low=row[LOW_IDX], high=row[HIGH_IDX]
)
for exit_ in exits:
t = self._get_exit_for_signal(trade, row, exit_)
if t:
return t
return None
def _get_exit_for_signal(self, trade: LocalTrade, row: Tuple,
exit_: ExitCheckTuple) -> Optional[LocalTrade]:
exit_candle_time: datetime = row[DATE_IDX].to_pydatetime()
if exit_.exit_flag:
trade.close_date = exit_candle_time
exit_reason = exit_.exit_reason
@@ -575,7 +588,8 @@ class Backtesting:
if order_type == 'limit':
close_rate = strategy_safe_wrapper(self.strategy.custom_exit_price,
default_retval=close_rate)(
pair=trade.pair, trade=trade,
pair=trade.pair,
trade=trade, # type: ignore[arg-type]
current_time=exit_candle_time,
proposed_rate=close_rate, current_profit=current_profit,
exit_tag=exit_reason)
@@ -589,7 +603,10 @@ class Backtesting:
time_in_force = self.strategy.order_time_in_force['exit']
if not strategy_safe_wrapper(self.strategy.confirm_trade_exit, default_retval=True)(
pair=trade.pair, trade=trade, order_type='limit', amount=trade.amount,
pair=trade.pair,
trade=trade, # type: ignore[arg-type]
order_type='limit',
amount=trade.amount,
rate=close_rate,
time_in_force=time_in_force,
sell_reason=exit_reason, # deprecated
@@ -694,7 +711,7 @@ class Backtesting:
return self._get_exit_trade_entry_for_candle(trade, row)
def get_valid_price_and_stake(
self, pair: str, row: Tuple, propose_rate: float, stake_amount: Optional[float],
self, pair: str, row: Tuple, propose_rate: float, stake_amount: float,
direction: LongShort, current_time: datetime, entry_tag: Optional[str],
trade: Optional[LocalTrade], order_type: str
) -> Tuple[float, float, float, float]:
@@ -768,8 +785,9 @@ class Backtesting:
order_type = self.strategy.order_types['entry']
pos_adjust = trade is not None and requested_rate is None
stake_amount_ = stake_amount or (trade.stake_amount if trade else 0.0)
propose_rate, stake_amount, leverage, min_stake_amount = self.get_valid_price_and_stake(
pair, row, row[OPEN_IDX], stake_amount, direction, current_time, entry_tag, trade,
pair, row, row[OPEN_IDX], stake_amount_, direction, current_time, entry_tag, trade,
order_type
)
@@ -939,7 +957,9 @@ class Backtesting:
Check if current analyzed order has to be canceled.
Returns True if the trade should be Deleted (initial order was canceled).
"""
timedout = self.strategy.ft_check_timed_out(trade, order, current_time)
timedout = self.strategy.ft_check_timed_out(
trade, # type: ignore[arg-type]
order, current_time)
if timedout:
if order.side == trade.entry_side:
self.timedout_entry_orders += 1
@@ -968,7 +988,8 @@ class Backtesting:
if order.side == trade.entry_side and current_time > order.order_date_utc:
requested_rate = strategy_safe_wrapper(self.strategy.adjust_entry_price,
default_retval=order.price)(
trade=trade, order=order, pair=trade.pair, current_time=current_time,
trade=trade, # type: ignore[arg-type]
order=order, pair=trade.pair, current_time=current_time,
proposed_rate=row[OPEN_IDX], current_order_rate=order.price,
entry_tag=trade.enter_tag, side=trade.trade_direction
) # default value is current order price

2
freqtrade/optimize/edge_cli.py
View File

@@ -44,7 +44,7 @@ class EdgeCli:
self.edge._timerange = TimeRange.parse_timerange(None if self.config.get(
'timerange') is None else str(self.config.get('timerange')))
self.strategy.bot_start()
self.strategy.ft_bot_start()
def start(self) -> None:
result = self.edge.calculate(self.config['exchange']['pair_whitelist'])

8
freqtrade/optimize/hyperopt.py
View File

@@ -27,8 +27,7 @@ from freqtrade.misc import deep_merge_dicts, file_dump_json, plural
from freqtrade.optimize.backtesting import Backtesting
# Import IHyperOpt and IHyperOptLoss to allow unpickling classes from these modules
from freqtrade.optimize.hyperopt_auto import HyperOptAuto
from freqtrade.optimize.hyperopt_interface import IHyperOpt # noqa: F401
from freqtrade.optimize.hyperopt_loss_interface import IHyperOptLoss # noqa: F401
from freqtrade.optimize.hyperopt_loss_interface import IHyperOptLoss
from freqtrade.optimize.hyperopt_tools import HyperoptTools, hyperopt_serializer
from freqtrade.optimize.optimize_reports import generate_strategy_stats
from freqtrade.resolvers.hyperopt_resolver import HyperOptLossResolver
@@ -62,7 +61,6 @@ class Hyperopt:
hyperopt = Hyperopt(config)
hyperopt.start()
"""
custom_hyperopt: IHyperOpt
def __init__(self, config: Dict[str, Any]) -> None:
self.buy_space: List[Dimension] = []
@@ -77,6 +75,7 @@ class Hyperopt:
self.backtesting = Backtesting(self.config)
self.pairlist = self.backtesting.pairlists.whitelist
self.custom_hyperopt: HyperOptAuto
if not self.config.get('hyperopt'):
self.custom_hyperopt = HyperOptAuto(self.config)
@@ -88,7 +87,8 @@ class Hyperopt:
self.backtesting._set_strategy(self.backtesting.strategylist[0])
self.custom_hyperopt.strategy = self.backtesting.strategy
self.custom_hyperoptloss = HyperOptLossResolver.load_hyperoptloss(self.config)
self.custom_hyperoptloss: IHyperOptLoss = HyperOptLossResolver.load_hyperoptloss(
self.config)
self.calculate_loss = self.custom_hyperoptloss.hyperopt_loss_function
time_now = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
strategy = str(self.config['strategy'])

2
freqtrade/persistence/__init__.py
View File

@@ -1,5 +1,5 @@
# flake8: noqa: F401
from freqtrade.persistence.models import clean_dry_run_db, cleanup_db, init_db
from freqtrade.persistence.models import cleanup_db, init_db
from freqtrade.persistence.pairlock_middleware import PairLocks
from freqtrade.persistence.trade_model import LocalTrade, Order, Trade

20
freqtrade/persistence/models.py
View File

@@ -21,14 +21,12 @@ logger = logging.getLogger(__name__)
_SQL_DOCS_URL = 'http://docs.sqlalchemy.org/en/latest/core/engines.html#database-urls'
def init_db(db_url: str, clean_open_orders: bool = False) -> None:
def init_db(db_url: str) -> None:
"""
Initializes this module with the given config,
registers all known command handlers
and starts polling for message updates
:param db_url: Database to use
:param clean_open_orders: Remove open orders from the database.
Useful for dry-run or if all orders have been reset on the exchange.
:return: None
"""
kwargs = {}
@@ -64,10 +62,6 @@ def init_db(db_url: str, clean_open_orders: bool = False) -> None:
_DECL_BASE.metadata.create_all(engine)
check_migrate(engine, decl_base=_DECL_BASE, previous_tables=previous_tables)
# Clean dry_run DB if the db is not in-memory
if clean_open_orders and db_url != 'sqlite://':
clean_dry_run_db()
def cleanup_db() -> None:
"""
@@ -75,15 +69,3 @@ def cleanup_db() -> None:
:return: None
"""
Trade.commit()
def clean_dry_run_db() -> None:
"""
Remove open_order_id from a Dry_run DB
:return: None
"""
for trade in Trade.query.filter(Trade.open_order_id.isnot(None)).all():
# Check we are updating only a dry_run order not a prod one
if 'dry_run' in trade.open_order_id:
trade.open_order_id = None
Trade.commit()

31
freqtrade/persistence/trade_model.py
View File

@@ -120,6 +120,25 @@ class Order(_DECL_BASE):
self.order_filled_date = datetime.now(timezone.utc)
self.order_update_date = datetime.now(timezone.utc)
def to_ccxt_object(self) -> Dict[str, Any]:
return {
'id': self.order_id,
'symbol': self.ft_pair,
'price': self.price,
'average': self.average,
'amount': self.amount,
'cost': self.cost,
'type': self.order_type,
'side': self.ft_order_side,
'filled': self.filled,
'remaining': self.remaining,
'datetime': self.order_date_utc.strftime('%Y-%m-%dT%H:%M:%S.%f'),
'timestamp': int(self.order_date_utc.timestamp() * 1000),
'status': self.status,
'fee': None,
'info': {},
}
def to_json(self, entry_side: str) -> Dict[str, Any]:
return {
'pair': self.ft_pair,
@@ -192,6 +211,14 @@ class Order(_DECL_BASE):
"""
return Order.query.filter(Order.ft_is_open.is_(True)).all()
@staticmethod
def order_by_id(order_id: str) -> Optional['Order']:
"""
Retrieve order based on order_id
:return: Order or None
"""
return Order.query.filter(Order.order_id == order_id).first()
class LocalTrade():
"""
@@ -892,8 +919,8 @@ class LocalTrade():
return o
return None
def select_order(
self, order_side: str = None, is_open: Optional[bool] = None) -> Optional[Order]:
def select_order(self, order_side: Optional[str] = None,
is_open: Optional[bool] = None) -> Optional[Order]:
"""
Finds latest order for this orderside and status
:param order_side: ft_order_side of the order (either 'buy', 'sell' or 'stoploss')

2
freqtrade/plot/plotting.py
View File

@@ -633,7 +633,7 @@ def load_and_plot_trades(config: Dict[str, Any]):
exchange = ExchangeResolver.load_exchange(config['exchange']['name'], config)
IStrategy.dp = DataProvider(config, exchange)
strategy.bot_start()
strategy.ft_bot_start()
strategy.bot_loop_start()
plot_elements = init_plotscript(config, list(exchange.markets), strategy.startup_candle_count)
timerange = plot_elements['timerange']

2
freqtrade/plugins/pairlist/SpreadFilter.py
View File

@@ -50,7 +50,7 @@ class SpreadFilter(IPairList):
:param ticker: ticker dict as returned from ccxt.fetch_tickers()
:return: True if the pair can stay, false if it should be removed
"""
if 'bid' in ticker and 'ask' in ticker and ticker['ask']:
if 'bid' in ticker and 'ask' in ticker and ticker['ask'] and ticker['bid']:
spread = 1 - ticker['bid'] / ticker['ask']
if spread > self._max_spread_ratio:
self.log_once(f"Removed {pair} from whitelist, because spread "

1
freqtrade/rpc/api_server/api_schemas.py
View File

@@ -256,6 +256,7 @@ class TradeSchema(BaseModel):
leverage: Optional[float]
interest_rate: Optional[float]
liquidation_price: Optional[float]
funding_fees: Optional[float]
trading_mode: Optional[TradingMode]

4
freqtrade/strategy/__init__.py
View File

@@ -1,9 +1,9 @@
# flake8: noqa: F401
from freqtrade.exchange import (timeframe_to_minutes, timeframe_to_msecs, timeframe_to_next_date,
timeframe_to_prev_date, timeframe_to_seconds)
from freqtrade.strategy.hyper import (BooleanParameter, CategoricalParameter, DecimalParameter,
IntParameter, RealParameter)
from freqtrade.strategy.informative_decorator import informative
from freqtrade.strategy.interface import IStrategy
from freqtrade.strategy.parameters import (BooleanParameter, CategoricalParameter, DecimalParameter,
IntParameter, RealParameter)
from freqtrade.strategy.strategy_helper import (merge_informative_pair, stoploss_from_absolute,
stoploss_from_open)

288
freqtrade/strategy/hyper.py
View File

@@ -3,295 +3,19 @@ IHyperStrategy interface, hyperoptable Parameter class.
This module defines a base class for auto-hyperoptable strategies.
"""
import logging
from abc import ABC, abstractmethod
from contextlib import suppress
from pathlib import Path
from typing import Any, Dict, Iterator, List, Optional, Sequence, Tuple, Union
from freqtrade.misc import deep_merge_dicts, json_load
from freqtrade.optimize.hyperopt_tools import HyperoptTools
with suppress(ImportError):
from skopt.space import Integer, Real, Categorical
from freqtrade.optimize.space import SKDecimal
from typing import Any, Dict, Iterator, List, Tuple
from freqtrade.enums import RunMode
from freqtrade.exceptions import OperationalException
from freqtrade.misc import deep_merge_dicts, json_load
from freqtrade.optimize.hyperopt_tools import HyperoptTools
from freqtrade.strategy.parameters import BaseParameter
logger = logging.getLogger(__name__)
class BaseParameter(ABC):
"""
Defines a parameter that can be optimized by hyperopt.
"""
category: Optional[str]
default: Any
value: Any
in_space: bool = False
name: str
def __init__(self, *, default: Any, space: Optional[str] = None,
optimize: bool = True, load: bool = True, **kwargs):
"""
Initialize hyperopt-optimizable parameter.
:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
parameter field
name is prefixed with 'buy_' or 'sell_'.
:param optimize: Include parameter in hyperopt optimizations.
:param load: Load parameter value from {space}_params.
:param kwargs: Extra parameters to skopt.space.(Integer|Real|Categorical).
"""
if 'name' in kwargs:
raise OperationalException(
'Name is determined by parameter field name and can not be specified manually.')
self.category = space
self._space_params = kwargs
self.value = default
self.optimize = optimize
self.load = load
def __repr__(self):
return f'{self.__class__.__name__}({self.value})'
@abstractmethod
def get_space(self, name: str) -> Union['Integer', 'Real', 'SKDecimal', 'Categorical']:
"""
Get-space - will be used by Hyperopt to get the hyperopt Space
"""
class NumericParameter(BaseParameter):
""" Internal parameter used for Numeric purposes """
float_or_int = Union[int, float]
default: float_or_int
value: float_or_int
def __init__(self, low: Union[float_or_int, Sequence[float_or_int]],
high: Optional[float_or_int] = None, *, default: float_or_int,
space: Optional[str] = None, optimize: bool = True, load: bool = True, **kwargs):
"""
Initialize hyperopt-optimizable numeric parameter.
Cannot be instantiated, but provides the validation for other numeric parameters
:param low: Lower end (inclusive) of optimization space or [low, high].
:param high: Upper end (inclusive) of optimization space.
Must be none of entire range is passed first parameter.
:param default: A default value.
:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
parameter fieldname is prefixed with 'buy_' or 'sell_'.
:param optimize: Include parameter in hyperopt optimizations.
:param load: Load parameter value from {space}_params.
:param kwargs: Extra parameters to skopt.space.*.
"""
if high is not None and isinstance(low, Sequence):
raise OperationalException(f'{self.__class__.__name__} space invalid.')
if high is None or isinstance(low, Sequence):
if not isinstance(low, Sequence) or len(low) != 2:
raise OperationalException(f'{self.__class__.__name__} space must be [low, high]')
self.low, self.high = low
else:
self.low = low
self.high = high
super().__init__(default=default, space=space, optimize=optimize,
load=load, **kwargs)
class IntParameter(NumericParameter):
default: int
value: int
def __init__(self, low: Union[int, Sequence[int]], high: Optional[int] = None, *, default: int,
space: Optional[str] = None, optimize: bool = True, load: bool = True, **kwargs):
"""
Initialize hyperopt-optimizable integer parameter.
:param low: Lower end (inclusive) of optimization space or [low, high].
:param high: Upper end (inclusive) of optimization space.
Must be none of entire range is passed first parameter.
:param default: A default value.
:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
parameter fieldname is prefixed with 'buy_' or 'sell_'.
:param optimize: Include parameter in hyperopt optimizations.
:param load: Load parameter value from {space}_params.
:param kwargs: Extra parameters to skopt.space.Integer.
"""
super().__init__(low=low, high=high, default=default, space=space, optimize=optimize,
load=load, **kwargs)
def get_space(self, name: str) -> 'Integer':
"""
Create skopt optimization space.
:param name: A name of parameter field.
"""
return Integer(low=self.low, high=self.high, name=name, **self._space_params)
@property
def range(self):
"""
Get each value in this space as list.
Returns a List from low to high (inclusive) in Hyperopt mode.
Returns a List with 1 item (`value`) in "non-hyperopt" mode, to avoid
calculating 100ds of indicators.
"""
if self.in_space and self.optimize:
# Scikit-optimize ranges are "inclusive", while python's "range" is exclusive
return range(self.low, self.high + 1)
else:
return range(self.value, self.value + 1)
class RealParameter(NumericParameter):
default: float
value: float
def __init__(self, low: Union[float, Sequence[float]], high: Optional[float] = None, *,
default: float, space: Optional[str] = None, optimize: bool = True,
load: bool = True, **kwargs):
"""
Initialize hyperopt-optimizable floating point parameter with unlimited precision.
:param low: Lower end (inclusive) of optimization space or [low, high].
:param high: Upper end (inclusive) of optimization space.
Must be none if entire range is passed first parameter.
:param default: A default value.
:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
parameter fieldname is prefixed with 'buy_' or 'sell_'.
:param optimize: Include parameter in hyperopt optimizations.
:param load: Load parameter value from {space}_params.
:param kwargs: Extra parameters to skopt.space.Real.
"""
super().__init__(low=low, high=high, default=default, space=space, optimize=optimize,
load=load, **kwargs)
def get_space(self, name: str) -> 'Real':
"""
Create skopt optimization space.
:param name: A name of parameter field.
"""
return Real(low=self.low, high=self.high, name=name, **self._space_params)
class DecimalParameter(NumericParameter):
default: float
value: float
def __init__(self, low: Union[float, Sequence[float]], high: Optional[float] = None, *,
default: float, decimals: int = 3, space: Optional[str] = None,
optimize: bool = True, load: bool = True, **kwargs):
"""
Initialize hyperopt-optimizable decimal parameter with a limited precision.
:param low: Lower end (inclusive) of optimization space or [low, high].
:param high: Upper end (inclusive) of optimization space.
Must be none if entire range is passed first parameter.
:param default: A default value.
:param decimals: A number of decimals after floating point to be included in testing.
:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
parameter fieldname is prefixed with 'buy_' or 'sell_'.
:param optimize: Include parameter in hyperopt optimizations.
:param load: Load parameter value from {space}_params.
:param kwargs: Extra parameters to skopt.space.Integer.
"""
self._decimals = decimals
default = round(default, self._decimals)
super().__init__(low=low, high=high, default=default, space=space, optimize=optimize,
load=load, **kwargs)
def get_space(self, name: str) -> 'SKDecimal':
"""
Create skopt optimization space.
:param name: A name of parameter field.
"""
return SKDecimal(low=self.low, high=self.high, decimals=self._decimals, name=name,
**self._space_params)
@property
def range(self):
"""
Get each value in this space as list.
Returns a List from low to high (inclusive) in Hyperopt mode.
Returns a List with 1 item (`value`) in "non-hyperopt" mode, to avoid
calculating 100ds of indicators.
"""
if self.in_space and self.optimize:
low = int(self.low * pow(10, self._decimals))
high = int(self.high * pow(10, self._decimals)) + 1
return [round(n * pow(0.1, self._decimals), self._decimals) for n in range(low, high)]
else:
return [self.value]
class CategoricalParameter(BaseParameter):
default: Any
value: Any
opt_range: Sequence[Any]
def __init__(self, categories: Sequence[Any], *, default: Optional[Any] = None,
space: Optional[str] = None, optimize: bool = True, load: bool = True, **kwargs):
"""
Initialize hyperopt-optimizable parameter.
:param categories: Optimization space, [a, b, ...].
:param default: A default value. If not specified, first item from specified space will be
used.
:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
parameter field
name is prefixed with 'buy_' or 'sell_'.
:param optimize: Include parameter in hyperopt optimizations.
:param load: Load parameter value from {space}_params.
:param kwargs: Extra parameters to skopt.space.Categorical.
"""
if len(categories) < 2:
raise OperationalException(
'CategoricalParameter space must be [a, b, ...] (at least two parameters)')
self.opt_range = categories
super().__init__(default=default, space=space, optimize=optimize,
load=load, **kwargs)
def get_space(self, name: str) -> 'Categorical':
"""
Create skopt optimization space.
:param name: A name of parameter field.
"""
return Categorical(self.opt_range, name=name, **self._space_params)
@property
def range(self):
"""
Get each value in this space as list.
Returns a List of categories in Hyperopt mode.
Returns a List with 1 item (`value`) in "non-hyperopt" mode, to avoid
calculating 100ds of indicators.
"""
if self.in_space and self.optimize:
return self.opt_range
else:
return [self.value]
class BooleanParameter(CategoricalParameter):
def __init__(self, *, default: Optional[Any] = None,
space: Optional[str] = None, optimize: bool = True, load: bool = True, **kwargs):
"""
Initialize hyperopt-optimizable Boolean Parameter.
It's a shortcut to `CategoricalParameter([True, False])`.
:param default: A default value. If not specified, first item from specified space will be
used.
:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
parameter field
name is prefixed with 'buy_' or 'sell_'.
:param optimize: Include parameter in hyperopt optimizations.
:param load: Load parameter value from {space}_params.
:param kwargs: Extra parameters to skopt.space.Categorical.
"""
categories = [True, False]
super().__init__(categories=categories, default=default, space=space, optimize=optimize,
load=load, **kwargs)
class HyperStrategyMixin:
"""
A helper base class which allows HyperOptAuto class to reuse implementations of buy/sell
@@ -345,7 +69,7 @@ class HyperStrategyMixin:
@classmethod
def detect_all_parameters(cls) -> Dict:
""" Detect all parameters and return them as a list"""
params: Dict = {
params: Dict[str, Any] = {
'buy': list(cls.detect_parameters('buy')),
'sell': list(cls.detect_parameters('sell')),
'protection': list(cls.detect_parameters('protection')),
@@ -424,7 +148,7 @@ class HyperStrategyMixin:
"""
Returns list of Parameters that are not part of the current optimize job
"""
params = {
params: Dict[str, Dict] = {
'buy': {},
'sell': {},
'protection': {},

64
freqtrade/strategy/interface.py
View File

@@ -16,7 +16,7 @@ from freqtrade.enums import (CandleType, ExitCheckTuple, ExitType, SignalDirecti
SignalType, TradingMode)
from freqtrade.exceptions import OperationalException, StrategyError
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_next_date, timeframe_to_seconds
from freqtrade.persistence import LocalTrade, Order, PairLocks, Trade
from freqtrade.persistence import Order, PairLocks, Trade
from freqtrade.strategy.hyper import HyperStrategyMixin
from freqtrade.strategy.informative_decorator import (InformativeData, PopulateIndicators,
_create_and_merge_informative_pair,
@@ -82,7 +82,7 @@ class IStrategy(ABC, HyperStrategyMixin):
}
# run "populate_indicators" only for new candle
process_only_new_candles: bool = False
process_only_new_candles: bool = True
use_exit_signal: bool
exit_profit_only: bool
@@ -144,6 +144,13 @@ class IStrategy(ABC, HyperStrategyMixin):
informative_data.candle_type = config['candle_type_def']
self._ft_informative.append((informative_data, cls_method))
def ft_bot_start(self, **kwargs) -> None:
"""
Strategy init - runs after dataprovider has been added.
Must call bot_start()
"""
strategy_safe_wrapper(self.bot_start)()
@abstractmethod
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
@@ -429,7 +436,7 @@ class IStrategy(ABC, HyperStrategyMixin):
return self.custom_sell(pair, trade, current_time, current_rate, current_profit, **kwargs)
def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
proposed_stake: float, min_stake: float, max_stake: float,
proposed_stake: float, min_stake: Optional[float], max_stake: float,
entry_tag: Optional[str], side: str, **kwargs) -> float:
"""
Customize stake size for each new trade.
@@ -447,8 +454,9 @@ class IStrategy(ABC, HyperStrategyMixin):
return proposed_stake
def adjust_trade_position(self, trade: Trade, current_time: datetime,
current_rate: float, current_profit: float, min_stake: float,
max_stake: float, **kwargs) -> Optional[float]:
current_rate: float, current_profit: float,
min_stake: Optional[float], max_stake: float,
**kwargs) -> Optional[float]:
"""
Custom trade adjustment logic, returning the stake amount that a trade should be increased.
This means extra buy orders with additional fees.
@@ -878,16 +886,16 @@ class IStrategy(ABC, HyperStrategyMixin):
def should_exit(self, trade: Trade, rate: float, current_time: datetime, *,
enter: bool, exit_: bool,
low: float = None, high: float = None,
force_stoploss: float = 0) -> ExitCheckTuple:
force_stoploss: float = 0) -> List[ExitCheckTuple]:
"""
This function evaluates if one of the conditions required to trigger an exit order
has been reached, which can either be a stop-loss, ROI or exit-signal.
:param low: Only used during backtesting to simulate (long)stoploss/(short)ROI
:param high: Only used during backtesting, to simulate (short)stoploss/(long)ROI
:param force_stoploss: Externally provided stoploss
:return: True if trade should be exited, False otherwise
:return: List of exit reasons - or empty list.
"""
exits: List[ExitCheckTuple] = []
current_rate = rate
current_profit = trade.calc_profit_ratio(current_rate)
@@ -917,19 +925,20 @@ class IStrategy(ABC, HyperStrategyMixin):
if exit_ and not enter:
exit_signal = ExitType.EXIT_SIGNAL
else:
custom_reason = strategy_safe_wrapper(self.custom_exit, default_retval=False)(
reason_cust = strategy_safe_wrapper(self.custom_exit, default_retval=False)(
pair=trade.pair, trade=trade, current_time=current_time,
current_rate=current_rate, current_profit=current_profit)
if custom_reason:
if reason_cust:
exit_signal = ExitType.CUSTOM_EXIT
if isinstance(custom_reason, str):
if len(custom_reason) > CUSTOM_EXIT_MAX_LENGTH:
if isinstance(reason_cust, str):
custom_reason = reason_cust
if len(reason_cust) > CUSTOM_EXIT_MAX_LENGTH:
logger.warning(f'Custom exit reason returned from '
f'custom_exit is too long and was trimmed'
f'to {CUSTOM_EXIT_MAX_LENGTH} characters.')
custom_reason = custom_reason[:CUSTOM_EXIT_MAX_LENGTH]
custom_reason = reason_cust[:CUSTOM_EXIT_MAX_LENGTH]
else:
custom_reason = None
custom_reason = ''
if (
exit_signal == ExitType.CUSTOM_EXIT
or (exit_signal == ExitType.EXIT_SIGNAL
@@ -938,24 +947,29 @@ class IStrategy(ABC, HyperStrategyMixin):
logger.debug(f"{trade.pair} - Sell signal received. "
f"exit_type=ExitType.{exit_signal.name}" +
(f", custom_reason={custom_reason}" if custom_reason else ""))
return ExitCheckTuple(exit_type=exit_signal, exit_reason=custom_reason)
exits.append(ExitCheckTuple(exit_type=exit_signal, exit_reason=custom_reason))
# Sequence:
# Exit-signal
# ROI (if not stoploss)
# Stoploss
if roi_reached and stoplossflag.exit_type != ExitType.STOP_LOSS:
logger.debug(f"{trade.pair} - Required profit reached. exit_type=ExitType.ROI")
return ExitCheckTuple(exit_type=ExitType.ROI)
# ROI
# Trailing stoploss
if stoplossflag.exit_flag:
if stoplossflag.exit_type == ExitType.STOP_LOSS:
logger.debug(f"{trade.pair} - Stoploss hit. exit_type={stoplossflag.exit_type}")
return stoplossflag
exits.append(stoplossflag)
# This one is noisy, commented out...
# logger.debug(f"{trade.pair} - No exit signal.")
return ExitCheckTuple(exit_type=ExitType.NONE)
if roi_reached:
logger.debug(f"{trade.pair} - Required profit reached. exit_type=ExitType.ROI")
exits.append(ExitCheckTuple(exit_type=ExitType.ROI))
if stoplossflag.exit_type == ExitType.TRAILING_STOP_LOSS:
logger.debug(f"{trade.pair} - Trailing stoploss hit.")
exits.append(stoplossflag)
return exits
def stop_loss_reached(self, current_rate: float, trade: Trade,
current_time: datetime, current_profit: float,
@@ -1070,7 +1084,7 @@ class IStrategy(ABC, HyperStrategyMixin):
else:
return current_profit > roi
def ft_check_timed_out(self, trade: LocalTrade, order: Order,
def ft_check_timed_out(self, trade: Trade, order: Order,
current_time: datetime) -> bool:
"""
FT Internal method.

289
freqtrade/strategy/parameters.py Normal file
View File

@@ -0,0 +1,289 @@
"""
IHyperStrategy interface, hyperoptable Parameter class.
This module defines a base class for auto-hyperoptable strategies.
"""
import logging
from abc import ABC, abstractmethod
from contextlib import suppress
from typing import Any, Optional, Sequence, Union
with suppress(ImportError):
from skopt.space import Integer, Real, Categorical
from freqtrade.optimize.space import SKDecimal
from freqtrade.exceptions import OperationalException
logger = logging.getLogger(__name__)
class BaseParameter(ABC):
"""
Defines a parameter that can be optimized by hyperopt.
"""
category: Optional[str]
default: Any
value: Any
in_space: bool = False
name: str
def __init__(self, *, default: Any, space: Optional[str] = None,
optimize: bool = True, load: bool = True, **kwargs):
"""
Initialize hyperopt-optimizable parameter.
:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
parameter field
name is prefixed with 'buy_' or 'sell_'.
:param optimize: Include parameter in hyperopt optimizations.
:param load: Load parameter value from {space}_params.
:param kwargs: Extra parameters to skopt.space.(Integer|Real|Categorical).
"""
if 'name' in kwargs:
raise OperationalException(
'Name is determined by parameter field name and can not be specified manually.')
self.category = space
self._space_params = kwargs
self.value = default
self.optimize = optimize
self.load = load
def __repr__(self):
return f'{self.__class__.__name__}({self.value})'
@abstractmethod
def get_space(self, name: str) -> Union['Integer', 'Real', 'SKDecimal', 'Categorical']:
"""
Get-space - will be used by Hyperopt to get the hyperopt Space
"""
class NumericParameter(BaseParameter):
""" Internal parameter used for Numeric purposes """
float_or_int = Union[int, float]
default: float_or_int
value: float_or_int
def __init__(self, low: Union[float_or_int, Sequence[float_or_int]],
high: Optional[float_or_int] = None, *, default: float_or_int,
space: Optional[str] = None, optimize: bool = True, load: bool = True, **kwargs):
"""
Initialize hyperopt-optimizable numeric parameter.
Cannot be instantiated, but provides the validation for other numeric parameters
:param low: Lower end (inclusive) of optimization space or [low, high].
:param high: Upper end (inclusive) of optimization space.
Must be none of entire range is passed first parameter.
:param default: A default value.
:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
parameter fieldname is prefixed with 'buy_' or 'sell_'.
:param optimize: Include parameter in hyperopt optimizations.
:param load: Load parameter value from {space}_params.
:param kwargs: Extra parameters to skopt.space.*.
"""
if high is not None and isinstance(low, Sequence):
raise OperationalException(f'{self.__class__.__name__} space invalid.')
if high is None or isinstance(low, Sequence):
if not isinstance(low, Sequence) or len(low) != 2:
raise OperationalException(f'{self.__class__.__name__} space must be [low, high]')
self.low, self.high = low
else:
self.low = low
self.high = high
super().__init__(default=default, space=space, optimize=optimize,
load=load, **kwargs)
class IntParameter(NumericParameter):
default: int
value: int
low: int
high: int
def __init__(self, low: Union[int, Sequence[int]], high: Optional[int] = None, *, default: int,
space: Optional[str] = None, optimize: bool = True, load: bool = True, **kwargs):
"""
Initialize hyperopt-optimizable integer parameter.
:param low: Lower end (inclusive) of optimization space or [low, high].
:param high: Upper end (inclusive) of optimization space.
Must be none of entire range is passed first parameter.
:param default: A default value.
:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
parameter fieldname is prefixed with 'buy_' or 'sell_'.
:param optimize: Include parameter in hyperopt optimizations.
:param load: Load parameter value from {space}_params.
:param kwargs: Extra parameters to skopt.space.Integer.
"""
super().__init__(low=low, high=high, default=default, space=space, optimize=optimize,
load=load, **kwargs)
def get_space(self, name: str) -> 'Integer':
"""
Create skopt optimization space.
:param name: A name of parameter field.
"""
return Integer(low=self.low, high=self.high, name=name, **self._space_params)
@property
def range(self):
"""
Get each value in this space as list.
Returns a List from low to high (inclusive) in Hyperopt mode.
Returns a List with 1 item (`value`) in "non-hyperopt" mode, to avoid
calculating 100ds of indicators.
"""
if self.in_space and self.optimize:
# Scikit-optimize ranges are "inclusive", while python's "range" is exclusive
return range(self.low, self.high + 1)
else:
return range(self.value, self.value + 1)
class RealParameter(NumericParameter):
default: float
value: float
def __init__(self, low: Union[float, Sequence[float]], high: Optional[float] = None, *,
default: float, space: Optional[str] = None, optimize: bool = True,
load: bool = True, **kwargs):
"""
Initialize hyperopt-optimizable floating point parameter with unlimited precision.
:param low: Lower end (inclusive) of optimization space or [low, high].
:param high: Upper end (inclusive) of optimization space.
Must be none if entire range is passed first parameter.
:param default: A default value.
:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
parameter fieldname is prefixed with 'buy_' or 'sell_'.
:param optimize: Include parameter in hyperopt optimizations.
:param load: Load parameter value from {space}_params.
:param kwargs: Extra parameters to skopt.space.Real.
"""
super().__init__(low=low, high=high, default=default, space=space, optimize=optimize,
load=load, **kwargs)
def get_space(self, name: str) -> 'Real':
"""
Create skopt optimization space.
:param name: A name of parameter field.
"""
return Real(low=self.low, high=self.high, name=name, **self._space_params)
class DecimalParameter(NumericParameter):
default: float
value: float
def __init__(self, low: Union[float, Sequence[float]], high: Optional[float] = None, *,
default: float, decimals: int = 3, space: Optional[str] = None,
optimize: bool = True, load: bool = True, **kwargs):
"""
Initialize hyperopt-optimizable decimal parameter with a limited precision.
:param low: Lower end (inclusive) of optimization space or [low, high].
:param high: Upper end (inclusive) of optimization space.
Must be none if entire range is passed first parameter.
:param default: A default value.
:param decimals: A number of decimals after floating point to be included in testing.
:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
parameter fieldname is prefixed with 'buy_' or 'sell_'.
:param optimize: Include parameter in hyperopt optimizations.
:param load: Load parameter value from {space}_params.
:param kwargs: Extra parameters to skopt.space.Integer.
"""
self._decimals = decimals
default = round(default, self._decimals)
super().__init__(low=low, high=high, default=default, space=space, optimize=optimize,
load=load, **kwargs)
def get_space(self, name: str) -> 'SKDecimal':
"""
Create skopt optimization space.
:param name: A name of parameter field.
"""
return SKDecimal(low=self.low, high=self.high, decimals=self._decimals, name=name,
**self._space_params)
@property
def range(self):
"""
Get each value in this space as list.
Returns a List from low to high (inclusive) in Hyperopt mode.
Returns a List with 1 item (`value`) in "non-hyperopt" mode, to avoid
calculating 100ds of indicators.
"""
if self.in_space and self.optimize:
low = int(self.low * pow(10, self._decimals))
high = int(self.high * pow(10, self._decimals)) + 1
return [round(n * pow(0.1, self._decimals), self._decimals) for n in range(low, high)]
else:
return [self.value]
class CategoricalParameter(BaseParameter):
default: Any
value: Any
opt_range: Sequence[Any]
def __init__(self, categories: Sequence[Any], *, default: Optional[Any] = None,
space: Optional[str] = None, optimize: bool = True, load: bool = True, **kwargs):
"""
Initialize hyperopt-optimizable parameter.
:param categories: Optimization space, [a, b, ...].
:param default: A default value. If not specified, first item from specified space will be
used.
:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
parameter field
name is prefixed with 'buy_' or 'sell_'.
:param optimize: Include parameter in hyperopt optimizations.
:param load: Load parameter value from {space}_params.
:param kwargs: Extra parameters to skopt.space.Categorical.
"""
if len(categories) < 2:
raise OperationalException(
'CategoricalParameter space must be [a, b, ...] (at least two parameters)')
self.opt_range = categories
super().__init__(default=default, space=space, optimize=optimize,
load=load, **kwargs)
def get_space(self, name: str) -> 'Categorical':
"""
Create skopt optimization space.
:param name: A name of parameter field.
"""
return Categorical(self.opt_range, name=name, **self._space_params)
@property
def range(self):
"""
Get each value in this space as list.
Returns a List of categories in Hyperopt mode.
Returns a List with 1 item (`value`) in "non-hyperopt" mode, to avoid
calculating 100ds of indicators.
"""
if self.in_space and self.optimize:
return self.opt_range
else:
return [self.value]
class BooleanParameter(CategoricalParameter):
def __init__(self, *, default: Optional[Any] = None,
space: Optional[str] = None, optimize: bool = True, load: bool = True, **kwargs):
"""
Initialize hyperopt-optimizable Boolean Parameter.
It's a shortcut to `CategoricalParameter([True, False])`.
:param default: A default value. If not specified, first item from specified space will be
used.
:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
parameter field
name is prefixed with 'buy_' or 'sell_'.
:param optimize: Include parameter in hyperopt optimizations.
:param load: Load parameter value from {space}_params.
:param kwargs: Extra parameters to skopt.space.Categorical.
"""
categories = [True, False]
super().__init__(categories=categories, default=default, space=space, optimize=optimize,
load=load, **kwargs)

10
freqtrade/strategy/strategy_wrapper.py
View File

@@ -1,5 +1,7 @@
import logging
from copy import deepcopy
from functools import wraps
from typing import Any, Callable, TypeVar, cast
from freqtrade.exceptions import StrategyError
@@ -7,12 +9,16 @@ from freqtrade.exceptions import StrategyError
logger = logging.getLogger(__name__)
def strategy_safe_wrapper(f, message: str = "", default_retval=None, supress_error=False):
F = TypeVar('F', bound=Callable[..., Any])
def strategy_safe_wrapper(f: F, message: str = "", default_retval=None, supress_error=False) -> F:
"""
Wrapper around user-provided methods and functions.
Caches all exceptions and returns either the default_retval (if it's not None) or raises
a StrategyError exception, which then needs to be handled by the calling method.
"""
@wraps(f)
def wrapper(*args, **kwargs):
try:
if 'trade' in kwargs:
@@ -37,4 +43,4 @@ def strategy_safe_wrapper(f, message: str = "", default_retval=None, supress_err
raise StrategyError(str(error)) from error
return default_retval
return wrapper
return cast(F, wrapper)

4
freqtrade/templates/base_strategy.py.j2
View File

@@ -6,7 +6,7 @@ import numpy as np # noqa
import pandas as pd # noqa
from pandas import DataFrame # noqa
from datetime import datetime # noqa
from typing import Optional # noqa
from typing import Optional, Union # noqa
from freqtrade.strategy import (BooleanParameter, CategoricalParameter, DecimalParameter,
IStrategy, IntParameter)
@@ -64,7 +64,7 @@ class {{ strategy }}(IStrategy):
# trailing_stop_positive_offset = 0.0 # Disabled / not configured
# Run "populate_indicators()" only for new candle.
process_only_new_candles = False
process_only_new_candles = True
# These values can be overridden in the config.
use_exit_signal = True

2
freqtrade/templates/sample_strategy.py
View File

@@ -62,7 +62,7 @@ class SampleStrategy(IStrategy):
timeframe = '5m'
# Run "populate_indicators()" only for new candle.
process_only_new_candles = False
process_only_new_candles = True
# These values can be overridden in the config.
use_exit_signal = True

10
freqtrade/templates/subtemplates/strategy_methods_advanced.j2
View File

@@ -13,7 +13,7 @@ def bot_loop_start(self, **kwargs) -> None:
pass
def custom_entry_price(self, pair: str, current_time: 'datetime', proposed_rate: float,
entry_tag: Optional[str], **kwargs) -> float:
entry_tag: 'Optional[str]', side: str, **kwargs) -> float:
"""
Custom entry price logic, returning the new entry price.
@@ -80,8 +80,8 @@ def custom_exit_price(self, pair: str, trade: 'Trade',
return proposed_rate
def custom_stake_amount(self, pair: str, current_time: 'datetime', current_rate: float,
proposed_stake: float, min_stake: float, max_stake: float,
side: str, entry_tag: Optional[str], **kwargs) -> float:
proposed_stake: float, min_stake: Optional[float], max_stake: float,
entry_tag: 'Optional[str]', side: str, **kwargs) -> float:
"""
Customize stake size for each new trade.
@@ -244,8 +244,8 @@ def check_exit_timeout(self, pair: str, trade: 'Trade', order: 'Order',
return False
def adjust_trade_position(self, trade: 'Trade', current_time: 'datetime',
current_rate: float, current_profit: float, min_stake: float,
max_stake: float, **kwargs) -> Optional[float]:
current_rate: float, current_profit: float, min_stake: Optional[float],
max_stake: float, **kwargs) -> 'Optional[float]':
"""
Custom trade adjustment logic, returning the stake amount that a trade should be increased.
This means extra buy orders with additional fees.