Merged feat/short into lev-strat

This commit is contained in:
Sam Germain
2021-09-19 17:44:12 -06:00
parent a89c67787b
commit 778f0d9d0a
41 changed files with 3173 additions and 614 deletions

View File

@@ -53,7 +53,7 @@ def start_hyperopt_list(args: Dict[str, Any]) -> None:
if epochs and export_csv:
HyperoptTools.export_csv_file(
config, epochs, total_epochs, not config.get('hyperopt_list_best', False), export_csv
config, epochs, export_csv
)

View File

@@ -119,7 +119,7 @@ class Edge:
)
# Download informative pairs too
res = defaultdict(list)
for p, t in self.strategy.informative_pairs():
for p, t in self.strategy.gather_informative_pairs():
res[t].append(p)
for timeframe, inf_pairs in res.items():
timerange_startup = deepcopy(self._timerange)

View File

@@ -20,4 +20,7 @@ class Bibox(Exchange):
# fetchCurrencies API point requires authentication for Bibox,
# so switch it off for Freqtrade load_markets()
_ccxt_config: Dict = {"has": {"fetchCurrencies": False}}
@property
def _ccxt_config(self) -> Dict:
# Parameters to add directly to ccxt sync/async initialization.
return {"has": {"fetchCurrencies": False}}

View File

@@ -1,10 +1,13 @@
""" Binance exchange subclass """
import json
import logging
from typing import Dict, List
from pathlib import Path
from typing import Dict, List, Optional, Tuple
import arrow
import ccxt
from freqtrade.enums import Collateral, TradingMode
from freqtrade.exceptions import (DDosProtection, InsufficientFundsError, InvalidOrderException,
OperationalException, TemporaryError)
from freqtrade.exchange import Exchange
@@ -26,36 +29,74 @@ class Binance(Exchange):
"l2_limit_range": [5, 10, 20, 50, 100, 500, 1000],
}
def stoploss_adjust(self, stop_loss: float, order: Dict) -> bool:
_supported_trading_mode_collateral_pairs: List[Tuple[TradingMode, Collateral]] = [
# TradingMode.SPOT always supported and not required in this list
# (TradingMode.MARGIN, Collateral.CROSS), # TODO-lev: Uncomment once supported
# (TradingMode.FUTURES, Collateral.CROSS), # TODO-lev: Uncomment once supported
# (TradingMode.FUTURES, Collateral.ISOLATED) # TODO-lev: Uncomment once supported
]
@property
def _ccxt_config(self) -> Dict:
# Parameters to add directly to ccxt sync/async initialization.
if self.trading_mode == TradingMode.MARGIN:
return {
"options": {
"defaultType": "margin"
}
}
elif self.trading_mode == TradingMode.FUTURES:
return {
"options": {
"defaultType": "future"
}
}
else:
return {}
def stoploss_adjust(self, stop_loss: float, order: Dict, side: str) -> bool:
"""
Verify stop_loss against stoploss-order value (limit or price)
Returns True if adjustment is necessary.
:param side: "buy" or "sell"
"""
return order['type'] == 'stop_loss_limit' and stop_loss > float(order['info']['stopPrice'])
return order['type'] == 'stop_loss_limit' and (
(side == "sell" and stop_loss > float(order['info']['stopPrice'])) or
(side == "buy" and stop_loss < float(order['info']['stopPrice']))
)
@retrier(retries=0)
def stoploss(self, pair: str, amount: float, stop_price: float, order_types: Dict) -> Dict:
def stoploss(self, pair: str, amount: float, stop_price: float,
order_types: Dict, side: str, leverage: float) -> Dict:
"""
creates a stoploss limit order.
this stoploss-limit is binance-specific.
It may work with a limited number of other exchanges, but this has not been tested yet.
:param side: "buy" or "sell"
"""
# Limit price threshold: As limit price should always be below stop-price
limit_price_pct = order_types.get('stoploss_on_exchange_limit_ratio', 0.99)
rate = stop_price * limit_price_pct
if side == "sell":
# TODO: Name limit_rate in other exchange subclasses
rate = stop_price * limit_price_pct
else:
rate = stop_price * (2 - limit_price_pct)
ordertype = "stop_loss_limit"
stop_price = self.price_to_precision(pair, stop_price)
bad_stop_price = (stop_price <= rate) if side == "sell" else (stop_price >= rate)
# Ensure rate is less than stop price
if stop_price <= rate:
if bad_stop_price:
raise OperationalException(
'In stoploss limit order, stop price should be more than limit price')
'In stoploss limit order, stop price should be better than limit price')
if self._config['dry_run']:
dry_order = self.create_dry_run_order(
pair, ordertype, "sell", amount, stop_price)
pair, ordertype, side, amount, stop_price, leverage)
return dry_order
try:
@@ -66,7 +107,8 @@ class Binance(Exchange):
rate = self.price_to_precision(pair, rate)
order = self._api.create_order(symbol=pair, type=ordertype, side='sell',
self._lev_prep(pair, leverage)
order = self._api.create_order(symbol=pair, type=ordertype, side=side,
amount=amount, price=rate, params=params)
logger.info('stoploss limit order added for %s. '
'stop price: %s. limit: %s', pair, stop_price, rate)
@@ -74,21 +116,96 @@ class Binance(Exchange):
return order
except ccxt.InsufficientFunds as e:
raise InsufficientFundsError(
f'Insufficient funds to create {ordertype} sell order on market {pair}. '
f'Tried to sell amount {amount} at rate {rate}. '
f'Insufficient funds to create {ordertype} {side} order on market {pair}. '
f'Tried to {side} amount {amount} at rate {rate}. '
f'Message: {e}') from e
except ccxt.InvalidOrder as e:
# Errors:
# `binance Order would trigger immediately.`
raise InvalidOrderException(
f'Could not create {ordertype} sell order on market {pair}. '
f'Tried to sell amount {amount} at rate {rate}. '
f'Could not create {ordertype} {side} order on market {pair}. '
f'Tried to {side} amount {amount} at rate {rate}. '
f'Message: {e}') from e
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not place sell order due to {e.__class__.__name__}. Message: {e}') from e
f'Could not place {side} order due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
@retrier
def fill_leverage_brackets(self):
"""
Assigns property _leverage_brackets to a dictionary of information about the leverage
allowed on each pair
"""
if self.trading_mode == TradingMode.FUTURES:
try:
if self._config['dry_run']:
leverage_brackets_path = (
Path(__file__).parent / 'binance_leverage_brackets.json'
)
with open(leverage_brackets_path) as json_file:
leverage_brackets = json.load(json_file)
else:
leverage_brackets = self._api.load_leverage_brackets()
for pair, brackets in leverage_brackets.items():
self._leverage_brackets[pair] = [
[
min_amount,
float(margin_req)
] for [
min_amount,
margin_req
] in brackets
]
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(f'Could not fetch leverage amounts due to'
f'{e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
def get_max_leverage(self, pair: Optional[str], nominal_value: Optional[float]) -> float:
"""
Returns the maximum leverage that a pair can be traded at
:param pair: The base/quote currency pair being traded
:nominal_value: The total value of the trade in quote currency (collateral + debt)
"""
pair_brackets = self._leverage_brackets[pair]
max_lev = 1.0
for [min_amount, margin_req] in pair_brackets:
if nominal_value >= min_amount:
max_lev = 1/margin_req
return max_lev
@ retrier
def _set_leverage(
self,
leverage: float,
pair: Optional[str] = None,
trading_mode: Optional[TradingMode] = None
):
"""
Set's the leverage before making a trade, in order to not
have the same leverage on every trade
"""
trading_mode = trading_mode or self.trading_mode
if self._config['dry_run'] or trading_mode != TradingMode.FUTURES:
return
try:
self._api.set_leverage(symbol=pair, leverage=leverage)
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not set leverage due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e

File diff suppressed because it is too large Load Diff

View File

@@ -22,6 +22,7 @@ from pandas import DataFrame
from freqtrade.constants import (DEFAULT_AMOUNT_RESERVE_PERCENT, NON_OPEN_EXCHANGE_STATES,
ListPairsWithTimeframes)
from freqtrade.data.converter import ohlcv_to_dataframe, trades_dict_to_list
from freqtrade.enums import Collateral, TradingMode
from freqtrade.exceptions import (DDosProtection, ExchangeError, InsufficientFundsError,
InvalidOrderException, OperationalException, PricingError,
RetryableOrderError, TemporaryError)
@@ -48,9 +49,6 @@ class Exchange:
_config: Dict = {}
# Parameters to add directly to ccxt sync/async initialization.
_ccxt_config: Dict = {}
# Parameters to add directly to buy/sell calls (like agreeing to trading agreement)
_params: Dict = {}
@@ -74,6 +72,10 @@ class Exchange:
}
_ft_has: Dict = {}
_supported_trading_mode_collateral_pairs: List[Tuple[TradingMode, Collateral]] = [
# TradingMode.SPOT always supported and not required in this list
]
def __init__(self, config: Dict[str, Any], validate: bool = True) -> None:
"""
Initializes this module with the given config,
@@ -83,6 +85,7 @@ class Exchange:
self._api: ccxt.Exchange = None
self._api_async: ccxt_async.Exchange = None
self._markets: Dict = {}
self._leverage_brackets: Dict = {}
self._config.update(config)
@@ -125,14 +128,25 @@ class Exchange:
self._trades_pagination = self._ft_has['trades_pagination']
self._trades_pagination_arg = self._ft_has['trades_pagination_arg']
self.trading_mode: TradingMode = (
TradingMode(config.get('trading_mode'))
if config.get('trading_mode')
else TradingMode.SPOT
)
self.collateral: Optional[Collateral] = (
Collateral(config.get('collateral'))
if config.get('collateral')
else None
)
# Initialize ccxt objects
ccxt_config = self._ccxt_config.copy()
ccxt_config = self._ccxt_config
ccxt_config = deep_merge_dicts(exchange_config.get('ccxt_config', {}), ccxt_config)
ccxt_config = deep_merge_dicts(exchange_config.get('ccxt_sync_config', {}), ccxt_config)
self._api = self._init_ccxt(exchange_config, ccxt_kwargs=ccxt_config)
ccxt_async_config = self._ccxt_config.copy()
ccxt_async_config = self._ccxt_config
ccxt_async_config = deep_merge_dicts(exchange_config.get('ccxt_config', {}),
ccxt_async_config)
ccxt_async_config = deep_merge_dicts(exchange_config.get('ccxt_async_config', {}),
@@ -140,6 +154,9 @@ class Exchange:
self._api_async = self._init_ccxt(
exchange_config, ccxt_async, ccxt_kwargs=ccxt_async_config)
if self.trading_mode != TradingMode.SPOT:
self.fill_leverage_brackets()
logger.info('Using Exchange "%s"', self.name)
if validate:
@@ -157,7 +174,7 @@ class Exchange:
self.validate_order_time_in_force(config.get('order_time_in_force', {}))
self.validate_required_startup_candles(config.get('startup_candle_count', 0),
config.get('timeframe', ''))
self.validate_trading_mode_and_collateral(self.trading_mode, self.collateral)
# Converts the interval provided in minutes in config to seconds
self.markets_refresh_interval: int = exchange_config.get(
"markets_refresh_interval", 60) * 60
@@ -190,6 +207,7 @@ class Exchange:
'secret': exchange_config.get('secret'),
'password': exchange_config.get('password'),
'uid': exchange_config.get('uid', ''),
# 'options': exchange_config.get('options', {})
}
if ccxt_kwargs:
logger.info('Applying additional ccxt config: %s', ccxt_kwargs)
@@ -210,6 +228,11 @@ class Exchange:
return api
@property
def _ccxt_config(self) -> Dict:
# Parameters to add directly to ccxt sync/async initialization.
return {}
@property
def name(self) -> str:
"""exchange Name (from ccxt)"""
@@ -355,6 +378,7 @@ class Exchange:
# Also reload async markets to avoid issues with newly listed pairs
self._load_async_markets(reload=True)
self._last_markets_refresh = arrow.utcnow().int_timestamp
self.fill_leverage_brackets()
except ccxt.BaseError:
logger.exception("Could not reload markets.")
@@ -370,7 +394,7 @@ class Exchange:
raise OperationalException(
'Could not load markets, therefore cannot start. '
'Please investigate the above error for more details.'
)
)
quote_currencies = self.get_quote_currencies()
if stake_currency not in quote_currencies:
raise OperationalException(
@@ -482,6 +506,25 @@ class Exchange:
f"This strategy requires {startup_candles} candles to start. "
f"{self.name} only provides {candle_limit} for {timeframe}.")
def validate_trading_mode_and_collateral(
self,
trading_mode: TradingMode,
collateral: Optional[Collateral] # Only None when trading_mode = TradingMode.SPOT
):
"""
Checks if freqtrade can perform trades using the configured
trading mode(Margin, Futures) and Collateral(Cross, Isolated)
Throws OperationalException:
If the trading_mode/collateral type are not supported by freqtrade on this exchange
"""
if trading_mode != TradingMode.SPOT and (
(trading_mode, collateral) not in self._supported_trading_mode_collateral_pairs
):
collateral_value = collateral and collateral.value
raise OperationalException(
f"Freqtrade does not support {collateral_value} {trading_mode.value} on {self.name}"
)
def exchange_has(self, endpoint: str) -> bool:
"""
Checks if exchange implements a specific API endpoint.
@@ -541,8 +584,8 @@ class Exchange:
else:
return 1 / pow(10, precision)
def get_min_pair_stake_amount(self, pair: str, price: float,
stoploss: float) -> Optional[float]:
def get_min_pair_stake_amount(self, pair: str, price: float, stoploss: float,
leverage: Optional[float] = 1.0) -> Optional[float]:
try:
market = self.markets[pair]
except KeyError:
@@ -576,12 +619,24 @@ class Exchange:
# The value returned should satisfy both limits: for amount (base currency) and
# for cost (quote, stake currency), so max() is used here.
# See also #2575 at github.
return max(min_stake_amounts) * amount_reserve_percent
return self._get_stake_amount_considering_leverage(
max(min_stake_amounts) * amount_reserve_percent,
leverage or 1.0
)
def _get_stake_amount_considering_leverage(self, stake_amount: float, leverage: float):
"""
Takes the minimum stake amount for a pair with no leverage and returns the minimum
stake amount when leverage is considered
:param stake_amount: The stake amount for a pair before leverage is considered
:param leverage: The amount of leverage being used on the current trade
"""
return stake_amount / leverage
# Dry-run methods
def create_dry_run_order(self, pair: str, ordertype: str, side: str, amount: float,
rate: float, params: Dict = {}) -> Dict[str, Any]:
rate: float, leverage: float, params: Dict = {}) -> Dict[str, Any]:
order_id = f'dry_run_{side}_{datetime.now().timestamp()}'
_amount = self.amount_to_precision(pair, amount)
dry_order: Dict[str, Any] = {
@@ -598,7 +653,8 @@ class Exchange:
'timestamp': arrow.utcnow().int_timestamp * 1000,
'status': "closed" if ordertype == "market" else "open",
'fee': None,
'info': {}
'info': {},
'leverage': leverage
}
if dry_order["type"] in ["stop_loss_limit", "stop-loss-limit"]:
dry_order["info"] = {"stopPrice": dry_order["price"]}
@@ -608,7 +664,7 @@ class Exchange:
average = self.get_dry_market_fill_price(pair, side, amount, rate)
dry_order.update({
'average': average,
'cost': dry_order['amount'] * average,
'cost': (dry_order['amount'] * average) / leverage
})
dry_order = self.add_dry_order_fee(pair, dry_order)
@@ -716,17 +772,26 @@ class Exchange:
# Order handling
def create_order(self, pair: str, ordertype: str, side: str, amount: float,
rate: float, time_in_force: str = 'gtc') -> Dict:
if self._config['dry_run']:
dry_order = self.create_dry_run_order(pair, ordertype, side, amount, rate)
return dry_order
def _lev_prep(self, pair: str, leverage: float):
if self.trading_mode != TradingMode.SPOT:
self.set_margin_mode(pair, self.collateral)
self._set_leverage(leverage, pair)
def _get_params(self, ordertype: str, leverage: float, time_in_force: str = 'gtc') -> Dict:
params = self._params.copy()
if time_in_force != 'gtc' and ordertype != 'market':
param = self._ft_has.get('time_in_force_parameter', '')
params.update({param: time_in_force})
return params
def create_order(self, pair: str, ordertype: str, side: str, amount: float,
rate: float, leverage: float = 1.0, time_in_force: str = 'gtc') -> Dict:
# TODO-lev: remove default for leverage
if self._config['dry_run']:
dry_order = self.create_dry_run_order(pair, ordertype, side, amount, rate, leverage)
return dry_order
params = self._get_params(ordertype, leverage, time_in_force)
try:
# Set the precision for amount and price(rate) as accepted by the exchange
@@ -735,6 +800,7 @@ class Exchange:
or self._api.options.get("createMarketBuyOrderRequiresPrice", False))
rate_for_order = self.price_to_precision(pair, rate) if needs_price else None
self._lev_prep(pair, leverage)
order = self._api.create_order(pair, ordertype, side,
amount, rate_for_order, params)
self._log_exchange_response('create_order', order)
@@ -758,14 +824,15 @@ class Exchange:
except ccxt.BaseError as e:
raise OperationalException(e) from e
def stoploss_adjust(self, stop_loss: float, order: Dict) -> bool:
def stoploss_adjust(self, stop_loss: float, order: Dict, side: str) -> bool:
"""
Verify stop_loss against stoploss-order value (limit or price)
Returns True if adjustment is necessary.
"""
raise OperationalException(f"stoploss is not implemented for {self.name}.")
def stoploss(self, pair: str, amount: float, stop_price: float, order_types: Dict) -> Dict:
def stoploss(self, pair: str, amount: float, stop_price: float,
order_types: Dict, side: str, leverage: float) -> Dict:
"""
creates a stoploss order.
The precise ordertype is determined by the order_types dict or exchange default.
@@ -1528,6 +1595,69 @@ class Exchange:
self._async_get_trade_history(pair=pair, since=since,
until=until, from_id=from_id))
def fill_leverage_brackets(self):
"""
# TODO-lev: Should maybe be renamed, leverage_brackets might not be accurate for kraken
Assigns property _leverage_brackets to a dictionary of information about the leverage
allowed on each pair
"""
return
def get_max_leverage(self, pair: Optional[str], nominal_value: Optional[float]) -> float:
"""
Returns the maximum leverage that a pair can be traded at
:param pair: The base/quote currency pair being traded
:nominal_value: The total value of the trade in quote currency (collateral + debt)
"""
return 1.0
@retrier
def _set_leverage(
self,
leverage: float,
pair: Optional[str] = None,
trading_mode: Optional[TradingMode] = None
):
"""
Set's the leverage before making a trade, in order to not
have the same leverage on every trade
"""
# TODO-lev: Make a documentation page that says you can't run 2 bots
# TODO-lev: on the same account with leverage
if self._config['dry_run'] or not self.exchange_has("setLeverage"):
# Some exchanges only support one collateral type
return
try:
self._api.set_leverage(symbol=pair, leverage=leverage)
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not set leverage due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
@retrier
def set_margin_mode(self, pair: str, collateral: Collateral, params: dict = {}):
'''
Set's the margin mode on the exchange to cross or isolated for a specific pair
:param symbol: base/quote currency pair (e.g. "ADA/USDT")
'''
if self._config['dry_run'] or not self.exchange_has("setMarginMode"):
# Some exchanges only support one collateral type
return
try:
self._api.set_margin_mode(pair, collateral.value, params)
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not set margin mode due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
def is_exchange_known_ccxt(exchange_name: str, ccxt_module: CcxtModuleType = None) -> bool:
return exchange_name in ccxt_exchanges(ccxt_module)

View File

@@ -1,9 +1,10 @@
""" FTX exchange subclass """
import logging
from typing import Any, Dict
from typing import Any, Dict, List, Optional, Tuple
import ccxt
from freqtrade.enums import Collateral, TradingMode
from freqtrade.exceptions import (DDosProtection, InsufficientFundsError, InvalidOrderException,
OperationalException, TemporaryError)
from freqtrade.exchange import Exchange
@@ -21,6 +22,12 @@ class Ftx(Exchange):
"ohlcv_candle_limit": 1500,
}
_supported_trading_mode_collateral_pairs: List[Tuple[TradingMode, Collateral]] = [
# TradingMode.SPOT always supported and not required in this list
# (TradingMode.MARGIN, Collateral.CROSS), # TODO-lev: Uncomment once supported
# (TradingMode.FUTURES, Collateral.CROSS) # TODO-lev: Uncomment once supported
]
def market_is_tradable(self, market: Dict[str, Any]) -> bool:
"""
Check if the market symbol is tradable by Freqtrade.
@@ -31,15 +38,19 @@ class Ftx(Exchange):
return (parent_check and
market.get('spot', False) is True)
def stoploss_adjust(self, stop_loss: float, order: Dict) -> bool:
def stoploss_adjust(self, stop_loss: float, order: Dict, side: str) -> bool:
"""
Verify stop_loss against stoploss-order value (limit or price)
Returns True if adjustment is necessary.
"""
return order['type'] == 'stop' and stop_loss > float(order['price'])
return order['type'] == 'stop' and (
side == "sell" and stop_loss > float(order['price']) or
side == "buy" and stop_loss < float(order['price'])
)
@retrier(retries=0)
def stoploss(self, pair: str, amount: float, stop_price: float, order_types: Dict) -> Dict:
def stoploss(self, pair: str, amount: float, stop_price: float,
order_types: Dict, side: str, leverage: float) -> Dict:
"""
Creates a stoploss order.
depending on order_types.stoploss configuration, uses 'market' or limit order.
@@ -47,7 +58,10 @@ class Ftx(Exchange):
Limit orders are defined by having orderPrice set, otherwise a market order is used.
"""
limit_price_pct = order_types.get('stoploss_on_exchange_limit_ratio', 0.99)
limit_rate = stop_price * limit_price_pct
if side == "sell":
limit_rate = stop_price * limit_price_pct
else:
limit_rate = stop_price * (2 - limit_price_pct)
ordertype = "stop"
@@ -55,7 +69,7 @@ class Ftx(Exchange):
if self._config['dry_run']:
dry_order = self.create_dry_run_order(
pair, ordertype, "sell", amount, stop_price)
pair, ordertype, side, amount, stop_price, leverage)
return dry_order
try:
@@ -67,7 +81,8 @@ class Ftx(Exchange):
params['stopPrice'] = stop_price
amount = self.amount_to_precision(pair, amount)
order = self._api.create_order(symbol=pair, type=ordertype, side='sell',
self._lev_prep(pair, leverage)
order = self._api.create_order(symbol=pair, type=ordertype, side=side,
amount=amount, params=params)
self._log_exchange_response('create_stoploss_order', order)
logger.info('stoploss order added for %s. '
@@ -75,19 +90,19 @@ class Ftx(Exchange):
return order
except ccxt.InsufficientFunds as e:
raise InsufficientFundsError(
f'Insufficient funds to create {ordertype} sell order on market {pair}. '
f'Insufficient funds to create {ordertype} {side} order on market {pair}. '
f'Tried to create stoploss with amount {amount} at stoploss {stop_price}. '
f'Message: {e}') from e
except ccxt.InvalidOrder as e:
raise InvalidOrderException(
f'Could not create {ordertype} sell order on market {pair}. '
f'Could not create {ordertype} {side} order on market {pair}. '
f'Tried to create stoploss with amount {amount} at stoploss {stop_price}. '
f'Message: {e}') from e
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not place sell order due to {e.__class__.__name__}. Message: {e}') from e
f'Could not place {side} order due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
@@ -152,3 +167,18 @@ class Ftx(Exchange):
if order['type'] == 'stop':
return safe_value_fallback2(order, order, 'id_stop', 'id')
return order['id']
def fill_leverage_brackets(self):
"""
FTX leverage is static across the account, and doesn't change from pair to pair,
so _leverage_brackets doesn't need to be set
"""
return
def get_max_leverage(self, pair: Optional[str], nominal_value: Optional[float]) -> float:
"""
Returns the maximum leverage that a pair can be traded at, which is always 20 on ftx
:param pair: Here for super method, not used on FTX
:nominal_value: Here for super method, not used on FTX
"""
return 20.0

View File

@@ -1,9 +1,10 @@
""" Kraken exchange subclass """
import logging
from typing import Any, Dict
from typing import Any, Dict, List, Optional, Tuple
import ccxt
from freqtrade.enums import Collateral, TradingMode
from freqtrade.exceptions import (DDosProtection, InsufficientFundsError, InvalidOrderException,
OperationalException, TemporaryError)
from freqtrade.exchange import Exchange
@@ -23,6 +24,12 @@ class Kraken(Exchange):
"trades_pagination_arg": "since",
}
_supported_trading_mode_collateral_pairs: List[Tuple[TradingMode, Collateral]] = [
# TradingMode.SPOT always supported and not required in this list
# (TradingMode.MARGIN, Collateral.CROSS), # TODO-lev: Uncomment once supported
# (TradingMode.FUTURES, Collateral.CROSS) # TODO-lev: No CCXT support
]
def market_is_tradable(self, market: Dict[str, Any]) -> bool:
"""
Check if the market symbol is tradable by Freqtrade.
@@ -67,16 +74,19 @@ class Kraken(Exchange):
except ccxt.BaseError as e:
raise OperationalException(e) from e
def stoploss_adjust(self, stop_loss: float, order: Dict) -> bool:
def stoploss_adjust(self, stop_loss: float, order: Dict, side: str) -> bool:
"""
Verify stop_loss against stoploss-order value (limit or price)
Returns True if adjustment is necessary.
"""
return (order['type'] in ('stop-loss', 'stop-loss-limit')
and stop_loss > float(order['price']))
return (order['type'] in ('stop-loss', 'stop-loss-limit') and (
(side == "sell" and stop_loss > float(order['price'])) or
(side == "buy" and stop_loss < float(order['price']))
))
@retrier(retries=0)
def stoploss(self, pair: str, amount: float, stop_price: float, order_types: Dict) -> Dict:
def stoploss(self, pair: str, amount: float, stop_price: float,
order_types: Dict, side: str, leverage: float) -> Dict:
"""
Creates a stoploss market order.
Stoploss market orders is the only stoploss type supported by kraken.
@@ -86,7 +96,10 @@ class Kraken(Exchange):
if order_types.get('stoploss', 'market') == 'limit':
ordertype = "stop-loss-limit"
limit_price_pct = order_types.get('stoploss_on_exchange_limit_ratio', 0.99)
limit_rate = stop_price * limit_price_pct
if side == "sell":
limit_rate = stop_price * limit_price_pct
else:
limit_rate = stop_price * (2 - limit_price_pct)
params['price2'] = self.price_to_precision(pair, limit_rate)
else:
ordertype = "stop-loss"
@@ -95,13 +108,13 @@ class Kraken(Exchange):
if self._config['dry_run']:
dry_order = self.create_dry_run_order(
pair, ordertype, "sell", amount, stop_price)
pair, ordertype, side, amount, stop_price, leverage)
return dry_order
try:
amount = self.amount_to_precision(pair, amount)
order = self._api.create_order(symbol=pair, type=ordertype, side='sell',
order = self._api.create_order(symbol=pair, type=ordertype, side=side,
amount=amount, price=stop_price, params=params)
self._log_exchange_response('create_stoploss_order', order)
logger.info('stoploss order added for %s. '
@@ -109,18 +122,70 @@ class Kraken(Exchange):
return order
except ccxt.InsufficientFunds as e:
raise InsufficientFundsError(
f'Insufficient funds to create {ordertype} sell order on market {pair}. '
f'Insufficient funds to create {ordertype} {side} order on market {pair}. '
f'Tried to create stoploss with amount {amount} at stoploss {stop_price}. '
f'Message: {e}') from e
except ccxt.InvalidOrder as e:
raise InvalidOrderException(
f'Could not create {ordertype} sell order on market {pair}. '
f'Could not create {ordertype} {side} order on market {pair}. '
f'Tried to create stoploss with amount {amount} at stoploss {stop_price}. '
f'Message: {e}') from e
except ccxt.DDoSProtection as e:
raise DDosProtection(e) from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not place sell order due to {e.__class__.__name__}. Message: {e}') from e
f'Could not place {side} order due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
def fill_leverage_brackets(self):
"""
Assigns property _leverage_brackets to a dictionary of information about the leverage
allowed on each pair
"""
leverages = {}
for pair, market in self.markets.items():
leverages[pair] = [1]
info = market['info']
leverage_buy = info.get('leverage_buy', [])
leverage_sell = info.get('leverage_sell', [])
if len(leverage_buy) > 0 or len(leverage_sell) > 0:
if leverage_buy != leverage_sell:
logger.warning(
f"The buy({leverage_buy}) and sell({leverage_sell}) leverage are not equal"
"for {pair}. Please notify freqtrade because this has never happened before"
)
if max(leverage_buy) <= max(leverage_sell):
leverages[pair] += [int(lev) for lev in leverage_buy]
else:
leverages[pair] += [int(lev) for lev in leverage_sell]
else:
leverages[pair] += [int(lev) for lev in leverage_buy]
self._leverage_brackets = leverages
def get_max_leverage(self, pair: Optional[str], nominal_value: Optional[float]) -> float:
"""
Returns the maximum leverage that a pair can be traded at
:param pair: The base/quote currency pair being traded
:nominal_value: Here for super class, not needed on Kraken
"""
return float(max(self._leverage_brackets[pair]))
def _set_leverage(
self,
leverage: float,
pair: Optional[str] = None,
trading_mode: Optional[TradingMode] = None
):
"""
Kraken set's the leverage as an option in the order object, so we need to
add it to params
"""
return
def _get_params(self, ordertype: str, leverage: float, time_in_force: str = 'gtc') -> Dict:
params = super()._get_params(ordertype, leverage, time_in_force)
if leverage > 1.0:
params['leverage'] = leverage
return params

View File

@@ -85,10 +85,10 @@ class FreqtradeBot(LoggingMixin):
self.dataprovider = DataProvider(self.config, self.exchange, self.pairlists)
# Attach Dataprovider to Strategy baseclass
IStrategy.dp = self.dataprovider
# Attach Wallets to Strategy baseclass
IStrategy.wallets = self.wallets
# Attach Dataprovider to strategy instance
self.strategy.dp = self.dataprovider
# Attach Wallets to strategy instance
self.strategy.wallets = self.wallets
# Initializing Edge only if enabled
self.edge = Edge(self.config, self.exchange, self.strategy) if \
@@ -162,7 +162,7 @@ class FreqtradeBot(LoggingMixin):
# Refreshing candles
self.dataprovider.refresh(self.pairlists.create_pair_list(self.active_pair_whitelist),
self.strategy.informative_pairs())
self.strategy.gather_informative_pairs())
strategy_safe_wrapper(self.strategy.bot_loop_start, supress_error=True)()
@@ -735,9 +735,14 @@ class FreqtradeBot(LoggingMixin):
:return: True if the order succeeded, and False in case of problems.
"""
try:
stoploss_order = self.exchange.stoploss(pair=trade.pair, amount=trade.amount,
stop_price=stop_price,
order_types=self.strategy.order_types)
stoploss_order = self.exchange.stoploss(
pair=trade.pair,
amount=trade.amount,
stop_price=stop_price,
order_types=self.strategy.order_types,
side=trade.exit_side,
leverage=trade.leverage
)
order_obj = Order.parse_from_ccxt_object(stoploss_order, trade.pair, 'stoploss')
trade.orders.append(order_obj)
@@ -829,11 +834,11 @@ class FreqtradeBot(LoggingMixin):
# if trailing stoploss is enabled we check if stoploss value has changed
# in which case we cancel stoploss order and put another one with new
# value immediately
self.handle_trailing_stoploss_on_exchange(trade, stoploss_order)
self.handle_trailing_stoploss_on_exchange(trade, stoploss_order, side=trade.exit_side)
return False
def handle_trailing_stoploss_on_exchange(self, trade: Trade, order: dict) -> None:
def handle_trailing_stoploss_on_exchange(self, trade: Trade, order: dict, side: str) -> None:
"""
Check to see if stoploss on exchange should be updated
in case of trailing stoploss on exchange
@@ -841,7 +846,7 @@ class FreqtradeBot(LoggingMixin):
:param order: Current on exchange stoploss order
:return: None
"""
if self.exchange.stoploss_adjust(trade.stop_loss, order):
if self.exchange.stoploss_adjust(trade.stop_loss, order, side):
# we check if the update is necessary
update_beat = self.strategy.order_types.get('stoploss_on_exchange_interval', 60)
if (datetime.utcnow() - trade.stoploss_last_update).total_seconds() >= update_beat:

View File

@@ -20,7 +20,7 @@ def interest(
:param exchange_name: The exchanged being trading on
:param borrowed: The amount of currency being borrowed
:param rate: The rate of interest
:param rate: The rate of interest (i.e daily interest rate)
:param hours: The time in hours that the currency has been borrowed for
Raises:
@@ -36,7 +36,8 @@ def interest(
# Rounded based on https://kraken-fees-calculator.github.io/
return borrowed * rate * (one+ceil(hours/four))
elif exchange_name == "ftx":
# TODO-lev: Add FTX interest formula
raise OperationalException(f"Leverage not available on {exchange_name} with freqtrade")
# As Explained under #Interest rates section in
# https://help.ftx.com/hc/en-us/articles/360053007671-Spot-Margin-Trading-Explainer
return borrowed * rate * ceil(hours)/twenty_four
else:
raise OperationalException(f"Leverage not available on {exchange_name} with freqtrade")

View File

@@ -157,7 +157,7 @@ class Backtesting:
self.strategy: IStrategy = strategy
strategy.dp = self.dataprovider
# Attach Wallets to Strategy baseclass
IStrategy.wallets = self.wallets
strategy.wallets = self.wallets
# Set stoploss_on_exchange to false for backtesting,
# since a "perfect" stoploss-sell is assumed anyway
# And the regular "stoploss" function would not apply to that case

View File

@@ -8,6 +8,7 @@ from typing import Any, Dict
from freqtrade import constants
from freqtrade.configuration import TimeRange, validate_config_consistency
from freqtrade.data.dataprovider import DataProvider
from freqtrade.edge import Edge
from freqtrade.optimize.optimize_reports import generate_edge_table
from freqtrade.resolvers import ExchangeResolver, StrategyResolver
@@ -33,6 +34,7 @@ class EdgeCli:
self.config['stake_amount'] = constants.UNLIMITED_STAKE_AMOUNT
self.exchange = ExchangeResolver.load_exchange(self.config['exchange']['name'], self.config)
self.strategy = StrategyResolver.load_strategy(self.config)
self.strategy.dp = DataProvider(config, None)
validate_config_consistency(self.config)

View File

@@ -7,6 +7,7 @@ from pathlib import Path
from typing import Any, Dict, Iterator, List, Optional, Tuple
import numpy as np
import pandas as pd
import rapidjson
import tabulate
from colorama import Fore, Style
@@ -298,8 +299,8 @@ class HyperoptTools():
f"Objective: {results['loss']:.5f}")
@staticmethod
def prepare_trials_columns(trials, legacy_mode: bool, has_drawdown: bool) -> str:
def prepare_trials_columns(trials: pd.DataFrame, legacy_mode: bool,
has_drawdown: bool) -> pd.DataFrame:
trials['Best'] = ''
if 'results_metrics.winsdrawslosses' not in trials.columns:
@@ -435,8 +436,7 @@ class HyperoptTools():
return table
@staticmethod
def export_csv_file(config: dict, results: list, total_epochs: int, highlight_best: bool,
csv_file: str) -> None:
def export_csv_file(config: dict, results: list, csv_file: str) -> None:
"""
Log result to csv-file
"""

View File

@@ -2,7 +2,7 @@
This module contains the class to persist trades into SQLite
"""
import logging
from datetime import datetime, timezone
from datetime import datetime, timedelta, timezone
from decimal import Decimal
from typing import Any, Dict, List, Optional
@@ -1026,17 +1026,21 @@ class Trade(_DECL_BASE, LocalTrade):
return total_open_stake_amount or 0
@staticmethod
def get_overall_performance() -> List[Dict[str, Any]]:
def get_overall_performance(minutes=None) -> List[Dict[str, Any]]:
"""
Returns List of dicts containing all Trades, including profit and trade count
NOTE: Not supported in Backtesting.
"""
filters = [Trade.is_open.is_(False)]
if minutes:
start_date = datetime.now(timezone.utc) - timedelta(minutes=minutes)
filters.append(Trade.close_date >= start_date)
pair_rates = Trade.query.with_entities(
Trade.pair,
func.sum(Trade.close_profit).label('profit_sum'),
func.sum(Trade.close_profit_abs).label('profit_sum_abs'),
func.count(Trade.pair).label('count')
).filter(Trade.is_open.is_(False))\
).filter(*filters)\
.group_by(Trade.pair) \
.order_by(desc('profit_sum_abs')) \
.all()

View File

@@ -2,7 +2,7 @@
Performance pair list filter
"""
import logging
from typing import Dict, List
from typing import Any, Dict, List
import pandas as pd
@@ -15,6 +15,13 @@ logger = logging.getLogger(__name__)
class PerformanceFilter(IPairList):
def __init__(self, exchange, pairlistmanager,
config: Dict[str, Any], pairlistconfig: Dict[str, Any],
pairlist_pos: int) -> None:
super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
self._minutes = pairlistconfig.get('minutes', 0)
@property
def needstickers(self) -> bool:
"""
@@ -40,7 +47,7 @@ class PerformanceFilter(IPairList):
"""
# Get the trading performance for pairs from database
try:
performance = pd.DataFrame(Trade.get_overall_performance())
performance = pd.DataFrame(Trade.get_overall_performance(self._minutes))
except AttributeError:
# Performancefilter does not work in backtesting.
self.log_once("PerformanceFilter is not available in this mode.", logger.warning)

View File

@@ -46,6 +46,12 @@ class Balances(BaseModel):
value: float
stake: str
note: str
starting_capital: float
starting_capital_ratio: float
starting_capital_pct: float
starting_capital_fiat: float
starting_capital_fiat_ratio: float
starting_capital_fiat_pct: float
class Count(BaseModel):

View File

@@ -459,6 +459,9 @@ class RPC:
raise RPCException('Error getting current tickers.')
self._freqtrade.wallets.update(require_update=False)
starting_capital = self._freqtrade.wallets.get_starting_balance()
starting_cap_fiat = self._fiat_converter.convert_amount(
starting_capital, stake_currency, fiat_display_currency) if self._fiat_converter else 0
for coin, balance in self._freqtrade.wallets.get_all_balances().items():
if not balance.total:
@@ -494,15 +497,25 @@ class RPC:
else:
raise RPCException('All balances are zero.')
symbol = fiat_display_currency
value = self._fiat_converter.convert_amount(total, stake_currency,
symbol) if self._fiat_converter else 0
value = self._fiat_converter.convert_amount(
total, stake_currency, fiat_display_currency) if self._fiat_converter else 0
starting_capital_ratio = 0.0
starting_capital_ratio = (total / starting_capital) - 1 if starting_capital else 0.0
starting_cap_fiat_ratio = (value / starting_cap_fiat) - 1 if starting_cap_fiat else 0.0
return {
'currencies': output,
'total': total,
'symbol': symbol,
'symbol': fiat_display_currency,
'value': value,
'stake': stake_currency,
'starting_capital': starting_capital,
'starting_capital_ratio': starting_capital_ratio,
'starting_capital_pct': round(starting_capital_ratio * 100, 2),
'starting_capital_fiat': starting_cap_fiat,
'starting_capital_fiat_ratio': starting_cap_fiat_ratio,
'starting_capital_fiat_pct': round(starting_cap_fiat_ratio * 100, 2),
'note': 'Simulated balances' if self._freqtrade.config['dry_run'] else ''
}

View File

@@ -603,12 +603,15 @@ class Telegram(RPCHandler):
output = ''
if self._config['dry_run']:
output += (
f"*Warning:* Simulated balances in Dry Mode.\n"
"This mode is still experimental!\n"
"Starting capital: "
f"`{self._config['dry_run_wallet']}` {self._config['stake_currency']}.\n"
)
output += "*Warning:* Simulated balances in Dry Mode.\n"
output += ("Starting capital: "
f"`{result['starting_capital']}` {self._config['stake_currency']}"
)
output += (f" `{result['starting_capital_fiat']}` "
f"{self._config['fiat_display_currency']}.\n"
) if result['starting_capital_fiat'] > 0 else '.\n'
total_dust_balance = 0
total_dust_currencies = 0
for curr in result['currencies']:
@@ -641,9 +644,12 @@ class Telegram(RPCHandler):
f"{round_coin_value(total_dust_balance, result['stake'], False)}`\n")
output += ("\n*Estimated Value*:\n"
f"\t`{result['stake']}: {result['total']: .8f}`\n"
f"\t`{result['stake']}: "
f"{round_coin_value(result['total'], result['stake'], False)}`"
f" `({result['starting_capital_pct']}%)`\n"
f"\t`{result['symbol']}: "
f"{round_coin_value(result['value'], result['symbol'], False)}`\n")
f"{round_coin_value(result['value'], result['symbol'], False)}`"
f" `({result['starting_capital_fiat_pct']}%)`\n")
self._send_msg(output, reload_able=True, callback_path="update_balance",
query=update.callback_query)
except RPCException as e:

View File

@@ -3,5 +3,7 @@ from freqtrade.exchange import (timeframe_to_minutes, timeframe_to_msecs, timefr
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.strategy_helper import merge_informative_pair, stoploss_from_open
from freqtrade.strategy.strategy_helper import (merge_informative_pair, stoploss_from_absolute,
stoploss_from_open)

View File

@@ -0,0 +1,128 @@
from typing import Any, Callable, NamedTuple, Optional, Union
from pandas import DataFrame
from freqtrade.exceptions import OperationalException
from freqtrade.strategy.strategy_helper import merge_informative_pair
PopulateIndicators = Callable[[Any, DataFrame, dict], DataFrame]
class InformativeData(NamedTuple):
asset: Optional[str]
timeframe: str
fmt: Union[str, Callable[[Any], str], None]
ffill: bool
def informative(timeframe: str, asset: str = '',
fmt: Optional[Union[str, Callable[[Any], str]]] = None,
ffill: bool = True) -> Callable[[PopulateIndicators], PopulateIndicators]:
"""
A decorator for populate_indicators_Nn(self, dataframe, metadata), allowing these functions to
define informative indicators.
Example usage:
@informative('1h')
def populate_indicators_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
return dataframe
:param timeframe: Informative timeframe. Must always be equal or higher than strategy timeframe.
:param asset: Informative asset, for example BTC, BTC/USDT, ETH/BTC. Do not specify to use
current pair.
:param fmt: Column format (str) or column formatter (callable(name, asset, timeframe)). When not
specified, defaults to:
* {base}_{quote}_{column}_{timeframe} if asset is specified.
* {column}_{timeframe} if asset is not specified.
Format string supports these format variables:
* {asset} - full name of the asset, for example 'BTC/USDT'.
* {base} - base currency in lower case, for example 'eth'.
* {BASE} - same as {base}, except in upper case.
* {quote} - quote currency in lower case, for example 'usdt'.
* {QUOTE} - same as {quote}, except in upper case.
* {column} - name of dataframe column.
* {timeframe} - timeframe of informative dataframe.
:param ffill: ffill dataframe after merging informative pair.
"""
_asset = asset
_timeframe = timeframe
_fmt = fmt
_ffill = ffill
def decorator(fn: PopulateIndicators):
informative_pairs = getattr(fn, '_ft_informative', [])
informative_pairs.append(InformativeData(_asset, _timeframe, _fmt, _ffill))
setattr(fn, '_ft_informative', informative_pairs)
return fn
return decorator
def _format_pair_name(config, pair: str) -> str:
return pair.format(stake_currency=config['stake_currency'],
stake=config['stake_currency']).upper()
def _create_and_merge_informative_pair(strategy, dataframe: DataFrame, metadata: dict,
inf_data: InformativeData,
populate_indicators: PopulateIndicators):
asset = inf_data.asset or ''
timeframe = inf_data.timeframe
fmt = inf_data.fmt
config = strategy.config
if asset:
# Insert stake currency if needed.
asset = _format_pair_name(config, asset)
else:
# Not specifying an asset will define informative dataframe for current pair.
asset = metadata['pair']
if '/' in asset:
base, quote = asset.split('/')
else:
# When futures are supported this may need reevaluation.
# base, quote = asset, ''
raise OperationalException('Not implemented.')
# Default format. This optimizes for the common case: informative pairs using same stake
# currency. When quote currency matches stake currency, column name will omit base currency.
# This allows easily reconfiguring strategy to use different base currency. In a rare case
# where it is desired to keep quote currency in column name at all times user should specify
# fmt='{base}_{quote}_{column}_{timeframe}' format or similar.
if not fmt:
fmt = '{column}_{timeframe}' # Informatives of current pair
if inf_data.asset:
fmt = '{base}_{quote}_' + fmt # Informatives of other pairs
inf_metadata = {'pair': asset, 'timeframe': timeframe}
inf_dataframe = strategy.dp.get_pair_dataframe(asset, timeframe)
inf_dataframe = populate_indicators(strategy, inf_dataframe, inf_metadata)
formatter: Any = None
if callable(fmt):
formatter = fmt # A custom user-specified formatter function.
else:
formatter = fmt.format # A default string formatter.
fmt_args = {
'BASE': base.upper(),
'QUOTE': quote.upper(),
'base': base.lower(),
'quote': quote.lower(),
'asset': asset,
'timeframe': timeframe,
}
inf_dataframe.rename(columns=lambda column: formatter(column=column, **fmt_args),
inplace=True)
date_column = formatter(column='date', **fmt_args)
if date_column in dataframe.columns:
raise OperationalException(f'Duplicate column name {date_column} exists in '
f'dataframe! Ensure column names are unique!')
dataframe = merge_informative_pair(dataframe, inf_dataframe, strategy.timeframe, timeframe,
ffill=inf_data.ffill, append_timeframe=False,
date_column=date_column)
return dataframe

View File

@@ -19,6 +19,9 @@ from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
from freqtrade.exchange.exchange import timeframe_to_next_date
from freqtrade.persistence import PairLocks, Trade
from freqtrade.strategy.hyper import HyperStrategyMixin
from freqtrade.strategy.informative_decorator import (InformativeData, PopulateIndicators,
_create_and_merge_informative_pair,
_format_pair_name)
from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
from freqtrade.wallets import Wallets
@@ -118,7 +121,7 @@ class IStrategy(ABC, HyperStrategyMixin):
# Class level variables (intentional) containing
# the dataprovider (dp) (access to other candles, historic data, ...)
# and wallets - access to the current balance.
dp: Optional[DataProvider] = None
dp: Optional[DataProvider]
wallets: Optional[Wallets] = None
# Filled from configuration
stake_currency: str
@@ -134,6 +137,24 @@ class IStrategy(ABC, HyperStrategyMixin):
self._last_candle_seen_per_pair: Dict[str, datetime] = {}
super().__init__(config)
# Gather informative pairs from @informative-decorated methods.
self._ft_informative: List[Tuple[InformativeData, PopulateIndicators]] = []
for attr_name in dir(self.__class__):
cls_method = getattr(self.__class__, attr_name)
if not callable(cls_method):
continue
informative_data_list = getattr(cls_method, '_ft_informative', None)
if not isinstance(informative_data_list, list):
# Type check is required because mocker would return a mock object that evaluates to
# True, confusing this code.
continue
strategy_timeframe_minutes = timeframe_to_minutes(self.timeframe)
for informative_data in informative_data_list:
if timeframe_to_minutes(informative_data.timeframe) < strategy_timeframe_minutes:
raise OperationalException('Informative timeframe must be equal or higher than '
'strategy timeframe!')
self._ft_informative.append((informative_data, cls_method))
@abstractmethod
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
@@ -379,6 +400,23 @@ class IStrategy(ABC, HyperStrategyMixin):
# END - Intended to be overridden by strategy
###
def gather_informative_pairs(self) -> ListPairsWithTimeframes:
"""
Internal method which gathers all informative pairs (user or automatically defined).
"""
informative_pairs = self.informative_pairs()
for inf_data, _ in self._ft_informative:
if inf_data.asset:
pair_tf = (_format_pair_name(self.config, inf_data.asset), inf_data.timeframe)
informative_pairs.append(pair_tf)
else:
if not self.dp:
raise OperationalException('@informative decorator with unspecified asset '
'requires DataProvider instance.')
for pair in self.dp.current_whitelist():
informative_pairs.append((pair, inf_data.timeframe))
return list(set(informative_pairs))
def get_strategy_name(self) -> str:
"""
Returns strategy class name
@@ -878,6 +916,12 @@ class IStrategy(ABC, HyperStrategyMixin):
:return: a Dataframe with all mandatory indicators for the strategies
"""
logger.debug(f"Populating indicators for pair {metadata.get('pair')}.")
# call populate_indicators_Nm() which were tagged with @informative decorator.
for inf_data, populate_fn in self._ft_informative:
dataframe = _create_and_merge_informative_pair(
self, dataframe, metadata, inf_data, populate_fn)
if self._populate_fun_len == 2:
warnings.warn("deprecated - check out the Sample strategy to see "
"the current function headers!", DeprecationWarning)

View File

@@ -5,7 +5,9 @@ from freqtrade.exchange import timeframe_to_minutes
def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame,
timeframe: str, timeframe_inf: str, ffill: bool = True) -> pd.DataFrame:
timeframe: str, timeframe_inf: str, ffill: bool = True,
append_timeframe: bool = True,
date_column: str = 'date') -> pd.DataFrame:
"""
Correctly merge informative samples to the original dataframe, avoiding lookahead bias.
@@ -25,6 +27,8 @@ def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame,
:param timeframe: Timeframe of the original pair sample.
:param timeframe_inf: Timeframe of the informative pair sample.
:param ffill: Forwardfill missing values - optional but usually required
:param append_timeframe: Rename columns by appending timeframe.
:param date_column: A custom date column name.
:return: Merged dataframe
:raise: ValueError if the secondary timeframe is shorter than the dataframe timeframe
"""
@@ -33,25 +37,29 @@ def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame,
minutes = timeframe_to_minutes(timeframe)
if minutes == minutes_inf:
# No need to forwardshift if the timeframes are identical
informative['date_merge'] = informative["date"]
informative['date_merge'] = informative[date_column]
elif minutes < minutes_inf:
# Subtract "small" timeframe so merging is not delayed by 1 small candle
# Detailed explanation in https://github.com/freqtrade/freqtrade/issues/4073
informative['date_merge'] = (
informative["date"] + pd.to_timedelta(minutes_inf, 'm') - pd.to_timedelta(minutes, 'm')
informative[date_column] + pd.to_timedelta(minutes_inf, 'm') -
pd.to_timedelta(minutes, 'm')
)
else:
raise ValueError("Tried to merge a faster timeframe to a slower timeframe."
"This would create new rows, and can throw off your regular indicators.")
# Rename columns to be unique
informative.columns = [f"{col}_{timeframe_inf}" for col in informative.columns]
date_merge = 'date_merge'
if append_timeframe:
date_merge = f'date_merge_{timeframe_inf}'
informative.columns = [f"{col}_{timeframe_inf}" for col in informative.columns]
# Combine the 2 dataframes
# all indicators on the informative sample MUST be calculated before this point
dataframe = pd.merge(dataframe, informative, left_on='date',
right_on=f'date_merge_{timeframe_inf}', how='left')
dataframe = dataframe.drop(f'date_merge_{timeframe_inf}', axis=1)
right_on=date_merge, how='left')
dataframe = dataframe.drop(date_merge, axis=1)
if ffill:
dataframe = dataframe.ffill()
@@ -97,3 +105,28 @@ def stoploss_from_open(
return min(stoploss, 0.0)
else:
return max(stoploss, 0.0)
def stoploss_from_absolute(stop_rate: float, current_rate: float) -> float:
"""
Given current price and desired stop price, return a stop loss value that is relative to current
price.
The requested stop can be positive for a stop above the open price, or negative for
a stop below the open price. The return value is always >= 0.
Returns 0 if the resulting stop price would be above the current price.
:param stop_rate: Stop loss price.
:param current_rate: Current asset price.
:return: Positive stop loss value relative to current price
"""
# formula is undefined for current_rate 0, return maximum value
if current_rate == 0:
return 1
stoploss = 1 - (stop_rate / current_rate)
# negative stoploss values indicate the requested stop price is higher than the current price
return max(stoploss, 0.0)