# pragma pylint: disable=W0603 """ Cryptocurrency Exchanges support """ import asyncio import inspect import logging import signal from copy import deepcopy from datetime import datetime, timedelta, timezone from math import floor from threading import Lock from typing import Any, Callable, Coroutine, Dict, List, Literal, Optional, Tuple, Union import ccxt import ccxt.async_support as ccxt_async from cachetools import TTLCache from ccxt import TICK_SIZE from dateutil import parser from pandas import DataFrame, concat from freqtrade.constants import (DEFAULT_AMOUNT_RESERVE_PERCENT, DEFAULT_TRADES_COLUMNS, NON_OPEN_EXCHANGE_STATES, BidAsk, BuySell, Config, EntryExit, ExchangeConfig, ListPairsWithTimeframes, MakerTaker, OBLiteral, PairWithTimeframe) from freqtrade.data.converter import clean_ohlcv_dataframe, ohlcv_to_dataframe, trades_dict_to_list from freqtrade.data.converter.converter import (_calculate_ohlcv_candle_start_and_end, clean_duplicate_trades, public_trades_to_dataframe) from freqtrade.enums import OPTIMIZE_MODES, CandleType, MarginMode, PriceType, RunMode, TradingMode from freqtrade.exceptions import (DDosProtection, ExchangeError, InsufficientFundsError, InvalidOrderException, OperationalException, PricingError, RetryableOrderError, TemporaryError) from freqtrade.exchange.common import (API_FETCH_ORDER_RETRY_COUNT, remove_exchange_credentials, retrier, retrier_async) from freqtrade.exchange.exchange_utils import (ROUND, ROUND_DOWN, ROUND_UP, CcxtModuleType, amount_to_contract_precision, amount_to_contracts, amount_to_precision, contracts_to_amount, date_minus_candles, is_exchange_known_ccxt, market_is_active, price_to_precision, timeframe_to_minutes, timeframe_to_msecs, timeframe_to_next_date, timeframe_to_prev_date, timeframe_to_seconds) from freqtrade.exchange.types import OHLCVResponse, OrderBook, Ticker, Tickers, TRADESResponse from freqtrade.misc import (chunks, deep_merge_dicts, file_dump_json, file_load_json, safe_value_fallback2) from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist from freqtrade.util import dt_from_ts, dt_now from freqtrade.util.datetime_helpers import dt_humanize, dt_ts logger = logging.getLogger(__name__) class Exchange: # Parameters to add directly to buy/sell calls (like agreeing to trading agreement) _params: Dict = {} # Additional parameters - added to the ccxt object _ccxt_params: Dict = {} # Dict to specify which options each exchange implements # This defines defaults, which can be selectively overridden by subclasses using _ft_has # or by specifying them in the configuration. _ft_has_default: Dict = { "stoploss_on_exchange": False, "stop_price_param": "stopLossPrice", # Used for stoploss_on_exchange request "stop_price_prop": "stopLossPrice", # Used for stoploss_on_exchange response parsing "order_time_in_force": ["GTC"], "ohlcv_params": {}, "ohlcv_candle_limit": 500, "ohlcv_has_history": True, # Some exchanges (Kraken) don't provide history via ohlcv "ohlcv_partial_candle": True, "ohlcv_require_since": False, # Check https://github.com/ccxt/ccxt/issues/10767 for removal of ohlcv_volume_currency "ohlcv_volume_currency": "base", # "base" or "quote" "tickers_have_quoteVolume": True, "tickers_have_bid_ask": True, # bid / ask empty for fetch_tickers "tickers_have_price": True, "trades_pagination": "time", # Possible are "time" or "id" "trades_pagination_arg": "since", "l2_limit_range": None, "l2_limit_range_required": True, # Allow Empty L2 limit (kucoin) "mark_ohlcv_price": "mark", "mark_ohlcv_timeframe": "8h", "funding_fee_timeframe": "8h", "ccxt_futures_name": "swap", "needs_trading_fees": False, # use fetch_trading_fees to cache fees "order_props_in_contracts": ['amount', 'filled', 'remaining'], # Override createMarketBuyOrderRequiresPrice where ccxt has it wrong "marketOrderRequiresPrice": False, } _ft_has: Dict = {} _ft_has_futures: Dict = {} _supported_trading_mode_margin_pairs: List[Tuple[TradingMode, MarginMode]] = [ # TradingMode.SPOT always supported and not required in this list ] def __init__(self, config: Config, *, exchange_config: Optional[ExchangeConfig] = None, validate: bool = True, load_leverage_tiers: bool = False) -> None: """ Initializes this module with the given config, it does basic validation whether the specified exchange and pairs are valid. :return: None """ self._api: ccxt.Exchange self._api_async: ccxt_async.Exchange = None self._markets: Dict = {} self._trading_fees: Dict[str, Any] = {} self._leverage_tiers: Dict[str, List[Dict]] = {} # Lock event loop. This is necessary to avoid race-conditions when using force* commands # Due to funding fee fetching. self._loop_lock = Lock() self.loop = self._init_async_loop() self._config: Config = {} self._config.update(config) # Holds last candle refreshed time of each pair self._pairs_last_refresh_time: Dict[PairWithTimeframe, int] = {} self._trades_last_refresh_time: Dict[PairWithTimeframe, int] = {} # Timestamp of last markets refresh self._last_markets_refresh: int = 0 # Cache for 10 minutes ... self._cache_lock = Lock() self._fetch_tickers_cache: TTLCache = TTLCache(maxsize=2, ttl=60 * 10) # Cache values for 300 to avoid frequent polling of the exchange for prices # Caching only applies to RPC methods, so prices for open trades are still # refreshed once every iteration. # Shouldn't be too high either, as it'll freeze UI updates in case of open orders. self._exit_rate_cache: TTLCache = TTLCache(maxsize=100, ttl=300) self._entry_rate_cache: TTLCache = TTLCache(maxsize=100, ttl=300) # Holds candles self._klines: Dict[PairWithTimeframe, DataFrame] = {} # Holds public_trades self._trades: Dict[PairWithTimeframe, DataFrame] = {} # Holds all open sell orders for dry_run self._dry_run_open_orders: Dict[str, Any] = {} if config['dry_run']: logger.info('Instance is running with dry_run enabled') logger.info(f"Using CCXT {ccxt.__version__}") exchange_conf: Dict[str, Any] = exchange_config if exchange_config else config['exchange'] remove_exchange_credentials(exchange_conf, config.get('dry_run', False)) self.log_responses = exchange_conf.get('log_responses', False) # Leverage properties self.trading_mode: TradingMode = config.get('trading_mode', TradingMode.SPOT) self.margin_mode: MarginMode = ( MarginMode(config.get('margin_mode')) if config.get('margin_mode') else MarginMode.NONE ) self.liquidation_buffer = config.get('liquidation_buffer', 0.05) # Deep merge ft_has with default ft_has options self._ft_has = deep_merge_dicts(self._ft_has, deepcopy(self._ft_has_default)) if self.trading_mode == TradingMode.FUTURES: self._ft_has = deep_merge_dicts(self._ft_has_futures, self._ft_has) if exchange_conf.get('_ft_has_params'): self._ft_has = deep_merge_dicts(exchange_conf.get('_ft_has_params'), self._ft_has) logger.info("Overriding exchange._ft_has with config params, result: %s", self._ft_has) # Assign this directly for easy access self._ohlcv_partial_candle = self._ft_has['ohlcv_partial_candle'] self._max_trades_candle_limit = self._config.get('exchange', {}).get('trades_candle_limit', 1000) # noqa: E501 self._trades_pagination = self._ft_has['trades_pagination'] self._trades_pagination_arg = self._ft_has['trades_pagination_arg'] # Initialize ccxt objects ccxt_config = self._ccxt_config ccxt_config = deep_merge_dicts(exchange_conf.get('ccxt_config', {}), ccxt_config) ccxt_config = deep_merge_dicts(exchange_conf.get('ccxt_sync_config', {}), ccxt_config) self._api = self._init_ccxt(exchange_conf, ccxt_kwargs=ccxt_config) ccxt_async_config = self._ccxt_config ccxt_async_config = deep_merge_dicts(exchange_conf.get('ccxt_config', {}), ccxt_async_config) ccxt_async_config = deep_merge_dicts(exchange_conf.get('ccxt_async_config', {}), ccxt_async_config) self._api_async = self._init_ccxt( exchange_conf, ccxt_async, ccxt_kwargs=ccxt_async_config) logger.info(f'Using Exchange "{self.name}"') self.required_candle_call_count = 1 if validate: # Initial markets load self._load_markets() self.validate_config(config) self._startup_candle_count: int = config.get('startup_candle_count', 0) self.required_candle_call_count = self.validate_required_startup_candles( self._startup_candle_count, config.get('timeframe', '')) # Converts the interval provided in minutes in config to seconds self.markets_refresh_interval: int = exchange_conf.get( "markets_refresh_interval", 60) * 60 * 1000 if self.trading_mode != TradingMode.SPOT and load_leverage_tiers: self.fill_leverage_tiers() self.additional_exchange_init() def __del__(self): """ Destructor - clean up async stuff """ self.close() def close(self): logger.debug("Exchange object destroyed, closing async loop") if (self._api_async and inspect.iscoroutinefunction(self._api_async.close) and self._api_async.session): logger.debug("Closing async ccxt session.") self.loop.run_until_complete(self._api_async.close()) if self.loop and not self.loop.is_closed(): self.loop.close() def _init_async_loop(self) -> asyncio.AbstractEventLoop: loop = asyncio.new_event_loop() asyncio.set_event_loop(loop) return loop def validate_config(self, config): # Check if timeframe is available self.validate_timeframes(config.get('timeframe')) # Check if all pairs are available self.validate_stakecurrency(config['stake_currency']) if not config['exchange'].get('skip_pair_validation'): self.validate_pairs(config['exchange']['pair_whitelist']) self.validate_ordertypes(config.get('order_types', {})) self.validate_order_time_in_force(config.get('order_time_in_force', {})) self.validate_trading_mode_and_margin_mode(self.trading_mode, self.margin_mode) self.validate_pricing(config['exit_pricing']) self.validate_pricing(config['entry_pricing']) def _init_ccxt(self, exchange_config: Dict[str, Any], ccxt_module: CcxtModuleType = ccxt, ccxt_kwargs: Dict = {}) -> ccxt.Exchange: """ Initialize ccxt with given config and return valid ccxt instance. """ # Find matching class for the given exchange name name = exchange_config['name'] if not is_exchange_known_ccxt(name, ccxt_module): raise OperationalException(f'Exchange {name} is not supported by ccxt') ex_config = { 'apiKey': exchange_config.get('key'), 'secret': exchange_config.get('secret'), 'password': exchange_config.get('password'), 'uid': exchange_config.get('uid', ''), } if ccxt_kwargs: logger.info('Applying additional ccxt config: %s', ccxt_kwargs) if self._ccxt_params: # Inject static options after the above output to not confuse users. ccxt_kwargs = deep_merge_dicts(self._ccxt_params, ccxt_kwargs) if ccxt_kwargs: ex_config.update(ccxt_kwargs) try: api = getattr(ccxt_module, name.lower())(ex_config) except (KeyError, AttributeError) as e: raise OperationalException(f'Exchange {name} is not supported') from e except ccxt.BaseError as e: raise OperationalException(f"Initialization of ccxt failed. Reason: {e}") from e return api @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": self._ft_has["ccxt_futures_name"] } } else: return {} @property def name(self) -> str: """exchange Name (from ccxt)""" return self._api.name @property def id(self) -> str: """exchange ccxt id""" return self._api.id @property def timeframes(self) -> List[str]: return list((self._api.timeframes or {}).keys()) @property def markets(self) -> Dict[str, Any]: """exchange ccxt markets""" if not self._markets: logger.info("Markets were not loaded. Loading them now..") self._load_markets() return self._markets @property def precisionMode(self) -> int: """exchange ccxt precisionMode""" return self._api.precisionMode def additional_exchange_init(self) -> None: """ Additional exchange initialization logic. .api will be available at this point. Must be overridden in child methods if required. """ pass def _log_exchange_response(self, endpoint: str, response, *, add_info=None) -> None: """ Log exchange responses """ if self.log_responses: add_info_str = "" if add_info is None else f" {add_info}: " logger.info(f"API {endpoint}: {add_info_str}{response}") def ohlcv_candle_limit( self, timeframe: str, candle_type: CandleType, since_ms: Optional[int] = None) -> int: """ Exchange ohlcv candle limit Uses ohlcv_candle_limit_per_timeframe if the exchange has different limits per timeframe (e.g. bittrex), otherwise falls back to ohlcv_candle_limit TODO: this is most likely no longer needed since only bittrex needed this. :param timeframe: Timeframe to check :param candle_type: Candle-type :param since_ms: Starting timestamp :return: Candle limit as integer """ return int(self._ft_has.get('ohlcv_candle_limit_per_timeframe', {}).get( timeframe, self._ft_has.get('ohlcv_candle_limit'))) def trades_candle_limit( self, timeframe: str, candle_type: CandleType, since_ms: Optional[int] = None) -> int: """ Exchange trades candle limit Uses trades_candle_limit_per_timeframe if the exchange has different limits per timeframe (e.g. bittrex), otherwise falls back to trades_candle_limit :param timeframe: Timeframe to check :param candle_type: Candle-type :param since_ms: Starting timestamp :return: Candle limit as integer """ #TODO: check if there are trades candle limits return int(self._ft_has.get('trade_candle_limit_per_timeframe', {}).get( timeframe, self._ft_has.get('trade_candle_limit',self._max_trades_candle_limit))) 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]: """ Return exchange ccxt markets, filtered out by base currency and quote currency if this was requested in parameters. """ markets = self.markets if not markets: raise OperationalException("Markets were not loaded.") if base_currencies: markets = {k: v for k, v in markets.items() if v['base'] in base_currencies} if quote_currencies: markets = {k: v for k, v in markets.items() if v['quote'] in quote_currencies} if tradable_only: markets = {k: v for k, v in markets.items() if self.market_is_tradable(v)} if spot_only: markets = {k: v for k, v in markets.items() if self.market_is_spot(v)} if margin_only: markets = {k: v for k, v in markets.items() if self.market_is_margin(v)} if futures_only: markets = {k: v for k, v in markets.items() if self.market_is_future(v)} if active_only: markets = {k: v for k, v in markets.items() if market_is_active(v)} return markets def get_quote_currencies(self) -> List[str]: """ Return a list of supported quote currencies """ markets = self.markets return sorted(set([x['quote'] for _, x in markets.items()])) def get_pair_quote_currency(self, pair: str) -> str: """ Return a pair's quote currency (base/quote:settlement) """ return self.markets.get(pair, {}).get('quote', '') def get_pair_base_currency(self, pair: str) -> str: """ Return a pair's base currency (base/quote:settlement) """ return self.markets.get(pair, {}).get('base', '') def market_is_future(self, market: Dict[str, Any]) -> bool: return ( market.get(self._ft_has["ccxt_futures_name"], False) is True and market.get('linear', False) is True ) def market_is_spot(self, market: Dict[str, Any]) -> bool: return market.get('spot', False) is True def market_is_margin(self, market: Dict[str, Any]) -> bool: return market.get('margin', False) is True def market_is_tradable(self, market: Dict[str, Any]) -> bool: """ Check if the market symbol is tradable by Freqtrade. Ensures that Configured mode aligns to """ return ( market.get('quote', None) is not None and market.get('base', None) is not None and (self.precisionMode != TICK_SIZE # Too low precision will falsify calculations or market.get('precision', {}).get('price') > 1e-11) and ((self.trading_mode == TradingMode.SPOT and self.market_is_spot(market)) or (self.trading_mode == TradingMode.MARGIN and self.market_is_margin(market)) or (self.trading_mode == TradingMode.FUTURES and self.market_is_future(market))) ) def klines(self, pair_interval: PairWithTimeframe, copy: bool = True) -> DataFrame: if pair_interval in self._klines: return self._klines[pair_interval].copy() if copy else self._klines[pair_interval] else: return DataFrame() def trades(self, pair_interval: PairWithTimeframe, copy: bool = True) -> DataFrame: if pair_interval in self._trades: if copy: return self._trades[pair_interval].copy() else: return self._trades[pair_interval] else: return DataFrame() def get_contract_size(self, pair: str) -> Optional[float]: if self.trading_mode == TradingMode.FUTURES: market = self.markets.get(pair, {}) contract_size: float = 1.0 if not market: return None if market.get('contractSize') is not None: # ccxt has contractSize in markets as string contract_size = float(market['contractSize']) return contract_size else: return 1 def _trades_contracts_to_amount(self, trades: List) -> List: if len(trades) > 0 and 'symbol' in trades[0]: contract_size = self.get_contract_size(trades[0]['symbol']) if contract_size != 1: for trade in trades: trade['amount'] = trade['amount'] * contract_size return trades def _order_contracts_to_amount(self, order: Dict) -> Dict: if 'symbol' in order and order['symbol'] is not None: contract_size = self.get_contract_size(order['symbol']) if contract_size != 1: for prop in self._ft_has.get('order_props_in_contracts', []): if prop in order and order[prop] is not None: order[prop] = order[prop] * contract_size return order def _amount_to_contracts(self, pair: str, amount: float) -> float: contract_size = self.get_contract_size(pair) return amount_to_contracts(amount, contract_size) def _contracts_to_amount(self, pair: str, num_contracts: float) -> float: contract_size = self.get_contract_size(pair) return contracts_to_amount(num_contracts, contract_size) def amount_to_contract_precision(self, pair: str, amount: float) -> float: """ Helper wrapper around amount_to_contract_precision """ contract_size = self.get_contract_size(pair) return amount_to_contract_precision(amount, self.get_precision_amount(pair), self.precisionMode, contract_size) def _load_async_markets(self, reload: bool = False) -> None: try: if self._api_async: self.loop.run_until_complete( self._api_async.load_markets(reload=reload, params={})) except (asyncio.TimeoutError, ccxt.BaseError) as e: logger.warning('Could not load async markets. Reason: %s', e) return def _load_markets(self) -> None: """ Initialize markets both sync and async """ try: self._markets = self._api.load_markets(params={}) self._load_async_markets() self._last_markets_refresh = dt_ts() if self._ft_has['needs_trading_fees']: self._trading_fees = self.fetch_trading_fees() except ccxt.BaseError: logger.exception('Unable to initialize markets.') def reload_markets(self, force: bool = False) -> None: """Reload markets both sync and async if refresh interval has passed """ # Check whether markets have to be reloaded if ( not force and self._last_markets_refresh > 0 and (self._last_markets_refresh + self.markets_refresh_interval > dt_ts()) ): return None logger.debug("Performing scheduled market reload..") try: self._markets = self._api.load_markets(reload=True, params={}) # Also reload async markets to avoid issues with newly listed pairs self._load_async_markets(reload=True) self._last_markets_refresh = dt_ts() self.fill_leverage_tiers() except ccxt.BaseError: logger.exception("Could not reload markets.") def validate_stakecurrency(self, stake_currency: str) -> None: """ Checks stake-currency against available currencies on the exchange. Only runs on startup. If markets have not been loaded, there's been a problem with the connection to the exchange. :param stake_currency: Stake-currency to validate :raise: OperationalException if stake-currency is not available. """ if not self._markets: 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( f"{stake_currency} is not available as stake on {self.name}. " f"Available currencies are: {', '.join(quote_currencies)}") def validate_pairs(self, pairs: List[str]) -> None: """ Checks if all given pairs are tradable on the current exchange. :param pairs: list of pairs :raise: OperationalException if one pair is not available :return: None """ if not self.markets: logger.warning('Unable to validate pairs (assuming they are correct).') return extended_pairs = expand_pairlist(pairs, list(self.markets), keep_invalid=True) invalid_pairs = [] for pair in extended_pairs: # Note: ccxt has BaseCurrency/QuoteCurrency format for pairs if self.markets and pair not in self.markets: raise OperationalException( f'Pair {pair} is not available on {self.name} {self.trading_mode.value}. ' f'Please remove {pair} from your whitelist.') # From ccxt Documentation: # markets.info: An associative array of non-common market properties, # including fees, rates, limits and other general market information. # The internal info array is different for each particular market, # its contents depend on the exchange. # It can also be a string or similar ... so we need to verify that first. elif (isinstance(self.markets[pair].get('info'), dict) and self.markets[pair].get('info', {}).get('prohibitedIn', False)): # Warn users about restricted pairs in whitelist. # We cannot determine reliably if Users are affected. logger.warning(f"Pair {pair} is restricted for some users on this exchange." f"Please check if you are impacted by this restriction " f"on the exchange and eventually remove {pair} from your whitelist.") if (self._config['stake_currency'] and self.get_pair_quote_currency(pair) != self._config['stake_currency']): invalid_pairs.append(pair) if invalid_pairs: raise OperationalException( f"Stake-currency '{self._config['stake_currency']}' not compatible with " f"pair-whitelist. Please remove the following pairs: {invalid_pairs}") def get_valid_pair_combination(self, curr_1: str, curr_2: str) -> str: """ Get valid pair combination of curr_1 and curr_2 by trying both combinations. """ for pair in [f"{curr_1}/{curr_2}", f"{curr_2}/{curr_1}"]: if pair in self.markets and self.markets[pair].get('active'): return pair raise ValueError(f"Could not combine {curr_1} and {curr_2} to get a valid pair.") def validate_timeframes(self, timeframe: Optional[str]) -> None: """ Check if timeframe from config is a supported timeframe on the exchange """ if not hasattr(self._api, "timeframes") or self._api.timeframes is None: # If timeframes attribute is missing (or is None), the exchange probably # has no fetchOHLCV method. # Therefore we also show that. raise OperationalException( f"The ccxt library does not provide the list of timeframes " f"for the exchange {self.name} and this exchange " f"is therefore not supported. ccxt fetchOHLCV: {self.exchange_has('fetchOHLCV')}") if timeframe and (timeframe not in self.timeframes): raise OperationalException( f"Invalid timeframe '{timeframe}'. This exchange supports: {self.timeframes}") if ( timeframe and self._config['runmode'] != RunMode.UTIL_EXCHANGE and timeframe_to_minutes(timeframe) < 1 ): raise OperationalException("Timeframes < 1m are currently not supported by Freqtrade.") def validate_ordertypes(self, order_types: Dict) -> None: """ Checks if order-types configured in strategy/config are supported """ if any(v == 'market' for k, v in order_types.items()): if not self.exchange_has('createMarketOrder'): raise OperationalException( f'Exchange {self.name} does not support market orders.') self.validate_stop_ordertypes(order_types) def validate_stop_ordertypes(self, order_types: Dict) -> None: """ Validate stoploss order types """ if (order_types.get("stoploss_on_exchange") and not self._ft_has.get("stoploss_on_exchange", False)): raise OperationalException( f'On exchange stoploss is not supported for {self.name}.' ) if self.trading_mode == TradingMode.FUTURES: price_mapping = self._ft_has.get('stop_price_type_value_mapping', {}).keys() if ( order_types.get("stoploss_on_exchange", False) is True and 'stoploss_price_type' in order_types and order_types['stoploss_price_type'] not in price_mapping ): raise OperationalException( f'On exchange stoploss price type is not supported for {self.name}.' ) def validate_pricing(self, pricing: Dict) -> None: if pricing.get('use_order_book', False) and not self.exchange_has('fetchL2OrderBook'): raise OperationalException(f'Orderbook not available for {self.name}.') if (not pricing.get('use_order_book', False) and ( not self.exchange_has('fetchTicker') or not self._ft_has['tickers_have_price'])): raise OperationalException(f'Ticker pricing not available for {self.name}.') def validate_order_time_in_force(self, order_time_in_force: Dict) -> None: """ Checks if order time in force configured in strategy/config are supported """ if any(v.upper() not in self._ft_has["order_time_in_force"] for k, v in order_time_in_force.items()): raise OperationalException( f'Time in force policies are not supported for {self.name} yet.') def validate_required_startup_candles(self, startup_candles: int, timeframe: str) -> int: """ Checks if required startup_candles is more than ohlcv_candle_limit(). Requires a grace-period of 5 candles - so a startup-period up to 494 is allowed by default. """ candle_limit = self.ohlcv_candle_limit( timeframe, self._config['candle_type_def'], int(date_minus_candles(timeframe, startup_candles).timestamp() * 1000) if timeframe else None) # Require one more candle - to account for the still open candle. candle_count = startup_candles + 1 # Allow 5 calls to the exchange per pair required_candle_call_count = int( (candle_count / candle_limit) + (0 if candle_count % candle_limit == 0 else 1)) if self._ft_has['ohlcv_has_history']: if required_candle_call_count > 5: # Only allow 5 calls per pair to somewhat limit the impact raise OperationalException( f"This strategy requires {startup_candles} candles to start, " "which is more than 5x " f"the amount of candles {self.name} provides for {timeframe}.") elif required_candle_call_count > 1: raise OperationalException( f"This strategy requires {startup_candles} candles to start, which is more than " f"the amount of candles {self.name} provides for {timeframe}.") if required_candle_call_count > 1: logger.warning(f"Using {required_candle_call_count} calls to get OHLCV. " f"This can result in slower operations for the bot. Please check " f"if you really need {startup_candles} candles for your strategy") return required_candle_call_count def validate_trading_mode_and_margin_mode( self, trading_mode: TradingMode, margin_mode: Optional[MarginMode] # Only None when trading_mode = TradingMode.SPOT ): """ Checks if freqtrade can perform trades using the configured trading mode(Margin, Futures) and MarginMode(Cross, Isolated) Throws OperationalException: If the trading_mode/margin_mode type are not supported by freqtrade on this exchange """ if trading_mode != TradingMode.SPOT and ( (trading_mode, margin_mode) not in self._supported_trading_mode_margin_pairs ): mm_value = margin_mode and margin_mode.value raise OperationalException( f"Freqtrade does not support {mm_value} {trading_mode.value} on {self.name}" ) def get_option(self, param: str, default: Optional[Any] = None) -> Any: """ Get parameter value from _ft_has """ return self._ft_has.get(param, default) def exchange_has(self, endpoint: str) -> bool: """ Checks if exchange implements a specific API endpoint. Wrapper around ccxt 'has' attribute :param endpoint: Name of endpoint (e.g. 'fetchOHLCV', 'fetchTickers') :return: bool """ return endpoint in self._api.has and self._api.has[endpoint] def get_precision_amount(self, pair: str) -> Optional[float]: """ Returns the amount precision of the exchange. :param pair: Pair to get precision for :return: precision for amount or None. Must be used in combination with precisionMode """ return self.markets.get(pair, {}).get('precision', {}).get('amount', None) def get_precision_price(self, pair: str) -> Optional[float]: """ Returns the price precision of the exchange. :param pair: Pair to get precision for :return: precision for price or None. Must be used in combination with precisionMode """ return self.markets.get(pair, {}).get('precision', {}).get('price', None) def amount_to_precision(self, pair: str, amount: float) -> float: """ Returns the amount to buy or sell to a precision the Exchange accepts """ return amount_to_precision(amount, self.get_precision_amount(pair), self.precisionMode) def price_to_precision(self, pair: str, price: float, *, rounding_mode: int = ROUND) -> float: """ Returns the price rounded to the precision the Exchange accepts. The default price_rounding_mode in conf is ROUND. For stoploss calculations, must use ROUND_UP for longs, and ROUND_DOWN for shorts. """ return price_to_precision(price, self.get_precision_price(pair), self.precisionMode, rounding_mode=rounding_mode) def price_get_one_pip(self, pair: str, price: float) -> float: """ Get's the "1 pip" value for this pair. Used in PriceFilter to calculate the 1pip movements. """ precision = self.markets[pair]['precision']['price'] if self.precisionMode == TICK_SIZE: return precision else: return 1 / pow(10, precision) def get_min_pair_stake_amount( self, pair: str, price: float, stoploss: float, leverage: Optional[float] = 1.0 ) -> Optional[float]: return self._get_stake_amount_limit(pair, price, stoploss, 'min', leverage) def get_max_pair_stake_amount(self, pair: str, price: float, leverage: float = 1.0) -> float: max_stake_amount = self._get_stake_amount_limit(pair, price, 0.0, 'max', leverage) if max_stake_amount is None: # * Should never be executed raise OperationalException(f'{self.name}.get_max_pair_stake_amount should' 'never set max_stake_amount to None') return max_stake_amount def _get_stake_amount_limit( self, pair: str, price: float, stoploss: float, limit: Literal['min', 'max'], leverage: Optional[float] = 1.0 ) -> Optional[float]: isMin = limit == 'min' try: market = self.markets[pair] except KeyError: raise ValueError(f"Can't get market information for symbol {pair}") if isMin: # reserve some percent defined in config (5% default) + stoploss margin_reserve: float = 1.0 + self._config.get('amount_reserve_percent', DEFAULT_AMOUNT_RESERVE_PERCENT) stoploss_reserve = ( margin_reserve / (1 - abs(stoploss)) if abs(stoploss) != 1 else 1.5 ) # it should not be more than 50% stoploss_reserve = max(min(stoploss_reserve, 1.5), 1) else: margin_reserve = 1.0 stoploss_reserve = 1.0 stake_limits = [] limits = market['limits'] if (limits['cost'][limit] is not None): stake_limits.append( self._contracts_to_amount(pair, limits['cost'][limit]) * stoploss_reserve ) if (limits['amount'][limit] is not None): stake_limits.append( self._contracts_to_amount(pair, limits['amount'][limit]) * price * margin_reserve ) if not stake_limits: return None if isMin else float('inf') # 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 self._get_stake_amount_considering_leverage( max(stake_limits) if isMin else min(stake_limits), leverage or 1.0 ) def _get_stake_amount_considering_leverage(self, stake_amount: float, leverage: float) -> 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, leverage: float, params: Dict = {}, stop_loss: bool = False) -> Dict[str, Any]: now = dt_now() order_id = f'dry_run_{side}_{pair}_{now.timestamp()}' # Rounding here must respect to contract sizes _amount = self._contracts_to_amount( pair, self.amount_to_precision(pair, self._amount_to_contracts(pair, amount))) dry_order: Dict[str, Any] = { 'id': order_id, 'symbol': pair, 'price': rate, 'average': rate, 'amount': _amount, 'cost': _amount * rate, 'type': ordertype, 'side': side, 'filled': 0, 'remaining': _amount, 'datetime': now.strftime('%Y-%m-%dT%H:%M:%S.%fZ'), 'timestamp': dt_ts(now), 'status': "open", 'fee': None, 'info': {}, 'leverage': leverage } if stop_loss: dry_order["info"] = {"stopPrice": dry_order["price"]} dry_order[self._ft_has['stop_price_prop']] = dry_order["price"] # Workaround to avoid filling stoploss orders immediately dry_order["ft_order_type"] = "stoploss" orderbook: Optional[OrderBook] = None if self.exchange_has('fetchL2OrderBook'): orderbook = self.fetch_l2_order_book(pair, 20) if ordertype == "limit" and orderbook: # Allow a 1% price difference allowed_diff = 0.01 if self._dry_is_price_crossed(pair, side, rate, orderbook, allowed_diff): logger.info( f"Converted order {pair} to market order due to price {rate} crossing spread " f"by more than {allowed_diff:.2%}.") dry_order["type"] = "market" if dry_order["type"] == "market" and not dry_order.get("ft_order_type"): # Update market order pricing average = self.get_dry_market_fill_price(pair, side, amount, rate, orderbook) dry_order.update({ 'average': average, 'filled': _amount, 'remaining': 0.0, 'status': "closed", 'cost': (dry_order['amount'] * average) }) # market orders will always incurr taker fees dry_order = self.add_dry_order_fee(pair, dry_order, 'taker') dry_order = self.check_dry_limit_order_filled( dry_order, immediate=True, orderbook=orderbook) self._dry_run_open_orders[dry_order["id"]] = dry_order # Copy order and close it - so the returned order is open unless it's a market order return dry_order def add_dry_order_fee( self, pair: str, dry_order: Dict[str, Any], taker_or_maker: MakerTaker, ) -> Dict[str, Any]: fee = self.get_fee(pair, taker_or_maker=taker_or_maker) dry_order.update({ 'fee': { 'currency': self.get_pair_quote_currency(pair), 'cost': dry_order['cost'] * fee, 'rate': fee } }) return dry_order def get_dry_market_fill_price(self, pair: str, side: str, amount: float, rate: float, orderbook: Optional[OrderBook]) -> float: """ Get the market order fill price based on orderbook interpolation """ if self.exchange_has('fetchL2OrderBook'): if not orderbook: orderbook = self.fetch_l2_order_book(pair, 20) ob_type: OBLiteral = 'asks' if side == 'buy' else 'bids' slippage = 0.05 max_slippage_val = rate * ((1 + slippage) if side == 'buy' else (1 - slippage)) remaining_amount = amount filled_value = 0.0 book_entry_price = 0.0 for book_entry in orderbook[ob_type]: book_entry_price = book_entry[0] book_entry_coin_volume = book_entry[1] if remaining_amount > 0: if remaining_amount < book_entry_coin_volume: # Orderbook at this slot bigger than remaining amount filled_value += remaining_amount * book_entry_price break else: filled_value += book_entry_coin_volume * book_entry_price remaining_amount -= book_entry_coin_volume else: break else: # If remaining_amount wasn't consumed completely (break was not called) filled_value += remaining_amount * book_entry_price forecast_avg_filled_price = max(filled_value, 0) / amount # Limit max. slippage to specified value if side == 'buy': forecast_avg_filled_price = min(forecast_avg_filled_price, max_slippage_val) else: forecast_avg_filled_price = max(forecast_avg_filled_price, max_slippage_val) return self.price_to_precision(pair, forecast_avg_filled_price) return rate def _dry_is_price_crossed(self, pair: str, side: str, limit: float, orderbook: Optional[OrderBook] = None, offset: float = 0.0) -> bool: if not self.exchange_has('fetchL2OrderBook'): return True if not orderbook: orderbook = self.fetch_l2_order_book(pair, 1) try: if side == 'buy': price = orderbook['asks'][0][0] if limit * (1 - offset) >= price: return True else: price = orderbook['bids'][0][0] if limit * (1 + offset) <= price: return True except IndexError: # Ignore empty orderbooks when filling - can be filled with the next iteration. pass return False def check_dry_limit_order_filled( self, order: Dict[str, Any], immediate: bool = False, orderbook: Optional[OrderBook] = None) -> Dict[str, Any]: """ Check dry-run limit order fill and update fee (if it filled). """ if (order['status'] != "closed" and order['type'] in ["limit"] and not order.get('ft_order_type')): pair = order['symbol'] if self._dry_is_price_crossed(pair, order['side'], order['price'], orderbook): order.update({ 'status': 'closed', 'filled': order['amount'], 'remaining': 0, }) self.add_dry_order_fee( pair, order, 'taker' if immediate else 'maker', ) return order def fetch_dry_run_order(self, order_id) -> Dict[str, Any]: """ Return dry-run order Only call if running in dry-run mode. """ try: order = self._dry_run_open_orders[order_id] 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._ft_has['stop_price_prop']) 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 # Order handling def _lev_prep(self, pair: str, leverage: float, side: BuySell, accept_fail: bool = False): if self.trading_mode != TradingMode.SPOT: self.set_margin_mode(pair, self.margin_mode, accept_fail) self._set_leverage(leverage, pair, accept_fail) def _get_params( self, side: BuySell, ordertype: str, leverage: float, reduceOnly: bool, time_in_force: str = 'GTC', ) -> Dict: params = self._params.copy() if time_in_force != 'GTC' and ordertype != 'market': params.update({'timeInForce': time_in_force.upper()}) if reduceOnly: params.update({'reduceOnly': True}) return params def _order_needs_price(self, ordertype: str) -> bool: return ( ordertype != 'market' or self._api.options.get("createMarketBuyOrderRequiresPrice", False) or self._ft_has.get('marketOrderRequiresPrice', False) ) def create_order( self, *, pair: str, ordertype: str, side: BuySell, amount: float, rate: float, leverage: float, reduceOnly: bool = False, time_in_force: str = 'GTC', ) -> Dict: if self._config['dry_run']: dry_order = self.create_dry_run_order( pair, ordertype, side, amount, self.price_to_precision(pair, rate), leverage) return dry_order params = self._get_params(side, ordertype, leverage, reduceOnly, time_in_force) try: # Set the precision for amount and price(rate) as accepted by the exchange amount = self.amount_to_precision(pair, self._amount_to_contracts(pair, amount)) needs_price = self._order_needs_price(ordertype) rate_for_order = self.price_to_precision(pair, rate) if needs_price else None if not reduceOnly: self._lev_prep(pair, leverage, side) order = self._api.create_order( pair, ordertype, side, amount, rate_for_order, params, ) if order.get('status') is None: # Map empty status to open. order['status'] = 'open' if order.get('type') is None: order['type'] = ordertype self._log_exchange_response('create_order', order) order = self._order_contracts_to_amount(order) return order except ccxt.InsufficientFunds as e: raise InsufficientFundsError( 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: raise InvalidOrderException( 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 {side} order due to {e.__class__.__name__}. Message: {e}') from e except ccxt.BaseError as e: raise OperationalException(e) from e 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. """ if not self._ft_has.get('stoploss_on_exchange'): raise OperationalException(f"stoploss is not implemented for {self.name}.") price_param = self._ft_has['stop_price_prop'] return ( order.get(price_param, None) is None or ((side == "sell" and stop_loss > float(order[price_param])) or (side == "buy" and stop_loss < float(order[price_param]))) ) def _get_stop_order_type(self, user_order_type) -> Tuple[str, str]: available_order_Types: Dict[str, str] = self._ft_has["stoploss_order_types"] if user_order_type in available_order_Types.keys(): ordertype = available_order_Types[user_order_type] else: # Otherwise pick only one available ordertype = list(available_order_Types.values())[0] user_order_type = list(available_order_Types.keys())[0] return ordertype, user_order_type def _get_stop_limit_rate(self, stop_price: float, order_types: Dict, side: str) -> float: # 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) if side == "sell": limit_rate = stop_price * limit_price_pct else: limit_rate = stop_price * (2 - limit_price_pct) bad_stop_price = ((stop_price < limit_rate) if side == "sell" else (stop_price > limit_rate)) # Ensure rate is less than stop price if bad_stop_price: # This can for example happen if the stop / liquidation price is set to 0 # Which is possible if a market-order closes right away. # The InvalidOrderException will bubble up to exit_positions, where it will be # handled gracefully. raise InvalidOrderException( "In stoploss limit order, stop price should be more than limit price. " f"Stop price: {stop_price}, Limit price: {limit_rate}, " f"Limit Price pct: {limit_price_pct}" ) return limit_rate def _get_stop_params(self, side: BuySell, ordertype: str, stop_price: float) -> Dict: params = self._params.copy() # Verify if stopPrice works for your exchange, else configure stop_price_param params.update({self._ft_has['stop_price_param']: stop_price}) return params @retrier(retries=0) def create_stoploss(self, pair: str, amount: float, stop_price: float, order_types: Dict, side: BuySell, leverage: float) -> Dict: """ creates a stoploss order. requires `_ft_has['stoploss_order_types']` to be set as a dict mapping limit and market to the corresponding exchange type. The precise ordertype is determined by the order_types dict or exchange default. The exception below should never raise, since we disallow starting the bot in validate_ordertypes() This may work with a limited number of other exchanges, but correct working needs to be tested individually. WARNING: setting `stoploss_on_exchange` to True will NOT auto-enable stoploss on exchange. `stoploss_adjust` must still be implemented for this to work. """ if not self._ft_has['stoploss_on_exchange']: raise OperationalException(f"stoploss is not implemented for {self.name}.") user_order_type = order_types.get('stoploss', 'market') ordertype, user_order_type = self._get_stop_order_type(user_order_type) round_mode = ROUND_DOWN if side == 'buy' else ROUND_UP stop_price_norm = self.price_to_precision(pair, stop_price, rounding_mode=round_mode) limit_rate = None if user_order_type == 'limit': limit_rate = self._get_stop_limit_rate(stop_price, order_types, side) limit_rate = self.price_to_precision(pair, limit_rate, rounding_mode=round_mode) if self._config['dry_run']: dry_order = self.create_dry_run_order( pair, ordertype, side, amount, stop_price_norm, stop_loss=True, leverage=leverage, ) return dry_order try: params = self._get_stop_params(side=side, ordertype=ordertype, stop_price=stop_price_norm) if self.trading_mode == TradingMode.FUTURES: params['reduceOnly'] = True if 'stoploss_price_type' in order_types and 'stop_price_type_field' in self._ft_has: price_type = self._ft_has['stop_price_type_value_mapping'][ order_types.get('stoploss_price_type', PriceType.LAST)] params[self._ft_has['stop_price_type_field']] = price_type amount = self.amount_to_precision(pair, self._amount_to_contracts(pair, amount)) self._lev_prep(pair, leverage, side, accept_fail=True) order = self._api.create_order(symbol=pair, type=ordertype, side=side, amount=amount, price=limit_rate, params=params) self._log_exchange_response('create_stoploss_order', order) order = self._order_contracts_to_amount(order) logger.info(f"stoploss {user_order_type} order added for {pair}. " f"stop price: {stop_price}. limit: {limit_rate}") return order except ccxt.InsufficientFunds as e: raise InsufficientFundsError( f'Insufficient funds to create {ordertype} {side} order on market {pair}. ' f'Tried to {side} amount {amount} at rate {limit_rate} with ' f'stop-price {stop_price_norm}. Message: {e}') from e except (ccxt.InvalidOrder, ccxt.BadRequest) as e: # Errors: # `Order would trigger immediately.` raise InvalidOrderException( f'Could not create {ordertype} {side} order on market {pair}. ' f'Tried to {side} amount {amount} at rate {limit_rate} with ' f'stop-price {stop_price_norm}. 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 stoploss order due to {e.__class__.__name__}. " f"Message: {e}") from e except ccxt.BaseError as e: raise OperationalException(e) from e @retrier(retries=API_FETCH_ORDER_RETRY_COUNT) 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: order = self._api.fetch_order(order_id, pair, params=params) self._log_exchange_response('fetch_order', order) order = self._order_contracts_to_amount(order) return order except ccxt.OrderNotFound as e: raise RetryableOrderError( f'Order not found (pair: {pair} id: {order_id}). Message: {e}') from e except ccxt.InvalidOrder as e: raise InvalidOrderException( f'Tried to get an invalid order (pair: {pair} id: {order_id}). 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 get order due to {e.__class__.__name__}. Message: {e}') from e except ccxt.BaseError as e: raise OperationalException(e) from e 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: """ Simple wrapper calling either fetch_order or fetch_stoploss_order depending on the stoploss_order parameter :param order_id: OrderId to fetch order :param pair: Pair corresponding to order_id :param stoploss_order: If true, uses fetch_stoploss_order, otherwise fetch_order. """ if stoploss_order: return self.fetch_stoploss_order(order_id, pair) return self.fetch_order(order_id, pair) def check_order_canceled_empty(self, order: Dict) -> bool: """ Verify if an order has been cancelled without being partially filled :param order: Order dict as returned from fetch_order() :return: True if order has been cancelled without being filled, False otherwise. """ return (order.get('status') in NON_OPEN_EXCHANGE_STATES and order.get('filled') == 0.0) @retrier 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) order.update({'status': 'canceled', 'filled': 0.0, 'remaining': order['amount']}) return order except InvalidOrderException: return {} try: order = self._api.cancel_order(order_id, pair, params=params) self._log_exchange_response('cancel_order', order) order = self._order_contracts_to_amount(order) return order except ccxt.InvalidOrder as e: raise InvalidOrderException( f'Could not cancel order. 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 cancel order due to {e.__class__.__name__}. Message: {e}') from e except ccxt.BaseError as e: raise OperationalException(e) from e 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): return False required = ('fee', 'status', 'amount') return all(corder.get(k, None) is not None for k in required) def cancel_order_with_result(self, order_id: str, pair: str, amount: float) -> Dict: """ Cancel order returning a result. Creates a fake result if cancel order returns a non-usable result and fetch_order does not work (certain exchanges don't return cancelled orders) :param order_id: Orderid to cancel :param pair: Pair corresponding to order_id :param amount: Amount to use for fake response :return: Result from either cancel_order if usable, or fetch_order """ try: corder = self.cancel_order(order_id, pair) if self.is_cancel_order_result_suitable(corder): return corder except InvalidOrderException: logger.warning(f"Could not cancel order {order_id} for {pair}.") try: order = self.fetch_order(order_id, pair) except InvalidOrderException: logger.warning(f"Could not fetch cancelled order {order_id}.") order = { 'id': order_id, 'status': 'canceled', 'amount': amount, 'filled': 0.0, 'fee': {}, 'info': {} } return order def cancel_stoploss_order_with_result(self, order_id: str, pair: str, amount: float) -> Dict: """ Cancel stoploss order returning a result. Creates a fake result if cancel order returns a non-usable result and fetch_order does not work (certain exchanges don't return cancelled orders) :param order_id: stoploss-order-id to cancel :param pair: Pair corresponding to order_id :param amount: Amount to use for fake response :return: Result from either cancel_order if usable, or fetch_order """ corder = self.cancel_stoploss_order(order_id, pair) if self.is_cancel_order_result_suitable(corder): return corder try: order = self.fetch_stoploss_order(order_id, pair) except InvalidOrderException: logger.warning(f"Could not fetch cancelled stoploss order {order_id}.") order = {'id': order_id, 'fee': {}, 'status': 'canceled', 'amount': amount, 'info': {}} return order @retrier def get_balances(self) -> dict: try: balances = self._api.fetch_balance() # Remove additional info from ccxt results balances.pop("info", None) balances.pop("free", None) balances.pop("total", None) balances.pop("used", None) return balances except ccxt.DDoSProtection as e: raise DDosProtection(e) from e except (ccxt.NetworkError, ccxt.ExchangeError) as e: raise TemporaryError( f'Could not get balance due to {e.__class__.__name__}. Message: {e}') from e except ccxt.BaseError as e: raise OperationalException(e) from e @retrier def fetch_positions(self, pair: Optional[str] = None) -> List[Dict]: """ Fetch positions from the exchange. If no pair is given, all positions are returned. :param pair: Pair for the query """ if self._config['dry_run'] or self.trading_mode != TradingMode.FUTURES: return [] try: symbols = [] if pair: symbols.append(pair) positions: List[Dict] = self._api.fetch_positions(symbols) self._log_exchange_response('fetch_positions', positions) return positions except ccxt.DDoSProtection as e: raise DDosProtection(e) from e except (ccxt.NetworkError, ccxt.ExchangeError) as e: raise TemporaryError( f'Could not get positions due to {e.__class__.__name__}. Message: {e}') from e except ccxt.BaseError as e: raise OperationalException(e) from e def _fetch_orders_emulate(self, pair: str, since_ms: int) -> List[Dict]: orders = [] if self.exchange_has('fetchClosedOrders'): orders = self._api.fetch_closed_orders(pair, since=since_ms) if self.exchange_has('fetchOpenOrders'): orders_open = self._api.fetch_open_orders(pair, since=since_ms) orders.extend(orders_open) return orders @retrier(retries=0) def fetch_orders(self, pair: str, since: datetime, params: Optional[Dict] = None) -> List[Dict]: """ Fetch all orders for a pair "since" :param pair: Pair for the query :param since: Starting time for the query """ if self._config['dry_run']: return [] try: since_ms = int((since.timestamp() - 10) * 1000) if self.exchange_has('fetchOrders'): if not params: params = {} try: orders: List[Dict] = self._api.fetch_orders(pair, since=since_ms, params=params) except ccxt.NotSupported: # Some exchanges don't support fetchOrders # attempt to fetch open and closed orders separately orders = self._fetch_orders_emulate(pair, since_ms) else: orders = self._fetch_orders_emulate(pair, since_ms) self._log_exchange_response('fetch_orders', orders) orders = [self._order_contracts_to_amount(o) for o in orders] return orders except ccxt.DDoSProtection as e: raise DDosProtection(e) from e except (ccxt.NetworkError, ccxt.ExchangeError) as e: raise TemporaryError( f'Could not fetch positions due to {e.__class__.__name__}. Message: {e}') from e except ccxt.BaseError as e: raise OperationalException(e) from e @retrier def fetch_trading_fees(self) -> Dict[str, Any]: """ Fetch user account trading fees Can be cached, should not update often. """ if (self._config['dry_run'] or self.trading_mode != TradingMode.FUTURES or not self.exchange_has('fetchTradingFees')): return {} try: trading_fees: Dict[str, Any] = self._api.fetch_trading_fees() self._log_exchange_response('fetch_trading_fees', trading_fees) return trading_fees except ccxt.DDoSProtection as e: raise DDosProtection(e) from e except (ccxt.NetworkError, ccxt.ExchangeError) as e: raise TemporaryError( f'Could not fetch trading fees due to {e.__class__.__name__}. Message: {e}') from e except ccxt.BaseError as e: raise OperationalException(e) from e @retrier def fetch_bids_asks(self, symbols: Optional[List[str]] = None, cached: bool = False) -> Dict: """ :param symbols: List of symbols to fetch :param cached: Allow cached result :return: fetch_bids_asks result """ if not self.exchange_has('fetchBidsAsks'): return {} if cached: with self._cache_lock: tickers = self._fetch_tickers_cache.get('fetch_bids_asks') if tickers: return tickers try: tickers = self._api.fetch_bids_asks(symbols) with self._cache_lock: self._fetch_tickers_cache['fetch_bids_asks'] = tickers return tickers except ccxt.NotSupported as e: raise OperationalException( f'Exchange {self._api.name} does not support fetching bids/asks in batch. ' 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 load bids/asks due to {e.__class__.__name__}. Message: {e}') from e except ccxt.BaseError as e: raise OperationalException(e) from e @retrier def get_tickers(self, symbols: Optional[List[str]] = None, cached: bool = False) -> Tickers: """ :param cached: Allow cached result :return: fetch_tickers result """ tickers: Tickers if not self.exchange_has('fetchTickers'): return {} if cached: with self._cache_lock: tickers = self._fetch_tickers_cache.get('fetch_tickers') # type: ignore if tickers: return tickers try: tickers = self._api.fetch_tickers(symbols) with self._cache_lock: self._fetch_tickers_cache['fetch_tickers'] = tickers return tickers except ccxt.NotSupported as e: raise OperationalException( f'Exchange {self._api.name} does not support fetching tickers in batch. ' f'Message: {e}') from e except ccxt.BadSymbol as e: logger.warning(f"Could not load tickers due to {e.__class__.__name__}. Message: {e} ." "Reloading markets.") self.reload_markets(True) # Re-raise exception to repeat the call. raise TemporaryError from e except ccxt.DDoSProtection as e: raise DDosProtection(e) from e except (ccxt.NetworkError, ccxt.ExchangeError) as e: raise TemporaryError( f'Could not load tickers due to {e.__class__.__name__}. Message: {e}') from e except ccxt.BaseError as e: raise OperationalException(e) from e # Pricing info @retrier def fetch_ticker(self, pair: str) -> Ticker: try: if (pair not in self.markets or self.markets[pair].get('active', False) is False): raise ExchangeError(f"Pair {pair} not available") data: Ticker = self._api.fetch_ticker(pair) return data except ccxt.DDoSProtection as e: raise DDosProtection(e) from e except (ccxt.NetworkError, ccxt.ExchangeError) as e: raise TemporaryError( f'Could not load ticker due to {e.__class__.__name__}. Message: {e}') from e except ccxt.BaseError as e: raise OperationalException(e) from e @staticmethod def get_next_limit_in_list(limit: int, limit_range: Optional[List[int]], range_required: bool = True): """ Get next greater value in the list. Used by fetch_l2_order_book if the api only supports a limited range """ if not limit_range: return limit result = min([x for x in limit_range if limit <= x] + [max(limit_range)]) if not range_required and limit > result: # Range is not required - we can use None as parameter. return None return result @retrier def fetch_l2_order_book(self, pair: str, limit: int = 100) -> OrderBook: """ Get L2 order book from exchange. Can be limited to a certain amount (if supported). Returns a dict in the format {'asks': [price, volume], 'bids': [price, volume]} """ limit1 = self.get_next_limit_in_list(limit, self._ft_has['l2_limit_range'], self._ft_has['l2_limit_range_required']) try: return self._api.fetch_l2_order_book(pair, limit1) except ccxt.NotSupported as e: raise OperationalException( f'Exchange {self._api.name} does not support fetching order book.' 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 get order book due to {e.__class__.__name__}. Message: {e}') from e except ccxt.BaseError as e: raise OperationalException(e) from e def _get_price_side(self, side: str, is_short: bool, conf_strategy: Dict) -> BidAsk: price_side = conf_strategy['price_side'] if price_side in ('same', 'other'): price_map = { ('entry', 'long', 'same'): 'bid', ('entry', 'long', 'other'): 'ask', ('entry', 'short', 'same'): 'ask', ('entry', 'short', 'other'): 'bid', ('exit', 'long', 'same'): 'ask', ('exit', 'long', 'other'): 'bid', ('exit', 'short', 'same'): 'bid', ('exit', 'short', 'other'): 'ask', } price_side = price_map[(side, 'short' if is_short else 'long', price_side)] return price_side def get_rate(self, pair: str, refresh: bool, side: EntryExit, is_short: bool, order_book: Optional[OrderBook] = None, ticker: Optional[Ticker] = None) -> float: """ Calculates bid/ask target bid rate - between current ask price and last price ask rate - either using ticker bid or first bid based on orderbook or remain static in any other case since it's not updating. :param pair: Pair to get rate for :param refresh: allow cached data :param side: "buy" or "sell" :return: float: Price :raises PricingError if orderbook price could not be determined. """ name = side.capitalize() strat_name = 'entry_pricing' if side == "entry" else 'exit_pricing' cache_rate: TTLCache = self._entry_rate_cache if side == "entry" else self._exit_rate_cache if not refresh: with self._cache_lock: rate = cache_rate.get(pair) # Check if cache has been invalidated if rate: logger.debug(f"Using cached {side} rate for {pair}.") return rate conf_strategy = self._config.get(strat_name, {}) price_side = self._get_price_side(side, is_short, conf_strategy) if conf_strategy.get('use_order_book', False): order_book_top = conf_strategy.get('order_book_top', 1) if order_book is None: order_book = self.fetch_l2_order_book(pair, order_book_top) rate = self._get_rate_from_ob(pair, side, order_book, name, price_side, order_book_top) else: logger.debug(f"Using Last {price_side.capitalize()} / Last Price") if ticker is None: ticker = self.fetch_ticker(pair) rate = self._get_rate_from_ticker(side, ticker, conf_strategy, price_side) if rate is None: raise PricingError(f"{name}-Rate for {pair} was empty.") with self._cache_lock: cache_rate[pair] = rate return rate def _get_rate_from_ticker(self, side: EntryExit, ticker: Ticker, conf_strategy: Dict[str, Any], price_side: BidAsk) -> Optional[float]: """ Get rate from ticker. """ ticker_rate = ticker[price_side] if ticker['last'] and ticker_rate: if side == 'entry' and ticker_rate > ticker['last']: balance = conf_strategy.get('price_last_balance', 0.0) ticker_rate = ticker_rate + balance * (ticker['last'] - ticker_rate) elif side == 'exit' and ticker_rate < ticker['last']: balance = conf_strategy.get('price_last_balance', 0.0) ticker_rate = ticker_rate - balance * (ticker_rate - ticker['last']) rate = ticker_rate return rate def _get_rate_from_ob(self, pair: str, side: EntryExit, order_book: OrderBook, name: str, price_side: BidAsk, order_book_top: int) -> float: """ Get rate from orderbook :raises: PricingError if rate could not be determined. """ logger.debug('order_book %s', order_book) # top 1 = index 0 try: obside: OBLiteral = 'bids' if price_side == 'bid' else 'asks' rate = order_book[obside][order_book_top - 1][0] except (IndexError, KeyError) as e: logger.warning( f"{pair} - {name} Price at location {order_book_top} from orderbook " f"could not be determined. Orderbook: {order_book}" ) raise PricingError from e logger.debug(f"{pair} - {name} price from orderbook {price_side.capitalize()}" f"side - top {order_book_top} order book {side} rate {rate:.8f}") return rate def get_rates(self, pair: str, refresh: bool, is_short: bool) -> Tuple[float, float]: entry_rate = None exit_rate = None if not refresh: with self._cache_lock: entry_rate = self._entry_rate_cache.get(pair) exit_rate = self._exit_rate_cache.get(pair) if entry_rate: logger.debug(f"Using cached buy rate for {pair}.") if exit_rate: logger.debug(f"Using cached sell rate for {pair}.") entry_pricing = self._config.get('entry_pricing', {}) exit_pricing = self._config.get('exit_pricing', {}) order_book = ticker = None if not entry_rate and entry_pricing.get('use_order_book', False): order_book_top = max(entry_pricing.get('order_book_top', 1), exit_pricing.get('order_book_top', 1)) order_book = self.fetch_l2_order_book(pair, order_book_top) entry_rate = self.get_rate(pair, refresh, 'entry', is_short, order_book=order_book) elif not entry_rate: ticker = self.fetch_ticker(pair) entry_rate = self.get_rate(pair, refresh, 'entry', is_short, ticker=ticker) if not exit_rate: exit_rate = self.get_rate(pair, refresh, 'exit', is_short, order_book=order_book, ticker=ticker) return entry_rate, exit_rate # Fee handling @retrier def get_trades_for_order(self, order_id: str, pair: str, since: datetime, params: Optional[Dict] = None) -> List: """ Fetch Orders using the "fetch_my_trades" endpoint and filter them by order-id. The "since" argument passed in is coming from the database and is in UTC, as timezone-native datetime object. From the python documentation: > Naive datetime instances are assumed to represent local time Therefore, calling "since.timestamp()" will get the UTC timestamp, after applying the transformation from local timezone to UTC. This works for timezones UTC+ since then the result will contain trades from a few hours instead of from the last 5 seconds, however fails for UTC- timezones, since we're then asking for trades with a "since" argument in the future. :param order_id order_id: Order-id as given when creating the order :param pair: Pair the order is for :param since: datetime object of the order creation time. Assumes object is in UTC. """ if self._config['dry_run']: return [] if not self.exchange_has('fetchMyTrades'): return [] try: # Allow 5s offset to catch slight time offsets (discovered in #1185) # since needs to be int in milliseconds _params = params if params else {} my_trades = self._api.fetch_my_trades( pair, int((since.replace(tzinfo=timezone.utc).timestamp() - 5) * 1000), params=_params) matched_trades = [trade for trade in my_trades if trade['order'] == order_id] self._log_exchange_response('get_trades_for_order', matched_trades) matched_trades = self._trades_contracts_to_amount(matched_trades) return matched_trades except ccxt.DDoSProtection as e: raise DDosProtection(e) from e except (ccxt.NetworkError, ccxt.ExchangeError) as e: raise TemporaryError( f'Could not get trades due to {e.__class__.__name__}. Message: {e}') from e except ccxt.BaseError as e: raise OperationalException(e) from e def get_order_id_conditional(self, order: Dict[str, Any]) -> str: return order['id'] @retrier def get_fee(self, symbol: str, type: str = '', side: str = '', amount: float = 1, price: float = 1, taker_or_maker: MakerTaker = 'maker') -> float: """ Retrieve fee from exchange :param symbol: Pair :param type: Type of order (market, limit, ...) :param side: Side of order (buy, sell) :param amount: Amount of order :param price: Price of order :param taker_or_maker: 'maker' or 'taker' (ignored if "type" is provided) """ if type and type == 'market': taker_or_maker = 'taker' try: if self._config['dry_run'] and self._config.get('fee', None) is not None: return self._config['fee'] # validate that markets are loaded before trying to get fee if self._api.markets is None or len(self._api.markets) == 0: self._api.load_markets(params={}) return self._api.calculate_fee(symbol=symbol, type=type, side=side, amount=amount, price=price, takerOrMaker=taker_or_maker)['rate'] except ccxt.DDoSProtection as e: raise DDosProtection(e) from e except (ccxt.NetworkError, ccxt.ExchangeError) as e: raise TemporaryError( f'Could not get fee info due to {e.__class__.__name__}. Message: {e}') from e except ccxt.BaseError as e: raise OperationalException(e) from e @staticmethod def order_has_fee(order: Dict) -> bool: """ Verifies if the passed in order dict has the needed keys to extract fees, and that these keys (currency, cost) are not empty. :param order: Order or trade (one trade) dict :return: True if the fee substructure contains currency and cost, false otherwise """ if not isinstance(order, dict): return False return ('fee' in order and order['fee'] is not None and (order['fee'].keys() >= {'currency', 'cost'}) and order['fee']['currency'] is not None and order['fee']['cost'] is not None ) def calculate_fee_rate( self, fee: Dict, symbol: str, cost: float, amount: float) -> Optional[float]: """ Calculate fee rate if it's not given by the exchange. :param fee: ccxt Fee dict - must contain cost / currency / rate :param symbol: Symbol of the order :param cost: Total cost of the order :param amount: Amount of the order """ if fee.get('rate') is not None: return fee.get('rate') fee_curr = fee.get('currency') if fee_curr is None: return None fee_cost = float(fee['cost']) # Calculate fee based on order details if fee_curr == self.get_pair_base_currency(symbol): # Base currency - divide by amount return round(fee_cost / amount, 8) elif fee_curr == self.get_pair_quote_currency(symbol): # Quote currency - divide by cost return round(fee_cost / cost, 8) if cost else None else: # If Fee currency is a different currency if not cost: # If cost is None or 0.0 -> falsy, return None return None try: comb = self.get_valid_pair_combination(fee_curr, self._config['stake_currency']) tick = self.fetch_ticker(comb) fee_to_quote_rate = safe_value_fallback2(tick, tick, 'last', 'ask') except (ValueError, ExchangeError): fee_to_quote_rate = self._config['exchange'].get('unknown_fee_rate', None) if not fee_to_quote_rate: return None return round((fee_cost * fee_to_quote_rate) / cost, 8) def extract_cost_curr_rate(self, fee: Dict, symbol: str, cost: float, amount: float) -> Tuple[float, str, Optional[float]]: """ Extract tuple of cost, currency, rate. Requires order_has_fee to run first! :param fee: ccxt Fee dict - must contain cost / currency / rate :param symbol: Symbol of the order :param cost: Total cost of the order :param amount: Amount of the order :return: Tuple with cost, currency, rate of the given fee dict """ return (float(fee['cost']), fee['currency'], self.calculate_fee_rate( fee, symbol, cost, amount ) ) # Historic data def get_historic_ohlcv(self, pair: str, timeframe: str, since_ms: int, candle_type: CandleType, is_new_pair: bool = False, until_ms: Optional[int] = None) -> List: """ Get candle history using asyncio and returns the list of candles. Handles all async work for this. Async over one pair, assuming we get `self.ohlcv_candle_limit()` candles per call. :param pair: Pair to download :param timeframe: Timeframe to get data for :param since_ms: Timestamp in milliseconds to get history from :param until_ms: Timestamp in milliseconds to get history up to :param candle_type: '', mark, index, premiumIndex, or funding_rate :return: List with candle (OHLCV) data """ pair, _, _, data, _ = self.loop.run_until_complete( self._async_get_historic_ohlcv(pair=pair, timeframe=timeframe, since_ms=since_ms, until_ms=until_ms, is_new_pair=is_new_pair, candle_type=candle_type)) logger.info(f"Downloaded data for {pair} with length {len(data)}.") return data 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: Optional[int] = None ) -> OHLCVResponse: """ Download historic ohlcv :param is_new_pair: used by binance subclass to allow "fast" new pair downloading :param candle_type: Any of the enum CandleType (must match trading mode!) """ one_call = timeframe_to_msecs(timeframe) * self.ohlcv_candle_limit( timeframe, candle_type, since_ms) logger.debug( "one_call: %s msecs (%s)", one_call, dt_humanize(dt_now() - timedelta(milliseconds=one_call), only_distance=True) ) input_coroutines = [self._async_get_candle_history( pair, timeframe, candle_type, since) for since in range(since_ms, until_ms or dt_ts(), one_call)] data: List = [] # Chunk requests into batches of 100 to avoid overwelming ccxt Throttling for input_coro in chunks(input_coroutines, 100): results = await asyncio.gather(*input_coro, return_exceptions=True) for res in results: if isinstance(res, BaseException): logger.warning(f"Async code raised an exception: {repr(res)}") if raise_: raise continue else: # Deconstruct tuple if it's not an exception p, _, c, new_data, _ = res if p == pair and c == candle_type: data.extend(new_data) # Sort data again after extending the result - above calls return in "async order" data = sorted(data, key=lambda x: x[0]) return pair, timeframe, candle_type, data, self._ohlcv_partial_candle async def _async_get_historic_trades(self, pair: str, timeframe: str, since_ms: int, candle_type: CandleType, is_new_pair: bool = False, raise_: bool = False, until_ms: Optional[int] = None ) -> Ticker: """ Download historic trades :param is_new_pair: used by binance subclass to allow "fast" new pair downloading :param candle_type: Any of the enum CandleType (must match trading mode!) """ one_call = timeframe_to_msecs(timeframe) * self.trades_candle_limit( timeframe, candle_type, since_ms) logger.debug( "one_call: %s msecs (%s)", one_call, dt_humanize(dt_now() - timedelta(milliseconds=one_call), only_distance=True) ) input_coroutines = [self._async_get_trades_history( pair, timeframe, candle_type, since) for since in range(since_ms, until_ms or dt_ts(), one_call)] data: List = [] # Chunk requests into batches of 100 to avoid overwelming ccxt Throttling for input_coro in chunks(input_coroutines, 100): results = await asyncio.gather(*input_coro, return_exceptions=True) for res in results: if isinstance(res, BaseException): logger.warning(f"Async code raised an exception: {repr(res)}") if raise_: raise continue else: # Deconstruct tuple if it's not an exception p, _, c, new_data, _ = res if p == pair and c == candle_type: data.extend(new_data) # Sort data again after extending the result - above calls return in "async order" data = sorted(data, key=lambda x: x['timestamp']) # TODO: sort via 'timestamp' or 'id'? return pair, timeframe, candle_type, data, self._ohlcv_partial_candle def _build_coroutine_get_ohlcv( self, pair: str, timeframe: str, candle_type: CandleType, since_ms: Optional[int], cache: bool) -> Coroutine[Any, Any, OHLCVResponse]: not_all_data = cache and self.required_candle_call_count > 1 if cache and (pair, timeframe, candle_type) in self._klines: candle_limit = self.ohlcv_candle_limit(timeframe, candle_type) min_date = date_minus_candles(timeframe, candle_limit - 5).timestamp() # Check if 1 call can get us updated candles without hole in the data. if min_date < self._pairs_last_refresh_time.get((pair, timeframe, candle_type), 0): # Cache can be used - do one-off call. not_all_data = False else: # Time jump detected, evict cache logger.info( f"Time jump detected. Evicting ohlcv cache for {pair}, {timeframe}, {candle_type}") del self._klines[(pair, timeframe, candle_type)] if (not since_ms and (self._ft_has["ohlcv_require_since"] or not_all_data)): # Multiple calls for one pair - to get more history since_ms = self.needed_candle_ms(timeframe, candle_type) if since_ms: return self._async_get_historic_ohlcv( pair, timeframe, since_ms=since_ms, raise_=True, candle_type=candle_type) else: # One call ... "regular" refresh return self._async_get_candle_history( pair, timeframe, since_ms=since_ms, candle_type=candle_type) def _build_coroutine_get_trades( self, pair: str, timeframe: str, candle_type: CandleType, since_ms: Optional[int], cache: bool) -> Coroutine[Any, Any, OHLCVResponse]: not_all_data = cache and self.required_candle_call_count > 1 if cache and (pair, timeframe, candle_type) in self._trades: candle_limit = self.trades_candle_limit(timeframe, candle_type) min_date = date_minus_candles(timeframe, candle_limit - 5).timestamp() # Check if 1 call can get us updated candles without hole in the data. if min_date < self._pairs_last_refresh_time.get((pair, timeframe, candle_type), 0): # Cache can be used - do one-off call. not_all_data = False else: # Time jump detected, evict cache logger.info( f"Time jump detected. Evicting trades cache for {pair}, {timeframe}, {candle_type}") del self._trades[(pair, timeframe, candle_type)] if (not since_ms or not_all_data): # Multiple calls for one pair - to get more history one_call = timeframe_to_msecs(timeframe) * self.ohlcv_candle_limit( timeframe, candle_type, since_ms) move_to = one_call * self.required_candle_call_count now = timeframe_to_next_date(timeframe) since_ms = int((now - timedelta(seconds=move_to // 1000)).timestamp() * 1000) if since_ms: return self._async_get_historic_trades( pair, timeframe, since_ms=since_ms, raise_=True, candle_type=candle_type) else: # One call ... "regular" refresh return self._async_get_trades_history( pair, timeframe, since_ms=since_ms, candle_type=candle_type) def _build_ohlcv_dl_jobs( self, pair_list: ListPairsWithTimeframes, since_ms: Optional[int], cache: bool) -> Tuple[List[Coroutine], List[Tuple[str, str, CandleType]]]: """ Build Coroutines to execute as part of refresh_latest_ohlcv """ input_coroutines: List[Coroutine[Any, Any, OHLCVResponse]] = [] cached_pairs = [] for pair, timeframe, candle_type in set(pair_list): if (timeframe not in self.timeframes and candle_type in (CandleType.SPOT, CandleType.FUTURES)): logger.warning( f"Cannot download ({pair}, {timeframe}) combination as this timeframe is " f"not available on {self.name}. Available timeframes are " f"{', '.join(self.timeframes)}.") continue if ((pair, timeframe, candle_type) not in self._klines or not cache or self._now_is_time_to_refresh(pair, timeframe, candle_type)): input_coroutines.append( self._build_coroutine_get_ohlcv(pair, timeframe, candle_type, since_ms, cache)) else: logger.debug( f"Using cached candle (OHLCV) data for {pair}, {timeframe}, {candle_type} ..." ) cached_pairs.append((pair, timeframe, candle_type)) return input_coroutines, cached_pairs def _build_trades_dl_jobs( self, pair_list: ListPairsWithTimeframes, since_ms: Optional[int], cache: bool) -> Tuple[List[Coroutine], List[Tuple[str, str, CandleType]]]: """ Build Coroutines to execute as part of refresh_latest_trades """ input_coroutines: List[Coroutine[Any, Any, TRADESResponse]] = [] cached_pairs = [] for pair, timeframe, candle_type in set(pair_list): if not since_ms: plr = self._pairs_last_refresh_time.get((pair, timeframe, candle_type), 0) # If we don't have a last refresh time, we need to download all trades # This is the case when the bot is started if not plr: # using ohlcv_candle_limit here, because we calculate the distance # to first required candle one_call = timeframe_to_msecs(timeframe) * self.ohlcv_candle_limit( timeframe, candle_type, since_ms) target_candle = one_call * self.required_candle_call_count now = timeframe_to_next_date(timeframe) since_ms = int((now - timedelta(seconds=target_candle // 1000)).timestamp() * 1000) else: since_ms = plr if (timeframe not in self.timeframes and candle_type in (CandleType.SPOT, CandleType.FUTURES)): logger.warning( f"Cannot download ({pair}, {timeframe}) combination as this timeframe is " f"not available on {self.name}. Available timeframes are " f"{', '.join(self.timeframes)}.") continue if ((pair, timeframe, candle_type) not in self._trades or not cache or self._now_is_time_to_refresh(pair, timeframe, candle_type)): input_coroutines.append( self._build_coroutine_get_trades(pair, timeframe, candle_type, since_ms, cache)) else: logger.debug( f"Using cached candle (TRADES) data for {pair}, {timeframe}, {candle_type} ..." ) cached_pairs.append((pair, timeframe, candle_type)) return input_coroutines, cached_pairs def _process_ohlcv_df(self, pair: str, timeframe: str, c_type: CandleType, ticks: List[List], cache: bool, drop_incomplete: bool) -> DataFrame: # keeping last candle time as last refreshed time of the pair if ticks and cache: idx = -2 if drop_incomplete and len(ticks) > 1 else -1 self._pairs_last_refresh_time[(pair, timeframe, c_type)] = ticks[idx][0] // 1000 # keeping parsed dataframe in cache ohlcv_df = ohlcv_to_dataframe(ticks, timeframe, pair=pair, fill_missing=True, drop_incomplete=drop_incomplete) if cache: if (pair, timeframe, c_type) in self._klines: old = self._klines[(pair, timeframe, c_type)] # Reassign so we return the updated, combined df ohlcv_df = clean_ohlcv_dataframe(concat([old, ohlcv_df], axis=0), timeframe, pair, fill_missing=True, drop_incomplete=False) candle_limit = self.ohlcv_candle_limit(timeframe, self._config['candle_type_def']) # Age out old candles ohlcv_df = ohlcv_df.tail(candle_limit + self._startup_candle_count) ohlcv_df = ohlcv_df.reset_index(drop=True) self._klines[(pair, timeframe, c_type)] = ohlcv_df else: self._klines[(pair, timeframe, c_type)] = ohlcv_df return ohlcv_df def _process_trades_df(self, pair: str, timeframe: str, c_type: CandleType, ticks: List[List], cache: bool, drop_incomplete: bool, first_required_candle_date: Optional[int]) -> DataFrame: # keeping parsed dataframe in cache trades_df = public_trades_to_dataframe(ticks, timeframe, pair=pair, fill_missing=False, drop_incomplete=drop_incomplete) # keeping last candle time as last refreshed time of the pair if ticks and cache: idx = -2 if drop_incomplete and len(ticks) > 1 else -1 self._trades_last_refresh_time[(pair, timeframe, c_type)] = trades_df['timestamp'].iat[idx] // 1000 # NOTE: // is floor: divides and rounds to nearest int if cache: if (pair, timeframe, c_type) in self._trades: old = self._trades[(pair, timeframe, c_type)] # Reassign so we return the updated, combined df trades_df = clean_duplicate_trades(concat( [old, trades_df], axis=0), timeframe, pair, fill_missing=False, drop_incomplete=False) # warn_of_tick_duplicates(trades_df, pair) # Age out old candles if first_required_candle_date: # slice of older dates trades_df = trades_df[first_required_candle_date < trades_df['timestamp']] trades_df = trades_df.reset_index(drop=True) self._trades[(pair, timeframe, c_type)] = trades_df return trades_df def refresh_latest_ohlcv(self, pair_list: ListPairsWithTimeframes, *, since_ms: Optional[int] = None, cache: bool = True, drop_incomplete: Optional[bool] = None ) -> Dict[PairWithTimeframe, DataFrame]: """ Refresh in-memory OHLCV asynchronously and set `_klines` with the result Loops asynchronously over pair_list and downloads all pairs async (semi-parallel). Only used in the dataprovider.refresh() method. :param pair_list: List of 2 element tuples containing pair, interval to refresh :param since_ms: time since when to download, in milliseconds :param cache: Assign result to _klines. Usefull for one-off downloads like for pairlists :param drop_incomplete: Control candle dropping. Specifying None defaults to _ohlcv_partial_candle :return: Dict of [{(pair, timeframe): Dataframe}] """ logger.debug("Refreshing candle (OHLCV) data for %d pairs", len(pair_list)) # Gather coroutines to run input_coroutines, cached_pairs = self._build_ohlcv_dl_jobs(pair_list, since_ms, cache) results_df = {} # Chunk requests into batches of 100 to avoid overwelming ccxt Throttling for input_coro in chunks(input_coroutines, 100): async def gather_stuff(): return await asyncio.gather(*input_coro, return_exceptions=True) with self._loop_lock: results = self.loop.run_until_complete(gather_stuff()) for res in results: if isinstance(res, Exception): logger.warning(f"Async code raised an exception: {repr(res)}") continue # Deconstruct tuple (has 5 elements) pair, timeframe, c_type, ticks, drop_hint = res drop_incomplete_ = drop_hint if drop_incomplete is None else drop_incomplete ohlcv_df = self._process_ohlcv_df( pair, timeframe, c_type, ticks, cache, drop_incomplete_) results_df[(pair, timeframe, c_type)] = ohlcv_df # Return cached klines for pair, timeframe, c_type in cached_pairs: results_df[(pair, timeframe, c_type)] = self.klines( (pair, timeframe, c_type), copy=False ) return results_df def needed_candle_ms(self, timeframe: str, candle_type:CandleType): one_call = timeframe_to_msecs(timeframe) * self.ohlcv_candle_limit( timeframe, candle_type) move_to = one_call * self.required_candle_call_count now = timeframe_to_next_date(timeframe) return int((now - timedelta(seconds=move_to // 1000)).timestamp() * 1000) def refresh_latest_trades(self, pair_list: ListPairsWithTimeframes, data_handler: Callable, # using IDataHandler ends with circular import, *, cache: bool = True, ) -> Dict[PairWithTimeframe, DataFrame]: """ Refresh in-memory TRADES asynchronously and set `_trades` with the result Loops asynchronously over pair_list and downloads all pairs async (semi-parallel). Only used in the dataprovider.refresh() method. :param pair_list: List of 3 element tuples containing (pair, timeframe, candle_type) :param since_ms: time since when to download, in milliseconds :param cache: Assign result to _trades. Usefull for one-off downloads like for pairlists :param drop_incomplete: Control candle dropping. Specifying None defaults to _ohlcv_partial_candle :return: Dict of [{(pair, timeframe): Dataframe}] """ logger.debug("Refreshing TRADES data for %d pairs", len(pair_list)) since_ms = None results_df = {} for pair, timeframe, candle_type in set(pair_list): new_ticks = [] all_stored_ticks_df = DataFrame(columns=DEFAULT_TRADES_COLUMNS + ['date']) first_candle_ms = self.needed_candle_ms(timeframe, candle_type) # refresh, if # a. not in _trades # b. no cache used # c. need new data is_in_cache = (pair, timeframe, candle_type) in self._trades if ( not is_in_cache or not cache or self._now_is_time_to_refresh_trades(pair, timeframe, candle_type)): logger.debug(f"Refreshing TRADES data for {pair}") # fetch trades since latest _trades and # store together with existing trades try: until = None from_id = None if is_in_cache: from_id = self._trades[(pair, timeframe, candle_type)].iloc[-1]['id'] until = dt_ts() # now else: until = int(timeframe_to_prev_date(timeframe).timestamp()) * 1000 all_stored_ticks_df = data_handler.trades_load(f"{pair}-cached") if not all_stored_ticks_df.empty: if all_stored_ticks_df.iloc[0]['timestamp'] <= first_candle_ms: last_cached_ms = all_stored_ticks_df.iloc[-1]['timestamp'] # only use cached if it's closer than first_candle_ms since_ms = last_cached_ms if last_cached_ms > first_candle_ms else first_candle_ms # doesn't go far enough else: all_stored_ticks_df = DataFrame(columns=DEFAULT_TRADES_COLUMNS + ['date']) # from_id overrules with exchange set to id paginate # TODO: DEBUG: # since_ms = 1698060269000 # from_id = None # TODO: /DEBUG [ticks_pair, new_ticks]=self._download_trades_history(pair, since=since_ms if since_ms else first_candle_ms, until=until, from_id=from_id) except Exception as e: logger.error(f"Refreshing TRADES data for {pair} failed") logger.error(e) raise e if new_ticks: drop_incomplete = False # TODO: remove, no incomplete trades # drop 'date' column from stored ticks all_stored_ticks_list = all_stored_ticks_df[DEFAULT_TRADES_COLUMNS].values.tolist() # noqa: E501 all_stored_ticks_list.extend(new_ticks) # NOTE: only process new trades # self._trades = until_first_candle(stored_trades) + fetch_trades trades_df = self._process_trades_df(pair, timeframe, candle_type, all_stored_ticks_list, cache, drop_incomplete, first_candle_ms) results_df[(pair, timeframe, candle_type)] = trades_df data_handler.trades_store(f"{pair}-cached", trades_df[DEFAULT_TRADES_COLUMNS]) else: raise "no new ticks" return results_df def _now_is_time_to_refresh(self, pair: str, timeframe: str, candle_type: CandleType) -> bool: # Timeframe in seconds interval_in_sec = timeframe_to_seconds(timeframe) plr = self._pairs_last_refresh_time.get((pair, timeframe, candle_type), 0) + interval_in_sec # current,active candle open date now = int(timeframe_to_prev_date(timeframe).timestamp()) return plr < now def _now_is_time_to_refresh_trades(self, pair: str, timeframe: str, candle_type: CandleType) -> bool: # Timeframe in seconds df = self.klines((pair, timeframe, candle_type), True) _calculate_ohlcv_candle_start_and_end(df, timeframe) timeframe_to_seconds(timeframe) # plr = self._trades_last_refresh_time.get((pair, timeframe, candle_type), 0) + interval_in_sec plr = round(df.iloc[-1]["candle_end"].timestamp()) now = int(timeframe_to_prev_date(timeframe).timestamp()) return plr < now @retrier_async async def _async_get_candle_history( self, pair: str, timeframe: str, candle_type: CandleType, since_ms: Optional[int] = None, ) -> OHLCVResponse: """ Asynchronously get candle history data using fetch_ohlcv :param candle_type: '', mark, index, premiumIndex, or funding_rate returns tuple: (pair, timeframe, ohlcv_list) """ try: # Fetch OHLCV asynchronously s = '(' + dt_from_ts(since_ms).isoformat() + ') ' if since_ms is not None else '' logger.debug( "Fetching pair %s, %s, interval %s, since %s %s...", pair, candle_type, timeframe, since_ms, s ) params = deepcopy(self._ft_has.get('ohlcv_params', {})) candle_limit = self.ohlcv_candle_limit( timeframe, candle_type=candle_type, since_ms=since_ms) if candle_type and candle_type != CandleType.SPOT: params.update({'price': candle_type.value}) if candle_type != CandleType.FUNDING_RATE: data = await self._api_async.fetch_ohlcv( pair, timeframe=timeframe, since=since_ms, limit=candle_limit, params=params) else: # Funding rate data = await self._fetch_funding_rate_history( pair=pair, timeframe=timeframe, limit=candle_limit, since_ms=since_ms, ) # Some exchanges sort OHLCV in ASC order and others in DESC. # Ex: Bittrex returns the list of OHLCV in ASC order (oldest first, newest last) # while GDAX returns the list of OHLCV in DESC order (newest first, oldest last) # Only sort if necessary to save computing time try: if data and data[0][0] > data[-1][0]: data = sorted(data, key=lambda x: x[0]) except IndexError: logger.exception("Error loading %s. Result was %s.", pair, data) return pair, timeframe, candle_type, [], self._ohlcv_partial_candle logger.debug("Done fetching pair %s, %s interval %s...", pair, candle_type, timeframe) return pair, timeframe, candle_type, data, self._ohlcv_partial_candle except ccxt.NotSupported as e: raise OperationalException( f'Exchange {self._api.name} does not support fetching historical ' f'candle (OHLCV) data. 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 fetch historical candle (OHLCV) data ' f'for pair {pair} due to {e.__class__.__name__}. ' f'Message: {e}') from e except ccxt.BaseError as e: raise OperationalException(f'Could not fetch historical candle (OHLCV) data ' f'for pair {pair}. Message: {e}') from e @retrier_async async def _async_get_trades_history( self, pair: str, timeframe: str, candle_type: CandleType, since_ms: Optional[int] = None, ) -> Ticker: """ Asynchronously get candle history data using fetch_trades :param candle_type: '', mark, index, premiumIndex, or funding_rate returns tuple: (pair, timeframe, trades_list) """ try: # Fetch TRADES asynchronously logger.debug( "Fetching pair %s, %s, interval %s, since %s ...", pair, candle_type, timeframe, since_ms ) params = deepcopy(self._ft_has.get('trades_params', {})) candle_limit = self.trades_candle_limit( timeframe, candle_type=candle_type, since_ms=since_ms) if candle_type and candle_type != CandleType.SPOT: params.update({'price': candle_type.value}) if candle_type != CandleType.FUNDING_RATE: assert since_ms is not None # NOTE: with none there seems no response data = await self._api_async.fetch_trades( pair, since=since_ms, limit=candle_limit, params=params) else: # Funding rate data = await self._fetch_funding_rate_history( pair=pair, timeframe=timeframe, limit=candle_limit, since_ms=since_ms, ) # Some exchanges sort TRADES in ASC order and others in DESC. # Ex: Bittrex returns the list of TRADES in ASC order (oldest first, newest last) # while GDAX returns the list of TRADES in DESC order (newest first, oldest last) # Only sort if necessary to save computing time try: # TODO: check if even needed? if data and data[0]['timestamp'] > data[-1]['timestamp']: data = sorted(data, key=lambda x: x[0]) except KeyError: logger.exception("Error loading %s. Result was %s.", pair, data) return pair, timeframe, candle_type, [], True logger.debug("Done fetching pair %s, interval %s ...", pair, timeframe) return pair, timeframe, candle_type, data, True except ccxt.NotSupported as e: raise OperationalException( f'Exchange {self._api.name} does not support fetching historical ' f'candle (TRADES) data. 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 fetch historical candle (TRADES) data ' f'for pair {pair} due to {e.__class__.__name__}. ' f'Message: {e}') from e except ccxt.BaseError as e: raise OperationalException(f'Could not fetch historical candle (TRADES) data ' f'for pair {pair}. Message: {e}') from e async def _fetch_funding_rate_history( self, pair: str, timeframe: str, limit: int, since_ms: Optional[int] = None, ) -> List[List]: """ Fetch funding rate history - used to selectively override this by subclasses. """ # Funding rate data = await self._api_async.fetch_funding_rate_history( pair, since=since_ms, limit=limit) # Convert funding rate to candle pattern data = [[x['timestamp'], x['fundingRate'], 0, 0, 0, 0] for x in data] return data # Fetch historic trades @retrier_async async def _async_fetch_trades(self, pair: str, since: Optional[int] = None, params: Optional[dict] = None) -> Tuple[List[List], Any]: """ Asyncronously gets trade history using fetch_trades. Handles exchange errors, does one call to the exchange. :param pair: Pair to fetch trade data for :param since: Since as integer timestamp in milliseconds returns: List of dicts containing trades, the next iteration value (new "since" or trade_id) """ try: candle_limit = self.trades_candle_limit("1m", candle_type=CandleType.FUTURES, since_ms=since) # fetch trades asynchronously if params: logger.debug("Fetching trades for pair %s, params: %s ", pair, params) trades = await self._api_async.fetch_trades(pair, params=params, limit=candle_limit) else: logger.debug( "Fetching trades for pair %s, since %s %s...", pair, since, '(' + dt_from_ts(since).isoformat() + ') ' if since is not None else '' ) trades = await self._api_async.fetch_trades(pair, since=since, limit=candle_limit) trades = self._trades_contracts_to_amount(trades) pagination_value = self._get_trade_pagination_next_value(trades) return trades_dict_to_list(trades), pagination_value except ccxt.NotSupported as e: raise OperationalException( f'Exchange {self._api.name} does not support fetching historical trade data.' 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 load trade history due to {e.__class__.__name__}. ' f'Message: {e}') from e except ccxt.BaseError as e: raise OperationalException(f'Could not fetch trade data. Msg: {e}') from e def _valid_trade_pagination_id(self, pair: str, from_id: str) -> bool: """ Verify trade-pagination id is valid. Workaround for odd Kraken issue where ID is sometimes wrong. """ return True def _get_trade_pagination_next_value(self, trades: List[Dict]): """ Extract pagination id for the next "from_id" value Applies only to fetch_trade_history by id. """ if not trades: return None if self._trades_pagination == 'id': return trades[-1].get('id') else: return trades[-1].get('timestamp') async def _async_get_trade_history_id(self, pair: str, until: int, since: Optional[int] = None, from_id: Optional[str] = None, stop_on_from_id: Optional[bool] = True) -> Tuple[str, List[List]]: """ Asyncronously gets trade history using fetch_trades use this when exchange uses id-based iteration (check `self._trades_pagination`) :param pair: Pair to fetch trade data for :param since: Since as integer timestamp in milliseconds :param until: Until as integer timestamp in milliseconds :param from_id: Download data starting with ID (if id is known). Ignores "since" if set. returns tuple: (pair, trades-list) """ trades: List[List] = [] # DEFAULT_TRADES_COLUMNS: 0 -> timestamp # DEFAULT_TRADES_COLUMNS: 1 -> id has_overlap = self._ft_has.get('trades_pagination_overlap', True) # Skip last trade by default since its the key for the next call x = slice(None, -1) if has_overlap else slice(None) if not until and not stop_on_from_id: raise "stop_on_from_id must be set if until is not set" if not from_id or not self._valid_trade_pagination_id(pair, from_id): # Fetch first elements using timebased method to get an ID to paginate on # Depending on the Exchange, this can introduce a drift at the start of the interval # of up to an hour. # e.g. Binance returns the "last 1000" candles within a 1h time interval # - so we will miss the first trades. t, from_id = await self._async_fetch_trades(pair, since=since) trades.extend(t[x]) while True: try: t, from_id_next = await self._async_fetch_trades( pair, params={self._trades_pagination_arg: from_id}) if t: trades.extend(t[x]) if from_id == from_id_next or (until and t[-1][0] > until): logger.debug(f"Stopping because from_id did not change. " f"Reached {t[-1][0]} > {until}") # Reached the end of the defined-download period - add last trade as well. if has_overlap: trades.extend(t[-1:]) break from_id = from_id_next else: logger.debug("Stopping as no more trades were returned.") break except asyncio.CancelledError: logger.debug("Async operation Interrupted, breaking trades DL loop.") break return (pair, trades) async def _async_get_trade_history_time(self, pair: str, until: int, since: Optional[int] = None) -> Tuple[str, List[List]]: """ Asyncronously gets trade history using fetch_trades, when the exchange uses time-based iteration (check `self._trades_pagination`) :param pair: Pair to fetch trade data for :param since: Since as integer timestamp in milliseconds :param until: Until as integer timestamp in milliseconds returns tuple: (pair, trades-list) """ trades: List[List] = [] # DEFAULT_TRADES_COLUMNS: 0 -> timestamp # DEFAULT_TRADES_COLUMNS: 1 -> id while True: try: t, since_next = await self._async_fetch_trades(pair, since=since) if t: # No more trades to download available at the exchange, # So we repeatedly get the same trade over and over again. if since == since_next and len(t) == 1: logger.debug("Stopping because no more trades are available.") break since = since_next trades.extend(t) # Reached the end of the defined-download period if until and since_next > until: logger.debug( f"Stopping because until was reached. {since_next} > {until}") break else: logger.debug("Stopping as no more trades were returned.") break except asyncio.CancelledError: logger.debug("Async operation Interrupted, breaking trades DL loop.") break return (pair, trades) async def _async_get_trade_history(self, pair: str, since: Optional[int] = None, until: Optional[int] = None, from_id: Optional[str] = None, stop_on_from_id: Optional[bool] = True, ) -> Tuple[str, List[List]]: """ Async wrapper handling downloading trades using either time or id based methods. """ logger.debug(f"_async_get_trade_history(), pair: {pair}, " f"since: {since}, until: {until}, from_id: {from_id}") if self._trades_pagination == 'time': if until is None: until = ccxt.Exchange.milliseconds() logger.debug(f"Exchange milliseconds: {until}") return await self._async_get_trade_history_time( pair=pair, since=since, until=until) elif self._trades_pagination == 'id': return await self._async_get_trade_history_id( pair=pair, since=since, until=until, from_id=from_id, stop_on_from_id=stop_on_from_id ) else: raise OperationalException(f"Exchange {self.name} does use neither time, " f"nor id based pagination") def get_historic_trades(self, pair: str, since: Optional[int] = None, until: Optional[int] = None, from_id: Optional[str] = None, stop_on_from_id: Optional[bool] = True ) -> Tuple[str, List]: """ Get trade history data using asyncio. Handles all async work and returns the list of candles. Async over one pair, assuming we get `self.ohlcv_candle_limit()` candles per call. :param pair: Pair to download :param since: Timestamp in milliseconds to get history from :param until: Timestamp in milliseconds. Defaults to current timestamp if not defined. :param from_id: Download data starting with ID (if id is known) :returns List of trade data """ if not self.exchange_has("fetchTrades"): raise OperationalException("This exchange does not support downloading Trades.") with self._loop_lock: task = asyncio.ensure_future(self._async_get_trade_history( pair=pair, since=since, until=until, from_id=from_id)) for sig in [signal.SIGINT, signal.SIGTERM]: try: self.loop.add_signal_handler(sig, task.cancel) except NotImplementedError: # Not all platforms implement signals (e.g. windows) pass return self.loop.run_until_complete(task) def _download_trades_history(self, pair: str, *, new_pairs_days: int = 30, since: Optional[int] = None, until: Optional[int] = None, from_id: Optional[int] = None, stop_on_from_id: Optional[bool] = False ) -> bool: """ Download trade history from the exchange. Appends to previously downloaded trades data. :param until: is in msecs :param since: is in msecs :return Boolean of success """ new_trades = self.get_historic_trades(pair=pair, since=since, until=until, from_id=from_id, stop_on_from_id=stop_on_from_id) return new_trades @retrier def _get_funding_fees_from_exchange(self, pair: str, since: Union[datetime, int]) -> float: """ Returns the sum of all funding fees that were exchanged for a pair within a timeframe Dry-run handling happens as part of _calculate_funding_fees. :param pair: (e.g. ADA/USDT) :param since: The earliest time of consideration for calculating funding fees, in unix time or as a datetime """ if not self.exchange_has("fetchFundingHistory"): raise OperationalException( f"fetch_funding_history() is not available using {self.name}" ) if type(since) is datetime: since = int(since.timestamp()) * 1000 # * 1000 for ms try: funding_history = self._api.fetch_funding_history( symbol=pair, since=since ) self._log_exchange_response('funding_history', funding_history, add_info=f"pair: {pair}, since: {since}") return sum(fee['amount'] for fee in funding_history) except ccxt.DDoSProtection as e: raise DDosProtection(e) from e except (ccxt.NetworkError, ccxt.ExchangeError) as e: raise TemporaryError( f'Could not get funding fees due to {e.__class__.__name__}. Message: {e}') from e except ccxt.BaseError as e: raise OperationalException(e) from e @retrier def get_leverage_tiers(self) -> Dict[str, List[Dict]]: try: return self._api.fetch_leverage_tiers() except ccxt.DDoSProtection as e: raise DDosProtection(e) from e except (ccxt.NetworkError, ccxt.ExchangeError) as e: raise TemporaryError( f'Could not load leverage tiers due to {e.__class__.__name__}. Message: {e}' ) from e except ccxt.BaseError as e: raise OperationalException(e) from e @retrier_async async def get_market_leverage_tiers(self, symbol: str) -> Tuple[str, List[Dict]]: """ Leverage tiers per symbol """ try: tier = await self._api_async.fetch_market_leverage_tiers(symbol) return symbol, tier except ccxt.DDoSProtection as e: raise DDosProtection(e) from e except (ccxt.NetworkError, ccxt.ExchangeError) as e: raise TemporaryError( f'Could not load leverage tiers for {symbol}' f' due to {e.__class__.__name__}. Message: {e}' ) from e except ccxt.BaseError as e: raise OperationalException(e) from e def load_leverage_tiers(self) -> Dict[str, List[Dict]]: if self.trading_mode == TradingMode.FUTURES: if self.exchange_has('fetchLeverageTiers'): # Fetch all leverage tiers at once return self.get_leverage_tiers() elif self.exchange_has('fetchMarketLeverageTiers'): # Must fetch the leverage tiers for each market separately # * This is slow(~45s) on Okx, makes ~90 api calls to load all linear swap markets markets = self.markets symbols = [ symbol for symbol, market in markets.items() if (self.market_is_future(market) and market['quote'] == self._config['stake_currency']) ] tiers: Dict[str, List[Dict]] = {} tiers_cached = self.load_cached_leverage_tiers(self._config['stake_currency']) if tiers_cached: tiers = tiers_cached coros = [ self.get_market_leverage_tiers(symbol) for symbol in sorted(symbols) if symbol not in tiers] # Be verbose here, as this delays startup by ~1 minute. if coros: logger.info( f"Initializing leverage_tiers for {len(symbols)} markets. " "This will take about a minute.") else: logger.info("Using cached leverage_tiers.") async def gather_results(input_coro): return await asyncio.gather(*input_coro, return_exceptions=True) for input_coro in chunks(coros, 100): with self._loop_lock: results = self.loop.run_until_complete(gather_results(input_coro)) for res in results: if isinstance(res, Exception): logger.warning(f"Leverage tier exception: {repr(res)}") continue symbol, tier = res tiers[symbol] = tier if len(coros) > 0: self.cache_leverage_tiers(tiers, self._config['stake_currency']) logger.info(f"Done initializing {len(symbols)} markets.") return tiers return {} def cache_leverage_tiers(self, tiers: Dict[str, List[Dict]], stake_currency: str) -> None: filename = self._config['datadir'] / "futures" / f"leverage_tiers_{stake_currency}.json" if not filename.parent.is_dir(): filename.parent.mkdir(parents=True) data = { "updated": datetime.now(timezone.utc), "data": tiers, } file_dump_json(filename, data) def load_cached_leverage_tiers(self, stake_currency: str) -> Optional[Dict[str, List[Dict]]]: filename = self._config['datadir'] / "futures" / f"leverage_tiers_{stake_currency}.json" if filename.is_file(): try: tiers = file_load_json(filename) updated = tiers.get('updated') if updated: updated_dt = parser.parse(updated) if updated_dt < datetime.now(timezone.utc) - timedelta(weeks=4): logger.info("Cached leverage tiers are outdated. Will update.") return None return tiers['data'] except Exception: logger.exception("Error loading cached leverage tiers. Refreshing.") return None def fill_leverage_tiers(self) -> None: """ Assigns property _leverage_tiers to a dictionary of information about the leverage allowed on each pair """ leverage_tiers = self.load_leverage_tiers() for pair, tiers in leverage_tiers.items(): pair_tiers = [] for tier in tiers: pair_tiers.append(self.parse_leverage_tier(tier)) self._leverage_tiers[pair] = pair_tiers def parse_leverage_tier(self, tier) -> Dict: info = tier.get('info', {}) return { 'minNotional': tier['minNotional'], 'maxNotional': tier['maxNotional'], 'maintenanceMarginRate': tier['maintenanceMarginRate'], 'maxLeverage': tier['maxLeverage'], 'maintAmt': float(info['cum']) if 'cum' in info else None, } def get_max_leverage(self, pair: str, stake_amount: Optional[float]) -> float: """ Returns the maximum leverage that a pair can be traded at :param pair: The base/quote currency pair being traded :stake_amount: The total value of the traders margin_mode in quote currency """ if self.trading_mode == TradingMode.SPOT: return 1.0 if self.trading_mode == TradingMode.FUTURES: # Checks and edge cases if stake_amount is None: raise OperationalException( f'{self.name}.get_max_leverage requires argument stake_amount' ) if pair not in self._leverage_tiers: # Maybe raise exception because it can't be traded on futures? return 1.0 pair_tiers = self._leverage_tiers[pair] if stake_amount == 0: return self._leverage_tiers[pair][0]['maxLeverage'] # Max lev for lowest amount for tier_index in range(len(pair_tiers)): tier = pair_tiers[tier_index] lev = tier['maxLeverage'] if tier_index < len(pair_tiers) - 1: next_tier = pair_tiers[tier_index + 1] next_floor = next_tier['minNotional'] / next_tier['maxLeverage'] if next_floor > stake_amount: # Next tier min too high for stake amount return min((tier['maxNotional'] / stake_amount), lev) # # With the two leverage tiers below, # - a stake amount of 150 would mean a max leverage of (10000 / 150) = 66.66 # - stakes below 133.33 = max_lev of 75 # - stakes between 133.33-200 = max_lev of 10000/stake = 50.01-74.99 # - stakes from 200 + 1000 = max_lev of 50 # # { # "min": 0, # stake = 0.0 # "max": 10000, # max_stake@75 = 10000/75 = 133.33333333333334 # "lev": 75, # }, # { # "min": 10000, # stake = 200.0 # "max": 50000, # max_stake@50 = 50000/50 = 1000.0 # "lev": 50, # } # else: # if on the last tier if stake_amount > tier['maxNotional']: # If stake is > than max tradeable amount raise InvalidOrderException(f'Amount {stake_amount} too high for {pair}') else: return tier['maxLeverage'] raise OperationalException( 'Looped through all tiers without finding a max leverage. Should never be reached' ) elif self.trading_mode == TradingMode.MARGIN: # Search markets.limits for max lev market = self.markets[pair] if market['limits']['leverage']['max'] is not None: return market['limits']['leverage']['max'] else: return 1.0 # Default if max leverage cannot be found else: return 1.0 @retrier def _set_leverage( self, leverage: float, pair: Optional[str] = None, accept_fail: bool = False, ): """ Set's the leverage before making a trade, in order to not have the same leverage on every trade """ if self._config['dry_run'] or not self.exchange_has("setLeverage"): # Some exchanges only support one margin_mode type return if self._ft_has.get('floor_leverage', False) is True: # Rounding for binance ... leverage = floor(leverage) try: res = self._api.set_leverage(symbol=pair, leverage=leverage) self._log_exchange_response('set_leverage', res) except ccxt.DDoSProtection as e: raise DDosProtection(e) from e except (ccxt.BadRequest, ccxt.InsufficientFunds) as e: if not accept_fail: raise TemporaryError( f'Could not set leverage due to {e.__class__.__name__}. Message: {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 def get_interest_rate(self) -> float: """ Retrieve interest rate - necessary for Margin trading. Should not call the exchange directly when used from backtesting. """ return 0.0 def funding_fee_cutoff(self, open_date: datetime) -> bool: """ Funding fees are only charged at full hours (usually every 4-8h). Therefore a trade opening at 10:00:01 will not be charged a funding fee until the next hour. :param open_date: The open date for a trade :return: True if the date falls on a full hour, False otherwise """ return open_date.minute == 0 and open_date.second == 0 @retrier def set_margin_mode(self, pair: str, margin_mode: MarginMode, accept_fail: bool = False, params: dict = {}): """ Set's the margin mode on the exchange to cross or isolated for a specific pair :param pair: base/quote currency pair (e.g. "ADA/USDT") """ if self._config['dry_run'] or not self.exchange_has("setMarginMode"): # Some exchanges only support one margin_mode type return try: res = self._api.set_margin_mode(margin_mode.value, pair, params) self._log_exchange_response('set_margin_mode', res) except ccxt.DDoSProtection as e: raise DDosProtection(e) from e except ccxt.BadRequest as e: if not accept_fail: raise TemporaryError( f'Could not set margin mode due to {e.__class__.__name__}. Message: {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 _fetch_and_calculate_funding_fees( self, pair: str, amount: float, is_short: bool, open_date: datetime, close_date: Optional[datetime] = None ) -> float: """ Fetches and calculates the sum of all funding fees that occurred for a pair during a futures trade. Only used during dry-run or if the exchange does not provide a funding_rates endpoint. :param pair: The quote/base pair of the trade :param amount: The quantity of the trade :param is_short: trade direction :param open_date: The date and time that the trade started :param close_date: The date and time that the trade ended """ if self.funding_fee_cutoff(open_date): # Shift back to 1h candle to avoid missing funding fees # Only really relevant for trades very close to the full hour open_date = timeframe_to_prev_date('1h', open_date) timeframe = self._ft_has['mark_ohlcv_timeframe'] timeframe_ff = self._ft_has['funding_fee_timeframe'] mark_price_type = CandleType.from_string(self._ft_has["mark_ohlcv_price"]) if not close_date: close_date = datetime.now(timezone.utc) since_ms = int(timeframe_to_prev_date(timeframe, open_date).timestamp()) * 1000 mark_comb: PairWithTimeframe = (pair, timeframe, mark_price_type) funding_comb: PairWithTimeframe = (pair, timeframe_ff, CandleType.FUNDING_RATE) candle_histories = self.refresh_latest_ohlcv( [mark_comb, funding_comb], since_ms=since_ms, cache=False, drop_incomplete=False, ) try: # we can't assume we always get histories - for example during exchange downtimes funding_rates = candle_histories[funding_comb] mark_rates = candle_histories[mark_comb] except KeyError: raise ExchangeError("Could not find funding rates.") from None funding_mark_rates = self.combine_funding_and_mark(funding_rates, mark_rates) return self.calculate_funding_fees( funding_mark_rates, amount=amount, is_short=is_short, open_date=open_date, close_date=close_date ) @staticmethod 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'}) 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, df: DataFrame, amount: float, is_short: bool, open_date: datetime, close_date: datetime, time_in_ratio: Optional[float] = None ) -> float: """ calculates the sum of all funding fees that occurred for a pair during a futures trade :param df: Dataframe containing combined funding and mark rates as `open_fund` and `open_mark`. :param amount: The quantity of the trade :param is_short: trade direction :param open_date: The date and time that the trade started :param close_date: The date and time that the trade ended :param time_in_ratio: Not used by most exchange classes """ fees: float = 0 if not df.empty: df1 = df[(df['date'] >= open_date) & (df['date'] <= close_date)] fees = sum(df1['open_fund'] * df1['open_mark'] * amount) # Negate fees for longs as funding_fees expects it this way based on live endpoints. return fees if is_short else -fees def get_funding_fees( self, pair: str, amount: float, is_short: bool, open_date: datetime) -> float: """ Fetch funding fees, either from the exchange (live) or calculates them based on funding rate/mark price history :param pair: The quote/base pair of the trade :param is_short: trade direction :param amount: Trade amount :param open_date: Open date of the trade :return: funding fee since open_date """ if self.trading_mode == TradingMode.FUTURES: try: if self._config['dry_run']: funding_fees = self._fetch_and_calculate_funding_fees( pair, amount, is_short, open_date) else: funding_fees = self._get_funding_fees_from_exchange(pair, open_date) return funding_fees except ExchangeError: logger.warning(f"Could not update funding fees for {pair}.") return 0.0 def get_liquidation_price( self, pair: str, # Dry-run open_rate: float, # Entry price of position is_short: bool, amount: float, # Absolute value of position size stake_amount: float, leverage: float, wallet_balance: float, mm_ex_1: float = 0.0, # (Binance) Cross only upnl_ex_1: float = 0.0, # (Binance) Cross only ) -> Optional[float]: """ Set's the margin mode on the exchange to cross or isolated for a specific pair """ if self.trading_mode == TradingMode.SPOT: return None elif (self.trading_mode != TradingMode.FUTURES): raise OperationalException( f"{self.name} does not support {self.margin_mode} {self.trading_mode}") liquidation_price = None if self._config['dry_run'] or not self.exchange_has("fetchPositions"): liquidation_price = self.dry_run_liquidation_price( pair=pair, open_rate=open_rate, is_short=is_short, amount=amount, leverage=leverage, stake_amount=stake_amount, wallet_balance=wallet_balance, mm_ex_1=mm_ex_1, upnl_ex_1=upnl_ex_1 ) else: positions = self.fetch_positions(pair) if len(positions) > 0: pos = positions[0] liquidation_price = pos['liquidationPrice'] if liquidation_price is not None: buffer_amount = abs(open_rate - liquidation_price) * self.liquidation_buffer liquidation_price_buffer = ( liquidation_price - buffer_amount if is_short else liquidation_price + buffer_amount ) return max(liquidation_price_buffer, 0.0) else: return None def dry_run_liquidation_price( self, pair: str, open_rate: float, # Entry price of position is_short: bool, amount: float, stake_amount: float, leverage: float, wallet_balance: float, # Or margin balance mm_ex_1: float = 0.0, # (Binance) Cross only upnl_ex_1: float = 0.0, # (Binance) Cross only ) -> Optional[float]: """ Important: Must be fetching data from cached values as this is used by backtesting! PERPETUAL: gate: https://www.gate.io/help/futures/futures/27724/liquidation-price-bankruptcy-price > Liquidation Price = (Entry Price ± Margin / Contract Multiplier / Size) / [ 1 ± (Maintenance Margin Ratio + Taker Rate)] Wherein, "+" or "-" depends on whether the contract goes long or short: "-" for long, and "+" for short. okex: https://www.okex.com/support/hc/en-us/articles/ 360053909592-VI-Introduction-to-the-isolated-mode-of-Single-Multi-currency-Portfolio-margin :param pair: Pair to calculate liquidation price for :param open_rate: Entry price of position :param is_short: True if the trade is a short, false otherwise :param amount: Absolute value of position size incl. leverage (in base currency) :param stake_amount: Stake amount - Collateral in settle currency. :param leverage: Leverage used for this position. :param trading_mode: SPOT, MARGIN, FUTURES, etc. :param margin_mode: Either ISOLATED or CROSS :param wallet_balance: Amount of margin_mode in the wallet being used to trade Cross-Margin Mode: crossWalletBalance Isolated-Margin Mode: isolatedWalletBalance # * Not required by Gate or OKX :param mm_ex_1: :param upnl_ex_1: """ market = self.markets[pair] taker_fee_rate = market['taker'] mm_ratio, _ = self.get_maintenance_ratio_and_amt(pair, stake_amount) if self.trading_mode == TradingMode.FUTURES and self.margin_mode == MarginMode.ISOLATED: if market['inverse']: raise OperationalException( "Freqtrade does not yet support inverse contracts") value = wallet_balance / amount mm_ratio_taker = (mm_ratio + taker_fee_rate) if is_short: return (open_rate + value) / (1 + mm_ratio_taker) else: return (open_rate - value) / (1 - mm_ratio_taker) else: raise OperationalException( "Freqtrade only supports isolated futures for leverage trading") def get_maintenance_ratio_and_amt( self, pair: str, nominal_value: float, ) -> Tuple[float, Optional[float]]: """ Important: Must be fetching data from cached values as this is used by backtesting! :param pair: Market symbol :param nominal_value: The total trade amount in quote currency including leverage maintenance amount only on Binance :return: (maintenance margin ratio, maintenance amount) """ if (self._config.get('runmode') in OPTIMIZE_MODES or self.exchange_has('fetchLeverageTiers') or self.exchange_has('fetchMarketLeverageTiers')): if pair not in self._leverage_tiers: raise InvalidOrderException( f"Maintenance margin rate for {pair} is unavailable for {self.name}" ) pair_tiers = self._leverage_tiers[pair] for tier in reversed(pair_tiers): if nominal_value >= tier['minNotional']: return (tier['maintenanceMarginRate'], tier['maintAmt']) raise ExchangeError("nominal value can not be lower than 0") # The lowest notional_floor for any pair in fetch_leverage_tiers is always 0 because it # describes the min amt for a tier, and the lowest tier will always go down to 0 else: raise ExchangeError(f"Cannot get maintenance ratio using {self.name}")