Merge branch 'feat/short' into fs_fix
This commit is contained in:
@@ -9,7 +9,7 @@ import logging
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from copy import deepcopy
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from datetime import datetime, timedelta, timezone
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from math import ceil
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from typing import Any, Dict, List, Literal, Optional, Tuple, Union
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from typing import Any, Coroutine, Dict, List, Literal, Optional, Tuple, Union
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import arrow
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import ccxt
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@@ -1639,6 +1639,24 @@ class Exchange:
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data = sorted(data, key=lambda x: x[0])
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return pair, timeframe, candle_type, data
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def _build_coroutine(self, pair: str, timeframe: str, candle_type: CandleType,
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since_ms: Optional[int]) -> Coroutine:
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if not since_ms and self.required_candle_call_count > 1:
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# Multiple calls for one pair - to get more history
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one_call = timeframe_to_msecs(timeframe) * self.ohlcv_candle_limit(timeframe)
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move_to = one_call * self.required_candle_call_count
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now = timeframe_to_next_date(timeframe)
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since_ms = int((now - timedelta(seconds=move_to // 1000)).timestamp() * 1000)
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if since_ms:
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return self._async_get_historic_ohlcv(
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pair, timeframe, since_ms=since_ms, raise_=True, candle_type=candle_type)
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else:
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# One call ... "regular" refresh
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return self._async_get_candle_history(
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pair, timeframe, since_ms=since_ms, candle_type=candle_type)
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def refresh_latest_ohlcv(self, pair_list: ListPairsWithTimeframes, *,
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since_ms: Optional[int] = None, cache: bool = True,
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drop_incomplete: bool = None
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@@ -1660,22 +1678,18 @@ class Exchange:
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cached_pairs = []
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# Gather coroutines to run
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for pair, timeframe, candle_type in set(pair_list):
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if (timeframe not in self.timeframes
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and candle_type in (CandleType.SPOT, CandleType.FUTURES)):
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logger.warning(
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f"Cannot download ({pair}, {timeframe}) combination as this timeframe is "
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f"not available on {self.name}. Available timeframes are "
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f"{', '.join(self.timeframes)}.")
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continue
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if ((pair, timeframe, candle_type) not in self._klines or not cache
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or self._now_is_time_to_refresh(pair, timeframe, candle_type)):
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if not since_ms and self.required_candle_call_count > 1:
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# Multiple calls for one pair - to get more history
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one_call = timeframe_to_msecs(timeframe) * self.ohlcv_candle_limit(timeframe)
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move_to = one_call * self.required_candle_call_count
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now = timeframe_to_next_date(timeframe)
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since_ms = int((now - timedelta(seconds=move_to // 1000)).timestamp() * 1000)
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input_coroutines.append(self._build_coroutine(
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pair, timeframe, candle_type=candle_type, since_ms=since_ms))
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if since_ms:
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input_coroutines.append(self._async_get_historic_ohlcv(
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pair, timeframe, since_ms=since_ms, raise_=True, candle_type=candle_type))
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else:
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# One call ... "regular" refresh
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input_coroutines.append(self._async_get_candle_history(
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pair, timeframe, since_ms=since_ms, candle_type=candle_type))
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else:
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logger.debug(
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f"Using cached candle (OHLCV) data for {pair}, {timeframe}, {candle_type} ..."
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@@ -1042,11 +1042,15 @@ class FreqtradeBot(LoggingMixin):
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stop_price = trade.open_rate * (1 + stoploss)
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if self.create_stoploss_order(trade=trade, stop_price=stop_price):
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# The above will return False if the placement failed and the trade was force-sold.
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# in which case the trade will be closed - which we must check below.
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trade.stoploss_last_update = datetime.utcnow()
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return False
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# If stoploss order is canceled for some reason we add it
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if stoploss_order and stoploss_order['status'] in ('canceled', 'cancelled'):
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if (trade.is_open
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and stoploss_order
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and stoploss_order['status'] in ('canceled', 'cancelled')):
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if self.create_stoploss_order(trade=trade, stop_price=trade.stop_loss):
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return False
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else:
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@@ -1056,7 +1060,7 @@ class FreqtradeBot(LoggingMixin):
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# Finally we check if stoploss on exchange should be moved up because of trailing.
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# Triggered Orders are now real orders - so don't replace stoploss anymore
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if (
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stoploss_order
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trade.is_open and stoploss_order
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and stoploss_order.get('status_stop') != 'triggered'
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and (self.config.get('trailing_stop', False)
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or self.config.get('use_custom_stoploss', False))
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@@ -195,6 +195,7 @@ def drop_orders_table(engine, table_back_name: str):
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def migrate_orders_table(engine, table_back_name: str, cols_order: List):
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ft_fee_base = get_column_def(cols_order, 'ft_fee_base', 'null')
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average = get_column_def(cols_order, 'average', 'null')
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# let SQLAlchemy create the schema as required
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leverage = get_column_def(cols_order, 'leverage', '1.0')
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@@ -205,8 +206,8 @@ def migrate_orders_table(engine, table_back_name: str, cols_order: List):
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status, symbol, order_type, side, price, amount, filled, average, remaining, cost,
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order_date, order_filled_date, order_update_date, ft_fee_base, leverage)
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select id, ft_trade_id, ft_order_side, ft_pair, ft_is_open, order_id,
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status, symbol, order_type, side, price, amount, filled, null average, remaining, cost,
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order_date, order_filled_date, order_update_date, {ft_fee_base} ft_fee_base,
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status, symbol, order_type, side, price, amount, filled, {average} average, remaining,
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cost, order_date, order_filled_date, order_update_date, {ft_fee_base} ft_fee_base,
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{leverage} leverage
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from {table_back_name}
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"""))
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@@ -100,7 +100,7 @@ class AgeFilter(IPairList):
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"""
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Validate age for the ticker
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:param pair: Pair that's currently validated
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:param ticker: ticker dict as returned from ccxt.fetch_tickers()
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:param daily_candles: Downloaded daily candles
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:return: True if the pair can stay, false if it should be removed
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"""
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# Check symbol in cache
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@@ -51,7 +51,7 @@ class PrecisionFilter(IPairList):
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:param ticker: ticker dict as returned from ccxt.fetch_tickers()
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:return: True if the pair can stay, false if it should be removed
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"""
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stop_price = ticker['ask'] * self._stoploss
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stop_price = ticker['last'] * self._stoploss
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# Adjust stop-prices to precision
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sp = self._exchange.price_to_precision(pair, stop_price)
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@@ -94,7 +94,7 @@ class VolatilityFilter(IPairList):
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"""
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Validate trading range
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:param pair: Pair that's currently validated
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:param ticker: ticker dict as returned from ccxt.fetch_tickers()
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:param daily_candles: Downloaded daily candles
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:return: True if the pair can stay, false if it should be removed
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"""
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# Check symbol in cache
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@@ -92,7 +92,7 @@ class RangeStabilityFilter(IPairList):
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"""
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Validate trading range
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:param pair: Pair that's currently validated
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:param ticker: ticker dict as returned from ccxt.fetch_tickers()
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:param daily_candles: Downloaded daily candles
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:return: True if the pair can stay, false if it should be removed
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"""
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# Check symbol in cache
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