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https://github.com/freqtrade/freqtrade.git
synced 2024-11-10 10:21:59 +00:00
commit
585536835a
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@ -6,6 +6,8 @@ from freqtrade.exchange.exchange import (get_exchange_bad_reason, # noqa: F401
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available_exchanges)
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from freqtrade.exchange.exchange import (timeframe_to_seconds, # noqa: F401
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timeframe_to_minutes,
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timeframe_to_msecs)
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timeframe_to_msecs,
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timeframe_to_next_date,
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timeframe_to_prev_date)
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from freqtrade.exchange.kraken import Kraken # noqa: F401
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from freqtrade.exchange.binance import Binance # noqa: F401
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@ -6,7 +6,7 @@ import asyncio
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import inspect
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import logging
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from copy import deepcopy
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from datetime import datetime
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from datetime import datetime, timezone
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from math import ceil, floor
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from random import randint
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from typing import Any, Dict, List, Optional, Tuple
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@ -790,13 +790,45 @@ def timeframe_to_seconds(ticker_interval: str) -> int:
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def timeframe_to_minutes(ticker_interval: str) -> int:
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"""
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Same as above, but returns minutes.
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Same as timeframe_to_seconds, but returns minutes.
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"""
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return ccxt.Exchange.parse_timeframe(ticker_interval) // 60
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def timeframe_to_msecs(ticker_interval: str) -> int:
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"""
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Same as above, but returns milliseconds.
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Same as timeframe_to_seconds, but returns milliseconds.
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"""
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return ccxt.Exchange.parse_timeframe(ticker_interval) * 1000
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def timeframe_to_prev_date(timeframe: str, date: datetime = None) -> datetime:
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"""
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Use Timeframe and determine last possible candle.
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:param timeframe: timeframe in string format (e.g. "5m")
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:param date: date to use. Defaults to utcnow()
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:returns: date of previous candle (with utc timezone)
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"""
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if not date:
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date = datetime.now(timezone.utc)
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timeframe_secs = timeframe_to_seconds(timeframe)
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# Get offset based on timerame_secs
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offset = date.timestamp() % timeframe_secs
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# Subtract seconds passed since last offset
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new_timestamp = date.timestamp() - offset
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return datetime.fromtimestamp(new_timestamp, tz=timezone.utc)
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def timeframe_to_next_date(timeframe: str, date: datetime = None) -> datetime:
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"""
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Use Timeframe and determine next candle.
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:param timeframe: timeframe in string format (e.g. "5m")
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:param date: date to use. Defaults to utcnow()
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:returns: date of next candle (with utc timezone)
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"""
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prevdate = timeframe_to_prev_date(timeframe, date)
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timeframe_secs = timeframe_to_seconds(timeframe)
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# Add one interval to previous candle
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new_timestamp = prevdate.timestamp() + timeframe_secs
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return datetime.fromtimestamp(new_timestamp, tz=timezone.utc)
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@ -16,7 +16,7 @@ from freqtrade import (DependencyException, OperationalException, InvalidOrderEx
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from freqtrade.data.converter import order_book_to_dataframe
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from freqtrade.data.dataprovider import DataProvider
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from freqtrade.edge import Edge
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from freqtrade.exchange import timeframe_to_minutes
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from freqtrade.exchange import timeframe_to_minutes, timeframe_to_next_date
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from freqtrade.persistence import Trade
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from freqtrade.rpc import RPCManager, RPCMessageType
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from freqtrade.resolvers import ExchangeResolver, StrategyResolver, PairListResolver
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@ -283,6 +283,9 @@ class FreqtradeBot(object):
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buycount = 0
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# running get_signal on historical data fetched
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for _pair in whitelist:
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if self.strategy.is_pair_locked(_pair):
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logger.info(f"Pair {_pair} is currently locked.")
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continue
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(buy, sell) = self.strategy.get_signal(
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_pair, interval, self.dataprovider.ohlcv(_pair, self.strategy.ticker_interval))
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@ -674,6 +677,9 @@ class FreqtradeBot(object):
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if stoploss_order and stoploss_order['status'] == 'closed':
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trade.sell_reason = SellType.STOPLOSS_ON_EXCHANGE.value
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trade.update(stoploss_order)
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# Lock pair for one candle to prevent immediate rebuys
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self.strategy.lock_pair(trade.pair,
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timeframe_to_next_date(self.config['ticker_interval']))
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self._notify_sell(trade)
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return True
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@ -884,6 +890,10 @@ class FreqtradeBot(object):
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if order.get('status', 'unknown') == 'closed':
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trade.update(order)
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Trade.session.flush()
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# Lock pair for one candle to prevent immediate rebuys
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self.strategy.lock_pair(trade.pair, timeframe_to_next_date(self.config['ticker_interval']))
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self._notify_sell(trade)
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def _notify_sell(self, trade: Trade):
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@ -4,7 +4,7 @@ This module defines the interface to apply for strategies
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"""
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import logging
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from abc import ABC, abstractmethod
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from datetime import datetime
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from datetime import datetime, timezone
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from enum import Enum
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from typing import Dict, List, NamedTuple, Optional, Tuple
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import warnings
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@ -107,6 +107,7 @@ class IStrategy(ABC):
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self.config = config
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# Dict to determine if analysis is necessary
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self._last_candle_seen_per_pair: Dict[str, datetime] = {}
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self._pair_locked_until: Dict[str, datetime] = {}
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@abstractmethod
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def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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@ -154,6 +155,24 @@ class IStrategy(ABC):
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"""
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return self.__class__.__name__
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def lock_pair(self, pair: str, until: datetime) -> None:
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"""
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Locks pair until a given timestamp happens.
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Locked pairs are not analyzed, and are prevented from opening new trades.
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:param pair: Pair to lock
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:param until: datetime in UTC until the pair should be blocked from opening new trades.
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Needs to be timezone aware `datetime.now(timezone.utc)`
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"""
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self._pair_locked_until[pair] = until
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def is_pair_locked(self, pair: str) -> bool:
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"""
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Checks if a pair is currently locked
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"""
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if pair not in self._pair_locked_until:
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return False
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return self._pair_locked_until[pair] >= datetime.now(timezone.utc)
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def analyze_ticker(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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"""
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Parses the given ticker history and returns a populated DataFrame
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@ -260,8 +279,8 @@ class IStrategy(ABC):
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sell: bool, low: float = None, high: float = None,
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force_stoploss: float = 0) -> SellCheckTuple:
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"""
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This function evaluate if on the condition required to trigger a sell has been reached
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if the threshold is reached and updates the trade record.
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This function evaluates if one of the conditions required to trigger a sell
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has been reached, which can either be a stop-loss, ROI or sell-signal.
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:param low: Only used during backtesting to simulate stoploss
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:param high: Only used during backtesting, to simulate ROI
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:param force_stoploss: Externally provided stoploss
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@ -14,7 +14,11 @@ from pandas import DataFrame
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from freqtrade import (DependencyException, InvalidOrderException,
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OperationalException, TemporaryError)
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from freqtrade.exchange import Binance, Exchange, Kraken
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from freqtrade.exchange.exchange import API_RETRY_COUNT
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from freqtrade.exchange.exchange import (API_RETRY_COUNT, timeframe_to_minutes,
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timeframe_to_msecs,
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timeframe_to_next_date,
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timeframe_to_prev_date,
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timeframe_to_seconds)
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from freqtrade.resolvers.exchange_resolver import ExchangeResolver
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from freqtrade.tests.conftest import get_patched_exchange, log_has, log_has_re
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@ -1540,3 +1544,74 @@ def test_get_valid_pair_combination(default_conf, mocker, markets):
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assert ex.get_valid_pair_combination("BTC", "ETH") == "ETH/BTC"
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with pytest.raises(DependencyException, match=r"Could not combine.* to get a valid pair."):
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ex.get_valid_pair_combination("NOPAIR", "ETH")
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def test_timeframe_to_minutes():
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assert timeframe_to_minutes("5m") == 5
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assert timeframe_to_minutes("10m") == 10
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assert timeframe_to_minutes("1h") == 60
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assert timeframe_to_minutes("1d") == 1440
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def test_timeframe_to_seconds():
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assert timeframe_to_seconds("5m") == 300
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assert timeframe_to_seconds("10m") == 600
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assert timeframe_to_seconds("1h") == 3600
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assert timeframe_to_seconds("1d") == 86400
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def test_timeframe_to_msecs():
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assert timeframe_to_msecs("5m") == 300000
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assert timeframe_to_msecs("10m") == 600000
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assert timeframe_to_msecs("1h") == 3600000
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assert timeframe_to_msecs("1d") == 86400000
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def test_timeframe_to_prev_date():
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# 2019-08-12 13:22:08
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date = datetime.fromtimestamp(1565616128, tz=timezone.utc)
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tf_list = [
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# 5m -> 2019-08-12 13:20:00
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("5m", datetime(2019, 8, 12, 13, 20, 0, tzinfo=timezone.utc)),
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# 10m -> 2019-08-12 13:20:00
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("10m", datetime(2019, 8, 12, 13, 20, 0, tzinfo=timezone.utc)),
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# 1h -> 2019-08-12 13:00:00
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("1h", datetime(2019, 8, 12, 13, 00, 0, tzinfo=timezone.utc)),
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# 2h -> 2019-08-12 12:00:00
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("2h", datetime(2019, 8, 12, 12, 00, 0, tzinfo=timezone.utc)),
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# 4h -> 2019-08-12 12:00:00
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("4h", datetime(2019, 8, 12, 12, 00, 0, tzinfo=timezone.utc)),
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# 1d -> 2019-08-12 00:00:00
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("1d", datetime(2019, 8, 12, 00, 00, 0, tzinfo=timezone.utc)),
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]
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for interval, result in tf_list:
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assert timeframe_to_prev_date(interval, date) == result
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date = datetime.now(tz=timezone.utc)
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assert timeframe_to_prev_date("5m", date) < date
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def test_timeframe_to_next_date():
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# 2019-08-12 13:22:08
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date = datetime.fromtimestamp(1565616128, tz=timezone.utc)
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tf_list = [
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# 5m -> 2019-08-12 13:25:00
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("5m", datetime(2019, 8, 12, 13, 25, 0, tzinfo=timezone.utc)),
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# 10m -> 2019-08-12 13:30:00
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("10m", datetime(2019, 8, 12, 13, 30, 0, tzinfo=timezone.utc)),
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# 1h -> 2019-08-12 14:00:00
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("1h", datetime(2019, 8, 12, 14, 00, 0, tzinfo=timezone.utc)),
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# 2h -> 2019-08-12 14:00:00
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("2h", datetime(2019, 8, 12, 14, 00, 0, tzinfo=timezone.utc)),
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# 4h -> 2019-08-12 14:00:00
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("4h", datetime(2019, 8, 12, 16, 00, 0, tzinfo=timezone.utc)),
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# 1d -> 2019-08-13 00:00:00
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("1d", datetime(2019, 8, 13, 0, 0, 0, tzinfo=timezone.utc)),
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]
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for interval, result in tf_list:
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assert timeframe_to_next_date(interval, date) == result
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date = datetime.now(tz=timezone.utc)
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assert timeframe_to_next_date("5m", date) > date
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@ -286,3 +286,19 @@ def test__analyze_ticker_internal_skip_analyze(ticker_history, mocker, caplog) -
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assert ret['sell'].sum() == 0
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assert not log_has('TA Analysis Launched', caplog)
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assert log_has('Skipping TA Analysis for already analyzed candle', caplog)
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def test_is_pair_locked(default_conf):
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strategy = DefaultStrategy(default_conf)
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# dict should be empty
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assert not strategy._pair_locked_until
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pair = 'ETH/BTC'
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assert not strategy.is_pair_locked(pair)
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strategy.lock_pair(pair, arrow.utcnow().shift(minutes=4).datetime)
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# ETH/BTC locked for 4 minutes
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assert strategy.is_pair_locked(pair)
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# XRP/BTC should not be locked now
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pair = 'XRP/BTC'
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assert not strategy.is_pair_locked(pair)
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@ -2598,6 +2598,43 @@ def test_sell_profit_only_disable_loss(default_conf, limit_buy_order, fee, marke
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assert trade.sell_reason == SellType.SELL_SIGNAL.value
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def test_locked_pairs(default_conf, ticker, fee, ticker_sell_down, markets, mocker, caplog) -> None:
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patch_RPCManager(mocker)
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mocker.patch.multiple(
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'freqtrade.exchange.Exchange',
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_load_markets=MagicMock(return_value={}),
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get_ticker=ticker,
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get_fee=fee,
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markets=PropertyMock(return_value=markets)
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)
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freqtrade = FreqtradeBot(default_conf)
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patch_get_signal(freqtrade)
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# Create some test data
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freqtrade.create_trades()
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trade = Trade.query.first()
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assert trade
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# Decrease the price and sell it
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mocker.patch.multiple(
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'freqtrade.exchange.Exchange',
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get_ticker=ticker_sell_down
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)
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freqtrade.execute_sell(trade=trade, limit=ticker_sell_down()['bid'],
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sell_reason=SellType.STOP_LOSS)
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trade.close(ticker_sell_down()['bid'])
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assert trade.pair in freqtrade.strategy._pair_locked_until
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assert freqtrade.strategy.is_pair_locked(trade.pair)
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# reinit - should buy other pair.
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caplog.clear()
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freqtrade.create_trades()
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assert log_has(f"Pair {trade.pair} is currently locked.", caplog)
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def test_ignore_roi_if_buy_signal(default_conf, limit_buy_order, fee, markets, mocker) -> None:
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patch_RPCManager(mocker)
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patch_exchange(mocker)
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