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https://github.com/freqtrade/freqtrade.git
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Merge branch 'develop' into tsl_on_exchange
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commit
a44f781284
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@ -221,7 +221,7 @@ class Backtesting(object):
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elif sell.sell_type == (SellType.ROI):
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# get next entry in min_roi > to trade duration
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# Interface.py skips on trade_duration <= duration
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roi_entry = max(list(filter(lambda x: trade_dur > x,
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roi_entry = max(list(filter(lambda x: trade_dur >= x,
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self.strategy.minimal_roi.keys())))
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roi = self.strategy.minimal_roi[roi_entry]
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@ -320,17 +320,18 @@ class IStrategy(ABC):
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def min_roi_reached(self, trade: Trade, current_profit: float, current_time: datetime) -> bool:
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"""
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Based an earlier trade and current price and ROI configuration, decides whether bot should
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sell
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sell. Requires current_profit to be in percent!!
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:return True if bot should sell at current rate
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"""
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# Check if time matches and current rate is above threshold
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time_diff = (current_time.timestamp() - trade.open_date.timestamp()) / 60
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for duration, threshold in self.minimal_roi.items():
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if time_diff <= duration:
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continue
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if current_profit > threshold:
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return True
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trade_dur = (current_time.timestamp() - trade.open_date.timestamp()) / 60
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# Get highest entry in ROI dict where key >= trade-duration
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roi_entry = max(list(filter(lambda x: trade_dur >= x, self.minimal_roi.keys())))
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threshold = self.minimal_roi[roi_entry]
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if current_profit > threshold:
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return True
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return False
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@ -530,10 +530,10 @@ def test_backtest(default_conf, fee, mocker) -> None:
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'open_time': [Arrow(2018, 1, 29, 18, 40, 0).datetime,
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Arrow(2018, 1, 30, 3, 30, 0).datetime],
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'close_time': [Arrow(2018, 1, 29, 22, 35, 0).datetime,
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Arrow(2018, 1, 30, 4, 15, 0).datetime],
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Arrow(2018, 1, 30, 4, 10, 0).datetime],
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'open_index': [78, 184],
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'close_index': [125, 193],
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'trade_duration': [235, 45],
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'close_index': [125, 192],
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'trade_duration': [235, 40],
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'open_at_end': [False, False],
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'open_rate': [0.104445, 0.10302485],
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'close_rate': [0.104969, 0.103541],
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@ -118,6 +118,7 @@ def test_tickerdata_to_dataframe(default_conf) -> None:
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def test_min_roi_reached(default_conf, fee) -> None:
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# Use list to confirm sequence does not matter
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min_roi_list = [{20: 0.05, 55: 0.01, 0: 0.1},
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{0: 0.1, 20: 0.05, 55: 0.01}]
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for roi in min_roi_list:
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@ -143,6 +144,47 @@ def test_min_roi_reached(default_conf, fee) -> None:
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assert strategy.min_roi_reached(trade, 0.02, arrow.utcnow().shift(minutes=-1).datetime)
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def test_min_roi_reached2(default_conf, fee) -> None:
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# test with ROI raising after last interval
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min_roi_list = [{20: 0.07,
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30: 0.05,
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55: 0.30,
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0: 0.1
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},
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{0: 0.1,
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20: 0.07,
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30: 0.05,
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55: 0.30
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},
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]
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for roi in min_roi_list:
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strategy = DefaultStrategy(default_conf)
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strategy.minimal_roi = roi
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trade = Trade(
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pair='ETH/BTC',
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stake_amount=0.001,
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open_date=arrow.utcnow().shift(hours=-1).datetime,
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fee_open=fee.return_value,
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fee_close=fee.return_value,
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exchange='bittrex',
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open_rate=1,
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)
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assert not strategy.min_roi_reached(trade, 0.02, arrow.utcnow().shift(minutes=-56).datetime)
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assert strategy.min_roi_reached(trade, 0.12, arrow.utcnow().shift(minutes=-56).datetime)
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assert not strategy.min_roi_reached(trade, 0.04, arrow.utcnow().shift(minutes=-39).datetime)
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assert strategy.min_roi_reached(trade, 0.071, arrow.utcnow().shift(minutes=-39).datetime)
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assert not strategy.min_roi_reached(trade, 0.04, arrow.utcnow().shift(minutes=-26).datetime)
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assert strategy.min_roi_reached(trade, 0.06, arrow.utcnow().shift(minutes=-26).datetime)
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# Should not trigger with 20% profit since after 55 minutes only 30% is active.
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assert not strategy.min_roi_reached(trade, 0.20, arrow.utcnow().shift(minutes=-2).datetime)
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assert strategy.min_roi_reached(trade, 0.31, arrow.utcnow().shift(minutes=-2).datetime)
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def test_analyze_ticker_default(ticker_history, mocker, caplog) -> None:
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caplog.set_level(logging.DEBUG)
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ind_mock = MagicMock(side_effect=lambda x, meta: x)
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