Document lock-pair implementation
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@ -455,6 +455,49 @@ Sample return value: ETH/BTC had 5 trades, with a total profit of 1.5% (ratio of
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!!! Warning
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!!! Warning
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Trade history is not available during backtesting or hyperopt.
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Trade history is not available during backtesting or hyperopt.
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### Prevent trades from happening for a specific pair
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Freqtrade locks pairs automatically for the current candle (until that candle is over) when a pair is sold, preventing an immediate re-buy of that pair.
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Locked pairs will show the message `Pair <pair> is currently locked.`.
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#### Locking pairs from within the strategy
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Sometimes it may be desired to lock a pair after certain events happen (e.g. multiple losing trades in a row).
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Freqtrade has an easy method to do this from within the strategy, by calling `self.lock_pair(pair, until)`.
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Until should be a time in the future, after which trading will be reenabled for that pair.
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Locks can also be lifted manually, by calling `self.unlock_pair(pair)`.
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!!! Note
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Locked pairs are not persisted, so a restart of the bot, or calling `/reload_conf` will reset locked pairs.
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!!! Warning
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Locking pairs is not functional during backtesting.
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##### Pair locking example
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``` python
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from freqtrade.persistence import Trade
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from datetime import timedelta, datetime, timezone
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# Put the above lines a the top of the strategy file, next to all the other imports
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# --------
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# Within populate indicators (or populate_buy):
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if self.config['runmode'] in ('live', 'dry_run'):
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# fetch closed trades for the last 2 days
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trades = Trade.get_trades([Trade.pair == metadata['pair'],
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Trade.open_date > datetime.utcnow() - timedelta(days=2),
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Trade.is_open == False,
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]).all()
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# Analyze the conditions you'd like to lock the pair .... will probably be different for every strategy
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sumprofit = sum(trade.close_profit for trade in trades)
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if sumprofit < 0:
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# Lock pair for 2 days
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self.lock_pair(metadata['pair'], until=datetime.now(timezone.utc) + timedelta(days=2))
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```
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### Print created dataframe
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### Print created dataframe
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To inspect the created dataframe, you can issue a print-statement in either `populate_buy_trend()` or `populate_sell_trend()`.
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To inspect the created dataframe, you can issue a print-statement in either `populate_buy_trend()` or `populate_sell_trend()`.
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