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https://github.com/KhizarImran/backtestingfx.git
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testing out python library integration
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import backtestingfx as _rust
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import pandas as pd
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class Strategy:
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def init(self):
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pass
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def next(self):
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pass
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def buy(self, lot_size, stop_loss=None, take_profit=None):
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self._broker.buy(self._bar.close, lot_size, self._bar.timestamp, stop_loss, take_profit)
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def sell(self, lot_size, stop_loss=None, take_profit=None):
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self._broker.sell(self._bar.close, lot_size, self._bar.timestamp, stop_loss, take_profit)
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def close_all(self):
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self._broker.close_all(self._bar.close, self._bar.timestamp)
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def close_position(self, id):
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self._broker.close_position(id, self._bar.close, self._bar.timestamp)
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class _Adapter:
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def __init__(self, strategy):
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self._strategy = strategy
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def init(self, bars):
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self._strategy.bars = bars
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self._strategy.init()
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def next(self, bar, broker):
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self._strategy._bar = bar
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self._strategy._broker = broker
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self._strategy.next()
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class Backtest:
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def __init__(self, df, strategy_class, cash=10000.0, commission=0.0, spread=0.0):
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self._df = df
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self._strategy_class = strategy_class
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self._cash = cash
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self._commission = commission
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self._spread = spread
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def _to_bars(self):
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bars = []
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for idx, row in self._df.iterrows():
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if isinstance(idx, pd.Timestamp):
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ts = int(idx.timestamp())
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else:
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ts = int(pd.Timestamp(row["timestamp"]).timestamp())
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bars.append(_rust.Bar(
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timestamp=ts,
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open=float(row["open"]),
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high=float(row["high"]),
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low=float(row["low"]),
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close=float(row["close"]),
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volume=float(row.get("volume", 0.0))
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))
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return bars
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def run(self):
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bars = self._to_bars()
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engine = _rust.Engine(bars, self._cash, self._commission, self._spread)
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strategy = self._strategy_class()
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return engine.run(_Adapter(strategy))
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