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https://github.com/manifoldbt/manifoldbt.git
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Jimmy7892
67ab17280b
Python DSL, examples, docs, benchmarks, and tests. Rust engine distributed as pre-compiled wheel via PyPI.
87 lines
2.8 KiB
Python
87 lines
2.8 KiB
Python
"""Standalone backtrader benchmark - EMA(12/26) crossover on synthetic 1m data."""
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import argparse
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import time
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import numpy as np
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import pandas as pd
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import backtrader as btdr
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def generate_ohlcv(rows, seed=42):
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rng = np.random.default_rng(seed)
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returns = rng.normal(0.0, 0.0003, size=rows)
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mid = 100.0 * np.exp(np.cumsum(returns))
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noise = rng.uniform(0.0001, 0.001, size=rows) * mid
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timestamps = pd.date_range("2022-01-01", periods=rows, freq="1min", tz="UTC")
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return pd.DataFrame({
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"timestamp": timestamps,
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"open": mid + rng.uniform(-0.5, 0.5, size=rows) * noise,
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"high": mid + noise,
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"low": mid - noise,
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"close": mid + rng.uniform(-0.5, 0.5, size=rows) * noise,
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"volume": rng.uniform(100, 10_000, size=rows),
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})
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class EmaCross(btdr.Strategy):
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def __init__(self):
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self.fast = btdr.indicators.EMA(self.data.close, period=12)
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self.slow = btdr.indicators.EMA(self.data.close, period=26)
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self.crossover = btdr.indicators.CrossOver(self.fast, self.slow)
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def next(self):
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if self.crossover > 0:
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self.order_target_percent(target=0.5)
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elif self.crossover < 0:
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self.close()
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument("--rows", type=int, default=500_000)
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parser.add_argument("--runs", type=int, default=5)
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args = parser.parse_args()
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print(f"Generating {args.rows:,} synthetic 1-min bars...")
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df = generate_ohlcv(args.rows)
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bt_df = df[["timestamp", "open", "high", "low", "close", "volume"]].copy()
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bt_df = bt_df.rename(columns={"timestamp": "datetime"}).set_index("datetime")
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bt_df.index = bt_df.index.tz_localize(None)
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# Warmup
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print("Warmup run...")
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cerebro = btdr.Cerebro()
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cerebro.addstrategy(EmaCross)
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cerebro.adddata(btdr.feeds.PandasData(dataname=bt_df))
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cerebro.broker.set_cash(10_000)
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cerebro.broker.setcommission(commission=0.0005)
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cerebro.run()
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# Timed runs
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print(f"Running {args.runs}x timed...")
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times = []
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for i in range(args.runs):
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cerebro = btdr.Cerebro()
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cerebro.addstrategy(EmaCross)
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cerebro.adddata(btdr.feeds.PandasData(dataname=bt_df))
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cerebro.broker.set_cash(10_000)
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cerebro.broker.setcommission(commission=0.0005)
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t0 = time.perf_counter()
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cerebro.run()
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elapsed = time.perf_counter() - t0
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times.append(elapsed)
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print(f" run {i+1}: {elapsed*1000:.1f} ms")
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med = np.median(times)
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avg = np.mean(times)
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print(f"\nbacktrader results ({args.rows:,} bars):")
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print(f" median = {med*1000:.1f} ms")
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print(f" mean = {avg*1000:.1f} ms")
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print(f" min = {min(times)*1000:.1f} ms")
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print(f" max = {max(times)*1000:.1f} ms")
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if __name__ == "__main__":
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main()
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