feat: add standalone HTML reports

examples/html_report.py

@@ -0,0 +1,61 @@
+import math
+
+import pandas as pd
+
+from backtestingfx import Backtest, Strategy
+
+
+class MovingAverageCycle(Strategy):
+    fast = 8
+    slow = 24
+
+    def next(self):
+        if self.index + 1 < self.slow:
+            return
+
+        closes = [bar.close for bar in self.data[-self.slow :]]
+        fast_average = sum(closes[-self.fast :]) / self.fast
+        slow_average = sum(closes) / self.slow
+        should_be_long = fast_average > slow_average
+
+        if self.positions and self.positions[0].is_long != should_be_long:
+            self.close_all()
+
+        if not self.positions:
+            if should_be_long:
+                self.buy(0.1)
+            else:
+                self.sell(0.1)
+
+
+def sample_data():
+    timestamps = pd.date_range("2025-01-01", periods=360, freq="h", tz="UTC")
+    closes = [
+        1.1000 + 0.0040 * math.sin(i / 13) + 0.0010 * math.sin(i / 3)
+        for i in range(len(timestamps))
+    ]
+    opens = [closes[0], *closes[:-1]]
+
+    return pd.DataFrame(
+        {
+            "open": opens,
+            "high": [max(open_, close) + 0.0004 for open_, close in zip(opens, closes)],
+            "low": [min(open_, close) - 0.0004 for open_, close in zip(opens, closes)],
+            "close": closes,
+            "volume": [800 + int(300 * abs(math.sin(i / 9))) for i in range(len(timestamps))],
+        },
+        index=timestamps,
+    )
+
+
+data = sample_data()
+backtest = Backtest(
+    data,
+    MovingAverageCycle,
+    cash=10_000,
+    commission=3.5,
+    spread=0.00002,
+)
+
+print(backtest.run())
+print(f"\nReport written to: {backtest.plot('backtestingfx-report.html')}")