feat: add standalone HTML reports

2026-07-27 12:07:44 +00:00 · 2026-07-17 14:54:59 +00:00
parent 4fcadca02e
commit c31e0088db
13 changed files with 539 additions and 17 deletions
@@ -16,6 +16,6 @@ jobs:
          python-version: "3.12"
      - run: cargo check
      - run: cargo test
-      - run: python -m pip install .
+      - run: python -m pip install ".[report]"
      - run: python -m unittest discover -s "$GITHUB_WORKSPACE/tests"
        working-directory: /tmp
@@ -6,3 +6,6 @@ __pycache__/
 CLAUDE.md
 data/
 .env
+.venv/
+uv.lock
+/backtestingfx-report.html
@@ -43,6 +43,24 @@ Profit Factor:  0.94
 Max Drawdown:   3.21%
 ```

+### Interactive HTML report
+
+Install the optional report dependency and generate a self-contained HTML file:
+
+```bash
+pip install "backtestingfx[report]"
+```
+
+```python
+bt = Backtest(df, MyCrossStrategy, cash=10000.0, spread=0.0001)
+stats = bt.run()
+bt.plot("strategy-report.html")
+```
+
+The report includes candlesticks, trade entries and exits, equity, drawdown,
+trade diagnostics, and a complete trade ledger. Plotly is embedded in the file,
+so the report works offline without a server.
+
 ## Installation

 ```
@@ -140,6 +158,9 @@ bt = Backtest(df, MyStrategy, cash=10000.0, spread=0.00015, quote_to_account=1.2
 | `worst_trade` | Worst single trade PnL in USD |
 | `profit_factor` | Gross profit / gross loss |
 | `max_drawdown_pct` | Maximum drawdown as a percentage |
+| `sharpe_ratio` | Unannualized Sharpe ratio |
+| `equity_curve` | Account equity from initial cash through final liquidation |
+| `trades` | Completed trades with entry, exit, size, direction, and net PnL |

 ## Data Format

@@ -1,2 +1,2 @@
-from backtestingfx._backtestingfx import Bar, Engine, Stats, Broker  # type: ignore
+from backtestingfx._backtestingfx import Bar, Broker, Engine, Stats, Trade  # type: ignore
 from backtestingfx.backtest import Strategy, Backtest
@@ -89,15 +89,17 @@ class Backtest:
        self._spread = spread
        self._contract_size = contract_size
        self._quote_to_account = quote_to_account
+        self._stats = None
+        self._report_df = None

-    def _to_bars(self):
+    def _to_bars(self, df):
        required = {"open", "high", "low", "close"}
-        missing = required - set(self._df.columns.str.lower())
+        missing = required - set(df.columns.str.lower())
        if missing:
            raise ValueError(f"DataFrame missing required columns: {sorted(missing)}")

        bars = []
-        for idx, row in self._df.iterrows():
+        for idx, row in df.iterrows():
            if isinstance(idx, pd.Timestamp):
                ts = int(idx.timestamp())
            else:
@@ -116,7 +118,10 @@ class Backtest:
        return bars

    def run(self):
-        bars = self._to_bars()
+        self._stats = None
+        self._report_df = None
+        report_df = self._df.copy(deep=True)
+        bars = self._to_bars(report_df)
        engine = _rust.Engine(  # type: ignore
            bars,
            self._cash,
@@ -126,4 +131,24 @@ class Backtest:
            self._quote_to_account,
        )
        strategy = self._strategy_class()
-        return engine.run(_Adapter(strategy))
+        self._stats = engine.run(_Adapter(strategy))
+        self._report_df = report_df
+        return self._stats
+
+    def plot(self, filename="backtest.html", open_browser=True):
+        if self._stats is None:
+            raise RuntimeError("Run the backtest before plotting it")
+
+        from backtestingfx.plotting import render_report
+
+        return render_report(
+            self._report_df,
+            self._stats,
+            strategy_name=self._strategy_class.__name__,
+            filename=filename,
+            open_browser=open_browser,
+            commission=self._commission,
+            spread=self._spread,
+            contract_size=self._contract_size,
+            quote_to_account=self._quote_to_account,
+        )
@@ -0,0 +1,369 @@
+import html
+import math
+from pathlib import Path
+import webbrowser
+
+import pandas as pd
+
+
+def render_report(
+    data,
+    stats,
+    *,
+    strategy_name,
+    filename,
+    open_browser,
+    commission,
+    spread,
+    contract_size,
+    quote_to_account,
+):
+    try:
+        import plotly.graph_objects as go
+        import plotly.io as pio
+        from plotly.subplots import make_subplots
+    except ModuleNotFoundError as error:
+        raise ModuleNotFoundError(
+            'Plotting requires Plotly. Install it with: pip install "backtestingfx[report]"'
+        ) from error
+
+    if data.empty:
+        raise ValueError("Cannot plot a backtest with no bars")
+
+    columns = {str(column).lower(): column for column in data.columns}
+    if isinstance(data.index, pd.DatetimeIndex):
+        timestamps = pd.to_datetime(data.index, utc=True)
+    else:
+        timestamps = pd.to_datetime(data[columns["timestamp"]], utc=True)
+
+    equity = list(stats.equity_curve)
+    if len(equity) == len(data) + 1:
+        equity = equity[1:]
+    if len(equity) != len(data):
+        raise ValueError("Equity curve does not match the number of bars")
+
+    equity_series = pd.Series(equity, dtype=float)
+    peaks = pd.Series([stats.initial_cash, *equity], dtype=float).cummax().iloc[1:]
+    peaks.index = equity_series.index
+    drawdown = ((equity_series / peaks) - 1.0).fillna(0.0) * 100.0
+    trades = list(stats.trades)
+
+    chart = make_subplots(
+        rows=3,
+        cols=1,
+        shared_xaxes=True,
+        vertical_spacing=0.045,
+        row_heights=[0.58, 0.24, 0.18],
+    )
+    chart.add_trace(
+        go.Candlestick(
+            x=timestamps,
+            open=data[columns["open"]],
+            high=data[columns["high"]],
+            low=data[columns["low"]],
+            close=data[columns["close"]],
+            name="Price",
+            increasing_line_color="#45d483",
+            decreasing_line_color="#ff6b57",
+        ),
+        row=1,
+        col=1,
+    )
+
+    entry_lines_x = []
+    entry_lines_y = []
+    for trade in trades:
+        entry_lines_x.extend(
+            [
+                pd.to_datetime(trade.entry_timestamp, unit="s", utc=True),
+                pd.to_datetime(trade.exit_timestamp, unit="s", utc=True),
+                None,
+            ]
+        )
+        entry_lines_y.extend([trade.entry_price, trade.exit_price, None])
+    if trades:
+        chart.add_trace(
+            go.Scatter(
+                x=entry_lines_x,
+                y=entry_lines_y,
+                mode="lines",
+                line={"color": "rgba(190, 190, 190, 0.28)", "width": 1},
+                hoverinfo="skip",
+                showlegend=False,
+            ),
+            row=1,
+            col=1,
+        )
+
+    for is_long, label, color, symbol in (
+        (True, "Long entry", "#45d483", "triangle-up"),
+        (False, "Short entry", "#ff6b57", "triangle-down"),
+    ):
+        matching = [trade for trade in trades if trade.is_long == is_long]
+        if matching:
+            chart.add_trace(
+                go.Scatter(
+                    x=[pd.to_datetime(t.entry_timestamp, unit="s", utc=True) for t in matching],
+                    y=[t.entry_price for t in matching],
+                    mode="markers",
+                    name=label,
+                    marker={"color": color, "size": 11, "symbol": symbol},
+                    customdata=[[t.lot_size, t.pnl] for t in matching],
+                    hovertemplate=(
+                        f"{label}<br>%{{x}}<br>Price %{{y:.5f}}"
+                        "<br>Lots %{customdata[0]:.2f}<br>Net PnL %{customdata[1]:.2f}<extra></extra>"
+                    ),
+                ),
+                row=1,
+                col=1,
+            )
+
+    if trades:
+        chart.add_trace(
+            go.Scatter(
+                x=[pd.to_datetime(t.exit_timestamp, unit="s", utc=True) for t in trades],
+                y=[t.exit_price for t in trades],
+                mode="markers",
+                name="Exit",
+                marker={
+                    "color": ["#45d483" if t.pnl >= 0 else "#ff6b57" for t in trades],
+                    "line": {"color": "#080808", "width": 1},
+                    "size": 9,
+                    "symbol": "circle",
+                },
+                customdata=[[t.pnl] for t in trades],
+                hovertemplate=(
+                    "Exit<br>%{x}<br>Price %{y:.5f}"
+                    "<br>Net PnL %{customdata[0]:.2f}<extra></extra>"
+                ),
+            ),
+            row=1,
+            col=1,
+        )
+
+    chart.add_trace(
+        go.Scatter(
+            x=timestamps,
+            y=equity,
+            mode="lines",
+            name="Equity",
+            line={"color": "#f1c75b", "width": 2},
+            hovertemplate="%{x}<br>Equity %{y:,.2f}<extra></extra>",
+        ),
+        row=2,
+        col=1,
+    )
+    chart.add_hline(
+        y=stats.initial_cash,
+        line={"color": "rgba(255,255,255,0.22)", "dash": "dot"},
+        row=2,
+        col=1,
+    )
+    chart.add_trace(
+        go.Scatter(
+            x=timestamps,
+            y=drawdown,
+            mode="lines",
+            name="Drawdown",
+            line={"color": "#ff6b57", "width": 1.5},
+            fill="tozeroy",
+            fillcolor="rgba(255, 107, 87, 0.20)",
+            hovertemplate="%{x}<br>Drawdown %{y:.2f}%<extra></extra>",
+        ),
+        row=3,
+        col=1,
+    )
+    chart.update_layout(
+        height=920,
+        margin={"l": 60, "r": 25, "t": 35, "b": 35},
+        paper_bgcolor="#111111",
+        plot_bgcolor="#111111",
+        font={"color": "#d0d0d0", "family": "IBM Plex Mono, ui-monospace, monospace"},
+        hovermode="x unified",
+        legend={"orientation": "h", "y": 1.03, "x": 0},
+        xaxis_rangeslider_visible=False,
+    )
+    chart.update_xaxes(gridcolor="rgba(255,255,255,0.06)", showspikes=True)
+    chart.update_yaxes(gridcolor="rgba(255,255,255,0.06)", zeroline=False)
+    chart.update_yaxes(title_text="Price", row=1, col=1)
+    chart.update_yaxes(title_text="Equity", row=2, col=1)
+    chart.update_yaxes(title_text="Drawdown %", row=3, col=1)
+
+    analytics = make_subplots(
+        rows=1,
+        cols=2,
+        subplot_titles=("Trade PnL distribution", "Cumulative realized PnL"),
+        horizontal_spacing=0.12,
+    )
+    pnls = [trade.pnl for trade in trades]
+    if pnls:
+        analytics.add_trace(
+            go.Histogram(x=pnls, marker_color="#9da3ad", name="Trade PnL"),
+            row=1,
+            col=1,
+        )
+        cumulative = pd.Series(pnls).cumsum()
+        analytics.add_trace(
+            go.Scatter(
+                x=list(range(1, len(pnls) + 1)),
+                y=cumulative,
+                mode="lines+markers",
+                line={"color": "#45d483", "width": 2},
+                marker={"size": 5},
+                name="Cumulative PnL",
+            ),
+            row=1,
+            col=2,
+        )
+    else:
+        analytics.add_annotation(
+            text="No completed trades",
+            x=0.5,
+            y=0.5,
+            xref="paper",
+            yref="paper",
+            showarrow=False,
+        )
+    analytics.update_layout(
+        height=390,
+        margin={"l": 55, "r": 25, "t": 55, "b": 45},
+        paper_bgcolor="#111111",
+        plot_bgcolor="#111111",
+        font={"color": "#d0d0d0", "family": "IBM Plex Mono, ui-monospace, monospace"},
+        showlegend=False,
+    )
+    analytics.update_xaxes(gridcolor="rgba(255,255,255,0.06)")
+    analytics.update_yaxes(gridcolor="rgba(255,255,255,0.06)", zeroline=False)
+
+    def number(value, suffix="", money=False):
+        if math.isinf(value):
+            return "&infin;"
+        prefix = "$" if money else ""
+        return f"{prefix}{value:,.2f}{suffix}"
+
+    metric_values = (
+        ("Total return", number(stats.total_return_pct, "%")),
+        ("Final equity", number(stats.final_cash, money=True)),
+        ("Max drawdown", number(stats.max_drawdown_pct, "%")),
+        ("Sharpe", number(stats.sharpe_ratio)),
+        ("Trades", str(stats.num_trades)),
+        ("Win rate", number(stats.win_rate_pct, "%")),
+        ("Profit factor", number(stats.profit_factor)),
+        ("Average trade", number(stats.avg_pnl, money=True)),
+    )
+    metrics_html = "".join(
+        f'<div class="metric"><span>{label}</span><strong>{value}</strong></div>'
+        for label, value in metric_values
+    )
+
+    rows = []
+    for trade in trades:
+        entry_time = pd.to_datetime(trade.entry_timestamp, unit="s", utc=True)
+        exit_time = pd.to_datetime(trade.exit_timestamp, unit="s", utc=True)
+        duration = exit_time - entry_time
+        result_class = "positive" if trade.pnl >= 0 else "negative"
+        rows.append(
+            "<tr>"
+            f"<td>{'LONG' if trade.is_long else 'SHORT'}</td>"
+            f"<td>{html.escape(entry_time.strftime('%Y-%m-%d %H:%M'))}</td>"
+            f"<td>{html.escape(exit_time.strftime('%Y-%m-%d %H:%M'))}</td>"
+            f"<td>{trade.entry_price:.5f}</td>"
+            f"<td>{trade.exit_price:.5f}</td>"
+            f"<td>{trade.lot_size:.2f}</td>"
+            f'<td class="{result_class}">{trade.pnl:,.2f}</td>'
+            f"<td>{html.escape(str(duration))}</td>"
+            "</tr>"
+        )
+    if not rows:
+        rows.append('<tr><td colspan="8" class="empty">No completed trades</td></tr>')
+
+    config = {"displaylogo": False, "responsive": True, "scrollZoom": True}
+    chart_html = pio.to_html(
+        chart,
+        full_html=False,
+        include_plotlyjs=True,
+        config=config,
+    )
+    analytics_html = pio.to_html(
+        analytics,
+        full_html=False,
+        include_plotlyjs=False,
+        config=config,
+    )
+    start = timestamps[0].strftime("%Y-%m-%d %H:%M UTC")
+    end = timestamps[-1].strftime("%Y-%m-%d %H:%M UTC")
+    safe_strategy_name = html.escape(strategy_name)
+
+    document = f"""<!doctype html>
+<html lang="en">
+<head>
+  <meta charset="utf-8">
+  <meta name="viewport" content="width=device-width, initial-scale=1">
+  <title>{safe_strategy_name} | backtestingfx report</title>
+  <style>
+    :root {{ color-scheme: dark; --bg: #080808; --panel: #111111; --line: #2b2b2b; --ink: #f1f1f1; --muted: #929292; --accent: #d8d8d8; --green: #45d483; --red: #ff6b57; --gold: #f1c75b; }}
+    * {{ box-sizing: border-box; }}
+    body {{ margin: 0; background: var(--bg); color: var(--ink); font-family: Inter, ui-sans-serif, system-ui, sans-serif; }}
+    body::before {{ content: ""; position: fixed; inset: 0; pointer-events: none; background-image: linear-gradient(rgba(255,255,255,.018) 1px, transparent 1px), linear-gradient(90deg, rgba(255,255,255,.018) 1px, transparent 1px); background-size: 42px 42px; mask-image: linear-gradient(to bottom, black, transparent 65%); }}
+    main {{ width: min(1500px, calc(100% - 40px)); margin: 0 auto; padding: 38px 0 70px; position: relative; }}
+    header {{ display: flex; justify-content: space-between; gap: 30px; align-items: end; padding: 8px 0 28px; border-bottom: 1px solid var(--line); }}
+    .eyebrow {{ color: var(--accent); font: 700 12px/1.4 ui-monospace, monospace; letter-spacing: .18em; text-transform: uppercase; }}
+    h1 {{ margin: 8px 0 14px; font-size: clamp(34px, 4.5vw, 64px); line-height: 1.08; letter-spacing: -.045em; overflow-wrap: anywhere; }}
+    .period {{ color: var(--muted); font: 13px/1.6 ui-monospace, monospace; }}
+    .status {{ border: 1px solid #444; color: var(--accent); background: rgba(255,255,255,.04); border-radius: 999px; padding: 9px 14px; font: 700 11px ui-monospace, monospace; letter-spacing: .12em; white-space: nowrap; }}
+    .metrics {{ display: grid; grid-template-columns: repeat(4, 1fr); gap: 1px; margin: 28px 0; background: var(--line); border: 1px solid var(--line); }}
+    .metric {{ background: var(--panel); padding: 18px 20px; min-height: 98px; display: flex; flex-direction: column; justify-content: space-between; }}
+    .metric span, .section-label {{ color: var(--muted); font: 700 10px ui-monospace, monospace; letter-spacing: .14em; text-transform: uppercase; }}
+    .metric strong {{ font: 600 clamp(21px, 2vw, 31px) ui-monospace, monospace; letter-spacing: -.04em; }}
+    .panel {{ background: var(--panel); border: 1px solid var(--line); margin-top: 18px; overflow: hidden; }}
+    .panel-head {{ display: flex; justify-content: space-between; align-items: center; padding: 18px 22px; border-bottom: 1px solid var(--line); }}
+    .panel-head h2 {{ margin: 0; font-size: 17px; letter-spacing: -.02em; }}
+    .assumptions {{ display: grid; grid-template-columns: repeat(4, 1fr); border-top: 1px solid var(--line); }}
+    .assumption {{ padding: 15px 20px; border-right: 1px solid var(--line); }}
+    .assumption:last-child {{ border-right: 0; }}
+    .assumption span {{ display: block; color: var(--muted); font: 10px ui-monospace, monospace; text-transform: uppercase; letter-spacing: .1em; margin-bottom: 5px; }}
+    .assumption strong {{ font: 14px ui-monospace, monospace; }}
+    .table-wrap {{ overflow-x: auto; }}
+    table {{ width: 100%; border-collapse: collapse; font: 12px ui-monospace, monospace; }}
+    th {{ color: var(--muted); text-align: left; font-size: 10px; letter-spacing: .09em; text-transform: uppercase; }}
+    th, td {{ padding: 13px 16px; border-bottom: 1px solid var(--line); white-space: nowrap; }}
+    tbody tr:hover {{ background: rgba(255,255,255,.025); }}
+    .positive {{ color: var(--green); }} .negative {{ color: var(--red); }} .empty {{ color: var(--muted); text-align: center; padding: 30px; }}
+    footer {{ color: var(--muted); display: flex; justify-content: space-between; margin-top: 28px; font: 10px ui-monospace, monospace; letter-spacing: .08em; text-transform: uppercase; }}
+    @media (max-width: 900px) {{ .metrics {{ grid-template-columns: repeat(2, 1fr); }} .assumptions {{ grid-template-columns: repeat(2, 1fr); }} header {{ align-items: start; flex-direction: column; }} }}
+    @media (max-width: 560px) {{ main {{ width: min(100% - 20px, 1500px); padding-top: 20px; }} .metrics {{ grid-template-columns: 1fr; }} .assumptions {{ grid-template-columns: 1fr; }} .metric {{ min-height: 82px; }} }}
+  </style>
+</head>
+<body>
+  <main>
+    <header>
+      <div><div class="eyebrow">backtestingfx / strategy report</div><h1>{safe_strategy_name}</h1><div class="period">{start} &rarr; {end} &nbsp; / &nbsp; {len(data):,} bars</div></div>
+      <div class="status">RUN COMPLETE</div>
+    </header>
+    <section class="metrics">{metrics_html}</section>
+    <section class="panel">
+      <div class="panel-head"><h2>Market replay</h2><span class="section-label">Price / Equity / Drawdown</span></div>
+      {chart_html}
+      <div class="assumptions">
+        <div class="assumption"><span>Commission / lot / side</span><strong>{commission:,.4f}</strong></div>
+        <div class="assumption"><span>Spread offset</span><strong>{spread:,.5f}</strong></div>
+        <div class="assumption"><span>Contract size</span><strong>{contract_size:,.0f}</strong></div>
+        <div class="assumption"><span>Quote conversion</span><strong>{quote_to_account:,.5f}</strong></div>
+      </div>
+    </section>
+    <section class="panel"><div class="panel-head"><h2>Trade diagnostics</h2><span class="section-label">Distribution / Sequence</span></div>{analytics_html}</section>
+    <section class="panel">
+      <div class="panel-head"><h2>Trade ledger</h2><span class="section-label">{len(trades)} completed</span></div>
+      <div class="table-wrap"><table><thead><tr><th>Side</th><th>Entry time</th><th>Exit time</th><th>Entry</th><th>Exit</th><th>Lots</th><th>Net PnL</th><th>Duration</th></tr></thead><tbody>{''.join(rows)}</tbody></table></div>
+    </section>
+    <footer><span>Generated by backtestingfx</span><span>Research output, not financial advice</span></footer>
+  </main>
+</body>
+</html>"""
+
+    output = Path(filename).expanduser().resolve()
+    output.parent.mkdir(parents=True, exist_ok=True)
+    output.write_text(document, encoding="utf-8")
+    if open_browser:
+        webbrowser.open(output.as_uri())
+    return str(output)
@@ -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')}")
@@ -11,6 +11,9 @@ dependencies = ["pandas"]
 license = { text = "MIT" }
 readme = "README.md"

+[project.optional-dependencies]
+report = ["plotly>=5"]
+
 [tool.maturin]
 module-name = "backtestingfx._backtestingfx"
 features = ["pyo3/extension-module"]
@@ -15,5 +15,6 @@ fn backtestingfx(m: &Bound<'_, PyModule>) -> PyResult<()> {
    m.add_class::<broker::Broker>()?;
    m.add_class::<engine::Engine>()?;
    m.add_class::<types::Position>()?;
+    m.add_class::<types::Trade>()?;
    Ok(())
 }
@@ -1,4 +1,5 @@
 use crate::broker::Broker;
+use crate::types::Trade;
 use pyo3::prelude::*;

 #[pyclass]
@@ -27,6 +28,10 @@ pub struct Stats {
    pub max_drawdown_pct: f64,
    #[pyo3(get)]
    pub sharpe_ratio: f64,
+    #[pyo3(get)]
+    pub equity_curve: Vec<f64>,
+    #[pyo3(get)]
+    pub trades: Vec<Trade>,
 }

 fn sharpe_ratio(equity_curve: &[f64]) -> f64 {
@@ -134,6 +139,8 @@ impl Stats {
            profit_factor,
            max_drawdown_pct,
            sharpe_ratio,
+            equity_curve: equity_curve.to_vec(),
+            trades: broker.trade_history.clone(),
        }
    }
 }
@@ -1,8 +1,7 @@
-use crate::types::Bar;
 use crate::broker::Broker;
+use crate::types::Bar;

 pub trait Strategy {
    fn init(&mut self, _data: &[Bar]) {}
    fn next(&mut self, bar: &Bar, broker: &mut Broker);
 }
-
@@ -66,14 +66,22 @@ impl Position {
    }
 }

+#[pyclass(from_py_object)]
 #[derive(Debug, Clone)]
 pub struct Trade {
    // the actual trade
+    #[pyo3(get)]
    pub entry_price: f64,
+    #[pyo3(get)]
    pub exit_price: f64,
+    #[pyo3(get)]
    pub lot_size: f64,
+    #[pyo3(get)]
    pub is_long: bool,
+    #[pyo3(get)]
    pub pnl: f64,
+    #[pyo3(get)]
    pub entry_timestamp: i64,
+    #[pyo3(get)]
    pub exit_timestamp: i64,
 }
@@ -1,3 +1,5 @@
+from pathlib import Path
+import tempfile
 import unittest

 import pandas as pd
@@ -7,33 +9,56 @@ from backtestingfx import Backtest, Strategy

 class BuyAndHold(Strategy):
    def next(self):
-        self.buy(1.0)
+        if not self.positions:
+            self.buy(1.0)


 class BacktestTest(unittest.TestCase):
    def test_run_returns_stats_from_python_strategy(self):
        data = pd.DataFrame(
            {
-                "open": [1.1],
-                "high": [1.1],
-                "low": [1.1],
-                "close": [1.1],
+                "open": [1.1, 1.1],
+                "high": [1.1, 1.1],
+                "low": [1.1, 1.1],
+                "close": [1.1, 1.1],
            },
-            index=pd.to_datetime(["2026-01-01"], utc=True),
+            index=pd.to_datetime(["2026-01-01 00:00", "2026-01-01 01:00"], utc=True),
        )

-        stats = Backtest(
+        backtest = Backtest(
            data,
            BuyAndHold,
            cash=10_000.0,
            commission=7.0,
            spread=0.0,
-        ).run()
+        )
+        stats = backtest.run()

        self.assertEqual(stats.initial_cash, 10_000.0)
        self.assertEqual(stats.final_cash, 9_986.0)
        self.assertEqual(stats.num_trades, 1)
        self.assertEqual(stats.avg_pnl, -14.0)
+        self.assertEqual(stats.equity_curve, [10_000.0, 9_993.0, 9_986.0])
+        self.assertEqual(len(stats.trades), 1)
+        self.assertEqual(stats.trades[0].pnl, -14.0)
+        self.assertEqual(
+            stats.trades[0].exit_timestamp - stats.trades[0].entry_timestamp,
+            3_600,
+        )
+
+        data.drop(index=data.index[-1], inplace=True)
+        with tempfile.TemporaryDirectory() as directory:
+            report = Path(
+                backtest.plot(Path(directory) / "report.html", open_browser=False)
+            )
+            contents = report.read_text(encoding="utf-8")
+
+            self.assertTrue(report.is_file())
+            self.assertIn("BuyAndHold | backtestingfx report", contents)
+            self.assertIn("Market replay", contents)
+            self.assertIn("Plotly.newPlot", contents)
+            self.assertIn("2026-01-01 00:00", contents)
+            self.assertIn("2026-01-01 01:00", contents)


 if __name__ == "__main__":