feat: add Plotly PnL chart to CLI

src/quant_research_starter/backtest/__init__.py

@@ -1,4 +1,4 @@
-"""Backtest module public API."""
+"""Backtesting engines and portfolio simulation."""
 
 from .vectorized import VectorizedBacktest
 

src/quant_research_starter/cli.py

@@ -10,7 +10,7 @@
 from .backtest import VectorizedBacktest
 from .data import SampleDataLoader, SyntheticDataGenerator
 from .factors import MomentumFactor, SizeFactor, ValueFactor, VolatilityFactor
-from .metrics import RiskMetrics
+from .metrics import RiskMetrics, create_equity_curve_plot
 
 
 @click.group()
@@ -127,7 +127,13 @@ def compute_factors(data_file, factors, output):
     help="Output file for results",
 )
 @click.option("--plot/--no-plot", default=True, help="Generate plot")
-def backtest(data_file, signals_file, initial_capital, output, plot):
+@click.option(
+    "--plotly",
+    is_flag=True,
+    default=False,
+    help="Also generate interactive Plotly HTML chart",
+)
+def backtest(data_file, signals_file, initial_capital, output, plot, plotly):
     """Run backtest with given signals."""
     click.echo("Running backtest...")
 
@@ -214,6 +220,20 @@ def backtest(data_file, signals_file, initial_capital, output, plot):
 
         click.echo(f"Plot saved -> {plot_path}")
 
+    # Generate Plotly HTML chart if requested
+    if plotly:
+        html_path = output_path.parent / "backtest_plot.html"
+
+        create_equity_curve_plot(
+            dates=results_dict["dates"],
+            portfolio_values=results_dict["portfolio_value"],
+            initial_capital=initial_capital,
+            output_path=str(html_path),
+            plot_type="html",
+        )
+
+        click.echo(f"Plotly HTML chart saved -> {html_path}")
+
     click.echo("Backtest completed!")
     click.echo(f"Final portfolio value: ${results['final_value']:,.2f}")
     click.echo(f"Total return: {results['total_return']:.2%}")

src/quant_research_starter/metrics/__init__.py

@@ -1,5 +1,6 @@
 """Metrics module public API."""
 
+from .plotting import create_equity_curve_plot
 from .risk import RiskMetrics
 
-__all__ = ["RiskMetrics"]
+__all__ = ["create_equity_curve_plot", "RiskMetrics"]

src/quant_research_starter/metrics/plotting.py

@@ -0,0 +1,94 @@
+"""Plotting utilities for backtest results."""
+
+from pathlib import Path
+from typing import List
+
+import pandas as pd
+
+try:
+    import plotly.graph_objects as go
+
+    PLOTLY_AVAILABLE = True
+except ImportError:
+    PLOTLY_AVAILABLE = False
+
+import matplotlib.pyplot as plt
+
+
+def create_equity_curve_plot(
+    dates: List[str],
+    portfolio_values: List[float],
+    initial_capital: float,
+    output_path: str,
+    plot_type: str = "png",
+) -> str:
+    """
+    Create equity curve plot in specified format.
+    Args:
+        dates: List of date strings
+        portfolio_values: List of portfolio values
+        initial_capital: Starting capital
+        output_path: Path to save the plot
+        plot_type: 'png' for matplotlib, 'html' for plotly
+
+    Returns:
+        Path to saved file
+    """
+    Path(output_path).parent.mkdir(parents=True, exist_ok=True)
+    dates = pd.to_datetime(dates)
+    portfolio_series = pd.Series(portfolio_values, index=dates)
+    if plot_type == "html" and PLOTLY_AVAILABLE:
+        return _create_plotly_chart(portfolio_series, initial_capital, output_path)
+    else:
+        return _create_matplotlib_chart(portfolio_series, output_path)
+
+
+def _create_plotly_chart(
+    portfolio_series: pd.Series, initial_capital: float, output_path: str
+) -> str:
+    """Create interactive Plotly HTML chart."""
+    fig = go.Figure()
+    fig.add_trace(
+        go.Scatter(
+            x=portfolio_series.index,
+            y=portfolio_series.values,
+            mode="lines",
+            name="Portfolio Value",
+            line={"color": "#2E86AB", "width": 3},
+            hovertemplate="<b>Date</b>: %{x|%Y-%m-%d}<br><b>Value</b>: $%{y:,.2f}<extra></extra>",
+        )
+    )
+    # Add initial capital reference line
+    fig.add_hline(
+        y=initial_capital,
+        line_dash="dash",
+        line_color="red",
+        annotation_text=f"Initial Capital: ${initial_capital:,.0f}",
+        annotation_position="bottom right",
+    )
+    total_return_pct = ((portfolio_series.iloc[-1] / initial_capital) - 1) * 10
+    fig.update_layout(
+        title=f"Backtest Performance (Total Return: {total_return_pct:+.1f}%)",
+        xaxis_title="Date",
+        yaxis_title="Portfolio Value ($)",
+        template="plotly_white",
+        hovermode="x unified",
+        height=500,
+    )
+    fig.update_yaxes(tickprefix="$", tickformat=",.0f")
+    fig.write_html(output_path)
+    return output_path
+
+
+def _create_matplotlib_chart(portfolio_series: pd.Series, output_path: str) -> str:
+    """Create static matplotlib PNG chart."""
+    plt.figure(figsize=(10, 6))
+    plt.plot(portfolio_series.index, portfolio_series.values, linewidth=2)
+    plt.title("Portfolio Value")
+    plt.ylabel("USD")
+    plt.grid(True, alpha=0.3)
+    plt.gcf().autofmt_xdate()
+    plt.tight_layout()
+    plt.savefig(output_path, dpi=150, bbox_inches="tight")
+    plt.close()
+    return output_path

tests/test_plotting.py

@@ -0,0 +1,55 @@
+import os
+
+from quant_research_starter.metrics.plotting import create_equity_curve_plot
+
+
+def test_plotly_html_creation():
+    # Create test data matching the backtest results structure
+    dates = [f"2020-01-{i+1:02d}" for i in range(20)]
+    portfolio_values = [1000000 + i * 5000 for i in range(20)]
+
+    # Test HTML creation
+    test_html_path = "test_output/backtest_plot.html"
+    html_path = create_equity_curve_plot(
+        dates=dates,
+        portfolio_values=portfolio_values,
+        initial_capital=1000000,
+        output_path=test_html_path,
+        plot_type="html",
+    )
+
+    # Verify file was created
+    assert os.path.exists(html_path)
+    assert html_path.endswith(".html")
+    assert os.path.getsize(html_path) > 1000
+
+    # Cleanup
+    if os.path.exists(html_path):
+        os.remove(html_path)
+    if os.path.exists("test_output"):
+        os.rmdir("test_output")
+
+
+def test_plotly_fallback_to_matplotlib():
+    """Test that PNG is created even if Plotly is not available."""
+    dates = [f"2020-01-{i+1:02d}" for i in range(15)]
+    portfolio_values = [1000000 + i * 3000 for i in range(15)]
+
+    # Test PNG creation
+    test_png_path = "test_output/backtest_plot.png"
+    png_path = create_equity_curve_plot(
+        dates=dates,
+        portfolio_values=portfolio_values,
+        initial_capital=1000000,
+        output_path=test_png_path,
+        plot_type="png",
+    )
+
+    assert os.path.exists(png_path)
+    assert png_path.endswith(".png")
+
+    # Cleanup
+    if os.path.exists(png_path):
+        os.remove(png_path)
+    if os.path.exists("test_output"):
+        os.rmdir("test_output")