Visualization

fincore provides pluggable visualization backends via the VizBackend protocol.

Built-in Backends

Matplotlib

from fincore.viz import get_backend
viz = get_backend("matplotlib")
viz.plot_returns(cum_returns)
viz.plot_drawdown(drawdown)
viz.plot_rolling_sharpe(rolling_sharpe)
viz.plot_monthly_heatmap(returns)

HTML (no extra dependencies)

from fincore.viz.html_backend import HtmlReportBuilder
builder = HtmlReportBuilder()
builder.add_title("My Report")
builder.add_stats_table(stats)
builder.save("report.html")

Via AnalysisContext

ctx = fincore.analyze(returns, factor_returns=benchmark)
ctx.plot(backend="matplotlib")
ctx.to_html(path="report.html")

API Reference

fincore.viz.base.VizBackend

Bases: Protocol

Protocol that every visualization backend must implement.

plot_returns(cum_returns, **kwargs)

Plot cumulative returns.

plot_drawdown(drawdown, **kwargs)

Plot drawdown underwater chart.

plot_rolling_sharpe(sharpe, benchmark_sharpe=None, window=252, **kwargs)

Plot rolling Sharpe ratio.

参数：

名称	类型	描述	默认
sharpe	Series	Rolling Sharpe ratio series.	必需
benchmark_sharpe	Series	Optional benchmark rolling Sharpe series.	None
window	int	Window size (used for title/annotation).	252

plot_monthly_heatmap(returns, **kwargs)

Plot monthly returns heatmap.

参数：

名称	类型	描述	默认
returns	Series or DataFrame	Either a daily returns series (will be aggregated internally) or a year x month table of monthly returns.	必需

fincore.viz.html_backend.HtmlReportBuilder()

Build a standalone HTML performance report.

This class also satisfies the :class:~fincore.viz.base.VizBackend protocol (the plot_* methods append HTML sections and return self for chaining).

Usage::

from fincore.viz.html_backend import HtmlReportBuilder
builder = HtmlReportBuilder()
builder.add_title("Performance Report")
builder.add_stats_table(perf_stats_series)
html_str = builder.build()

add_title(title='Performance Report')

Append an <h1> title section to the report.

add_heading(text, level=2)

Append a heading (<h2> … <h6>) section to the report.

add_stats_table(stats)

Render a two-column key/value table from a pandas Series.

add_metric_cards(stats, keys=None)

Render inline metric cards for selected keys from stats.

add_html(raw_html)

Append raw HTML directly to the report body.

plot_returns(cum_returns, **kwargs)

Append a cumulative-returns table section (VizBackend protocol).

plot_drawdown(drawdown, **kwargs)

Append a drawdown table section (VizBackend protocol).

plot_rolling_sharpe(sharpe, benchmark_sharpe=None, window=APPROX_BDAYS_PER_YEAR, **kwargs)

Append a rolling Sharpe ratio table section (VizBackend protocol).

plot_monthly_heatmap(returns, **kwargs)

Append a monthly-returns pivot table section (VizBackend protocol).

build()

Assemble all sections into a complete HTML document string.

save(path)

Write the report to a file at path.