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@poramet-bit/dashboard-widgets

v0.1.0

Published

Config-driven React dashboard widgets (stat card, gauge, donut, bar, stacked bar, line/area, table) extracted from the graph-template presentation module.

Readme

@poramet-bit/dashboard-widgets

Config-driven React dashboard widgets, extracted from modules/presentation/models/dashboard.html. Renders the same dashboard_layout.schema.json widget config the HTML template consumes, as real npm-installable components.

Install

npm install @poramet-bit/dashboard-widgets react react-dom

Usage

import { DashboardGrid } from "@poramet-bit/dashboard-widgets";
import "@poramet-bit/dashboard-widgets/styles.css";

function App({ config }) {
  return (
    <div>
      <h1>{config.title}</h1>
      <DashboardGrid widgets={config.widgets} />
    </div>
  );
}

config.widgets is an array of { size: "quarter" | "half" | undefined, data: {...} } entries — see templates/dashboard_layout.schema.json and templates/examples/dashboard_layout.example.json in this repo for the full shape. DashboardGrid packs widgets into rows by size and renders each through <Widget>, which dispatches on data.type: stat_card, gauge, pie, bar, stacked_bar, line, area, table.

Exports

  • DashboardGrid, Widget — layout + dispatch
  • StatCard, Gauge, Donut, GroupedBar, StackedBar, XYChart (+ LineChart, AreaChart), Table — individual widgets, usable standalone
  • fmtNumber, fmtCompact, fmtValue, niceMax, topRoundedRectPath, polarPoint, valueToAngle, packRows, widgetSubtitle — formatting and chart-math helpers

styles.css ships the dark theme (:root CSS vars: --bg, --surface, --accent, --good/--warning/--critical, --chart-1..4, etc.) and all component classes. Override the vars to retheme.

Build

npm install
npm run build   # tsup -> dist/{index.js,index.cjs,index.d.ts,styles.css}

Scope note

This package only covers the generic widgets from dashboard.html. dashboard-legacy.html (ICT Budget Control Center) has app-specific components (Sidebar, Topbar, DetailPanel, CSV export) that were left out — they're hardcoded to that one dataset and would need generalizing first.