Your Plotly figures,
presented clearly.

Introduction

What DashForge solves

You already made the charts; DashForge makes them feel like a finished dashboard. It turns Plotly figures into cards inside a ready-to-run Dash application, with optional titles, KPIs, branding, a footer, and a searchable dataset page.

Getting started

Install DashForge

Install it into the same Python environment that creates your Plotly figures.

pip install dashforge

The package brings in Dash, Plotly, pandas, Flask, and param. Import Dashboard wherever you build the report.

Getting started

Build your first dashboard

The smallest complete workflow is: create one or more Plotly figures, add them, build the app, then start its local server.

import plotly.express as px
from dashforge import Dashboard

sales_chart = px.bar(
    x=["North", "South", "East", "West"],
    y=[18, 24, 14, 21],
    title="Quarterly sales",
)

dashboard = Dashboard()
dashboard.set_title("Sales overview")
dashboard.add_chart(sales_chart)
dashboard.build_dashboard()
dashboard.run()

1. Create figures with Plotly Express or Plotly Graph Objects.
2. Configure the dashboard with the methods relevant to the report.
3. Build once, run once after configuration is complete.

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