vizro: Build Data Visualization Apps with Python

Overview

Vizro helps Python developers and data teams assemble data visualization apps without writing every layout, control, and interaction from scratch. Its configuration-based approach provides reusable dashboard components and visual defaults, while optional code extensions allow deeper customization.

Use it when you want a quicker path from data and charts to a multi-page app, but still need the flexibility of the Plotly and Dash ecosystem. For highly bespoke interfaces or workflows outside dashboarding, a more general application framework may be a better fit.

Key Features

• Define dashboards with Pydantic models, JSON, YAML, or Python dictionaries.
• Build multi-page apps with configurable navigation and layouts.
• Add charts, tables, cards, KPI indicators, and forms.
• Connect filters and parameters to dashboard components.
• Configure interactions such as drill-throughs and exports.
• Extend dashboards with custom Python, JavaScript, HTML, and CSS.
• Use companion Vizro-MCP tools to help create charts and dashboards with MCP-enabled LLM clients.

Use Cases

• Data analysts can turn exploratory charts into shareable dashboards with filters and navigation.
• Product or operations teams can assemble KPI views for recurring reporting without building every interface element from scratch.
• Python developers can prototype dashboard experiences quickly, then add custom code where configuration is not enough.
• Teams evaluating chart choices can use the companion visual vocabulary to compare chart examples before building an app.

Project Facts

• Language: Python
• License: Apache-2.0
• Stars: 3.8k
• Forks: 302
• Topics: dashboard, data-visualization, plotly, plotly-dash, pydantic, python, visualization
• Archived: No

Getting Started

Install the package with:

pip install vizro

See the README and documentation for setup instructions and a first-dashboard tutorial.

Alternatives

• superset: Superset is a full BI platform for SQL exploration and managed dashboards, while Vizro is a Python toolkit for building configured visualization apps.
• gradio: Gradio builds interactive interfaces around Python functions and ML models, while Vizro focuses on configurable, multi-page data visualization dashboards.

Considerations

Vizro is centered on Python dashboards and builds on the Plotly, Dash, and Pydantic ecosystems, so it is best suited to projects comfortable with that stack. Configuration reduces routine implementation work but does not eliminate the need for custom code when requirements exceed its built-in components and patterns. The repository is a monorepo that also includes Vizro-AI and Vizro-MCP; the README says Vizro-AI dashboard generation is no longer actively developed and is superseded by Vizro-MCP.