#### Vizro is a low-code toolkit for building high-quality data visualization apps [![Python version](https://img.shields.io/python/required-version-toml?tomlFilePath=https%3A%2F%2Fraw.githubusercontent.com%2Fmckinsey%2Fvizro%2Frefs%2Fheads%2Fmain%2Fvizro-core%2Fpyproject.toml)](https://pypi.org/project/vizro/) [![PyPI version](https://badge.fury.io/py/vizro.svg)](https://badge.fury.io/py/vizro) [![Downloads](https://static.pepy.tech/badge/vizro)](https://pepy.tech/projects/vizro) [![License](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](https://github.com/mckinsey/vizro/blob/main/LICENSE.txt) [![Documentation](https://readthedocs.org/projects/vizro/badge/?version=stable)](https://vizro.readthedocs.io/) [![OpenSSF Best Practices](https://www.bestpractices.dev/projects/7858/badge)](https://www.bestpractices.dev/projects/7858) [Documentation](https://vizro.readthedocs.io/en/stable/) | [Get Started](https://vizro.readthedocs.io/en/stable/pages/tutorials/quickstart-tutorial/)

Gif to demonstrate Vizro features

## What is Vizro? Vizro is an open-source Python-based toolkit. Use it to build beautiful and powerful data visualization apps quickly and easily, without needing advanced engineering or visual design expertise. Then customize and deploy your app to production at scale. In just a few lines of simple low-code configuration, with in-built visual design best practices, you can quickly assemble high-quality, multi-page prototypes, that are production-ready.

Every Vizro app is defined by a simple configuration, using these high-level categories: - **[Components](https://vizro.readthedocs.io/en/stable/pages/user-guides/components/):** charts, tables, cards, KPI indicators, forms and more. - **[Controls](https://vizro.readthedocs.io/en/stable/pages/user-guides/controls/):** filters and parameters, using a range of selectors such as drop-down menus and sliders. - **[Actions](https://vizro.readthedocs.io/en/stable/pages/user-guides/actions/):** interactions between components, drill-throughs, export functionality and more. - **[Layouts](https://vizro.readthedocs.io/en/stable/pages/user-guides/layouts/):** grid layouts or flexible containers, with a range of pre-set styles. - **[Navigation](https://vizro.readthedocs.io/en/stable/pages/user-guides/navigation/):** a range of app layout and navigation settings, including nested page hierarchies. Configuration can be written in multiple formats including **Pydantic models**, **JSON**, **YAML** or **Python dictionaries** for added flexibility of implementation. Optional high-code extensions enable almost infinite customization in a modular way, combining the best of low-code and high-code - including bespoke [**visual formatting**](https://vizro.readthedocs.io/en/stable/pages/user-guides/visual-formatting/) and [**custom components**](https://vizro.readthedocs.io/en/stable/pages/user-guides/extensions/). Visit the ["How-to guides"](https://vizro.readthedocs.io/en/stable/pages/user-guides/install/) for a more detailed explanation of Vizro features. ## Why use Vizro? The benefits of the Vizro toolkit include:

Vizro helps you to build data visualization apps that are: **Quick and easy** Build apps in minutes. Use a few lines of simple configuration (via Pydantic models, JSON, YAML, or Python dictionaries) in place of thousands of lines of code. **Beautiful and powerful** Build high-quality multi-page apps without needing advanced engineering or visual design expertise. Use powerful features of production-grade BI tools, with in-built visual design best practices. **Flexible** Benefit from the capabilities and flexibility of open-source packages. Use the trusted dependencies of Plotly, Dash, and Pydantic. **Customizable** Almost infinite control for advanced users. Use Python, JavaScript, HTML and CSS code extensions. **Scalable** Rapidly prototype and deploy to production. Use the in-built production-grade capabilities of Plotly, Dash and Pydantic. Visit ["Why should I use Vizro?"](https://vizro.readthedocs.io/en/stable/pages/explanation/faq/#why-should-i-use-vizro) for a more detailed explanation of Vizro use cases. ## When to use Vizro? Use Vizro when you need to combine the speed and ease of low-code Python tools, with production capabilities of JavaScript and BI tools, and the freedom of open source: - Have an app that looks beautiful and professional by default. - Enjoy the simplicity of low-code, plus the option to customize with code almost infinitely. - Rapidly create prototypes which are production-ready and easy to deploy at scale. ## How to use Vizro? Explore a few live demos to see different Vizro dashboards in action:

Basic Dashboard Try it live	Visual Vocabulary Try it live	BI Dashboard Try it live
Call Center Dashboard Try it live	KPI Dashboard Try it live	Features Dashboard Try it live

Browse the full [Vizro Gallery](https://huggingface.co/collections/vizro/vizro-official-gallery) for more examples. ## [Vizro framework](https://vizro.readthedocs.io/en/stable/) **Low-code framework for building dashboards.** The Vizro framework underpins the entire Vizro toolkit. It is a Python package (called `vizro`). Visit the [documentation](https://vizro.readthedocs.io/en/stable/) for more details. ## [Vizro visual vocabulary](https://py.cafe/app/vizro-official/vizro-visual-vocabulary) **Chart examples.** The visual vocabulary helps you to decide which chart type to use for your requirements, and offers sample code to create these charts with Plotly or embed them into a Vizro dashboard. Visit the [visual vocabulary](https://py.cafe/app/vizro-official/vizro-visual-vocabulary) to search for charts or get inspiration.

## [Vizro-MCP](https://vizro.readthedocs.io/projects/vizro-mcp/) **A [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) server for Vizro.** Vizro-MCP works alongside an LLM to help you create Vizro dashboards and charts. It provides tools and templates to create a functioning Vizro chart or dashboard step-by-step. Compatible with MCP-enabled LLM clients such as Cursor or Claude Desktop. Vizro MCP Demo

Vizro MCP Demo

## Installation and first steps ```console pip install vizro ``` See the [installation guide](https://vizro.readthedocs.io/en/stable/pages/user-guides/install/) for more information. The [get started documentation](https://vizro.readthedocs.io/en/stable/pages/tutorials/quickstart-tutorial/) explains how to create your first dashboard. > **Upgrading from a 0.1.x release?** Vizro 1.0.0 is the first stable release and introduces some breaking changes. See the [migration guide](https://vizro.readthedocs.io/en/stable/pages/API-reference/migration/) to update your existing dashboards. ## For AI agents and LLMs If you are an AI agent or LLM building Vizro apps, start with the [Vizro for LLMs cheatsheet](https://vizro.readthedocs.io/en/stable/pages/for-llms/) and use [llms.txt](https://vizro.readthedocs.io/en/stable/llms.txt) as the machine-readable documentation index. Detailed documentation is available in these forms: 1. **Per-page Markdown:** Remove the trailing `/` from any canonical documentation URL and append `.md`; use `/index.md` for the documentation root. No custom request header is needed. 2. **Content negotiation:** Send `Accept: text/markdown, text/html;q=0.9`. Include the HTML fallback because upstream conversion returns HTTP 406 for pages over 2 MB. 3. **Bulk documentation:** Fetch [llms-full.txt](https://vizro.readthedocs.io/en/stable/llms-full.txt) for the narrative documentation and user guides in one request, excluding the API reference. 4. **Targeted model reference:** Fetch per-model files such as [`graph.md`](https://vizro.readthedocs.io/en/stable/pages/API-reference/models/graph.md) instead of loading the combined Models API page. All per-model files are listed in `llms.txt`. ## Packages This repository is a monorepo containing the following packages: | Folder | Version | Documentation | | :----: | :-----: | :-----------: | | [vizro-core](https://github.com/mckinsey/vizro/tree/main/vizro-core) | [![PyPI version](https://badge.fury.io/py/vizro.svg)](https://badge.fury.io/py/vizro) | [Vizro Docs](https://vizro.readthedocs.io/en/stable/) | | [vizro-ai](https://github.com/mckinsey/vizro/tree/main/vizro-ai) | [![PyPI version](https://badge.fury.io/py/vizro-ai.svg)](https://badge.fury.io/py/vizro-ai) | [Vizro-AI Docs](https://vizro.readthedocs.io/projects/vizro-ai/) | | [vizro-mcp](https://github.com/mckinsey/vizro/tree/main/vizro-mcp) | [![PyPI version](https://badge.fury.io/py/vizro-mcp.svg)](https://badge.fury.io/py/vizro-mcp) | [Vizro-MCP Docs](https://vizro.readthedocs.io/projects/vizro-mcp/) | ## Community and development We encourage you to ask and discuss any technical questions via the [GitHub Issues](https://github.com/mckinsey/vizro/issues). This is also the place where you can submit bug reports or request new features. ## Want to contribute to Vizro? The [contributing guide](https://vizro.readthedocs.io/en/stable/pages/explanation/contributing/) explains how you can contribute to Vizro. You can also view current and former contributors [here](https://vizro.readthedocs.io/en/stable/pages/explanation/authors/). ## Want to report a security vulnerability? See our [security policy](https://github.com/mckinsey/vizro/security/policy). ## License `vizro` is distributed under the terms of the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0).