Build Web Applications With Dash

Plotly Dash

Put AI and ML
in the hands of business users

Plotly’s Dash enables Data Science teams to focus on the data and models, while producing and sharing enterprise-ready analytic apps that sit on top of RAPIDS-accelerated Python dataframes. What would typically require a team of back-end developers, front-end developers, and IT can all be done by Data Science teams with Dash.

Why Use Dash

Productive & Light

Before Dash, it would take an entire team of engineers and designers to create interactive analytics apps. Dash apps require very little boilerplate to get started. A fully-functional analytics app can weigh in at just 40 lines of Python code.

Customizable

Every aesthetic element of a Dash app is customizable and rendered in the web so you can employ the full power of CSS.

Direct Control

Dash links interactive UI controls and displays, like sliders, dropdown menus, and graphs, to your data analytics code, giving you hands-on input for your data views.

Using Dash with RAPIDS

viz app

Easy Integration

Read how straightforward it is to integrate RAPIDS libraries like cuDF with a Plotly Dash App on the Making Of Census Viz Blog Post.

Example Apps

Explore the code for the Plotly Dash + RAPIDS 2010 Census Visualization and its Covid-19 Branch on GitHub.

RAPIDS Partnership

Learn more about the partnership with RAPIDS and future plans on this Blog Post Announcement.

Getting Started

Get started with Dash by checking out the Plotly example gallery and comprehensive documentation.

Install Dash

Install Dash via pip or conda Find details here.

Get an Overview

Read the Plotly 1.0 launch article from 2019 or rewind back to 2017 for the essay that kicked everything off.

See what’s possible with Dash at the App Gallery.

Read Our Tutorial

The Dash tutorial walks you through how to create an app, from layout to callbacks.

Show and Tell

Members of the Dash community share what they’ve build in the Community Forum.

Articles

Read a comprehensive list of articles and more on Medium, or view some of the highlighted articles below:

Pattern-Matching Callbacks in Dash

Productionize Object Detection Models with Dash Enterprise

Develop NLP Visualizations for clear, immediate insights into text data and outputs

Understanding Word Embedding Arithmetic: Why there’s no single answer to “King − Man + Woman = ?”

Component Libraries

Dash is comprised of several component libraries suited for a variety of use cases. See the overview below.

Dash HTML Components

Dash is a web application framework that provides pure Python abstraction around HTML, CSS, and JavaScript. Instead of writing HTML or using an HTML templating engine, you compose your layout using Python structures with the dash-html-components library.
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Dash Core Components

Dash ships with supercharged components for interactive user interfaces. A core set of components, written and maintained by the Dash team, is available in the dash-core-components library.
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Dash DataTable

Dash DataTable is an interactive table component designed for viewing, editing, and exploring large datasets. DataTable is rendered with standard, semantic HTML <table/> markup, which makes it accessible, responsive, and easy to style.
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Dash Bio

Dash Bio is a suite of bioinformatics components that make it simpler to analyze and visualize bioinformatics data and interact with them in a Dash application.
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Dash DAQ

Dash DAQ comprises a robust set of controls that make it simpler to integrate data acquisition and controls into your Dash applications.
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Dash Cytoscape

Dash Cytoscape is a graph visualization component for creating easily customizable, high-performance, interactive, and web-based networks.
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Get Started with Plotly Dash