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Dash

A Python framework for building interactive data dashboards and web apps without writing JavaScript.

GitHub Download v4.5.0
Stars
24.5k
Forks
2.3k
Licence
MIT
Language
Python
Last update
7 days ago
Type
Framework

What it is

Dash is a Python framework for building interactive web apps, such as dashboards, that combine UI elements like dropdowns, sliders, and graphs with your analytical Python code. It is built on Plotly.js, React, and Flask, so you write Python and the framework handles the front end. People use it to turn data analysis into something others can click through in a browser.

  • Build a dashboard where a dropdown selection updates a Plotly graph, as shown in the README's example
  • Create a multi-input, multi-output app with cross-filtering across charts
  • Map data with Mapbox-based charts
  • Build a report-style layout styled to look like a PDF, per the README's financial report example

Great for

  • Python developers who want to share data analysis as an interactive web app
  • Data scientists building internal dashboards or ML demos
  • Teams that want interactive charts without learning JavaScript
  • Users who want charts with about 50 chart types, including maps, via Plotly.js

Not ideal for

  • People who need a hosted, multi-user app out of the box: the README says Dash Open Source apps run on your local machine and are not easily accessible to others, which is where the paid Dash Enterprise product comes in
  • Non-programmers, since building apps requires writing Python code
  • Projects that need a non-Python, non-JavaScript stack, since the README centers on Python
Step-by-step guide: how to use DashInstall, first run, examples, tips and FAQs
Dash vs NiceGUIDash vs Lepton

How to get it

  1. 1

    Install with a package manager

    You'll need: Python

    Install Dash from PyPI

    pip install dash
  2. 2

    Run it

    • Install Dash with pip install dash
    • Follow the getting-started tutorial at dash.plotly.com/getting-started
    • Write a short Python script that defines a layout and callbacks
    • Run the script and open the local address it prints in your browser
  3. 3

    Get the most out of it

    • Browse the app gallery at dash.gallery for complete Python and R examples
    • Use the Plotly chart types (about 50 supported) for richer visuals
    • Read the user guide at plotly.com/dash for layout and callback patterns
    • Consider Dash Enterprise if you need hosting, authentication, or background job queues for wider use

Downloads

Source code (.zip)dev branch · straight from GitHubRelease v4.5.0Release notes and sourceOfficial website & docsplotly.com/dash

Strengths

  • The README describes the whole app as Python code, with no JavaScript required
  • Callbacks tie UI controls to Python functions in a declarative, reactive style
  • Uses well-known components (Plotly.js, React, Flask) and has a large user base (about 24k GitHub stars)

Trade-offs

  • Dash Open Source is aimed at local use; sharing with an organization requires the commercial Dash Enterprise product for hosting, auth, and scaling
  • The README is truncated, so details on deployment options and performance limits are not covered here

How it compares

ProjectStarsTypeLevelUpdatedBest for
dash (this)24.5kFrameworkintermediate7 days agoPython developers who want to share data analysis as an interactive web app
plotly.js18.4kLibrarybeginner7 days agoWeb developers who want interactive charts in their own site or app
Data-Science-For-Beginners37.9kLearning resourcebeginner16 days agoComplete beginners who want a guided, week-by-week data science course
awesome-datascience30.3kCurated listbeginner5 days agoBeginners who want a guided set of links to start learning data science
machine-learning-for-trading21.7kLearning resourceintermediate8 days agoReaders of the Machine Learning for Trading book who want to run its code
awesome-bigdata14.7kCurated listbeginner7 days agoDevelopers looking for an overview of big data tools to evaluate

Stats synced from GitHub. The assessment above was drafted with AI from the project's README on 2026-10-29 and may miss recent changes — check the README before relying on a command. MIT licence: free to use, modify and distribute, including commercially, as long as you keep the copyright notice.