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    Dash by Plotly Alternatives

    Dash by Plotly is described as 'Dash is a Python framework for building analytical web applications. No JavaScript required'. There are five alternatives to Dash by Plotly for a variety of platforms, including Mac, Windows, Linux, Self-Hosted solutions and R (programming language). The best alternative is OpenBoard, which is both free and Open Source. Other great apps like Dash by Plotly are Shiny (Freemium, Open Source), Voilà (Free, Open Source), Panel (Free, Open Source) and Streamlit (Freemium, Open Source).

    This page was last updated May 3, 2022
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    Dash is a Python framework for building analytical web applications. No JavaScript required.
    Learn more about Dash by Plotly

    1. OpenBoard is a cross-platform (Linux / Windows / macOS) interactive whiteboard application. It is currently maintained by the Education Department (DIP) of the Canton of Geneva in Switzerland.
      • FreemiumOpen Source
      • Mac
      • Windows
      • Linux
      • R (programming language)
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      Shiny is an R package that makes it easy to build interactive web apps straight from R. You can host standalone apps on a webpage or embed them in R Markdown documents or build dashboards. You can also extend your Shiny apps with CSS themes, htmlwidgets, and JavaScript actions.


      • FreeOpen Source
      • Mac
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      • Self-Hosted
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      Voilà turns Jupyter notebooks into standalone web applications. Each user connecting to the Voilà tornado application gets a dedicated Jupyter kernel which can execute the callbacks to changes in Jupyter interactive widgets.
      • FreeOpen Source
      • Self-Hosted
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      Panel is an open-source Python library that lets you create custom interactive web apps and dashboards by connecting user-defined widgets to plots, images, tables, or text.
      • FreemiumOpen Source
      • Online
      • Self-Hosted
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      Streamlit is an open-source Python library that makes it easy to create and share beautiful, custom web apps for machine learning and data science. In just a few minutes you can build and deploy powerful data apps.
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