Boilerplate for bootstrapping scalable multi-page Dash applications
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Boilerplate for bootstrapping scalable multi-page Dash applications

Dash is a Python framework for building analytical web applications. Slapdash provides a sensible project layout for quickly building out a multi-page Dash application with room for growth. It includes pre-built layouts based on Bootstrap (with the help of Dash Bootstrap Components), which can be extended or swapped out for layouts constructed using your own Dash/CSS components.

This project is intended for bootstrapping initial Dash applications, rather than being a dependency for your application. You shouldn't assume that Slapdash's internal structure and interfaces will be stable, as they will change.


Note: Slapdash requires Python 3.6+

After cloning/downloading the repository, simply install Slapdash as a package into your target virtualenv:

pip install -e


  1. In, select the main layout you want from
  2. Create the pages of your app in different files within the pages directory, by defining within each a top-level layout attribute and callbacks registered with the Dash app instance from the appmodule.
  3. Add your pages to the URLS attribute in
  4. Add desired pages to the NAV_ITEMS attribute in
  5. Modify assets/slapdash.css or add additional stylesheets in assets.
  6. Modify config in as required.

Running Your App

You can launch the app using the script, which uses Flask's development server (and which shouldn't be used in production). The script takes a couple of arguments optional parameters, which you can discover with the --help flag. The --debug flag is particularly useful, activating the Dash dev tools, including hot reloading.

$ python --debug

You can run your app using a WSGI server (such as Gunicorn) with the entry point like so:

$ gunicorn slapdash.wsgi

Or if you'd rather not install the Slapdash package, relative to the root directory:

$ gunicorn src.slapdash.wsgi

Note: if you want to enable Dash's debug mode while running with a WSGI server, you'll need to set the DASH_DEBUG environment variable to true. See the Dev Tools section of the Dash Docs for more details.

Boilerplate Overview

  • Contains helper functions for creating the Flask and Dash instances.
  • Entry point into the app. Creates both the Flask and Dash instances used for the app and then imports the rest of the app through the index module.
  • Contains the URL routes and corresponding callback router, as well as the entries to be used for the nav bar, along with the corresponding callback for the nav bar.
  • Contains the Flask application attribute suitable for pointing WSGI servers at.
  • Configurable settings for the application.
  • Exceptions used by your app can be defined here.
  • Convenient Python pseudo-components are defined here.
  • Utility things.
  • pages The suggested project layout is to place each page of your app within this directory, treating each page as a modular sub-app with a layouts attribute that you can register with the router in
  • assets Location for static assets that will be exposed to the web server.

Included Libraries

Slapdash includes a few libraries for getting fully functional applications off the ground faster. These include:

Useful References

  1. The Dash User Guide

  2. Plotly Python client figure reference Documents the contents of plotly.graph_objs, which contains the different types of charts available, as well the Layout class, for customising the appearance of charts.

  3. The Dash Community Forum

  4. Dash Show and Tell Community Thread

  5. The Dash GitHub Repository


PRs are welcome! If you have broader changes in mind, then creating an issue first for discussion would be best.

Seeting up a Dev Environment

  1. Install Slapdash into your virtualenv:
    $ pip install -e
  2. Install the development requirements:
    $ pip install -r requirements-dev.txt
  3. Install the pre-commit hook (for the Black code formatter)
    $ pre-commit install