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Generate interactive plotly dash dashboards in an instant

Project description

dasher: Generate interactive plotly dash dashboards in an instant


pip install dasher

You can also install the in-development version with:

pip install

First steps

Creating a simple, interactive dashboard with a nice layout is as easy as this:

from dasher import Dasher
import dash_html_components as html

app = Dasher(__name__, title="My first dashboard")

    _name="My first callback",
    _desc="Try out the widgets!",
    _labels=["Greeting", "Place"],
    place=["World", "Universe"],
def my_callback(text, place):
    msg = "{} {}!".format(text, place)
    return [html.H1(msg)]

if __name__ == "__main__":

The resulting dashboard looks like this:

hello world example

The code for this dashboard can be found in examples/


To view the full project documentation, visit


Free software, MIT License


To run the all tests run:


Note, to combine the coverage data from all the tox environments run:


set PYTEST_ADDOPTS=--cov-append


PYTEST_ADDOPTS=--cov-append tox


0.3.1 (2019-12-17)

  • Update and fix documentation.

  • Fix documentation build using .readthedocs.yml.

0.3.0 (2019-12-15)

  • Generate id property from name for every callback. The id is now used to identify the callback, while name is used in the layout for displaying.

0.2.0 (2019-11-03)

  • Use cookiecutter to create a proper project structure.

  • Refactor core functionality into dasher.Api.

  • Combine widget factory and template logic into unified layout implementation.

  • Fix resizing bug when switching tabs by using callback-based tab switching.

  • Add support of fully custom widgets.

  • Add documentation.

  • Add more examples.

0.1.2 (2019-07-16)

  • Add _labels argument to the callback decorator to enable customization of widget labels.

0.1.1 (2019-06-10)

  • Add credits argument to DasherStandardTemplate to toggle whether to show credits in the navbar.

  • Update docstrings and documentation.

  • Add margin to navbar.

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