Demo Dash application visualizing a real-time data signal (BTC-USD), featuring:
- multi-page routing and navigation (slapdash, dash-bootstrap-components)
- trace updates using extendData rather than figure (dash-extendable-graph)
- clientside callbacks implemented for basic UI actions (figure relayout, sampling frequency, disable/enable)
- clientside callback example for saving data from a figure
- clientside callback example for accessing a static file using asynchronous calls
- TODO clientside implementation of simple signal processing
This demo is deployable to Heroku via Procfile. See a live demo here.
The following README text was (mostly) auto-generated by slapdash:
After cloning/downloading the repository, simply install this app as a package into your target virtual environment:
$ pip install .
During development you will likely want to perform an editable install so that changes to the source code take immediate effect on the installed package.
$ pip install -e .
This project comes with two convenience scripts for running your project in development and production environments, or you can use your own WSGI server to run the app.
Installing this package into your virtualenv will result into the run-app-dev
executable being installed into the same virtualenv. This command invokes your
Dash app's run_server method, which in turn uses the Flask development server
to run your app.
$ run-app-dev
The script takes a couple of arguments optional parameters, which you can
discover with the --help. You may need to set the port using the --port
parameter. If you need to expose your app outside your local machine, you will
want to set --host 0.0.0.0.
While convenient, the development webserver should not be used in
production. Installing this package will also result in the bash script
run-app-prod being installed in your virtualenv.
This is a wrapper around the mod_wsgi-express command, which
streamlines use of the mod_wsgi Apache
module to run your your app. In addition to
installing the mod_wsgi Python package, you will need to have installed
Apache. See installation instructions in the mod_wsgi
documentation. Like its development
counterpart, run-app-prod takes a range of command line arguments, which
can be discovered with the --help flag.
$ run-app-prod
run-app-prod will also apply settings found in the
module dash_clientside_demo.prod_settings (or a custom Python file
supplied with the --settings flag) and which take precedence over the same
settings found in dash_clientside_demo.settings.
A notable advantage of using mod_wsgi over other WSGI servers is that we do
not need to configure and run a web server separate to the WSGI server. When
using other WSGI servers (such as Gunicorn or uWSGI), you do not want to expose
them directly to web requests from the outside world for two reasons: 1)
incoming requests will not be buffered, exposing you to potential denial of
service attacks, and 2) you will be serving your static assets via Dash's Flask
instance, which is slow. run-app-prod uses mod_wsgi-express to spin up an
Apache process (separate to any process already running and listening on port
80) that will buffer requests, passing them off to the worker processes running
your app, and will also set up the Apache instance to serve your static assets
much faster than would be the case through the Python worker processes.
Note: You will need to reinstall this package in order for changes to the
run-app-prod script to take effect even if you installed its an editable
install with (ie pip install -e).
You can easily run your app using a WSGI server of your choice (such as Gunicorn
for example) with the dash_clientside_app.wsgi entry point
(defined in wsgi.py) like so:
$ gunicorn dash_clientside_download.wsgi
Note: if you want to enable Dash's debug mode while running with a WSGI server,
you'll need to export the DASH_DEBUG environment variable to true. See the
Dev Tools section of the Dash Docs for more
details.