dashserve: Plotly Dash Served Easily

dashserve supports developing and serving Plotly Dash apps within Jupyter Notebook. dashserve can also serialize Dash apps and serve them anywhere from a file.

What makes dashserve awesome?

  • it takes just a single simple change to your existing Dash app (change dash.Dash to JupyterDash)
  • serve straight from Jupyter Notebook or JupyterLab
  • publish Dash apps in a standalone server
  • no dependencies other than Plotly Dash (ok, some dill for serialization)

Installation

$ pip install dashserve

Run from within Jupyter Notebook or Jupyter Lab

# in Jupyter Notebook
from dashserve import JupyterDash

app = JupyterDash(__name__)
app.layout = ...
app.run_server()

* Serving Flask app "__main__" (lazy loading)
* Environment: production
  WARNING: Do not use the development server in a production environment.
  Use a production WSGI server instead.
* Debug mode: off
* Running on http://127.0.0.1:8050/ (Press CTRL+C to quit)

Run as a standalone server

Running a standalone server is just as easy

  1. Save the JupyterDash app to a file

    # in Jupyter notebook
app.save('/path/to/myapp.dash')

  2. Run dashserve

    # from the command line
$ python -m dashserve /path/to/myapp.dash
dashserve (c) 2019 one2seven GmbH, makers of omegaml.io - productize your AI/ML applications
 * Serving Flask app "__main__" (lazy loading)
 * Environment: production
   WARNING: Do not use the development server in a production environment.
   Use a production WSGI server instead.
 * Debug mode: off
 * Running on http://127.0.0.1:8050/ (Press CTRL+C to quit)

Run as a production server

If you need to run in a production environment, use a WSGI server

$ DASH_APP=/path/to/myapp.dash gunicorn dashserve.wsgi:app -b localhost:8050
[2019-03-30 17:11:41 +0100] [19727] [INFO] Starting gunicorn 19.7.1
[2019-03-30 17:11:41 +0100] [19727] [INFO] Listening at: http://127.0.0.1:8050 (19727)
[2019-03-30 17:11:41 +0100] [19727] [INFO] Using worker: sync
[2019-03-30 17:11:41 +0100] [19731] [INFO] Booting worker with pid: 19731

Build Powerful Machine Learning Apps

dashserve is an extension to omega|ml, our core product to productize data science

Looking for a way to build & deploy machine learning apps with a single line of code? Look no further. Just combine dashserve with omega|ml. Then you can integrate machine learning models in Plotly Dash apps as easily as this:

app = JupyterDash(...)

@app.callback(...)
def prediction_output(input_value):
   model = om.models.get('mymodel')
   yhat = model.predict(input_value)
   return 'prediction yhat={}'.format(yhat)

Getting data from omega|ml is also just one line of code:

# in your Dash app
import omegaml as om
df = om.datasets.get('mydata')

# see https://dash.plot.ly/getting-started, Reusable components for a full example

Publishing data and the trained model directly from Jupyter is straight forward - it’s literally just two lines of code. Here’s a full example:

# in your jupyter notebook (model training)
from sklearn import datasets
from sklearn import svm
import omegaml as om

iris = datasets.load_iris()

# train model
clf = svm.SVC(gamma='scale')
X, y = iris.data, iris.target
clf.fit(X, y)

# save model and data
om.datasets.put(iris, 'mydata')
om.models.put(clf, 'mymodel')

Dependencies

dashserve supports Plotly Dash version 0.39 or later. It uses the dill package by Mike McKerns to serialize applications. Requires Python 3.6 or later.

Why dashserve?

We looked at several other options, however found none matched our needs: to develop Plotly Dash apps using Jupyter Notebook or JupyterLab and deploy them later.

License

The MIT License (MIT)

Copyright (c) 2019 one2seven GmbH, makers of omega|ml, http://omegaml.io

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Commercial support

dashserve is brought to you by omega|ml - productize machine learning

The commercial version of dashserve is a module of omega|ml to provide multi-user analytics dashboards, enterprise-grade security, full data integration and machine learning applications. From laptop to web scale, all deployed with a single-line of code.

We can help you build and deploy analytics applications easily. Get in touch at info@omegaml.io or chat with us at http://omegaml.io

  • Serving machine learning models to applications using our state-of-the art REST API
  • Getting your data science team from zero to speed using omega|ml, batteries included
  • Consulting on data science, visualizations using Plotly and machine learning frameworks

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