dashserve

develop and serve Plotly Dash apps in Jupyter Notebook


Keywords
data-science, plotly, plotly-dash, scikit-learn
License
MIT
Install
pip install dashserve==0.1.7

Documentation

dashserve: Plotly Dash Served Easily

dashserve supports developing and serving Plotly Dash apps within Jupyter Notebook and JupyterLab. dashserve can also serialize Dash apps to a file and serve it using your favorite WSGI server.

Documentation https://omegaml.github.io/dashserve

Run from within Jupyter Notebook or Jupyter Lab

# in Jupyter Notebook
from dashserve import JupyterDash

app = JupyterDash(__name__)
app.layout = html.Div(children=[
   ...
]
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)

More options are available, see documentation

License

dashserve is MIT licensed. Details see LICENSE file

Note Plotly Dash is Copyright (c) 2018 Plotly Inc, and is not part of dashserve

Commercial options

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 via a 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