Inside Dash - a plotly framework

Alex Pawlowski

knoxpy may 2018 meetup

@apawlows

KnoxPy

Python users group in Knoxville, TN

Meetings are the first Thursday of the month

6:30 - 8:30pm @ Technology Cooperative

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Shameless plugs

KnoxDataSci

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data science group in Knoxville, TN

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Technology Cooperative

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meets every third Thursday 6:30-8:00

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  • You write code.

  • Maybe you're generating or displaying data.

  • How do you get others to interface with it?

True, a spreadsheet can give others away from code, access to data...

but the logic is locked away in the sheet...

Enter Dashboards...

  • Obviously, dashboards aren't new.

The fundamentals really haven't changed

Why do something different?

  • Reporting tools often are locked to vendors
  • often fall behind users' expectations of what they get elsewhere
  • code to create dashboard is different that remaining area of expertise

hey. I thought this was a python talk

  • It is.
  • plotly made something that allow you to just write python so you can be like the cool kids

h/t @mock

didn't you give a talk in R or something

  • I did.
  • That package is called shiny
  • It allows you do a lot of cool things
  • I like R
  • I like the community that builds packages
  • But maybe the rest of your server logic doesn't use R to run...
  • also plotly claims that dash is not a replica of Shiny. ¯\_(ツ)_/¯
    • "Idioms and philosophies are different."
    • I believe 'em

Dash. what is it?

History

dash-logo-stripe
+
++
+
++

2017-06

2017-08

2018-04

2017-09

Editable and sortable tables

Today

You know about dash

Inside a Dash app

  • 1 file for [your-app].py, import modules like normal py scripts

Core Components

  • the cool stuff
    • dropdowns, graphs, markdown, tabs, upload, etc.
import dash
import dash_core_components as dcc
import dash_html_components as html
app = dash.Dash()

app.layout = html.Div([

    # Your code

])

if __name__ == '__main__':
    app.run_server(debug=True)

HTML Components

  • the needed stuff
    • HTML tags, HTML attributes

What do good packages need?

  • Support from a community
  • Documentation
  • Good License; Ability to Contribute
  • Active support for experiments
  • Corporate sponsors to keep the OSS dream alive

They're serious about community

One of my favorite Dash apps

@adrianomy

What I am most excited about

Interactive tables (experimental)

Cross-filtering

A science example

  • Resonant Ultrasound Spectroscopy is a technique to apply vibrations to a material to determine the stiffness of the material
    • provides some sense of material properties w/o destroying a sample
    • reverse solution is robustly available (known stiffness, unknown peaks)
    • forward solution (known peaks, unknown stiffness) does not exist
    • can only be solved through iteration
      • local minima can be a $@#&*#@^
      • visualization is helpful

A science demo

So. how do i haz Dash?

pip install dash==0.21.1  # The core dash backend
pip install dash-renderer==0.12.1  # The dash front-end
pip install dash-html-components==0.10.1  # HTML components
pip install dash-core-components==0.22.1  # Supercharged components
pip install plotly --upgrade  # Plotly graphing library used in examples

"install and upgrade often" - magic sloth

i know.

plotly's guide to deploy

Deploy? What about containers?

Docker can (should) be used

https://hub.docker.com/r/michaelerasmus/dash/~/dockerfile/

But still. When all else fails. Clean.

# Delete every Docker containers
# Must be run first because images are attached to containers
docker rm -f $(docker ps -a -q)

# Delete every Docker image
docker rmi -f $(docker images -q)

Isn't the title of this talk, Dash - using your Python beyond a dashboard in the galaxy?

Glad you asked.

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