The Python Podcast.__init__

The Python Podcast.__init__



The podcast about Python and the people who make it great


08 September 2015

Bryan Van de Ven on Bokeh - E22

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Summary

Bryan Van de Ven is the project maintainer for Bokeh, a plotting and visualization toolkit that allows Python developers to easily create attractive interactive visualizations for the web. We talked about the project’s history, some interesting use cases for it, and what its near future looks like. Bryan also told us about how Bokeh compares to some of the other visualization libraries in both Python and Javascript, as well as how to use Bokeh from other languages such as Scala and Lua.

Brief Introduction

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  • We are recording today on Aug 18th, 2015 and your hosts as usual are Tobias Macey and Chris Patti
  • Today we are interviewing Bryan Van de Ven about the Bokeh project

Interview with Bryan Van de Ven

  • Introductions
  • How did you get introduced to Python?
  • For our listeners who aren’t familiar with what Bokeh is, can you describe it?
  • What inspired you to create Bokeh?
  • Bokeh has integrations with some of the other Python graphing libraries such as matplotlib and seaborn. I can see how this would be useful to easily update existing code to publish visualizations on the web. Are there other use cases for these integrations?
  • I noticed that Bokeh has bindings for some languages other than Python. R and Julia are obvious candidates due to their strong focus on analytics work, I’m curious what made you choose Scala and Lua as languages worth targeting?
  • Do you lose any capabilities using the javascript library by itself?
  • Other than the sample data sets that come with Bokeh, can you suggest a good publicly available data set with accompanying tutorial for people who want to get started with data visualization using Bokeh?
  • Can you provide some comparisons between D3.js and the Bokeh javascript library in terms of capabilities and performance?
  • The Bokeh project has a server component that allows for streaming data to clients. Can you describe the architecture of that and some example uses for it?
  • Why was the server written as a Flask blueprint as opposed to making it a component of another framework such as Django or Pyramid and how difficult would it be to port the functionality to another system?
  • What’s the most interesting use of Bokeh you’ve seen?
  • Are you aware of any projects in other languages that are comparable to Bokeh?

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