Data Science & XP Explained: Practices

In the previous two posts in this series we have explored the values and principles outlined in Extreme Programming Explained by Kent Beck and Cynthia Anders (XP Explained). In this post we will discuss perhaps the most contentious of the three layers: practices.

What relevance do XP practices have for data scientists? What are the benefits and disadvantages of these practices? Are there any that we should modify for a data science environment?

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Data Science & XP Explained: Principles

The values described in Extreme Programming Explained are the foundation on which principles and practices are built. Last time we started to talk about those values through the lens of data science.

Today I’m going to describe some of the principles outlined by Beck and Anders, again asking whether they are applicable to data science, and whether data science could benefit from their application.
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Data Science & ‘Extreme Programming Explained’

A new event in the Pivotal London office this week was our first lunchtime book club meeting. The first book suggested for discussion was Kent Beck and Cynthia Andres’ Extreme Programming (XP) Explained (2nd Edition).

This is a classic of the agile programming community and Kent Beck’s shorter first edition (1999) can lay claim to being one of the first books about agile programming practices. In this long post I’m going to start discussing the message of the book, and how I think some of the ideas apply in the world of data science. [Update: The next parts of this post about principles and practices are now up.]

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Python on Cloud Foundry

I’m very happy to be giving a talk at the latest PyData conference in New York this weekend.

This is a long post but I wanted a place to collect all the code I am showing in my talk and to provide a few more resources for those interested in trying out Python on Cloud Foundry further.

Resources Cloud Foundry

What is Cloud Foundry?

My talk is about how to use Python and the PyData stack on Cloud Foundry the open source cloud platform. Cloud Foundry started life at VMware and development transferred to Pivotal when it was formed. Cloud Foundry has grown much bigger since then with over 30 companies joining together to form the Cloud Foundry Foundation which will guide the development of the open source project.
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Pivotal Webinar, DS Amsterdam and PyData London

It looks like this is going to be a busy week. First up Noelle Sio, Alexander Kagoshima and I are presenting a webinar on Tuesday about our traffic analysis and prediction work. We talked about this topic at Strata Santa Clara but this webinar will take an extended look at the data, the challenges and the technology we used. You can sign up on the Pivotal website and the recording will be available afterwards.

Data Science AmsterdamOn Wednesday I am heading to Amsterdam to talk at the second Data Science Amsterdam meetup. The organisers of this meetup are branching out from their highly successful Data Science London event which regularly has hundreds of data scientists on the waiting list for each meeting. My talk on Wednesday will be about how to do massively parallel processing using familiar Python and R packages using the procedural languages PL/Python and PL/R.

On the subject of PL/Python, the video of my talk at PyData London is now available. Thankfully the video was edited to remove five minutes of me banging on the keyboard as my laptop crashed half way through my talk! In Amsterdam I will be talking about PL/R as well as PL/Python so hopefully this time the laptop holds up.

And finally, the PyData London conference was such a success that Ian Ozsvald and other organisers are starting a regular PyData meetup in London. We’re very excited at Pivotal to be hosting the first event in our London office on June 3rd. The meetup page is now up and places are filling up fast.

 

 
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