120 Hours in the Python’s Den: PyCon 2011

120 Hours in the Python’s Den: PyCon 2011

120 Hours in the Python’s Den: PyCon 2011

Published March 22, 2011 by GISi George












Starting in Version 10, Python is the de facto geoprocessing scripting language for the ESRI suite of software.  I primarily use python to automate the data processing work I perform.  I also use Python to create geoprocessing scripts for the ArcServer environment.  This year I attended PyCon, the Python languages community convention, to further develop my Python skills and see how others are using this powerful language.

I started my excursion to Atlanta for PyCon with three questions in mind:

1)      How can I utilize the multiprocessing capabilities of the python language?  What obstacles have others faced in implementing this functionality with ESRI’s ArcPy package?

2)      I would like to create intuitive input dialogs for my geoprocessing tasks.  How can I leverage other GUI frameworks (Qt, TK, wxPython) to create input dialogs with more built in functionality?

3)      How can we utilize the cloud to reduce the time for complex and time intensive geoprocessing tasks?

I took four classes to start the conference: Python 101, Google App Engine, Creating GUI Applications in Python using Qt I, and Deploying web applications to the cloud.  I learned a few cool tidbits from these four classes.

  • The print statement will be replaced with a print function in Python 3.  Syntactically this change makes a lot of sense.  In case you are wondering, you can actually backport this functionality into the Python 2.6 that comes with Version 10.  Quick code sample:


# Old

>>> Print “%s is a very fun language for %s” % (‘python’, ‘geoprocessing’)

# New

>>> Print (“{0} is a very fun language for {1}”.format(‘python’,’geoprocessing’))

>>> Print (“{langauge} is a very fun language for {task}”.format(language = ‘python’, task = ’geoprocessing’))


  • Google App Engine is cool, but I do not have a reason to use it yet.  I feel in the future, using this service, I will be able to quickly stand up a site without having to worry about infrastructure.
  • Qt can run on almost everything and every operating system.  This is a huge plus, however I am going to hold judgment until the dust settles with Nokia.
  • In a little under three hours I was able to setup a distributed, load balanced django application on the Amazon Cloud pulling data from their Relational Database Server and distributed using their CloudFront CDN.  I definitely see this as a resource I will invest more time in learning.

It is amazing to see what people are doing with python, primarily in the distributed computing and web application end of the python development spectrum.  My new goal for the year is to finally get around to learning to develop with Django.  It seems every other presentation was a huge django proponent.  There were also a few interesting talks on the forecast of Python language development and IDE’s for writing your code. Fortunately, for you the Python Foundation videotaped most of the presentations this year, http://pycon.blip.tv/posts?view=archive.

Alright and onto a few takeaway lessons I learned from my experience at PyCon.

  • ESRI is investing tons of resources into building Python as a quick, efficient geoprocessing language for their tools.  PyCon ran concurrently with ESRI’s developer summit; however, they were still able to send out 7+ representatives to PyCon.  I spent a couple nights with the ESRI folks, and to be honest I am incredibly pumped about version 10.1.  Tons of cool new features are coming down the pike.
  • Microsoft is gradually pushing into the Python/Open Source community.  I am in the process of downloading Microsoft’s Python extension for Visual Studio.  The latest and greatest release promises to debug both cPython (what ESRI uses) and IronPython (a .Net variety).  Currently I am using WinPython, the default with ArcGIS, but I see the Visual Studio version quickly superseding its use.
  • The python community could learn a lot from the GIS side of the house.  Almost every presentation involved crunching data, processing it in some way and displaying it graphically.  I definitely see an opportunity to step in and show a more intuitive method for displaying spatial data.
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