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http://lucumr.pocoo.org/2011/7/9/python-and-pola/ written on Saturday, July 9, 2011

Python and the Principle of Least Astonishment

Python On Cloudfoundry

For those that haven’t yet had a look Cloudfoundry from VMware is two things, one of which is nice, one of which is very cool indeed: On one hand it’s a platform as a service, allowing you to easily deploy Ruby, Java and Node.js applications to cloudfoundry.com . On the other hand it’s an open source project with all the code on Github allowing you to run the entire stack wherever you like. I’m pretty interested in the latter. Its API could in theory become a defacto standard for application and service buildouts, in the same way as we’re seeing the EC2 API expand outside AWS for managing infrastructure (and arguably how we’re using Chef and Puppet for managing the things installed on that infrastructure). The really interesting bit is the fact it’s all open source. http://www.morethanseven.net/2011/05/15/Python-on-cloudfoundry

unnamed pearl

Spoiler: This post is primarily gonna be an excerpt of my bookmarks collection. http://blog.dispatched.ch/2011/06/12/how-to-become-a-proficient-python-programmer/

scikit learn

http://scikit-learn.github.com/scikit-learn-tutorial/working_with_text_data.html The goal of this section is to explore some of the main scikit-learn tools on a single practical task: analysing a collection of text documents (newsgroups posts) on twenty different topics. In this section we will see how to: load the file contents and the categories extract feature vectors suitable for machine learning train a linear model to perform categorization use a grid search strategy to find a good configuration of both the feature extraction components and the classifier