I am Director of Engineering for Discovery Communications Emerging Business and Strategy team. We just relaunched Curiosity.com. We use Python all over the place along with MongoDB/Redis/ElasticSearch The site lives within AWS utilizing several of their services. Including EC2, ELB, Route53, Cloudwatch, S3 I would like to discuss our overall architecture and our use/love of Python. And answer any questions on architecture/scalability/process/code.

Brian will talk about his experiences using Python and NLTK http://nltk.org/ to run language comparisons to generate lexical difference graphs like the one mentioned in the "Lexical Distance Among the Languages of Europe" article. http://bit.ly/1cS46Ba The focus will be on the NLTK and how its internals work to process a language. This talk will be his best one ever.

Reference counting is very useful but it has an odd problem. We employ a technique from graphs to approach it. The solution works but it's a bit slow.

Seen on garish LED roadway signs all around Chicago on New Year's Eve, 2013: 986 TRAFFIC DEATHS IN 2013. It leads to many questions: On what roads? When did the accidents happen? What do we do now? I'm scared to drive. I will talk about purging my fears by finding the data to answer some of those questions. http://tothebeat.github.io/fatal-car-crashes/ This talk will involve PythonAnywhere, IPython, a module that's not even on PyPi (dbfpy), searching for and finding open government data, CartoDB, Google Fusion Tables, csv, and maybe Pandas. Rest assured, there will be no graphic photos.

A walking tour of Storm, what it is, what you can do, and how you can use it with python.

Pandas is the data-munging Swiss Army knife of the Python world. Often you know how your data should look but it's not so obvious how to get there, so I'll present a visual approach to learning the library and data manipulation.

Braintree needs to be highly available and secure, while still maintaining a rapid development pace and strict backwards compatibility. In order to achieve that, we use what has become known as the "Chicago Process". This involves pairing, strict TDD, a team structure, and weekly iterations, all to empower the devs to make decisions and get work of a high quality done while avoiding siloing.

measure_it provides timing and counting for iterators (and other code segments). https://measure_it.readthedocs.org/en/latest/

Recap of last weeks PyData conference in NYC.

In this talk, I will present on a slice of the maker movement called "civic making" and a new space that has opened up in Chicago to encourage this type creation, CivicLab. As an example of "civic making" I will discuss Between the Bars, a paper based blogging platform for those who are incarcerated, built in Django. I will also discuss our choice in framework and the pros/cons of our approach.