Keynote Talks

Invited Talks

In addition to the keynotes, this year -- for the first time in PyCon's history -- we have asked a select group of fantastic Python speakers to deliver a series of invited talks. They are, alphabetically:

Abstraction as Leverage by Alex Martelli

Abstraction is a powerful servant, but a dangerous master. We code, design, think, debug ... on a tower of abstractions. Spolsky's Law tells us that "All abstractions leak". This talk explores why they leak, why that's often a problem, what to do about it; moreover, I cover why sometimes abstractions SHOULD "leak", and thus how best to produce and consume abstraction layers.

Behind the scenes of EveryBlock.com by Adrian Holovaty

Adrian Holovaty, bad-boy YouTube guitar star (search for him, if you dare!) and co-author of the Django web framework, takes you under the hood of EveryBlock.com, a Knight Foundation News Challenge startup which rounds up local news and information, and is powered 100% by Python and Django.

Building tests for large, untested codebases by C. Titus Brown

Covering large codebases with automated tests is a challenging and frustrating task that can be made much easier by approaching the problem systematically and choosing good tools. I will discuss a number of approaches and freely available tools that can help people "tame" pre-existing codebases with automated tests, and show the evolution of tests for a complex codebase under these approaches and tools.

Challenges and Opportunities for Python by Ted Leung

We are moving firmly back into a "polyglot" world in terms of programming languages. This presents great opportunities for Python (and other dynamic languages) as well as challenges. In this talk I'll be discussing some of the challenges and opportunities that I see for Python, based on my experience with dynamic language runtimes at Sun.

Drop ACID and think about data by Bob Ippolito

Building large systems on top of a traditional single-master RDBMS data storage layer is no longer good enough. This talk explores the landscape of new technologies available today to augment your data layer to improve performance and reliability. Is your application a good fit for caches, bloom filters, bitmap indexes, column stores, distributed key/value stores, or document databases? Learn how they work (in theory and practice) and decide for yourself.

Easy AI with Python by Raymond Hettinger

Survey several basic AI techniques implemented with short, open-source Python code recipes. Appropriate for educators and programmers who want to experiment with AI and apply the recipes to their own problem domains. For each technique, learn the basic operating principle, discuss an approach using Python, and review a worked out-example. We'll cover database mining using neural nets, automated categorization with a naive Bayesian classifier, solving popular puzzles with depth-first and breath-first searches, solving more complex puzzles with constraint propagation, and playing a popular game using a probing search strategy.

How Python is Developed by Brett Cannon

Python, like any other open source project, has its own way of doing things when it comes to development. To an outsider it can seem complicated and difficult to break into. But in fact, Python's development practices are simple as long as you know what the basic workflow is. This talk will go over that workflow, from how a bug ends up getting fixed to how a new language feature get added. In the end people should have an understanding of how Python is developed and how anyone can contribute to the project.

IronPython: Directions, Data and Demos by Jim Hugunin

Come learn about our secret plans to use IronPython to take over the world. The emphasis will be on demos showing the seductive possibilities that IronPython enables for Python developers. These include taking advantage of the newest features in Windows 7, running your Python code in the browser with Silverlight, and many more.

Metaprogramming with Decorators and Metaclasses by Bruce Eckel

The goal of metaprogramming is to provide greater leverage by writing code that modifies other code. This presentation introduces metaprogramming and shows examples using both decorators and metaclasses. Although decorators are preferable because they are more straightforward, there are situations where metaclasses are still necessary; we'll look at these special cases and visit some initialization issues along the way.

The State of the Python Community: Leading the Python tribe by Steve Holden

Steve Holden, Chairman of the Python Software Foundation, reflects on the meaning of the phrase "the Python community" and the changes that have taken place in the PSF in the last year. He discusses further possible changes that could turn the PSF into a more "community-facing" organization, and solicits your input on what kind of projects and activities it should be supporting.

Topics of Interest by Ian Bicking

Ian Bicking, man of interest, discusses topics of interest. Interesting topics may include metaprogramming, whitespace, process models, past design mistakes, ambitious new directions for future design mistakes, a best dressed/worst dressed guide to Python libraries, open source community design patterns, and whatever else meets his exacting standards for Interestingness.