Unfortunately, solving simple problems with Python isn't always 'import antigravity'. This talk will analyze the high barriers of entry that clutter the Python landscape. We'll discuss ways to make Python more accessable for newcomers and less of a headache for seasoned veterans.
People keep trying to invent ways to make python run faster - JITs, Java and .Net runtimes, threads, eliminating the Global Interpreter Lock. So why can bup process more than 80 megabytes per second per core? Why can the sshuttle VPN route packets at wire speeds? How does plain python thoroughly trounce JITted languages in certain kinds of benchmarks? And what's really so great about deterministic destructors, anyway? Come hear Avery explain it all in this action-packed whirlwind of fact, fiction, and "other."
I've made a huge mistake: I've judged programming languages and communities without cause and been the worse for it. With luck, my story of failure will save others the misfortune and embarrassment.
Django, Pyramid, Flask, WSGI itself, so many choices. This talk goes into detail how to make different frameworks play together and which parts of WSGI are good and which ones you should avoid. The talk also shows how to combine applications with code written in other languages and answers why having the choice of multiple solutions is good and not a bad thing.
Breakdancer is a simple python testing tool that allows you to test all possibilities of complex interactions in your application by expressing simple constraints and effects. More details available here: http://dustin.github.com/2010/10...
In this talk I will describe what NumPy is and why it matters. I will then talk about NumPy and SciPy's future as it should evolve to allow high-level descriptions of optimized low-level calculations as well as it's connection to large-scale data manipulation and processing. I will then spend a few minutes talking about early efforts in evolving NumPy and SciPy and on where people can help.
6th–7th October 2011