PyCon 2014 Notes

PyCon 2014 in Montreal was a fabulous conference. I'm blown away by the Python community everytime I go to the various flavors of Python conferences. They are just plain fun. The talks are superb. I learns tons. The people are inspiring. I love the fact that the last half of the conference is dedicated to people working together on common projects. Never have I seen something like that at any academic conference. If only I can figure out how to bring that kind of community spirit to the academic world...

Favorite Talks

First off, I'd like to recommend some of the talks that I saw or heard good things about. The great thing is that all of the talks are online so that you can view them even if you didn't come to the conference!

IPython Keynote

Fernando Perez

IPython is growing rapidly and getting all kinds of funding. Really nice overview as usual.

Education Keynote

Jessica McKellar

Jessica is really paving the way for programming education and minority groups.

All Your Ducks In A Row: Data Structures in the Standard Library and Beyond

Brandon Rhodes

Nice talk giving you some insight on what is happening behind the Python code. Brandon is an excellent speaker and always engaging. His talk last year convinced me to use longer more informative variable names (all though I may have taken that to an extreme).

Birth and Death of Javascript

Gary Bernhardt

Funny expose on what the future will look like once we move beyond having to write Javascript.

Games for Science: Creating interactive psychology experiments in Python with Panda3D

Jessica Hamrick

Nice demo of using Python tools and Physics simulations to do Psychological research.

Getting Started Testing

Ned Batchedler

Really succint intro to unit testing.

Discovering Python

David Beazley

Fantastic talk on what it is like to be an expert witness to a patent case. One of the best talks of the conference!

Software Carpentry: Lessons Learned

Greg Wilson

Really good insight on teaching programming to scientists, researchers, and engineers over the years.

Farewell and Welcome Home: Python in Two Genders

Naomi Ceder

Unbelievably moving talk about being transgender in the world and how the Python community may not be as bad as the rest of the world when it comes to marginalized people. A must see.

Analyzing Rap Lyrics with Python

Julie Lavoie

Didn't see this yet, but heard many people say it was good.

It's Dangerous to Go Alone: Battling the Invisible Monsters in Tech

Julie Pagano

I didn't see this but many people told me that it was good. It talks about imposter syndrome in tech.

Data intensive biology in the cloud: instrumenting ALL the things

Titus Brown

An academic researchers perspective on how big data can really get and what to do about it.

My Notes

Brandom Rhodes

lists: are slow on prepending, inserting in middle deque: allows for prepending and appending

Cache me if you can: memcached, caching patterns and best practices


Import-ant Decisions

hacker school in new york @akaptur

The Pipline Problem

Ned batchelors talks is 15 minture earlr

Physics engine in your head

simulated physics for games panda3d jhamrick

Python in the browser

Poetic APIs

Erik Rose

Greg Wilson

most scientists think of programming as a tax they have to pay in order to do science

you have to convince the prof that computing is worth more than thermodynamics

goal is to reach graduate students and wait 15 years when they are on committees

  • live coding shows mistakes and students can see how to recover from mistakes
  • run an etherpad for people to ask questions
  • green and red sticky notes to signal need help
  • minute cards: at break jot down one thing they didnt learn and one thing they did, this will tell you what you need to repeat.
  • sign up in groups: more diversity, because they are there with people they trust
  • editors are hard, don't use the word "just" "just install ubuntu"

Book: how learning works

He thinks Khan academy is not good, because they don't read about the research papers on pedagogy.

website to post videos of your teaching to get feedback

most important thing for novices: give them a model of the terrain not the knowledge

difference in novice and competent: density of connections between things they know

competnet to expert: self reflection (review your own code)

peer instruction: better results in less time. vote on multiple choice, then talk to you neighbors to persuade them, then vote again, then get right answer, then talk to neighbors again (eric misure's work)

train your trainers: just make sure everyone is on the same page

python 3 didn't matter(didn't bring any new users) We need to fix the standard library (bad organization)

stefik and siebert: random programming language syntax

for and while are least likely that means repeat

check out quorum: AB test for language design (why doesnt a pep)

why don't we write lessons like we write software and encyclopedia. there is no culture of contribution in education collaborative

book: seeing like a state