Tag Archives: PyCon

11:33: The jobs fair and poster boards were interesting. Nothing directly applicable to my current work, though.

It’s great to reconnect with friends at PyCon. This is a social event almost as much as it is a technical one.

08:50: In lightning talks ATM.

The last day of the conference. I’m dragging my luggage around all day because I’ve checked out of the hotel. Had a real breakfast this morning because the conference’s overcooked eggs and fruit got boring.

Besides the keynotes, the talks I’m attending today are mostly about asynchronous computing and asyncio.

17:33: I’m bushed. I planned on attending the lightning talks and then the conference dinner, but I feel my control rods auto-inserting and I know it’s best to pace myself.

Great talks on Python 3.6 performance and antiquated Python anti-patterns. A very good talk about conda. And a talk about pdb that started off at a beginner level (and so was disappointing; I had expected it to be at a different level) but then contained unexpected nuggets of useful information. I love serendipity!

Tonight I’m chilling and going to sleep early.

10:35: Jake VanderPlas described Jupyter’s usefulness for the scientific community far better than I did yesterday. Immersive IDE, iterative, experiments, sharing!

07:43: I hate swag bags. They’re an anachronism that needs to die. So wasteful. I know conferences must raise sponsorship money, but they’re going to die eventually and PyCon ought to be a leader here. My entire bag went into the recycling bin.

06:49: Up for the day and eager for it to start! Not sure how I’ll update this or even if I will. There will be something like eight talks, three addresses, who knows how many lightning talks, and maybe some unconference-ish meetings today. Perhaps I’ll just list notable topics and thoughts.


19:10: We went to Nicholas. Decent place. Had a nice lamb kabob.


13:20: Parallel data analysis.

Wow. An expansive survey of the SOTA in Python parallelizing technologies: Concurrent.futures, SparkDask, etc. This is what a good tutorial does — surveys a taxonomy and illuminates the tradeoffs and overlaps. It can beat reading N articles by Y authors who are trying to convey Z messages. For some topics I don’t need this but for others I do.

Some of these technologies/tools are directly applicable to the data munging we do at Coffee Meets Bagel to fix database issues and migrate data for new features. Lots of things clicked into place!

My head filled up after about two hours. So many great technologies available, a fertile ground for innovation. Lots of parallel fun.

Now for dinner with Kirk and Aaron.
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17:00: This afternoon’s tutorial was an introduction to statistical modeling.

We started off badly when the instructor sent us the preparatory instructions about two hours before the start. It included downloading and installing Anaconda, which is a mother of a download and a mother of an install. The available time was actually less than two hours because it included our lunch “hour.” And our wi-fi has been unreliable and slow for most of the day.

Getting past that, this was a very good survey of statistical methods, and using pandas and pymc to do modeling. The instructor was one of the authors (I think the primary author) of pymc. Smart dude, lots of insightful asides.

The first hour was fine, the second hour I hung on, and in the beginning of the third hour my head exploded.


The missus called during a break and announced that our existing master bath toilet was leaking and a new one costing $$$ was being installed as we spoke. Glad I don’t have to deal with that.

Time for dinner.

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