PyCascades 2019 Recap
Once again, I attended and volunteered at PyCascades! This year it was hosted in Seattle at the University of Washington. In 2018, I watched every talk. This year, I only watched about half of the talks, and spent the rest of my time in the hallway track.
I rode the Amtrak train from Vancouver to Seattle. Originally, I had planned to bring my bike to get around Seattle. But the recent arctic vortex weather combined with the fact that I would have had to wake up even earlier than 4:00am the day of departure made me decide not to take my bike on this trip. Worst of all, it turned out that the weather in Seattle over the weekend was quite cheery!
The Amtrak ride down was pleasant. The tickets were cheap, but the coffee and food available on-board was rather overpriced. I was able to leverage the WiFi on the train to get some work done, and even attend my sprint demo. I would definitely ride the Amtrak again. It may not be the fastest option, but it was cheap and stress free.
As always the talks at PyCascades were high quality. My favourites included Turning ‘wat’ into ‘why’ talk by Katie McLaughlin, as well as Meaningful Mentoring Moments by Trey Hunner. The mentoring talk was quite relevant for me, as I’ve been mentoring for Canada Learning Code lately.
I spent about half the conference in the hallway track; socialising and catching up with old friends. The previous PyCascades I attended every talk, and ended up missing out on all the social activities during and after the conference on each day. I’m happy that I was able to strike a balance between the talks and the hallway-track this year. As an added bonus, all the talks are available on YouTube anyway.
Oh, I was also able to attend a live taping of Python Bytes!
I was a stage runner through the morning on Sunday. It was uneventful, but rewarding! I also jumped in and helped out during the initial registration rush on Saturday.
I hopped on an issue for isort. However, it turns out what was originally scoped as a small bug fix turned into a gigantic feature request. Unfortunately, I don’t believe there was time in the day to add the feature. I would have liked to finish implementing the requested feature, but it was going to take longer than the sprint time and I’m leaving on a several week vacation in 2 days! I wish I had spent my time better during the sprints, but that is unavoidable sometimes.