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I went to PyCon a few weeks ago and while there, saw Peter Wang’s keynote on a new project called PyScript. PyScript is, essentially, a set of tools for running Python code in the browser – potentially even user-submitted code. I think that’s going to have a significant impact on the Python world, though maybe not in the way you’d first expect. Some Background For years now, various groups have been working on finding a way to “run” Python in the browser.

I recently returned from a 10-day road trip. Nowhere too exciting, just through the middle of the continental US: St. Louis, Memphis, northeast Arkansas, and Champaign (home of the University of Illinois Urbana-Champaign). People who know me probably wouldn’t describe me as the road trip type. But I had a few weeks off before I started a new job and the opportunity to travel without any commitments (or a finite amount of PTO) doesn’t present itself often; I figured that there would never be a better time to travel somewhat spontaneously.

I recently crossed the 9-month mark as a Chicago resident. The time has come for a big decision: renew my lease, or make the move to a new apartment?

I really like my current home. Two bedrooms, a back porch, a garage, and more grounded outlets than even a tech nerd like me could want. It’s in Little Italy, which is not a popular choice for Chicago young professionals, but is comfortable and has a decent set of restaurants. I suspect that a similar unit in a more “hip” neighborhood might be out of my price range. And my real office (as opposed to my extra bedroom, which has been serving in that capacity since I moved here) is a 10-minute bike ride away. The north side, home of many of those hip neighborhoods, would bring with it a commute at least twice as long.

On the other hand, my primary motivation in moving to a big city was exploration and experience. I wanted to get to know Chicago, particularly its neighborhoods. Moving would offer me a change of location, unlocking many new walkable or bikable destinations. Additionally, none of my friends live near my current apartment; most are in various parts of the northern neighborhoods, while I live somewhat south and west of the Loop (the downtown area of Chicago). Seeing most friends requires a 15+ minute drive or 30+ minute train ride.

I suspect meetings at most American companies are full of jargon. There’s company- or industry-specific jargon: abbreviations or nicknames for common ideas (sometimes this is extended to the naming of internal teams as well). While frustrating to newcomers, these terms and phrases typically have a fair amount of value. Shorthands for industry-specific concepts are useful, both in time savings and added precision. A good example is MAU, monthly active users. Investors care a lot about who is using a product regularly, so this probably comes up regularly in Silicon Valley communications – both with the investors and within a company, as leadership pushes MAU as a proxy goal.

In data science and engineering, technical skills are often the quickest way to early-career advancement – a new contributor who can write decent code is immediately an asset, in a way that a business-savvy developer with no coding ability is not. Companies often publicly espouse the benefits of softer skills, but that may not ring true in entry-level positions. In some technical fields, non-technical strengths can actually be viewed as negatives by peers, a betrayal of the ethos of the programmer.

With the announcement of Apple One in September, I decided to reevaluate my loyalty to Spotify. If Apple was going to offer me a (slightly) discounted rate if I went all-in on their services, I wanted to have a good look at Apple Music and see if it could replace Spotify for me. After almost three months of use, my conclusion is that I could live with Apple Music, but I’d happily pay a small premium for Spotify instead.

I recently discovered and binged the Ben, Ben and Blue podcast. The hosts all work in STEM education to some degree, and while that topic isn’t explicitly the focus of the show, it comes up a lot. In one episode, Grant Sanderson (one of the hosts) talks about how it’s tempting to teach new ideas by recapping the actual discovery of the concept as it happened. For example, I don’t know the exact details of the creation of the internet, but you could imagine an explanation that walks through the journey of universities wanting some kind of decentralized communication protocol, and how that effort was funded by government money with the justification that it could be useful for national defense.

For those not already in-the-know about Tony Horton’s infamous X-treme workout series, P90X was a collection of video workouts released in 2005. They’ve achieved something of a cult following in the years since, and Tony has returned in several reprisals – though none seem to have gained the fame of the original P90X. The workouts require minimal equipment: just a pull-up bar, a yoga mat, and a modest collection of dumbbells.

I spend a lot of time on meta-productivity: thinking about how to get work done better and faster. The majority of that thinking is around technology and specifically the tech tools I use. Maybe thinking about my workflow has returns large enough to offset the time it consumes in my life, but frankly it doesn’t matter too much to me since life optimization is as much a hobby as an objective.

For a while now, I’ve been thinking about how interesting it would be to look at data on my running habits. Depending on the time of year and some other factors, I probably run 1-4 times a week, and I’ve been running semi-regularly since college.

For the vast majority of that time, I’ve recorded my runs in Under Armour’s MapMyRun app. It’s a bit buggy and feels non-native, but it has a good Apple Watch app and collects the information I need fairly reliably.