Those videos completely changed the way I drain pasta noodles, from dumping them into a strainer over the sink and losing all the starchy water to scooping them out with a spider and dropping them directly into the saucepan. Seriously upped my pasta game.

The article reminds me of the "Yes, and..." rule from improv comedy. In replying to someone else's proposal, creating a habit of literally starting your sentence with "Yes, and..." is a way to build collaboration skills.

Agree with this. Nvim-R plus dplyr and the plotting libraries are the best tools I've found for manipulating and understanding the characteristics of a dataset quickly. Eventually I moved to Python for the specific reason that the R packages for interacting with cloud platforms couldn't really keep up with the development of those platforms, and I got tired of having projects that mashed together both languages. I haven't checked, maybe things have stabilized enough now that I would be happy going back to R.

That makes sense. I don't much like crossing streams between languages on a project. It's great if you can keep R for analysis and Python for production, but if R can't keep up with the wrangling part, you're a bit up a creek. I'm lucky in that most of my analysis only needs to query fairly well-behaved SQL databases.

As an American in Germany trying to speak German, I've made some effort to hide my accent. But then I think about Arnold and Werner Herzog. Would they be who they are without their accents in English? Then again, no one here has ever mocked the way I speak.

I'm building a simple replacement for Apache Airflow to manage some small data pipeline projects: https://github.com/fieldryand/goflow. Airflow started to feel too heavyweight for these projects where all the computation was offloaded to independent services. I wanted a solution with minimal memory requirements to save costs and avoid the occasional high memory usage/leak issues I was facing with Airflow. I know there are tons of existing solutions in this space, but nothing I found seem to match the Airflow features I needed, so I decided to build it myself. It's been a great way to learn Go.