Love DuckDB. It’s so fast and portable! I mainly use the query engine as part of my ETL process for creating SQLite database. I’d love to pitch it at work, but we’re heavily invested in BigQuery, which makes it a bit difficult.
I'm a big fan of the Flash-Lite models. They're exceedingly fast and deliver great outputs for high volume use cases where you need to process requests at scale. Can't wait to try the newer version.
In this particular case they are power usage and rate optimization problems to do peak shaving/demand shifting with a combination of batteries and optionally, solar. It tells you the max you can save, the amount of battery/solar you should have (including the pareto front because sometimes it's like 2x the battery for $5 more in savings), and how to program the inverters.
For free, mind you, this is not part of a paid offering on my part.
These are easy for the case of non-demand rates (IE the rate just changes at x hour to x price), and can be solved by HIGHS/et al in a second or two. You can actually prove there is at least one optimal solution that only changes inverter programming at a rate change point.
They are actually quite complex when the rate has a demand charge (IE you are charged not just for x price per kwh, but also some amount * max demand usage of any single hour in a month).
The max demand charge is usually 80% of the bill.
The complexity is because recharging the batteries (particularly without solar) is the same as any other load from a demand perspective. So they have to be trickled (or charged from solar), etc. On top of that, lots of inverters have a limited amount of TOU slots you can use (for example, sol-ark inverters only support 6 periods). Which constrains it painfully. Gurobi can solve it in about 30 seconds. HIGHS takes around 15 minutes to solve it for 2 years of hourly history data.
I built a Python script (with a little help from Claude) that scrapes YouTube for football (soccer) match highlights each game week, filters them using regex + Gemini, and emails me the compiled list.
- Recently I found out that Google Maps doesn't automatically reorder points. One has to manually do the optimization. So I decided to use Google's own wonderful optimization library OR-Tools to do this. This seems to work :). Feedback is highly appreciated.
- Along the way, I found that there are paid services that do this. Well here is my humble attempt.
- One of the most surprising things I observed is that you can only place 10 points in GMaps for routing and apparently GMaps work for only up to 25 points (by manipulating the URL). Beyond that, no paths are shown between points. Apparently, there is an open issue [1] for this since 2014 :). For more than 25 points, I have added the functionality of printing the ordered coordinates.
