toit VS advent_of_code

It uses toit, a high-level language, and is thus quite easy to learn. At the same time it's an order of magnitude faster than micropython.

We have been faced with the same question and decided to open-source pretty much all of our product (https://github.com/toitlang/toit).

I also really like MicroPython! Having said that, I have been working on an alternative to it for a number of years now -- primarily to provide a more robust and performant high-level alternative to C and Rust on the ESP32-family of chips:

https://github.com/toitlang/toit

I'd love to pick your brain and fully understand your experience with MicroPython. I've been doing programming languages for a number of years now, and I find that it is incredibly useful to understand what developers appreciate (and dislike) about the available stacks.

Thank you for the mention!

I have been working on the Toit language for the ESP32 for a number of years now -- and it has been an enjoyable challenge to build an open source stack capable of supporting live reloading on a micro-controller that can run for years on batteries.

https://github.com/toitlang/toit

We use it for some of our tools, so it's possible (and works nicely). Our LSP server was initially written in Toit: https://github.com/toitlang/toit/tree/master/tools/lsp/serve...

Here's the relevant extract from my (recursive) solution. Full code on GitHub.

Like others, I used lcm. Here's an extract of the solution, omitting parsing and main(). Full solution on GitHub.

Solutions to parts 1 and 2 nearly identical and pretty much worked first time. Nothing clever here. This was far simpler than I thought it would be. I probably spent most time trying to think of a mathematical way of getting all points between p1 and p2. In the end, I just constructed two ranges. Full code here.

Full code on github.

The core of my solution below using numpy (because I'm learning it!). See github for full code.

Python 3 solution using numpy. I got held up because I assume (but know better) that numpy arrays are [x,y] instead of [row, col], which is [y,x].

Below is the new solution, which works for part 1 and 2. The full code is on GitHub.

These are the key functions. The whole code is on GitHub

Part 2 (extract shown below) was a matter of starting with the low points found in part 1 then recursively looking around for relevant points. Full code on GitHub

Code is on GitHub.