Advent of Code 2017 in #rstats: Day 6

The solution was a simple concept but harder than I thought to implement.  I learned some lessons today:

  • Read the instructions carefully.  I built the balancing function balance_banks to return how many distributions it made of the maximum value, but removed this code when I realized that the full distribution of a bank of N values counted as one iteration, not N iterations.
  • Related: Up until now, Git has felt unnecessary for these challenges, and I’ve been too lazy to use it (though it would do wonders for my GitHub contribution graph).  Today I got nervous deleting and reworking code for Part 1 … would I need it for the not-yet-known Part 2?
  • I built my balance_banks function inside of my go_til_repeat function (because I thought it would help with passing counter information, which I did not need).  When editing and then testing, I kept failing to load both into memory; I’d update one, load the other into memory, and call the first one.  I don’t work much with nested functions of any complexity; TIL to avoid loading just one while programming and testing them.

Today was the first day that run-time performance became an issue.  My outputs for each part were correct on the first try, but each took a while (3 minutes?) to run.  Suspicious that my code was stuck in a loop, I never let it finish the first call I made: I broke the loop manually and added the counter to print every 1,000 rebalances.

But it was just slow.  To check completion, I switched to the use of double duplicated you see below instead of janitor::get_dupes(), which is easier on the brain but a relatively expensive operation.

Lastly, when I thought I had to return multiple outputs from balance_banks I had it return them in a list.  I removed the increment counter code and the function now returns just one result (the balanced vector), but I left the list syntax in place since it worked.  That’s why you see the $output in last_result <- balance_banks(last_result$output)for instance.

Adding Part 2 onto Part 1 was trivial.  I’d seen Jenny Bryan use diff(range()) in a solution to an earlier puzzle and was stoked to reuse it in Part 2.

I resorted to rbind instead of my beloved dplyr::bind_rows because my data.frames don’t have column names.  I remain tickled by situations where I work with data.frames in R while ignoring column names.

Parts 1 and 2

 

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