Dmitry Petrov Back

Advent of code quiz reflections

This December a big chunk of my free time was spent on solving quize from Advent of code challenge. While I wasn’t anywhere amongst the leaders it was a pure joy to see how clojure helps to gradually build solutions without constant switching between the editor and console.

If the only thing you have is a hammer then everything looks like a nail and majority of tasks ended as some sort of list generation which is somehow reduced to the to the answer value. If you look at the task from this point of view you will discover that it really helps to avoid most of side effects or temporary states which can be a big source of bugs.

If you think about everything as list it becomes immediately evident how rich and cool core library is. Apart from it I used only clojure.string, clojure.set and math.combinatorics namespaces.

The main disadvantage for me was that with certain number of map/reduce/filter functions in one expression code becomes much harder to read for anyone who is not very familiar with them and sometimes it’s evident that in some cases types can really help because it’s hard to say how structure looks like at given point of transformation. May record is 9 map/reduce calls in one function.

The other pain point is emacs cider and changing project dependencies. Maybe I don’t read documentation correctly but the only good way to load new dependencies is to restart repl and to do that I had to kill it. Sad news is that after that in most cases I ended up with restarting emacs which meant losing undo history and repl logs.

Ok, back to interesting stuff. I want to share a few incredibly useful functions from the core library that I discovered while doing the challenge. Although simple sometimes they drastically simplify the code.


Used in day 1

This function takes the same arguments as reduce but instead of final value returns a sequence of all intermideary reduction states. It’s useful if every reduction step has it’s own meaning, e.g. distinct state that you want to analyze. Or if you have an infinite sequence you can use reductions to count the steps to get to the desired state.


Used in day 5 and day 11.

Takes any number of functions and returns new function that will return true only if all the functions return true with arguments passed. Very useful to write conditions in compact way:

(def ans1 (count (filter
                  (every-pred has-wovels
                  (str/split input #"\n"))))


Used in day 5, day 11 and day 13

Function allows to get a sequence of list every of which is a subsequence from original of some width and with some offset from the begining. In my case it was very useful to check any connections between sequence items.

Here is an example:

(def chmap (apply hash-map
                  (flatten (partition 2 1
                           (concat (char-range \a \z)
                                   (list \a))))))

This expression generates a hashmap with keys that are individual characters and the values that are the charecters that alphabetically follow them, except a follows z. partition takes (\a \b .. \z \a) list as input and returns sequence like ((\a \b) (\b \c) … (\y \z) (\z \a)). After that I transform this sequence to the flat list and feed it to hash-map function.


Used in day 12

Groups sequence according to return values of predicate.


Used in day 18 , day 17 and day 25

Function takes value and another function and returns a sequence that starts from the value and continues with applying function to previous sequence item to generate next one. Helps to avoid loops in all situations where you need to build next value on top of current one.


Used in day 19, day 21, day 22, day 23 and day 25

Works like re-find but returns a lazy sequence of all consequtive matches.