Day 9: Disk Fragmenter

Megathread guidelines

  • Keep top level comments as only solutions, if you want to say something other than a solution put it in a new post. (replies to comments can be whatever)
  • You can send code in code blocks by using three backticks, the code, and then three backticks or use something such as https://topaz.github.io/paste/ if you prefer sending it through a URL

FAQ

  • VegOwOtenks@lemmy.world
    2·
    13 days ago

    Thank you for the detailed explanation!, it made me realize that our solutions are very similar. Instead of keeping a Dict[Int, List[Int]] where the value list is ordered I have a Dict[Int, Tree[Int]] which allows for easy (and fast!) lookup due to the nature of trees. (Also lists in haskell are horrible to mutate)

    I also apply the your technique of only processing each file once, instead of calculating the checksum afterwards on the entire list of file blocks I calculate it all the time whenever I process a file. Using some maths I managed to reduce the sum to a constant expression.

    • Acters@lemmy.world
      2·
      13 days ago

      yeah, I was a bit exhausted thinking in a high level abstract way. I do think that if I do the checksum at the same time I could shave off a few more milliseconds. though it is at like the limits of speed, especially for python with limited data types(no trees lol). Decently fast enough for me :)

      edit: I also just tested it and splitting into two lists gave no decent speed up and made it slower. really iterating backwards is fast with that list slice. I can’t think of another way to speed it up past it can do rn

        • Acters@lemmy.world
          2·
          13 days ago

          so if I look at each part of my code. the first 4 lines will take 20 ms

          input_data = input_data.replace('\r', '').replace('\n', '')
part2_data = [[i//2 for _ in range(int(x))] if i%2==0 else ['.' for _ in range(int(x))] for i,x in enumerate(input_data)]
part2_data = [ x for x in part2_data if x!= [] ]
part1_data = [y for x in part2_data for y in x]

          The part1 for loop will take 10 ms.

          The for loop to set up next_empty_slot_by_length will take another 10 ms.

          The part2 for loop will take 10 ms, too!

          and adding up the part2 checksums will add another 10 ms.

          So, in total, it will do it in ~60 ms, but python startup overhead seems to add 20-40 ms depending if you are on Linux(20 ms) or Windows(40 ms). both are Host, not virtual. Linux usually has faster startup time.

          I am not sure where I would see a speed up. It seems that the startup overhead makes this just slower than the other top performing solutions which are also hitting a limit of 40-60 ms.

        • Acters@lemmy.world
          2·
          13 days ago

          ah well, I tried switching to python’s set() but it was slow because of the fact it is unordered. I would need to use a min() to find the minimum index number, which was slow af. indexing might be fast but pop(0) on a list is also just as fast.(switching to deque had no speed up either) The list operations I am using are mostly O(1) time

          If I comment out this which does the adding:

          # adds checksums
    part2_data = [y for x in part2_data for y in x]
    part2 = 0
    for i,x in enumerate(part2_data):
        if x != '.':
            part2 += i*x

          so that it isolates the checksum part. it is still only 80-100ms. so the checksum part had no noticeable slowdown, even if I were to do the check sum at the same time I do the sorting it would not lower execution time.