Reflections on #aoc2017
This post is part of the series Advent of Code 2017
- > Reflections on #aoc2017 <
- The Halting Problem — Python — #adventofcode Day 25
- Electromagnetic Moat — Rust — #adventofcode Day 24
- Coprocessor Conflagration — Haskell — #adventofcode Day 23
- Sporifica Virus — Rust — #adventofcode Day 22
- Fractal Art — Python — #adventofcode Day 21
- Particle Swarm — Python — #adventofcode Day 20
- A Series of Tubes — Rust — #adventofcode Day 19
- Duet — Haskell — #adventofcode Day 18
- Spinlock — Rust/Python — #adventofcode Day 17
- Permutation Promenade — Julia — #adventofcode Day 16
- Dueling Generators — Rust — #adventofcode Day 15
- Disk Defragmentation — Haskell — #adventofcode Day 14
- Packet Scanners — Haskell — #adventofcode Day 13
- Digital Plumber — Python — #adventofcode Day 12
- Hex Ed — Python — #adventofcode Day 11
- Knot Hash — Haskell — #adventofcode Day 10
- Stream Processing — Haskell — #adventofcode Day 9
- I Heard You Like Registers — Python — #adventofcode Day 8
- Recursive Circus — Ruby — #adventofcode Day 7
- Memory Reallocation — Python — #adventofcode Day 6
- A Maze of Twisty Trampolines — C++ — #adventofcode Day 5
- High Entropy Passphrases — Python — #adventofcode Day 4
- Spiral Memory — Go — #adventofcode Day 3
- Corruption Checksum — Python — #adventofcode Day 2
- Inverse Captcha — Coconut — #adventofcode Day 1
- Advent of Code 2017: introduction
All of my code is available on GitHub if you’re interested in seeing what I did, and I managed to get out a blog post for every one with a bit more commentary, which you can see in the series list above.
How did I approach it?
I’ve not really done any serious programming challenges before. I don’t get to write a lot of code at the moment, so all I wanted from AoC was an excuse to do some proper problem-solving.
I never really intended to take a polyglot approach, though I did think that I might use mainly Python with a bit of Haskell. In the end, though, I used: Python (×12); Haskell (×7); Rust (×4); Go; C++; Ruby; Julia; and Coconut.
For the most part, my priorities were getting the right answer, followed by writing readable code. I didn’t specifically focus on performance but did try to avoid falling into traps that I knew about.
What did I learn?
I found Python the easiest to get on with: it’s the language I know best and although I can’t always remember exact method names and parameters I know what’s available and where to look to remind myself, as well as most of the common idioms and some performance traps to avoid. Python was therefore the language that let me focus most on solving the problem itself. C++ and Ruby were more challenging, and it was harder to write good idiomatic code but I can still remember quite a lot.
Haskell I haven’t used since university, and just like back then I really enjoyed working out how to solve problems in a functional style while still being readable and efficient (not always something I achieved…). I learned a lot about core Haskell concepts like monads & functors, and I’m really amazed by the way the Haskell community and ecosystem has grown up in the last decade.
I also wanted to learn at least one modern, memory-safe compiled language, so I tried both Go and Rust. Both seem like useful languages, but Rust really intrigued me with its conceptual similarities to both Haskell and C++ and its promise of memory safety without a garbage collector. I struggled a lot initially with the “borrow checker” (the component that enforces memory safety at compile time) but eventually started thinking in terms of ownership and lifetimes after which things became easier. The Rust community seems really vibrant and friendly too.
I really want to keep this up, so I’m going to look out some more programming challenges (Project Euler looks interesting). It turns out there’s a regular Code Dojo meetup in Leeds, so hopefully I’ll try that out too. I’d like to do more realistic data-science stuff, so I’ll be taking a closer look at stuff like Kaggle too, and figuring out how to do a bit more analysis at work.
I’m also feeling motivated to find an open source project to contribute to and/or release a project of my own, so we’ll see if that goes anywhere! I’ve always found the advice to “scratch your own itch” difficult to follow because everything I think of myself has already been done better. Most of the projects I use enough to want to contribute to tend to be pretty well developed with big communities and any bugs that might be accessible to me will be picked off and fixed before I have a chance to get started. Maybe it’s time to get over myself and just reimplement something that already exists, just for the fun of it!