fwojtan / aoc22

My Rust solutions for advent of code 2022

AdventOfCodeTemplate

A sample template for Rust solutions to any one year of Advent of Code.

Adapted by Finlay Wojtan from a previous template by Simon Castle (which was itself adapted from a previous template by Chris Paterson).

How to Use

Get setup

1. Set up your Rust environment
2. Clone this template (git clone https://github.com/CastleQuirm/AdventOfCodeTemplate.git)
3. Test you can run the code, using the Day 00 example.
   • In the terminal, go to the directory you've cloned the repo into (the directory containing this README.md file)
   • Run cargo run 0
     • This should show some build output (the first time this is run), followed by

     Day 0

     Part 1: 5971

     Part 2: 1155077

     0.024ms (exact time may vary) ----------

   • Run cargo test 00
     • This should show some build output (the first time this is run), followed by

     running 3 tests

     test day00::tests::check_day00_both_case1 ... ok

     test day00::tests::check_day00_part1_case1 ... ok

     test day00::tests::check_day00_part2_case1 ... ok

     test result: ok. 3 passed; 0 failed; 0 ignored; 0 measured; 75 filtered out; finished in 0.00s

4. Optionally, in order to use the benchmarking functionality, please install valgrind e.g. sudo apt install valgrind.

Solving puzzles

Start implementing solutions! - Copy and paste your input for the day (e.g. 2020 Day 1's input) into the matching numbered file in the inputs directory - Implement the solution in the matching numbered dayXX.rs file in src - Run the program using cargo run (with the day number to run just that one day, rather than all of 1-25). Add --release to perform a release build for a faster run! - (Optional) Add examples from the puzzle statement into tests in the same file. - Run the tests using cargo test (with the day number to run just the appropriate tests, rather than the tests for every day).

Benchmarking

Pass --bench when running (e.g. cargo run 0 --bench) to benchmark your code using iai. For the purposes of benchmarking, each solution is split into parse_input, part_one and part_two.

Other things I might at some point add...

• benchmarking using criterion
• cargo flamegraph CPU profiles
• heap allocation info using valgrind/massif
• better parsing of bench output