(This repository's structure and the base classes and utils functions were heavily inspired by nitekat1124's, all rights reserved.
The solutions implemented in the solutions/naive folder I came up with without looking at other people's code.)
My personal solutions to Advent of Code 2024, implemented in Python 3.
For each day, a single ⭐ is listed if only the first part of the puzzle was solved, and both ⭐⭐ if both parts are solved correctly. A 🌠 signifies that consulting external resources was required in order to solve a part (usually out of frustration for not finding a solution by myself for several hours or days).
| Day | Naive Solutions | Optimal Solutions |
|---|---|---|
| 01 | ⭐⭐ | ⭐⭐ |
| 02 | ⭐⭐ | -- |
| 03 | ⭐⭐ | -- |
| 04 | ⭐⭐ | -- |
| 05 | ⭐⭐ | -- |
| 06 | ⭐⭐ | -- |
| 07 | ⭐⭐ | -- |
| 08 | ⭐⭐ | -- |
| 09 | ⭐⭐ | -- |
| 10 | ⭐⭐ | -- |
| 11 | ⭐⭐ | -- |
| 12 | ⭐🌠 | -- |
| 13 | ⭐⭐ | -- |
| 14 | ⭐⭐ | -- |
| 15 | ⭐⭐ | -- |
| 16 | ⭐⭐ | -- |
| 17 | ⭐⭐ | -- |
| 18 | ⭐⭐ | -- |
| 19 | ⭐⭐ | ⭐⭐ |
| 20 | ⭐⭐ | -- |
Under the solutions/naive folder I list the solution I came up on the spot, while trying to solve the daily Advent of Code challenge, without any particular refactoring or optimization, just some minor cleanup.
Under the solutions/optimal folder I will list progressively some better and optimized solution, possibly the best among the ones I find online, if not the actually optimal ones.
Both folder have a dedicated README.md with some personal commentary on specific solutions where I find it interesting to document my thought process, or the credits to an optimal solution I found online.
For each day you intend to test my solutions against, you need to provide manually the puzzle inputs (see why here).
In order to do so, the plaintext of the sample input and of your personal input need to be put respectively in two distinct files, in inputs/test/09 and inputs/puzzle/09 assuming you're testing just day 9 (in general, the file name is the zero-fill at two positions of a given day).
This is the general usage helper, provided by Python's argparse:
usage: runner.py [-h] [-d day_number] [-p part_number] [--optimal] [--skip-test] [--no-elapsed] [--run-all]
Bulk runner of gabxcos' Advent of Code 2024 solutions
options:
-h, --help show this help message and exit
-d day_number, --day day_number
Required, day number of the AoC event
-p part_number, --part part_number
Required, part number of the day of the AoC event
--optimal Optional, use the intended optimal solution instead of the one I actually came up with
--skip-test Optional, skipping tests
--no-elapsed Optional, avoid elapsed prints
--debug Optional, add debug prints and computations, if available
--run-all Optional, runs all available days with the given options; if set, -d and -p are ignored
-
running for part 2 of day 9:
python -m runner -d 9 -p 2 -
running all available naive solutions:
python -m runner --run-all -
running all available optimal solutions:
python -m runner --optimal --run-all -
running all available naive solutions without testing sample inputs:
python -m runner --run-all --skip-test -
running all available naive solutions without measuring elapsed time:
python -m runner --run-all --no-elapsed -
running all available naive solutions with debug computations:
python -m runner --run-all --debug