Project Euler is an online platform that contains around one thousand problems intended to be solved with coding. The problems present an interesting intersection between mathematics and algorithms, providing challenges that span various domains in both fields. The platform also offers a collaborative forum where enthusiasts from all around the world share their thoughts and solutions (the discussion for a particular problem becomes available once the problem is solved).
I have a bachelor degree in computer science and, back when I was a student, I started solving these problems but they quickly progress into something that requires more mathematical knowledge than I had back then. Now that I am pursuing a degree in math, I re-discovered this challenge and once again started to work on the problems. I'll try to solve them all, but I am not sure how far I'll get. However, Project Euler's about page states that, in order to be in the top 1%, one must solve more than 115 problems and that's my goal for the moment.
It only needs Python (I use python 3.10.9), but don't forget to run
pip install -r requirements.txt to install all requirements and
pre-commit install to initialize the pre-commit hooks.
After that, you can run a single solution by running
python run.py -p <problem_id> where problem_id is the problem number.
Example: python run.py -p 45.
Tests are automated and run at every commit. There's also a pre-commit hook that
runs black on modified files to linter them.
There's an option to run all problems at once and list the 10 slowest ones. It is python run.py -t. Don't know if this can be useful to anyone at all, but I use it to track slow solutions to eventually make them faster, saving time whenever unittest runs. It will output something like this:
Problem ID Runtime (seconds)
------------ -------------------
092 18.8423
034 11.3672
027 4.9794
037 1.8677
030 1.7468
014 1.6722
010 1.0345
023 0.862
047 0.7111
050 0.6244
I hope you can learn something from my solutions. Happy coding!
