awesome-algorithms VS crumsort

Solved. https://github.com/tayllan/awesome-algorithms

This repo.

I found this with zero effort: https://github.com/tayllan/awesome-algorithms. Just pick one of the courses there if you can't make up your mind.

https://github.com/tayllan/awesome-algorithms this curated list should be able to help you find more

2. Awesome Algorithms

Also, GitHub: Awesome algorithms — curated list of resources to learn and/or practice algorithms

See also https://github.com/tayllan/awesome-algorithms for a list of interactive visualizations, learning resources, etc.

Check out TCS, Algorithms, and Math awesome lists.

Blitsort is a hybrid quicksort, see title.

It is slower than it's unstable brother, aptly named crumsort. https://github.com/scandum/crumsort

https://github.com/scandum/crumsort claims better performance than pdqsort

Any chance you could comment on fluxsort[0], another fast quicksort? It's stable and uses a buffer about the size of the original array, which sounds like it puts it in a similar category as glidesort. Benchmarks against pdqsort at the end of that README; I can verify that it's faster on random data by 30% or so, and the stable partitioning should mean it's at least as adaptive (but the current implementation uses an initial analysis pass followed by adaptive mergesort rather than optimistic insertion sort to deal with nearly-sorted data, which IMO is fragile). There's an in-place effort called crumsort along similar lines, but it's not stable.

I've been doing a lot of work on sorting[2], in particular working to hybridize various approaches better. Very much looking forward to seeing how glidesort works.

[0] https://github.com/scandum/fluxsort

[1] https://github.com/scandum/crumsort

[2] https://mlochbaum.github.io/BQN/implementation/primitive/sor...