This is a nice little algorithm and it shows how to approach it in Python while keeping it efficient in term of operations.

Or how a problem is represented matters a lot. Going for a constraint solver might be what you want sometimes.

Looks like we'll be able to leave Dijkstra's algorithm behind at some point.

Nice explanation of how graph search algorithms work. If you need to build some path finding feature this is for you.

Interesting new proof on the relationships between P and PSPACE. Let's see where this leads.

An old one now, but since I keep giving this advice it seems relevant still. If you're using raw loops at least that no again, there is likely a good alternative in the STL.

Nice principle for a search in a sorted list when you don't know the upper bound.

Can you see this kind of models getting abused quickly? Clearly it says something about the tech industry wanting to reduce costs.

This is a nice view into how a query planner roughly works and a nice algorithm which can be used internally to properly estimate the number of distinct values in a column.

A nice pattern to separate decision from actions in complex algorithms.

Need to know if two shapes overlap? Good explanation of an elegant algorithm to do it.

Useful list of gotchas if you need to dabble in linear algebra. You gotta love those floats.

Really cool optimizations for B-Trees. Once the layout is reworked this is a neat way to use SIMD as well.