I studied urban planning back in the university and one of the classes was road design. Though I forgot most, one part of the class was about how to design roads with curves that's safe for cars. This post just brought that memory back to me.
"Problem Solving" is a good reference for understanding algorithms and data structures. It uses Python but Python language is not its main focus.
However, "Problem Solving" is one of the best places where I've learnt programming.
Yes, I agree with you. Strictly speaking, I was creating new semantics of the operators which looks like "new" syntax, to mimic "syntactic sugar". But I have no idea how to name this in a more understandable way.
Leaves me wondering if I'd be shooting off my little toe or my whole foot!
Might be fun to show pythonic equivalents for the ones that are relatively easy to make pythonic. You might discover some useful pythonic functions along the way.
Math notations are so badly designed (if there exists any design) If you'd spoken in plain English, Lamport, most people in the room could have understood the concept of your tedious formula.
So it's not because we don't understand math - it's because the math notations are usually over abbreviated, obscure and inconsistent. Math itself is strict but there's no strict common language to express it, which eventually prevents people from understanding it.
There is a strict common language to express it. The speaker used that language (except for the nonstandard replacement of brackets with square brackets, which was apparently clearly pointed out at the start). The problems start when you speak in plain English: then you get things like everyone using different definitions of continuity and thinking everyone else is just spouting nonsense until someone comes up with epsilon-deltas.
