In fact, what performance oriented devs need to be taught about these days is how to not use hash tables, or, more generally, dictionaries. They are a super-easy data structure to reach for, but often it is possible to arrange your data such that their use is unnecessary.

One example that was brought up elsewhere in the thread is the way python looks up variables in successive scope dictionaries. This is obviously terrible for performance, and that's a big part of why Python is slow.

But how are other languages fast? Doesn't every language have to resolve variable names to memory locations? Well, yes, but fast languages do this mostly at compile time. How? Well, I'm not an expert in this, but at a high level, each variable is assigned a location in memory or registers, and then future references to that variable are rewritten to refer to the memory location by register name or memory address. This takes the whole "looking up a name" issue out of the path of work that has to get done at runtime. And you've switched from looking up things in tables to operating directly on registers and memory locations.

BTW, this has nothing to do with high-versus-low level. It's more about how mutable the process of name resolution is after program compilation. One could theoretically write an assembly language where memory locations are names, not numbers. If reflective features like runtime scope editing are available, this would be a very low-level language that still requires some kind of dictionary lookup at runtime.