> you need to know these numbers on Python to know when to actually build something in C

People usually approach this the other way, use something like pandas or numpy from the beginning if it solves your problem. Do not write matrix multiplications or joins in python at all.

If there is no library that solves your problem, it's a great indication that you should avoid python. Unless you are willing to spend 5 man-years writing a C or C++ library with good python interop.

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oivey 6 hours ago | parent [-]

People generally aren’t rolling their own matmuls or joins or whatever in production code. There are tons of tools like Numba, Jax, Triton, etc that you can use to write very fast code for new, novel, and unsolved problems. The idea that “if you need fast code, don’t write Python” has been totally obsolete for over a decade.

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fooker 6 hours ago | parent [-]

Yes, that's what I said.

If you are writing performance sensitive code that is not covered by a popular Python library, don't do it unless you are a megacorp that can put a team to write and maintain a library.

	▲	oivey 6 hours ago \| parent [-]
		It isn’t what you said. If you want, you can write your own matmul in Numba and it will be roughly as fast as similar C code. You shouldn’t, of course, for the same reason handrolling your own matmuls in C is stupid. Many problems can performantly solved in pure Python, especially via the growing set of tools like the JIT libraries I cited. Even more will be solvable when things like free threaded Python land. It will be a minority of problems that can’t be, if it isn’t already.