It seems that JIT is overloaded with at least 2 meaning.

The canonical definition of JIT is "compilation during execution of a program". Usually, a program is being interpreted first, then switches to compiled code in the middle of execution. This is not what this article does.

What this article does is sometimes called on-the-fly AOT, or just on-the-fly compilation. I'd prefer not overloading the term "JIT".

Following is the closed form solution linked in the article (from a since-deleted Reddit comment):

    from functools import reduce

    def recurrence(ops, a0, n):
        def transform(x, op):
            return eval(repr(x) + op)
        ops = ops.split()
        m = reduce(transform, [op for op in ops if op[0] in ('*', '/')], 1)
        b = reduce(transform, ops, 0)
        for k in range(n + 1):
            print('Term 0: ', a0 * m ** k + b * (m ** k - 1) / (m - 1))

> This is really only interesting if a particular (potentially really large) term of the sequence is desired, as opposed to all terms up to a point. The key observation is that any sequence of the given set of operations reduces to a linear recurrence which has the given solution.

Is it just me or is the author using static wrong? Someone mentioned it in the thread on the previous post, where it felt more like an oversight. But in this article it seems much more like an actual misunderstanding. Should it actually be the function level static variable? I feel like in the right context the optimizer might be able to leave that in a register if there the calling function is in the compilation unit.