  Given a computable sequence of natural numbers, it is a natural task to find
a G\"odel number of a program that generates this sequence. It is easy to see
that this problem is neither continuous nor computable. In algorithmic learning
theory this problem is well studied from several perspectives and one question
studied there is for which sequences this problem is at least learnable in the
limit. Here we study the problem on all computable sequences and we classify
the Weihrauch complexity of it. For this purpose we can, among other methods,
utilize the amalgamation technique known from learning theory. As a benchmark
for the classification we use closed and compact choice problems and their
jumps on natural numbers, and we argue that these problems correspond to
induction and boundedness principles, as they are known from the Kirby-Paris
hierarchy in reverse mathematics. We provide a topological as well as a
computability-theoretic classification, which reveal some significant
differences.
