Generally, I would be in favor of having an option for immutable vectors by
default, as I had similar uses before. Usually, I just convert everything
to tuples.
However, I am not sure if having an additional flag on the parent is worth
the extra burden on maintenance. Already the sparsity flag is not always
handled correctly (#29359, #29360), immutability may be even easier to
miss. In my own code, I tend to construct vectors by `vector(ring, [..])`,
which relies on the uniqueness of the parent and will not preserve
immutability of vectors. Though, it is fair to say that this code is
already broken as it does not preserve sparsity either. On the other hand,
code that is careful about preserving the parent could break if now the
parent vector space does not allow for mutation. For example, in case of a
(fabricated) function like
def f(vec, i):
w = vec.parent()(0)
w[i] = vec[i]
return w
one would have to convert the vector from an immutable vector space to one
that allows for mutable elements before calling it. This just displaces the
original problem.
Regarding the performance discussion, (although this was not the question)
using vectors also has the potential of being much slower than using numpy
arrays directly.
sage: a = vector(CDF, [CDF(1, i/(i+1)) for i in range(10^6)])
sage: %time c1 = a.conjugate()
Wall time: 4.39 s
sage: %time c2 = a.parent()(a.numpy().conj())
Wall time: 11.8 ms
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