PERF: improve StringArray.isna

[jorisvandenbossche]

See #57431 (comment) for context.

• closes #xxxx (Replace xxxx with the GitHub issue number)
• Tests added and passed if fixing a bug or adding a new feature
• All code checks passed.
• Added type annotations to new arguments/methods/functions.
• Added an entry in the latest doc/source/whatsnew/vX.X.X.rst file if fixing a bug or adding a new feature.

Speed-up is around 2x for this case (extracted from one of our ASVs):

dtype = "string"
N = 10**6
data = np.array([str(i) * 5 for i in range(N)], dtype=object)
na_value = pd.NA
ser = pd.Series(data, dtype=dtype)

%timeit ser.isna()
# 11.3 ms ± 47.4 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)    <-- main
# 5.01 ms ± 55.2 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)    <-- PR

Not entirely sure it is worth the extra code, but so it definitely gives a decent speedup for a common operation.

[WillAyd]

You can just assign 1U - no need for the cast on the right hand side

[WillAyd]

Can we return a const uint8_t memory view instead of an ndarray? I still think generally better to use memoryviews over the long term to stay somewhat backend agnostic

[jorisvandenbossche]

I think for the return value we want a numpy array? (inside the function we could use more memoryviews)
I am actually only using this function from python, so can make this a def function and remove the return type

[github-actions]

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