feat(python): Implement bitmap unpacking

[paleolimbot]

In prototyping a real-world use case, I remembered that unpacking bits is exceedingly difficult to get right if you need to support an arbitrary offset/length. The math for this is very fiddly and we spent a few rounds getting it right in the C function ArrowBitsUnpackInt(8|32). This PR makes that available so that we can do things like (1) convert bool arrays to numpy and (2) convert null masks to something that somebody else can work with (e.g., a numpy mask).

This seems to be relatively performant (thanks to @WillAyd's work optimizing this!)

import numpy as np
import nanoarrow as na
import pyarrow as pa

bool_np = np.random.random(int(1e6)) > 0.5
bool_na = na.Array(iter(bool_array), na.bool_())
bool_pa = pa.array(bool_np)

def to_numpy_na(x):
    x_view = na.c_array(x).view()
    out = np.empty(x_view.length, bool)
    x_view.buffer(1).unpack_bits_into(out, x_view.offset, x_view.length)
    return out

%timeit to_numpy_na(bool_na)
#> 162 µs ± 812 ns per loop (mean ± std. dev. of 7 runs, 10,000 loops each)

%timeit bool_pa.to_numpy(False)
#> 609 µs ± 833 ns per loop (mean ± std. dev. of 7 runs, 1,000 loops each)

[WillAyd]

Really cool change - I can see there being a lot of uses for this

[WillAyd]

Maybe worth also checking that dest_offset is non-negative? I think you'd get UB if a user decides to do something like unpack_bits_into(..., len(dest) + 1, -1) (not that they should...)

[paleolimbot]

Good catch! Thanks for the review!