[Python] Add a PyArrow sanitizers build

### Describe the enhancement requested

As part of:
- https://github.com/apache/arrow/issues/36411

The discussion about adding a sanitizers build for PyArrow popped up. I am creating this issue to track the discussion and raise it as a separate enhancement.

So far the summary of the discussion there:

> I think the main difficulty for a PyArrow sanitizers build is that the sanitizer instrumentation should be enabled in CPython as well (and potentially NumPy?).

_Originally posted by @pitrou [#36411](https://github.com/apache/arrow/issues/36411#issuecomment-3916508307)_

> You may be interested in how numpy & scipy are doing this, in conjunction with CPython. That setup uses pixi as a kind of "light-weight conda-build" orchestrator that wraps the various rebuilds (independent of whether that's via CMake/meson/whatever):
> * https://github.com/python/cpython/issues/142466
> * https://github.com/python/cpython/pull/142872
> * https://github.com/numpy/numpy/pull/30510
> * https://github.com/scipy/scipy/pull/24066
> * etc.

_Originally posted by @h-vetinari in [#36411](https://github.com/apache/arrow/issues/36411#issuecomment-3916859990)_

> That's an ideal setup but I don't think its required - you could use point LD_PRELOAD to the sanitizer library to have it loaded correctly from a process that was not built with sanitizers enabled (i.e. Python). We used to do that in CI with pandas, although we did abandon it after time due to it being a maintenance burden

_Originally posted by @WillAyd in [#36411](https://github.com/apache/arrow/issues/36411#issuecomment-3916925502)_

> Is that enough, though? Ideally, the code is instrumented at compile time (memory accesses etc.). For example, if PyArrow passes a bogus memory pointer to NumPy, we want ASan to notice and that might not happen if NumPy was not compiled with ASan enabled.
>

_Originally posted by @pitrou in [#36411](https://github.com/apache/arrow/issues/36411#issuecomment-3916949900)_

> Yeah, for ASAN/TSAN, you need to instrument the other relevant libraries, which means rebuilding them, which is generally a huge pain, which is why the approach I referenced above provides a real benefit. Once all the pieces are in place, it comes down to
> ```
> pixi run test-asan -t some_test
> ```
> which rebuilds (& caches) instrumented cpython, numpy etc. as necessary. I haven't been very involved, but the scipy PR contains more details; and I'm pretty sure that Lucas wouldn't mind answering questions (not tagged here because it's already a bit OT).

_Originally posted by @h-vetinari in [#36411](https://github.com/apache/arrow/issues/36411#issuecomment-3917154312)_

### Component(s)

Python