Trial different memory profiler in benchmarks

[pp-mo]

From work elsewhere, we find that it might be better to track Python heap usage, instead of Linux RSS space

At least the observation here ("When initially run, this claimed that no memory at all was used ") is relevant : It show that "RSS" is not working for a simple tests where a setup may allocate space that is then re-used within the tested operation -- but "tracemalloc" does seem to do that right.

[pp-mo]

A really simple tracemalloc solution may look like this (thanks to @jamesp )

class MemoryMonitor:
    def __init__(self):
        self.memory_mb = None

    @contextmanager
    def context(self):
        """Measure the time+memory used by a codeblock."""
        tracemalloc.start()
        yield
        _, peak_mem = tracemalloc.get_traced_memory()
        tracemalloc.stop()
        self.memory_mb = peak_mem * 1.0 / 1024 ** 2

memmon = MemoryMonitor()
with memmon.context():
  op()
print(memmon.memory_mb)

(though syntax usage might be improved?)

[pp-mo]

TODO : need to compare results with/without offline to assess. As @trexfeathers points out, you can't use ASV for this !

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[pp-mo]

Having used tracemalloc elsewhere, I'm increasingly convinced that it does offer a better solution. E.G. See #5753

[pp-mo]

Having used tracemalloc elsewhere, I'm increasingly convinced that it does offer a better solution. E.G. See #5753

See now also : #5796