Hi all,
Using numpy, I can create large 2-dimensional arrays quite easily.
>>> import numpy
>>> mylist = numpy.zeros((100000000,2), dtype=numpy.int32)
Unfortunately, my target audience may not have numpy so I'd prefer not to use
it.
Similarly, a list-of-tuples using standard python syntax.
>>> mylist = [(0,0) for i in xrange(100000000)
but this method uses way too much memory (>4GB for 100 million items, compared
to 1.5GB for numpy method).
Since I want to keep the two elements together during a sort, I *can't* use
array.array.
>>> mylist = [array.array('i',xrange(100000000)),
>>> array.array('i',xrange(100000000))]
If I knew the size in advance, I could use ctypes arrays.
>>> from ctypes import *
>>> class myStruct(Structure):
>>> _fields_ = [('x',c_int),('y',c_int)]
>>> mylist_type = myStruct * 100000000
>>> mylist = mylist_type()
but I don't know that size (and it can vary between 1 million-200 million), so
preallocating doesn't seem to be an option.
Is there a python standard library way of creating *efficient* 2-dimensional
lists/arrays, still allowing me to sort and append?
Thanks!
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