I am using python 2.6.2, so it may no longer be a problem.
I am open to using another data type, but the way I read the
documentation array.array only supports numeric types, not arbitrary
objects. I also tried playing around with numpy arrays, albeit for
only a short time, and it seems that alth
The answer it turns out is the garbage collector. When I disable the
garbage collector before the loop that loads the data into the list
and then enable it after the loop the program runs without issue.
This raises a question though, can the logic of the garbage collector
be changed so that it is
I have a large (10gb) data file for which I want to parse each line into
an object and then append this object to a list for sorting and further
processing. I have noticed however that as the length of the list
increases the rate at which objects are added to it decreases
dramatically. My fir
The example I have in mind is list like [2,2,2,2,2,2,1,3,3,3,3] where
you want to loop until you see not a 2 and then you want to loop until
you see not a 3. In this situation you cannot use a for loop as
follows:
foo_list_iter = iter([2,2,2,2,2,2,1,3,3,3,3])
for foo_item in foo_list_iter:
if
I have been programing in python for a while now and by in large love
it. One thing I don't love though is that as far as I know iterators
have no has_next type functionality. As a result if I want to iterate
until an element that might or might not be present is found I either
wrap the while
