First a trap for new players, then a question to developers Code accelerated by numpy can be slowed down by a large factor is you neglect to import numpy.sum .
from timeit import Timer frag = 'x=sum(linspace(0,1,1000))' Timer(frag ,setup='from numpy import linspace').timeit(1000) # 0.6 sec Timer(frag, setup='from numpy import sum, linspace').timeit(1000) # difference is I import numpy.sum # 0.04 sec 15x faster! This is obvious of course - but it is very easy to forget to import numpy.sum and pay the price in execution. Question: Can I replace the builtin sum function globally for test purposes so that my large set of codes uses the replacement? The replacement would simply issue warnings.warn() if it detected an ndarray argument, then call the original sum I could then find the offending code and use the appropriate import to get numpy.sum -- http://mail.python.org/mailman/listinfo/python-list
