On Sat, Feb 13, 2016 at 9:43 PM, <josef.p...@gmail.com> wrote: > > > On Sat, Feb 13, 2016 at 8:57 PM, Antony Lee <antony....@berkeley.edu> > wrote: > >> Compare (on Python3 -- for Python2, read "xrange" instead of "range"): >> >> In [2]: %timeit np.array(range(1000000), np.int64) >> 10 loops, best of 3: 156 ms per loop >> >> In [3]: %timeit np.arange(1000000, dtype=np.int64) >> 1000 loops, best of 3: 853 µs per loop >> >> >> Note that while iterating over a range is not very fast, it is still much >> better than the array creation: >> >> In [4]: from collections import deque >> >> In [5]: %timeit deque(range(1000000), 1) >> 10 loops, best of 3: 25.5 ms per loop >> >> >> On one hand, special cases are awful. On the other hand, the range >> builtin is probably important enough to deserve a special case to make this >> construction faster. Or not? I initially opened this as >> https://github.com/numpy/numpy/issues/7233 but it was suggested there >> that this should be discussed on the ML first. >> >> (The real issue which prompted this suggestion: I was building sparse >> matrices using scipy.sparse.csc_matrix with some indices specified using >> range, and that construction step turned out to take a significant portion >> of the time because of the calls to np.array). >> > > > IMO: I don't see a reason why this should be supported. There is np.arange > after all for this usecase, and from_iter. > range and the other guys are iterators, and in several cases we can use > larange = list(range(...)) as a short cut to get python list.for python 2/3 > compatibility. > > I think this might be partially a learning effect in the python 2 to 3 > transition. After using almost only python 3 for maybe a year, I don't > think it's difficult to remember the differences when writing code that is > py 2.7 and py 3.x compatible. > > > It's just **another** thing to watch out for if milliseconds matter in > your application. >
side question: Is there a simple way to distinguish a iterator or generator from an iterable data structure? Josef > > Josef > > >> >> Antony >> >> _______________________________________________ >> NumPy-Discussion mailing list >> NumPy-Discussion@scipy.org >> https://mail.scipy.org/mailman/listinfo/numpy-discussion >> >> >
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
