Revision history [back]
 | 1 | initial version |
Sage includes numpy, you can compare the different timings:
sage: %timeit [random.randint(0,10) for i in xrange(1000)]
100 loops, best of 3: 5.61 ms per loop
sage: %timeit [random.randrange(0,11) for i in xrange(1000)]
100 loops, best of 3: 4.82 ms per loop
sage: import numpy
sage: %timeit [numpy.random.random_integers(0,10) for i in xrange(1000)]
1000 loops, best of 3: 1.5 ms per loop
sage: %timeit numpy.random.random_integers(0,10,1000)
10000 loops, best of 3: 53.7 µs per loop
| | 2 | No.2 Revision |
Sage includes numpy, numpy, you can compare the different timings:
sage: %timeit [random.randint(0,10) for i in xrange(1000)]
100 loops, best of 3: 5.61 ms per loop
sage: %timeit [random.randrange(0,11) for i in xrange(1000)]
100 loops, best of 3: 4.82 ms per loop
sage: import numpy
sage: %timeit [numpy.random.random_integers(0,10) for i in xrange(1000)]
1000 loops, best of 3: 1.5 ms per loop
sage: %timeit numpy.random.random_integers(0,10,1000)
10000 loops, best of 3: 53.7 µs per loop
