if you're doing a lot of this kind of thing you should consider using numpy.
In [56]: import random, numpy
In [57]: lst = numpy.array([random.uniform(0, 5) for _ in range(1000)]) # example list
In [58]: a, b = 1, 3
In [59]: numpy.flatnonzero((lst > a) & (lst < b))[:10]
Out[59]: array([ 0, 12, 13, 15, 18, 19, 23, 24, 26, 29])
In response to Seanny123's question, I used this timing code:
import numpy, timeit, random
a, b = 1, 3
lst = numpy.array([random.uniform(0, 5) for _ in range(1000)])
def numpy_way():
numpy.flatnonzero((lst > 1) & (lst < 3))[:10]
def list_comprehension():
[e for e in lst if 1 < e < 3][:10]
print timeit.timeit(numpy_way)
print timeit.timeit(list_comprehension)
The numpy version is over 60 times faster.