Adding to @HYRY's answer in1d seems to be fastest for numpy. This is using numpy 1.8 and python 2.7.6.
In this test in1d was fastest, however 10 in a look cleaner:
a = arange(0,99999,3)
%timeit 10 in a
%timeit in1d(a, 10)
10000 loops, best of 3: 150 µs per loop
10000 loops, best of 3: 61.9 µs per loop
Constructing a set is slower than calling in1d, but checking if the value exists is a bit faster:
s = set(range(0, 99999, 3))
%timeit 10 in s
10000000 loops, best of 3: 47 ns per loop