Using large index in python (numpy or lists)
I can propose to use such notation [5*10**5:1*10**6] but it's not so clear as in case of 5e5 and 1e6. And even worse in case of 3.5e6 = 35*10**5
I frequently need to enter large integers for indexing and creating numpy arrays, such as 3500000 or 250000.  Normally I'd enter these using scientific notation, 3.5e6 or .25e6 or such.  This is quicker, and much less likely to have errors.
Unfortunately, python expects integer datatypes for indexing.  The obvious solution is to convert datatypes.  So [5e5:1e6] becomes [int(5e5):int(1e6)], but this decreases readability and is somewhat longer to type. Not to mention, it's easy to forget what datatype an index is until an indexing operation fails on a list or numpy.ndarray.
Is there a way to have numpy or python interpret large floats as integers, or is there an easy way to create large integers in python?