Python is an inherently memory heavy programming language. There are some ways you can get around this. __slots__ is one way. Another, more extreme approach is to use numpy to store your data. You can use numpy to create a structured array or record -- a complex data type that uses minimal memory, but suffers a substantial loss of functionality compared to a normal python class. That is, you are working with the numpy array class, rather than your own class -- you cannot define your own methods on your array.
import numpy as np
# data type for a record with three 32-bit ints called x, y and z
dtype = [(name, np.int32) for name in 'xyz']
arr = np.zeros(1000, dtype=dtype)
# access member of x of a record
arr[0]['x'] = 1 # name based access
# or
assert arr[0][0] == 1 # index based access
# accessing all x members of records in array
assert arr['x'].sum() == 1
# size of array used to store elements in memory
assert arr.nbytes == 12000 # 1000 elements * 3 members * 4 bytes per int
See more here.