Question

Does anybody know how much memory is used by a numpy ndarray? (with let’s say 10,000,000 float elements).

Answer 1

The array is simply stored in one consecutive block in memory. Assuming by “float” you mean standard double precision floating point numbers, then the array will need 8 bytes per element.

In general, you can simply query the nbytes attribute for the total memory requirement of an array, and itemsize for the size of a single element in bytes:

>>> a = numpy.arange(1000.0)
>>> a.nbytes
8000
>>> a.itemsize
8

In addtion to the actual array data, there will also be a small data structure containing the meta-information on the array. Especially for large arrays, the size of this data structure is negligible.