Motivation behind numpy's datetime64 type?

Question

I noticed recently that numpy includes a datetime64 data type beginning in numpy 1.7:

http://www.compsci.wm.edu/SciClone/documentation/software/math/NumPy/html1.7/reference/arrays.datetime.html

I am wondering what is the motivation behind including this as a separate type within the numpy package rather than using the builtin datetime.datetime provided by Python?

Some of the reasons I am interested in understanding this better include:

1. I want to know when it is appropriate to use datetime.datetime vs when to use numpy.datetime64
2. Since numpy includes no date type analogous to datetime.date, should I use numpy.datetime64 for dates when I need to interact with numpy.datetime64 objects? Or should I intermingle datetime.date and numpy.datetime64 in my code?

Answer 1

The reason is identical as to why there is a np.int and an np.float. These numpy types get stored by value in an array, rather than by boxed reference, as generic python object are. The latter takes far more memory, allocation overhead, and is much less cache friendly to traverse.

Answer 2

I avoid intermingling datetime64 and python's inbuilt datetime objects. The reason for this is that the code that you write to work with a datetime.datetime will not work with a numpy.datetime64 scalar. For example any of the methods or properties of a datetime.datetime would not be availble on a numpy.datetime64 object.

In order to avoid the intermingling, what I tend to do is when I am dealing with scalars, I use python's datetime.datetime or datetime.date. When I am dealing with numpy array's, I use datetime64. This means that when I am extracting or iterating over single values from a numpy datetime64 array, I convert them into a datetime object first before I let propagate into other parts of the codebase.

Also you can read about different units of datetime64, that will allow you use a datetime64 as a datetime.date or datetime.datetime here:

http://docs.scipy.org/doc/numpy-dev/reference/arrays.datetime.html#arrays-dtypes-dateunits