I've replaced the previous two pull requests with a single pull request rolling up all the changes so far. The newest changes include finishing the generic unit and np.arange function support.
https://github.com/numpy/numpy/pull/87 Because of the nature of datetime and timedelta, arange has to be slightly different than with all the other types. In particular, for datetime the primary signature is np.arange(datetime, datetime, timedelta). I've implemented a simple extension which allows for another way to specify a date range, as np.arange(datetime, timedelta, timedelta). Here (start, delta) represents the datetime range [start, start+delta). Some examples: >>> np.arange('2011', '2020', dtype='M8[Y]') array(['2011', '2012', '2013', '2014', '2015', '2016', '2017', '2018', '2019'], dtype='datetime64[Y]') >>> np.arange('today', 10, 3, dtype='M8') array(['2011-06-09', '2011-06-12', '2011-06-15', '2011-06-18'], dtype='datetime64[D]') >>> a = np.datetime64('today', 'M') >>> np.arange(a, a+1, dtype='M8[D]') array(['2011-06-01', '2011-06-02', '2011-06-03', '2011-06-04', '2011-06-05', '2011-06-06', '2011-06-07', '2011-06-08', '2011-06-09', '2011-06-10', '2011-06-11', '2011-06-12', '2011-06-13', '2011-06-14', '2011-06-15', '2011-06-16', '2011-06-17', '2011-06-18', '2011-06-19', '2011-06-20', '2011-06-21', '2011-06-22', '2011-06-23', '2011-06-24', '2011-06-25', '2011-06-26', '2011-06-27', '2011-06-28', '2011-06-29', '2011-06-30'], dtype='datetime64[D]') Please build the branch available here, https://github.com/m-paradox/numpy try it out, and then discuss! -Mark
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