Converting a numpy.datetime64 into DateTime?

I load some data using Python's xarray, which result to datetime-vectors, for example:
```

julia> x = w["time"].values
PyObject array(['2000-01-01T00:00:00.000000000', '2000-02-01T00:00:00.000000000',
'2000-03-01T00:00:00.000000000', '2000-04-01T00:00:00.000000000',
'2000-05-01T00:00:00.000000000', '2000-06-01T00:00:00.000000000',
'2000-07-01T00:00:00.000000000', '2000-08-01T00:00:00.000000000',
'2000-09-01T00:00:00.000000000', '2000-10-01T00:00:00.000000000',
'2000-11-01T00:00:00.000000000', '2000-12-01T00:00:00.000000000',
'2001-01-01T00:00:00.000000000', '2001-02-01T00:00:00.000000000',
'2001-03-01T00:00:00.000000000', '2001-04-01T00:00:00.000000000',
.....
'2019-07-01T00:00:00.000000000', '2019-08-01T00:00:00.000000000',
'2019-09-01T00:00:00.000000000', '2019-10-01T00:00:00.000000000',
'2019-11-01T00:00:00.000000000', '2019-12-01T00:00:00.000000000',
'2020-01-01T00:00:00.000000000', '2020-02-01T00:00:00.000000000',
'2020-03-01T00:00:00.000000000', '2020-04-01T00:00:00.000000000',
'2020-05-01T00:00:00.000000000', '2020-06-01T00:00:00.000000000',
'2020-07-01T00:00:00.000000000', '2020-08-01T00:00:00.000000000',
'2020-09-01T00:00:00.000000000'], dtype='datetime64[ns]')

julia> y = x[1]
PyObject numpy.datetime64('2000-01-01T00:00:00.000000000')
```

The data are not automatically put into Julia form, which happens if the type of `w["dimension"]` is Float64 or Integer. But that's okay, I don't mind converting myself. The problem is, that is not possible either:

```
julia> DateTime(y)
ERROR: MethodError: no method matching Int64(::PyObject)
Closest candidates are:
Int64(::Union{Bool, Int32, Int64, UInt32, UInt64, UInt8, Int128, Int16, Int8, UInt128, UInt16}) at boot.jl:708
Int64(::Ptr) at boot.jl:718
Int64(::Float32) at float.jl:706
...
Stacktrace:
[1] DateTime(::PyObject, ::Int64, ::Int64, ::Int64, ::Int64, ::Int64, ::Int64, ::Dates.AMPM) at D:\buildbot\worker\package_win64\build\usr\share\julia\stdlib\v1.5\Dates\src\types.jl:367 (repeats 2 times)
[2] top-level scope at none:1
```
I've tried other variants of date-related functions but it didn't work.

No repository files or tests are named. Reproduce the xarray/NumPy datetime64 example in Julia, then inspect PyCall's handling of NumPy scalar and array conversions. Done means the reported datetime64 value converts to a Julia DateTime, or the supported conversion behavior is clearly documented.

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