Merge branch 'dalleyg-dtype' of https://github.com/dalleyg/cython into master

Cython/Includes/numpy/__init__.pxd

@@ -52,6 +52,8 @@ cdef extern from "numpy/arrayobject.h":
         NPY_STRING
         NPY_UNICODE
         NPY_VOID
+        NPY_DATETIME
+        NPY_TIMEDELTA
         NPY_NTYPES
         NPY_NOTYPE
 
@@ -152,11 +154,22 @@ cdef extern from "numpy/arrayobject.h":
 
     ctypedef void (*PyArray_VectorUnaryFunc)(void *, void *, npy_intp, void *,  void *)
 
+    ctypedef struct PyArray_ArrayDescr:
+        # shape is a tuple, but Cython doesn't support "tuple shape"
+        # inside a non-PyObject declaration, so we have to declare it
+        # as just a PyObject*.
+        PyObject* shape
+
     ctypedef class numpy.dtype [object PyArray_Descr]:
         # Use PyDataType_* macros when possible, however there are no macros
         # for accessing some of the fields, so some are defined.
         cdef char kind
         cdef char type
+        # Numpy sometimes mutates this without warning (e.g. it'll
+        # sometimes change "|" to "<" in shared dtype objects on
+        # little-endian machines). If this matters to you, use
+        # PyArray_IsNativeByteOrder(dtype.byteorder) instead of
+        # directly accessing this field.
         cdef char byteorder
         cdef char flags
         cdef int type_num
@@ -164,6 +177,10 @@ cdef extern from "numpy/arrayobject.h":
         cdef int alignment
         cdef dict fields
         cdef tuple names
+        # Use PyDataType_HASSUBARRAY to test whether this field is
+        # valid (the pointer can be NULL). Most users should access
+        # this field via the inline helper method PyDataType_SHAPE.
+        cdef PyArray_ArrayDescr* subarray
 
     ctypedef extern class numpy.flatiter [object PyArrayIterObject]:
         # Use through macros
@@ -428,6 +445,7 @@ cdef extern from "numpy/arrayobject.h":
     bint PyDataType_ISEXTENDED(dtype)
     bint PyDataType_ISOBJECT(dtype)
     bint PyDataType_HASFIELDS(dtype)
+    bint PyDataType_HASSUBARRAY(dtype)
 
     bint PyArray_ISBOOL(ndarray)
     bint PyArray_ISUNSIGNED(ndarray)
@@ -782,6 +800,12 @@ cdef inline object PyArray_MultiIterNew4(a, b, c, d):
 cdef inline object PyArray_MultiIterNew5(a, b, c, d, e):
     return PyArray_MultiIterNew(5, <void*>a, <void*>b, <void*>c, <void*> d, <void*> e)
 
+cdef inline tuple PyDataType_SHAPE(dtype d):
+    if PyDataType_HASSUBARRAY(d):
+        return <tuple>d.subarray.shape
+    else:
+        return ()
+
 cdef inline char* _util_dtypestring(dtype descr, char* f, char* end, int* offset) except NULL:
     # Recursive utility function used in __getbuffer__ to get format
     # string. The new location in the format string is returned.

tests/run/numpy_subarray.pyx

+# tag: numpy
+
+cimport numpy as np
+cimport cython
+
+import numpy as py_numpy
+
+__doc__ = u"""
+
+    >>> test_record_subarray()
+    
+"""
+
+def test_record_subarray():
+    cdef np.ndarray x = py_numpy.zeros((2,2),
+                                       dtype=[('a', py_numpy.int32),
+                                              ('b', py_numpy.float64, (3, 3))])
+    cdef np.dtype descr   = x.dtype
+    cdef np.dtype a_descr = descr.fields['a'][0]
+    cdef np.dtype b_descr = descr.fields['b'][0]
+
+    # Make sure the dtype looks like we expect
+    assert descr.fields == {'a': (py_numpy.dtype('int32'), 0),
+                            'b': (py_numpy.dtype(('<f8', (3, 3))), 4)}
+
+    # Make sure that HASSUBARRAY is working
+    assert not np.PyDataType_HASSUBARRAY(descr)
+    assert not np.PyDataType_HASSUBARRAY(a_descr)
+    assert np.PyDataType_HASSUBARRAY(b_descr)
+
+    # Make sure the direct field access works
+    assert <tuple>b_descr.subarray.shape == (3, 3)
+
+    # Make sure the safe high-level helper function works
+    assert np.PyDataType_SHAPE(descr) == ()
+    assert np.PyDataType_SHAPE(a_descr) == ()
+    assert np.PyDataType_SHAPE(b_descr) == (3, 3)