Merge branch 'struct_cleanup'

16 files changed, 1011 insertions, 216 deletions

diff --git a/doc/source/reference/arrays.dtypes.rst b/doc/source/reference/arrays.dtypes.rst
index c89a282f4..2fc1add99 100644
--- a/doc/source/reference/arrays.dtypes.rst
+++ b/doc/source/reference/arrays.dtypes.rst
@@ -23,7 +23,7 @@ following aspects of the data:
    2. what is the data-type of each :term:`field`, and
    3. which part of the memory block each field takes.
 
-5. If the data is a sub-array, what is its shape and data type.
+5. If the data type is a sub-array, what is its shape and data type.
 
 .. index::
    pair: dtype; scalar
@@ -42,24 +42,28 @@ needed in Numpy.
    pair: dtype; field
    pair: dtype; record
 
-Record data types are formed by creating a data type whose
+Struct data types are formed by creating a data type whose
 :term:`fields` contain other data types. Each field has a name by
 which it can be :ref:`accessed <arrays.indexing.rec>`. The parent data
 type should be of sufficient size to contain all its fields; the
-parent can for example be based on the :class:`void` type which allows
-an arbitrary item size. Record data types may also contain other record
-types and fixed-size sub-array data types in their fields.
+parent is nearly always based on the :class:`void` type which allows
+an arbitrary item size. Struct data types may also contain nested struct
+sub-array data types in their fields.
 
 .. index::
    pair: dtype; sub-array
 
 Finally, a data type can describe items that are themselves arrays of
 items of another data type. These sub-arrays must, however, be of a
-fixed size. If an array is created using a data-type describing a
-sub-array, the dimensions of the sub-array are appended to the shape
+fixed size.
+
+If an array is created using a data-type describing a sub-array,
+the dimensions of the sub-array are appended to the shape
 of the array when the array is created. Sub-arrays in a field of a
 record behave differently, see :ref:`arrays.indexing.rec`.
 
+Sub-arrays always have a C-contiguous memory layout.
+
 .. admonition:: Example
 
    A simple data type containing a 32-bit big-endian integer:
@@ -226,7 +230,7 @@ Array-protocol type strings (see :ref:`arrays.interface`)
    ``'c'``            complex-floating point
    ``'S'``, ``'a'``   string
    ``'U'``            unicode
-   ``'V'``            anything (:class:`void`)
+   ``'V'``            raw data (:class:`void`)
    ================   ========================
 
    .. admonition:: Example
@@ -243,7 +247,7 @@ String with comma-separated fields
 
    A basic format in this context is an optional shape specifier
    followed by an array-protocol type string. Parenthesis are required
-   on the shape if it is greater than 1-d. NumPy allows a modification
+   on the shape if it has more than one dimension. NumPy allows a modification
    on the format in that any string that can uniquely identify the
    type can be used to specify the data-type in a field.
    The generated data-type fields are named ``'f0'``, ``'f1'``, ...,
@@ -283,8 +287,8 @@ Type strings
 ``(flexible_dtype, itemsize)``
 
     The first argument must be an object that is converted to a
-    flexible data-type object (one whose element size is 0), the
-    second argument is an integer providing the desired itemsize.
+    zero-sized flexible data-type object, the second argument is
+    an integer providing the desired itemsize.
 
     .. admonition:: Example
 
@@ -309,30 +313,6 @@ Type strings
        >>> dt = np.dtype(('S10', 1))                 # 10-character string
        >>> dt = np.dtype(('i4, (2,3)f8, f4', (2,3))) # 2 x 3 record sub-array
 
-``(base_dtype, new_dtype)``
-
-    Both arguments must be convertible to data-type objects in this
-    case. The *base_dtype* is the data-type object that the new
-    data-type builds on. This is how you could assign named fields to
-    any built-in data-type object.
-
-    .. admonition:: Example
-
-       32-bit integer, whose first two bytes are interpreted as an integer
-       via field ``real``, and the following two bytes via field ``imag``.
-
-       >>> dt = np.dtype((np.int32,{'real':(np.int16, 0),'imag':(np.int16, 2)})
-
-       32-bit integer, which is interpreted as consisting of a sub-array
-       of shape ``(4,)`` containing 8-bit integers:
-
-       >>> dt = np.dtype((np.int32, (np.int8, 4)))
-
-       32-bit integer, containing fields ``r``, ``g``, ``b``, ``a`` that
-       interpret the 4 bytes in the integer as four unsigned integers:
-
-       >>> dt = np.dtype(('i4', [('r','u1'),('g','u1'),('b','u1'),('a','u1')]))
-
 .. index::
    triple: dtype; construction; from list
 
@@ -376,15 +356,15 @@ Type strings
 .. index::
    triple: dtype; construction; from dict
 
-``{'names': ..., 'formats': ..., 'offsets': ..., 'titles': ...}``
+``{'names': ..., 'formats': ..., 'offsets': ..., 'titles': ..., 'itemsize': ...}``
 
-    This style has two required and two optional keys.  The *names*
+    This style has two required and three optional keys.  The *names*
     and *formats* keys are required. Their respective values are
     equal-length lists with the field names and the field formats.
     The field names must be strings and the field formats can be any
     object accepted by :class:`dtype` constructor.
 
-    The optional keys in the dictionary are *offsets* and *titles* and
+    When the optional keys *offsets* and *titles* are provided,
     their values must each be lists of the same length as the *names*
     and *formats* lists. The *offsets* value is a list of byte offsets
     (integers) for each field, while the *titles* value is a list of
@@ -395,6 +375,11 @@ Type strings
     field tuple which will contain the title as an additional tuple
     member.
 
+    The *itemsize* key allows the total size of the dtype to be
+    set, and must be an integer large enough so all the fields
+    are within the dtype. If the dtype being constructed is aligned,
+    the *itemsize* must also be divisible by the struct alignment.
+
     .. admonition:: Example
 
        Data type with fields ``r``, ``g``, ``b``, ``a``, each being
@@ -414,6 +399,11 @@ Type strings
 
 ``{'field1': ..., 'field2': ..., ...}``
 
+    This usage is discouraged, because it is ambiguous with the
+    other dict-based construction method. If you have a field
+    called 'names' and a field called 'formats' there will be
+    a conflict.
+
     This style allows passing in the :attr:`fields <dtype.fields>`
     attribute of a data-type object.
 
@@ -429,6 +419,34 @@ Type strings
        >>> dt = np.dtype({'col1': ('S10', 0), 'col2': (float32, 10),
            'col3': (int, 14)})
 
+``(base_dtype, new_dtype)``
+
+    This usage is discouraged. In NumPy 1.7 and later, it is possible
+    to specify struct dtypes with overlapping fields, functioning like
+    the 'union' type in C. The union mechanism is preferred.
+
+    Both arguments must be convertible to data-type objects in this
+    case. The *base_dtype* is the data-type object that the new
+    data-type builds on. This is how you could assign named fields to
+    any built-in data-type object.
+
+    .. admonition:: Example
+
+       32-bit integer, whose first two bytes are interpreted as an integer
+       via field ``real``, and the following two bytes via field ``imag``.
+
+       >>> dt = np.dtype((np.int32,{'real':(np.int16, 0),'imag':(np.int16, 2)})
+
+       32-bit integer, which is interpreted as consisting of a sub-array
+       of shape ``(4,)`` containing 8-bit integers:
+
+       >>> dt = np.dtype((np.int32, (np.int8, 4)))
+
+       32-bit integer, containing fields ``r``, ``g``, ``b``, ``a`` that
+       interpret the 4 bytes in the integer as four unsigned integers:
+
+       >>> dt = np.dtype(('i4', [('r','u1'),('g','u1'),('b','u1'),('a','u1')]))
+
 
 :class:`dtype`
 ==============
diff --git a/numpy/add_newdocs.py b/numpy/add_newdocs.py
index 58594b15a..760d258f2 100644
--- a/numpy/add_newdocs.py
+++ b/numpy/add_newdocs.py
@@ -5563,7 +5563,8 @@ add_newdoc('numpy.core.multiarray', 'dtype',
     align : bool, optional
         Add padding to the fields to match what a C compiler would output
         for a similar C-struct. Can be ``True`` only if `obj` is a dictionary
-        or a comma-separated string.
+        or a comma-separated string. If a struct dtype is being created,
+        this also sets a sticky alignment flag ``isalignedstruct``.
     copy : bool, optional
         Make a new copy of the data-type object. If ``False``, the result
         may just be a reference to a built-in data-type object.
@@ -5787,6 +5788,14 @@ add_newdoc('numpy.core.multiarray', 'dtype', ('isnative',
 
     """))
 
+add_newdoc('numpy.core.multiarray', 'dtype', ('isalignedstruct',
+    """
+    Boolean indicating whether the dtype is a struct which maintains
+    field alignment. This flag is sticky, so when combining multiple
+    structs together, it is preserved and produces new dtypes which
+    are also aligned.
+    """))
+
 add_newdoc('numpy.core.multiarray', 'dtype', ('itemsize',
     """
     The element size of this data-type object.
diff --git a/numpy/core/_internal.py b/numpy/core/_internal.py
index a5b6d117a..99e64d475 100644
--- a/numpy/core/_internal.py
+++ b/numpy/core/_internal.py
@@ -12,7 +12,7 @@ if (sys.byteorder == 'little'):
 else:
     _nbo = asbytes('>')
 
-def _makenames_list(adict):
+def _makenames_list(adict, align):
     from multiarray import dtype
     allfields = []
     fnames = adict.keys()
@@ -26,7 +26,7 @@ def _makenames_list(adict):
         num = int(obj[1])
         if (num < 0):
             raise ValueError("invalid offset.")
-        format = dtype(obj[0])
+        format = dtype(obj[0], align=align)
         if (format.itemsize == 0):
             raise ValueError("all itemsizes must be fixed.")
         if (n > 2):
@@ -53,7 +53,7 @@ def _usefields(adict, align):
     except KeyError:
         names = None
     if names is None:
-        names, formats, offsets, titles = _makenames_list(adict)
+        names, formats, offsets, titles = _makenames_list(adict, align)
     else:
         formats = []
         offsets = []
diff --git a/numpy/core/include/numpy/ndarraytypes.h b/numpy/core/include/numpy/ndarraytypes.h
index 562665821..5ffb97053 100644
--- a/numpy/core/include/numpy/ndarraytypes.h
+++ b/numpy/core/include/numpy/ndarraytypes.h
@@ -502,7 +502,8 @@ typedef struct {
 #define NPY_USE_GETITEM     0x20
 /* Use f.setitem when setting creating 0-d array from this data-type.*/
 #define NPY_USE_SETITEM     0x40
-/* define NPY_IS_COMPLEX */
+/* A sticky flag specifically for structured arrays */
+#define NPY_ALIGNED_STRUCT  0x80
 
 /*
  *These are inherited for global data-type if any data-types in the
@@ -1344,6 +1345,7 @@ PyArrayNeighborhoodIter_Next2D(PyArrayNeighborhoodIterObject* iter);
 #define PyDataType_ISEXTENDED(obj) PyTypeNum_ISEXTENDED(((PyArray_Descr*)(obj))->type_num)
 #define PyDataType_ISOBJECT(obj) PyTypeNum_ISOBJECT(((PyArray_Descr*)(obj))->type_num)
 #define PyDataType_HASFIELDS(obj) (((PyArray_Descr *)(obj))->names != NULL)
+#define PyDataType_HASSUBARRAY(dtype) ((dtype)->subarray != NULL)
 
 #define PyArray_ISBOOL(obj) PyTypeNum_ISBOOL(PyArray_TYPE(obj))
 #define PyArray_ISUNSIGNED(obj) PyTypeNum_ISUNSIGNED(PyArray_TYPE(obj))
diff --git a/numpy/core/src/multiarray/arraytypes.c.src b/numpy/core/src/multiarray/arraytypes.c.src
index 6ad9c4848..a3df9c203 100644
--- a/numpy/core/src/multiarray/arraytypes.c.src
+++ b/numpy/core/src/multiarray/arraytypes.c.src
@@ -544,7 +544,7 @@ VOID_getitem(char *ip, PyArrayObject *ap)
     int itemsize;
 
     descr = ap->descr;
-    if (descr->names != NULL) {
+    if (PyDataType_HASFIELDS(descr)) {
         PyObject *key;
         PyObject *names;
         int i, n;
@@ -3304,10 +3304,14 @@ static PyArray_ArrFuncs _Py@NAME@_ArrFuncs = {
     (PyArray_FillWithScalarFunc*)NULL,
 #if @sort@
     {
-        quicksort_@suff@, heapsort_@suff@, mergesort_@suff@
+        (PyArray_SortFunc *)quicksort_@suff@,
+        (PyArray_SortFunc *)heapsort_@suff@,
+        (PyArray_SortFunc *)mergesort_@suff@
     },
     {
-        aquicksort_@suff@, aheapsort_@suff@, amergesort_@suff@
+        (PyArray_ArgSortFunc *)aquicksort_@suff@,
+        (PyArray_ArgSortFunc *)aheapsort_@suff@,
+        (PyArray_ArgSortFunc *)amergesort_@suff@
     },
 #else
     {
@@ -3408,10 +3412,14 @@ static PyArray_ArrFuncs _Py@NAME@_ArrFuncs = {
     (PyArray_FillWithScalarFunc*)@from@_fillwithscalar,
 #if @sort@
     {
-        quicksort_@suff@, heapsort_@suff@, mergesort_@suff@
+        (PyArray_SortFunc *)quicksort_@suff@,
+        (PyArray_SortFunc *)heapsort_@suff@,
+        (PyArray_SortFunc *)mergesort_@suff@
     },
     {
-        aquicksort_@suff@, aheapsort_@suff@, amergesort_@suff@
+        (PyArray_ArgSortFunc *)aquicksort_@suff@,
+        (PyArray_ArgSortFunc *)aheapsort_@suff@,
+        (PyArray_ArgSortFunc *)amergesort_@suff@
     },
 #else
     {
diff --git a/numpy/core/src/multiarray/descriptor.c b/numpy/core/src/multiarray/descriptor.c
index 2e793fe1f..6f4ae124f 100644
--- a/numpy/core/src/multiarray/descriptor.c
+++ b/numpy/core/src/multiarray/descriptor.c
@@ -15,9 +15,19 @@
 
 #include "_datetime.h"
 #include "common.h"
+#include "descriptor.h"
 
-#define _chk_byteorder(arg) (arg == '>' || arg == '<' ||        \
-                             arg == '|' || arg == '=')
+/*
+ * offset:    A starting offset.
+ * alignment: A power-of-two alignment.
+ *
+ * This macro returns the smallest value >= 'offset'
+ * that is divisible by 'alignment'. Because 'alignment'
+ * is a power of two and integers are twos-complement,
+ * it is possible to use some simple bit-fiddling to do this.
+ */
+#define NPY_NEXT_ALIGNED_OFFSET(offset, alignment) \
+                (((offset) + (alignment) - 1) & (-(alignment)))
 
 static PyObject *typeDict = NULL;   /* Must be explicitly loaded */
 
@@ -102,6 +112,9 @@ array_set_typeDict(PyObject *NPY_UNUSED(ignored), PyObject *args)
     return Py_None;
 }
 
+#define _chk_byteorder(arg) (arg == '>' || arg == '<' ||        \
+                             arg == '|' || arg == '=')
+
 static int
 _check_for_commastring(char *type, Py_ssize_t len)
 {
@@ -135,6 +148,8 @@ _check_for_commastring(char *type, Py_ssize_t len)
     return 0;
 }
 
+#undef _chk_byteorder
+
 static int
 is_datetime_typestr(char *type, Py_ssize_t len)
 {
@@ -159,10 +174,6 @@ is_datetime_typestr(char *type, Py_ssize_t len)
     return 0;
 }
 
-
-
-#undef _chk_byteorder
-
 static PyArray_Descr *
 _convert_from_tuple(PyObject *obj)
 {
@@ -362,14 +373,25 @@ _convert_from_array_descr(PyObject *obj, int align)
         /* Process rest */
 
         if (PyTuple_GET_SIZE(item) == 2) {
-            ret = PyArray_DescrConverter(PyTuple_GET_ITEM(item, 1), &conv);
+            if (align) {
+                ret = PyArray_DescrAlignConverter(PyTuple_GET_ITEM(item, 1),
+                                                        &conv);
+            }
+            else {
+                ret = PyArray_DescrConverter(PyTuple_GET_ITEM(item, 1), &conv);
+            }
             if (ret == PY_FAIL) {
                 PyObject_Print(PyTuple_GET_ITEM(item, 1), stderr, 0);
             }
         }
         else if (PyTuple_GET_SIZE(item) == 3) {
             newobj = PyTuple_GetSlice(item, 1, 3);
-            ret = PyArray_DescrConverter(newobj, &conv);
+            if (align) {
+                ret = PyArray_DescrAlignConverter(newobj, &conv);
+            }
+            else {
+                ret = PyArray_DescrConverter(newobj, &conv);
+            }
             Py_DECREF(newobj);
         }
         else {
@@ -379,15 +401,13 @@ _convert_from_array_descr(PyObject *obj, int align)
             goto fail;
         }
         if ((PyDict_GetItem(fields, name) != NULL)
-#if defined(NPY_PY3K)
              || (title
+#if defined(NPY_PY3K)
                  && PyUString_Check(title)
-                 && (PyDict_GetItem(fields, title) != NULL))) {
 #else
-             || (title
                  && (PyUString_Check(title) || PyUnicode_Check(title))
-                 && (PyDict_GetItem(fields, title) != NULL))) {
 #endif
+                 && (PyDict_GetItem(fields, title) != NULL))) {
             PyErr_SetString(PyExc_ValueError,
                     "two fields with the same name");
             goto fail;
@@ -400,7 +420,7 @@ _convert_from_array_descr(PyObject *obj, int align)
 
             _align = conv->alignment;
             if (_align > 1) {
-                totalsize = ((totalsize + _align - 1)/_align)*_align;
+                totalsize = NPY_NEXT_ALIGNED_OFFSET(totalsize, _align);
             }
             maxalign = MAX(maxalign, _align);
         }
@@ -433,15 +453,25 @@ _convert_from_array_descr(PyObject *obj, int align)
         totalsize += conv->elsize;
         Py_DECREF(tup);
     }
+
+    if (maxalign > 1) {
+        totalsize = NPY_NEXT_ALIGNED_OFFSET(totalsize, maxalign);
+    }
+
     new = PyArray_DescrNewFromType(PyArray_VOID);
+    if (new == NULL) {
+        Py_XDECREF(fields);
+        Py_XDECREF(nameslist);
+        return NULL;
+    }
     new->fields = fields;
     new->names = nameslist;
     new->elsize = totalsize;
     new->flags=dtypeflags;
-    if (maxalign > 1) {
-        totalsize = ((totalsize + maxalign - 1)/maxalign)*maxalign;
-    }
+
+    /* Structured arrays get a sticky aligned bit */
     if (align) {
+        new->flags |= NPY_ALIGNED_STRUCT;
         new->alignment = maxalign;
     }
     return new;
@@ -494,7 +524,12 @@ _convert_from_list(PyObject *obj, int align)
     for (i = 0; i < n; i++) {
         tup = PyTuple_New(2);
         key = PyUString_FromFormat("f%d", i);
-        ret = PyArray_DescrConverter(PyList_GET_ITEM(obj, i), &conv);
+        if (align) {
+            ret = PyArray_DescrAlignConverter(PyList_GET_ITEM(obj, i), &conv);
+        }
+        else {
+            ret = PyArray_DescrConverter(PyList_GET_ITEM(obj, i), &conv);
+        }
         if (ret == PY_FAIL) {
             Py_DECREF(tup);
             Py_DECREF(key);
@@ -507,7 +542,7 @@ _convert_from_list(PyObject *obj, int align)
 
             _align = conv->alignment;
             if (_align > 1) {
-                totalsize = ((totalsize + _align - 1)/_align)*_align;
+                totalsize = NPY_NEXT_ALIGNED_OFFSET(totalsize, _align);
             }
             maxalign = MAX(maxalign, _align);
         }
@@ -520,11 +555,13 @@ _convert_from_list(PyObject *obj, int align)
     new = PyArray_DescrNewFromType(PyArray_VOID);
     new->fields = fields;
     new->names = nameslist;
-    new->flags=dtypeflags;
+    new->flags = dtypeflags;
     if (maxalign > 1) {
-        totalsize = ((totalsize+maxalign-1)/maxalign)*maxalign;
+        totalsize = NPY_NEXT_ALIGNED_OFFSET(totalsize, maxalign);
     }
+    /* Structured arrays get a sticky aligned bit */
     if (align) {
+        new->flags |= NPY_ALIGNED_STRUCT;
         new->alignment = maxalign;
     }
     new->elsize = totalsize;
@@ -570,8 +607,10 @@ _convert_from_commastring(PyObject *obj, int align)
         return NULL;
     }
     if (PyList_GET_SIZE(listobj) == 1) {
-        if (PyArray_DescrConverter(
-                    PyList_GET_ITEM(listobj, 0), &res) == NPY_FAIL) {
+        int retcode;
+        retcode = PyArray_DescrConverter(PyList_GET_ITEM(listobj, 0),
+                                                &res);
+        if (retcode == NPY_FAIL) {
             res = NULL;
         }
     }
@@ -641,7 +680,7 @@ _use_inherit(PyArray_Descr *type, PyObject *newobj, int *errflag)
         goto fail;
     }
     new->elsize = conv->elsize;
-    if (conv->names) {
+    if (PyDataType_HASFIELDS(conv)) {
         new->fields = conv->fields;
         Py_XINCREF(new->fields);
         new->names = conv->names;
@@ -658,6 +697,77 @@ _use_inherit(PyArray_Descr *type, PyObject *newobj, int *errflag)
 }
 
 /*
+ * Validates that any field of the structured array 'dtype' which has
+ * the NPY_ITEM_HASOBJECT flag set does not overlap with another field.
+ *
+ * This algorithm is worst case O(n^2). It could be done with a sort
+ * and sweep algorithm, but the structured dtype representation is
+ * rather ugly right now, so writing something better can wait until
+ * that representation is made sane.
+ *
+ * Returns 0 on success, -1 if an exception is raised.
+ */
+static int
+validate_object_field_overlap(PyArray_Descr *dtype)
+{
+    PyObject *names, *fields, *key, *tup, *title;
+    Py_ssize_t i, j, names_size;
+    PyArray_Descr *fld_dtype, *fld2_dtype;
+    int fld_offset, fld2_offset, align;
+
+    /* Get some properties from the dtype */
+    names = dtype->names;
+    names_size = PyTuple_GET_SIZE(names);
+    fields = dtype->fields;
+    align = PyDataType_FLAGCHK(dtype, NPY_ALIGNED_STRUCT);
+
+    for (i = 0; i < names_size; ++i) {
+        key = PyTuple_GET_ITEM(names, i);
+        if (key == NULL) {
+            return -1;
+        }
+        tup = PyDict_GetItem(fields, key);
+        if (tup == NULL) {
+            return -1;
+        }
+        if (!PyArg_ParseTuple(tup, "Oi|O", &fld_dtype, &fld_offset, &title)) {
+            return -1;
+        }
+
+        /* If this field has objects, check for overlaps */
+        if (PyDataType_REFCHK(fld_dtype)) {
+            for (j = 0; j < names_size; ++j) {
+                if (i != j) {
+                    key = PyTuple_GET_ITEM(names, j);
+                    if (key == NULL) {
+                        return -1;
+                    }
+                    tup = PyDict_GetItem(fields, key);
+                    if (tup == NULL) {
+                        return -1;
+                    }
+                    if (!PyArg_ParseTuple(tup, "Oi|O", &fld2_dtype,
+                                                &fld2_offset, &title)) {
+                        return -1;
+                    }
+                    /* Raise an exception if it overlaps */
+                    if (fld_offset < fld2_offset + fld2_dtype->elsize &&
+                                fld2_offset < fld_offset + fld_dtype->elsize) {
+                        PyErr_SetString(PyExc_TypeError,
+                                "Cannot create a NumPy dtype with overlapping "
+                                "object fields");
+                        return -1;
+                    }
+                }
+            }
+        }
+    }
+
+    /* It passed all the overlap tests */
+    return 0;
+}
+
+/*
  * a dictionary specifying a data-type
  * must have at least two and up to four
  * keys These must all be sequences of the same length.
@@ -715,12 +825,13 @@ _convert_from_dict(PyObject *obj, int align)
 {
     PyArray_Descr *new;
     PyObject *fields = NULL;
-    PyObject *names, *offsets, *descrs, *titles;
+    PyObject *names, *offsets, *descrs, *titles, *tmp;
     PyObject *metadata;
     int n, i;
-    int totalsize;
+    int totalsize, itemsize;
     int maxalign = 0;
     int dtypeflags = 0;
+    int has_out_of_order_fields = 0;
 
     fields = PyDict_New();
     if (fields == NULL) {
@@ -745,21 +856,21 @@ _convert_from_dict(PyObject *obj, int align)
 
     totalsize = 0;
     for (i = 0; i < n; i++) {
-        PyObject *tup, *descr, *index, *item, *name, *off;
+        PyObject *tup, *descr, *index, *title, *name, *off;
         int len, ret, _align = 1;
         PyArray_Descr *newdescr;
 
         /* Build item to insert (descr, offset, [title])*/
         len = 2;
-        item = NULL;
+        title = NULL;
         index = PyInt_FromLong(i);
         if (titles) {
-            item=PyObject_GetItem(titles, index);
-            if (item && item != Py_None) {
+            title=PyObject_GetItem(titles, index);
+            if (title && title != Py_None) {
                 len = 3;
             }
             else {
-                Py_XDECREF(item);
+                Py_XDECREF(title);
             }
             PyErr_Clear();
         }
@@ -768,7 +879,12 @@ _convert_from_dict(PyObject *obj, int align)
         if (!descr) {
             goto fail;
         }
-        ret = PyArray_DescrConverter(descr, &newdescr);
+        if (align) {
+            ret = PyArray_DescrAlignConverter(descr, &newdescr);
+        }
+        else {
+            ret = PyArray_DescrConverter(descr, &newdescr);
+        }
         Py_DECREF(descr);
         if (ret == PY_FAIL) {
             Py_DECREF(tup);
@@ -788,23 +904,32 @@ _convert_from_dict(PyObject *obj, int align)
             }
             offset = PyInt_AsLong(off);
             PyTuple_SET_ITEM(tup, 1, off);
+            /* Flag whether the fields are specified out of order */
             if (offset < totalsize) {
-                PyErr_SetString(PyExc_ValueError,
-                        "invalid offset (must be ordered)");
+                has_out_of_order_fields = 1;
+            }
+            /* If align=True, enforce field alignment */
+            if (align && offset % newdescr->alignment != 0) {
+                PyErr_Format(PyExc_ValueError,
+                        "offset %d for NumPy dtype with fields is "
+                        "not divisible by the field alignment %d "
+                        "with align=True",
+                        (int)offset, (int)newdescr->alignment);
                 ret = PY_FAIL;
             }
-            if (offset > totalsize) {
-                totalsize = offset;
+            else if (offset + newdescr->elsize > totalsize) {
+                totalsize = offset + newdescr->elsize;
             }
         }
         else {
             if (align && _align > 1) {
-                totalsize = ((totalsize + _align - 1)/_align)*_align;
+                totalsize = NPY_NEXT_ALIGNED_OFFSET(totalsize, _align);
             }
             PyTuple_SET_ITEM(tup, 1, PyInt_FromLong(totalsize));
+            totalsize += newdescr->elsize;
         }
         if (len == 3) {
-            PyTuple_SET_ITEM(tup, 2, item);
+            PyTuple_SET_ITEM(tup, 2, title);
         }
         name = PyObject_GetItem(names, index);
         if (!name) {
@@ -831,16 +956,16 @@ _convert_from_dict(PyObject *obj, int align)
         Py_DECREF(name);
         if (len == 3) {
 #if defined(NPY_PY3K)
-            if (PyUString_Check(item)) {
+            if (PyUString_Check(title)) {
 #else
-            if (PyUString_Check(item) || PyUnicode_Check(item)) {
+            if (PyUString_Check(title) || PyUnicode_Check(title)) {
 #endif
-                if (PyDict_GetItem(fields, item) != NULL) {
+                if (PyDict_GetItem(fields, title) != NULL) {
                     PyErr_SetString(PyExc_ValueError,
                             "title already used as a name or title.");
                     ret=PY_FAIL;
                 }
-                PyDict_SetItem(fields, item, tup);
+                PyDict_SetItem(fields, title, tup);
             }
         }
         Py_DECREF(tup);
@@ -848,15 +973,14 @@ _convert_from_dict(PyObject *obj, int align)
             goto fail;
         }
         dtypeflags |= (newdescr->flags & NPY_FROM_FIELDS);
-        totalsize += newdescr->elsize;
     }
 
-    new = PyArray_DescrNewFromType(PyArray_VOID);
+    new = PyArray_DescrNewFromType(NPY_VOID);
     if (new == NULL) {
         goto fail;
     }
     if (maxalign > 1) {
-        totalsize = ((totalsize + maxalign - 1)/maxalign)*maxalign;
+        totalsize = NPY_NEXT_ALIGNED_OFFSET(totalsize, maxalign);
     }
     if (align) {
         new->alignment = maxalign;
@@ -872,6 +996,53 @@ _convert_from_dict(PyObject *obj, int align)
     new->fields = fields;
     new->flags = dtypeflags;
 
+    /*
+     * If the fields weren't in order, and there was an OBJECT type,
+     * need to verify that no OBJECT types overlap with something else.
+     */
+    if (has_out_of_order_fields && PyDataType_REFCHK(new)) {
+        if (validate_object_field_overlap(new) < 0) {
+            Py_DECREF(new);
+            return NULL;
+        }
+    }
+
+    /* Structured arrays get a sticky aligned bit */
+    if (align) {
+        new->flags |= NPY_ALIGNED_STRUCT;
+    }
+
+    /* Override the itemsize if provided */
+    tmp = PyDict_GetItemString(obj, "itemsize");
+    if (tmp != NULL) {
+        itemsize = (int)PyInt_AsLong(tmp);
+        if (itemsize == -1 && PyErr_Occurred()) {
+            Py_DECREF(new);
+            return NULL;
+        }
+        /* Make sure the itemsize isn't made too small */
+        if (itemsize < new->elsize) {
+            PyErr_Format(PyExc_ValueError,
+                    "NumPy dtype descriptor requires %d bytes, "
+                    "cannot override to smaller itemsize of %d",
+                    (int)new->elsize, (int)itemsize);
+            Py_DECREF(new);
+            return NULL;
+        }
+        /* If align is set, make sure the alignment divides into the size */
+        if (align && itemsize % new->alignment != 0) {
+            PyErr_Format(PyExc_ValueError,
+                    "NumPy dtype descriptor requires alignment of %d bytes, "
+                    "which is not divisible into the specified itemsize %d",
+                    (int)new->alignment, (int)itemsize);
+            Py_DECREF(new);
+            return NULL;
+        }
+        /* Set the itemsize */
+        new->elsize = itemsize;
+    }
+
+    /* Add the metadata if provided */
     metadata = PyDict_GetItemString(obj, "metadata");
 
     if (new->metadata == NULL) {
@@ -1326,7 +1497,7 @@ static PyMemberDef arraydescr_members[] = {
 static PyObject *
 arraydescr_subdescr_get(PyArray_Descr *self)
 {
-    if (self->subarray == NULL) {
+    if (!PyDataType_HASSUBARRAY(self)) {
         Py_INCREF(Py_None);
         return Py_None;
     }
@@ -1422,7 +1593,7 @@ arraydescr_typename_get(PyArray_Descr *self)
 static PyObject *
 arraydescr_base_get(PyArray_Descr *self)
 {
-    if (self->subarray == NULL) {
+    if (!PyDataType_HASSUBARRAY(self)) {
         Py_INCREF(self);
         return (PyObject *)self;
     }
@@ -1433,7 +1604,7 @@ arraydescr_base_get(PyArray_Descr *self)
 static PyObject *
 arraydescr_shape_get(PyArray_Descr *self)
 {
-    if (self->subarray == NULL) {
+    if (!PyDataType_HASSUBARRAY(self)) {
         return PyTuple_New(0);
     }
     /*TODO
@@ -1453,7 +1624,7 @@ arraydescr_protocol_descr_get(PyArray_Descr *self)
     PyObject *dobj, *res;
     PyObject *_numpy_internal;
 
-    if (self->names == NULL) {
+    if (!PyDataType_HASFIELDS(self)) {
         /* get default */
         dobj = PyTuple_New(2);
         if (dobj == NULL) {
@@ -1501,7 +1672,7 @@ arraydescr_isbuiltin_get(PyArray_Descr *self)
 static int
 _arraydescr_isnative(PyArray_Descr *self)
 {
-    if (self->names == NULL) {
+    if (!PyDataType_HASFIELDS(self)) {
         return PyArray_ISNBO(self->byteorder);
     }
     else {
@@ -1546,9 +1717,18 @@ arraydescr_isnative_get(PyArray_Descr *self)
 }
 
 static PyObject *
+arraydescr_isalignedstruct_get(PyArray_Descr *self)
+{
+    PyObject *ret;
+    ret = (self->flags&NPY_ALIGNED_STRUCT) ? Py_True : Py_False;
+    Py_INCREF(ret);
+    return ret;
+}
+
+static PyObject *
 arraydescr_fields_get(PyArray_Descr *self)
 {
-    if (self->names == NULL) {
+    if (!PyDataType_HASFIELDS(self)) {
         Py_INCREF(Py_None);
         return Py_None;
     }
@@ -1579,7 +1759,7 @@ arraydescr_hasobject_get(PyArray_Descr *self)
 static PyObject *
 arraydescr_names_get(PyArray_Descr *self)
 {
-    if (self->names == NULL) {
+    if (!PyDataType_HASFIELDS(self)) {
         Py_INCREF(Py_None);
         return Py_None;
     }
@@ -1594,12 +1774,18 @@ arraydescr_names_set(PyArray_Descr *self, PyObject *val)
     int i;
     PyObject *new_names;
     PyObject *new_fields;
-    if (self->names == NULL) {
+
+    if (!PyDataType_HASFIELDS(self)) {
         PyErr_SetString(PyExc_ValueError,
                 "there are no fields defined");
         return -1;
     }
 
+    if (DEPRECATE("Setting NumPy dtype names is deprecated, the dtype "
+                    "will become immutable in a future version") < 0) {
+        return -1;
+    }
+
     N = PyTuple_GET_SIZE(self->names);
     if (!PySequence_Check(val) || PyObject_Size((PyObject *)val) != N) {
         PyErr_Format(PyExc_ValueError,
@@ -1683,6 +1869,9 @@ static PyGetSetDef arraydescr_getsets[] = {
     {"isnative",
         (getter)arraydescr_isnative_get,
         NULL, NULL, NULL},
+    {"isalignedstruct",
+        (getter)arraydescr_isalignedstruct_get,
+        NULL, NULL, NULL},
     {"fields",
         (getter)arraydescr_fields_get,
         NULL, NULL, NULL},
@@ -1717,25 +1906,29 @@ _invalid_metadata_check(PyObject *metadata)
 }
 
 static PyObject *
-arraydescr_new(PyTypeObject *NPY_UNUSED(subtype), PyObject *args, PyObject *kwds)
+arraydescr_new(PyTypeObject *NPY_UNUSED(subtype),
+                PyObject *args, PyObject *kwds)
 {
-    PyObject *odescr, *ometadata=NULL;
+    PyObject *odescr, *metadata=NULL;
     PyArray_Descr *descr, *conv;
-    Bool align = FALSE;
-    Bool copy = FALSE;
-    Bool copied = FALSE;
+    npy_bool align = FALSE;
+    npy_bool copy = FALSE;
+    npy_bool copied = FALSE;
+
     static char *kwlist[] = {"dtype", "align", "copy", "metadata", NULL};
 
     if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|O&O&O!", kwlist,
-                &odescr, PyArray_BoolConverter, &align,
+                &odescr,
+                PyArray_BoolConverter, &align,
                 PyArray_BoolConverter, &copy,
-                &PyDict_Type, &ometadata)) {
+                &PyDict_Type, &metadata)) {
         return NULL;
     }
 
-    if ((ometadata != NULL) && (_invalid_metadata_check(ometadata))) {
+    if ((metadata != NULL) && (_invalid_metadata_check(metadata))) {
         return NULL;
     }
+
     if (align) {
         if (!PyArray_DescrAlignConverter(odescr, &conv)) {
             return NULL;
@@ -1744,6 +1937,7 @@ arraydescr_new(PyTypeObject *NPY_UNUSED(subtype), PyObject *args, PyObject *kwds
     else if (!PyArray_DescrConverter(odescr, &conv)) {
         return NULL;
     }
+
     /* Get a new copy of it unless it's already a copy */
     if (copy && conv->fields == Py_None) {
         descr = PyArray_DescrNew(conv);
@@ -1752,20 +1946,22 @@ arraydescr_new(PyTypeObject *NPY_UNUSED(subtype), PyObject *args, PyObject *kwds
         copied = TRUE;
     }
 
-    if ((ometadata != NULL)) {
+    if ((metadata != NULL)) {
         /*
          * We need to be sure to make a new copy of the data-type and any
          * underlying dictionary
          */
         if (!copied) {
+            copied = TRUE;
             descr = PyArray_DescrNew(conv);
             Py_DECREF(conv);
             conv = descr;
         }
         if ((conv->metadata != NULL)) {
             /*
-             * Make a copy of the metadata before merging with ometadata
-             * so that this data-type descriptor has it's own copy
+             * Make a copy of the metadata before merging with the
+             * input metadata so that this data-type descriptor has
+             * it's own copy
              */
             /* Save a reference */
             odescr = conv->metadata;
@@ -1777,14 +1973,14 @@ arraydescr_new(PyTypeObject *NPY_UNUSED(subtype), PyObject *args, PyObject *kwds
              * Update conv->metadata with anything new in metadata
              * keyword, but do not over-write anything already there
              */
-            if (PyDict_Merge(conv->metadata, ometadata, 0) != 0) {
+            if (PyDict_Merge(conv->metadata, metadata, 0) != 0) {
                 Py_DECREF(conv);
                 return NULL;
             }
         }
         else {
             /* Make a copy of the input dictionary */
-            conv->metadata = PyDict_Copy(ometadata);
+            conv->metadata = PyDict_Copy(metadata);
         }
     }
 
@@ -1926,7 +2122,7 @@ arraydescr_reduce(PyArray_Descr *self, PyObject *NPY_UNUSED(args))
 
     PyTuple_SET_ITEM(state, 1, PyUString_FromFormat("%c", endian));
     PyTuple_SET_ITEM(state, 2, arraydescr_subdescr_get(self));
-    if (self->names) {
+    if (PyDataType_HASFIELDS(self)) {
         Py_INCREF(self->names);
         Py_INCREF(self->fields);
         PyTuple_SET_ITEM(state, 3, self->names);
@@ -2184,7 +2380,7 @@ arraydescr_setstate(PyArray_Descr *self, PyObject *args)
         }
 
         self->subarray = PyArray_malloc(sizeof(PyArray_ArrayDescr));
-        if (self->subarray == NULL) {
+        if (!PyDataType_HASSUBARRAY(self)) {
             return PyErr_NoMemory();
         }
         self->subarray->base = (PyArray_Descr *)PyTuple_GET_ITEM(subarray, 0);
@@ -2366,7 +2562,7 @@ PyArray_DescrNewByteorder(PyArray_Descr *self, char newendian)
             new->byteorder = newendian;
         }
     }
-    if (new->names) {
+    if (PyDataType_HASFIELDS(new)) {
         PyObject *newfields;
         PyObject *key, *value;
         PyObject *newvalue;
@@ -2408,7 +2604,7 @@ PyArray_DescrNewByteorder(PyArray_Descr *self, char newendian)
         Py_DECREF(new->fields);
         new->fields = newfields;
     }
-    if (new->subarray) {
+    if (PyDataType_HASSUBARRAY(new)) {
         Py_DECREF(new->subarray->base);
         new->subarray->base = PyArray_DescrNewByteorder(
                 self->subarray->base, newendian);
@@ -2443,95 +2639,451 @@ static PyMethodDef arraydescr_methods[] = {
     {NULL, NULL, 0, NULL}           /* sentinel */
 };
 
-static PyObject *
-arraydescr_str(PyArray_Descr *self)
+/*
+ * Checks whether the structured data type in 'dtype'
+ * has a simple layout, where all the fields are in order,
+ * and follow each other with no alignment padding.
+ *
+ * When this returns true, the dtype can be reconstructed
+ * from a list of the field names and dtypes with no additional
+ * dtype parameters.
+ *
+ * Returns 1 if it has a simple layout, 0 otherwise.
+ */
+static int
+is_dtype_struct_simple_unaligned_layout(PyArray_Descr *dtype)
 {
-    PyObject *sub;
+    PyObject *names, *fields, *key, *tup, *title;
+    Py_ssize_t i, names_size;
+    PyArray_Descr *fld_dtype;
+    int fld_offset;
+    npy_intp total_offset;
+
+    /* Get some properties from the dtype */
+    names = dtype->names;
+    names_size = PyTuple_GET_SIZE(names);
+    fields = dtype->fields;
+
+    /* Start at offset zero */
+    total_offset = 0;
+
+    for (i = 0; i < names_size; ++i) {
+        key = PyTuple_GET_ITEM(names, i);
+        if (key == NULL) {
+            return 0;
+        }
+        tup = PyDict_GetItem(fields, key);
+        if (tup == NULL) {
+            return 0;
+        }
+        if (!PyArg_ParseTuple(tup, "Oi|O", &fld_dtype, &fld_offset, &title)) {
+            PyErr_Clear();
+            return 0;
+        }
+        /* If this field doesn't follow the pattern, not a simple layout */
+        if (total_offset != fld_offset) {
+            return 0;
+        }
+        /* Get the next offset */
+        total_offset += fld_dtype->elsize;
+    }
 
-    if (self->names) {
-        PyObject *lst;
-        lst = arraydescr_protocol_descr_get(self);
-        if (!lst) {
-            sub = PyUString_FromString("<err>");
+    /*
+     * If the itemsize doesn't match the final offset, it's
+     * not a simple layout.
+     */
+    if (total_offset != dtype->elsize) {
+        return 0;
+    }
+
+    /* It's a simple layout, since all the above tests passed */
+    return 1;
+}
+
+/*
+ * Returns a string representation of a structured array,
+ * in a list format.
+ */
+static PyObject *
+arraydescr_struct_list_str(PyArray_Descr *dtype)
+{
+    PyObject *names, *key, *fields, *ret, *tmp, *tup, *title;
+    Py_ssize_t i, names_size;
+    PyArray_Descr *fld_dtype;
+    int fld_offset;
+
+    names = dtype->names;
+    names_size = PyTuple_GET_SIZE(names);
+    fields = dtype->fields;
+
+    /* Build up a string to make the list */
+
+    /* Go through all the names */
+    ret = PyUString_FromString("[");
+    for (i = 0; i < names_size; ++i) {
+        key = PyTuple_GET_ITEM(names, i);
+        tup = PyDict_GetItem(fields, key);
+        if (tup == NULL) {
+            return 0;
+        }
+        title = NULL;
+        if (!PyArg_ParseTuple(tup, "Oi|O", &fld_dtype, &fld_offset, &title)) {
             PyErr_Clear();
+            return 0;
+        }
+        PyUString_ConcatAndDel(&ret, PyUString_FromString("("));
+        /* Check for whether to do titles as well */
+        if (title != NULL && title != Py_None) {
+            PyUString_ConcatAndDel(&ret, PyUString_FromString("("));
+            PyUString_ConcatAndDel(&ret, PyObject_Repr(title));
+            PyUString_ConcatAndDel(&ret, PyUString_FromString(", "));
+            PyUString_ConcatAndDel(&ret, PyObject_Repr(key));
+            PyUString_ConcatAndDel(&ret, PyUString_FromString("), "));
         }
         else {
-            sub = PyObject_Str(lst);
-        }
-        Py_XDECREF(lst);
-        if (self->type_num != PyArray_VOID) {
-            PyObject *p, *t;
-            t=PyUString_FromString("'");
-            p = arraydescr_protocol_typestr_get(self);
-            PyUString_Concat(&p, t);
-            PyUString_ConcatAndDel(&t, p);
-            p = PyUString_FromString("(");
-            PyUString_ConcatAndDel(&p, t);
-            PyUString_ConcatAndDel(&p, PyUString_FromString(", "));
-            PyUString_ConcatAndDel(&p, sub);
-            PyUString_ConcatAndDel(&p, PyUString_FromString(")"));
-            sub = p;
-        }
-    }
-    else if (self->subarray) {
-        PyObject *p;
-        PyObject *t = PyUString_FromString("(");
-        PyObject *sh;
-        p = arraydescr_str(self->subarray->base);
-        if (!self->subarray->base->names && !self->subarray->base->subarray) {
-            PyObject *tmp=PyUString_FromString("'");
-            PyUString_Concat(&p, tmp);
-            PyUString_ConcatAndDel(&tmp, p);
-            p = tmp;
-        }
-        PyUString_ConcatAndDel(&t, p);
-        PyUString_ConcatAndDel(&t, PyUString_FromString(","));
-        /*TODO
-         * self->subarray->shape should always be a tuple,
-         * so this check should be unnecessary
-         */
-        if (!PyTuple_Check(self->subarray->shape)) {
-            sh = Py_BuildValue("(O)", self->subarray->shape);
+            PyUString_ConcatAndDel(&ret, PyObject_Repr(key));
+            PyUString_ConcatAndDel(&ret, PyUString_FromString(", "));
+        }
+        /* Special case subarray handling here */
+        if (PyDataType_HASSUBARRAY(fld_dtype)) {
+            tmp = arraydescr_short_construction_repr(
+                            fld_dtype->subarray->base);
+            PyUString_ConcatAndDel(&ret, tmp);
+            PyUString_ConcatAndDel(&ret, PyUString_FromString(", "));
+            PyUString_ConcatAndDel(&ret,
+                            PyObject_Str(fld_dtype->subarray->shape));
         }
         else {
-            sh = self->subarray->shape;
-            Py_INCREF(sh);
+            tmp = arraydescr_short_construction_repr(fld_dtype);
+            PyUString_ConcatAndDel(&ret, tmp);
+        }
+        PyUString_ConcatAndDel(&ret, PyUString_FromString(")"));
+        if (i != names_size - 1) {
+            PyUString_ConcatAndDel(&ret, PyUString_FromString(", "));
         }
-        PyUString_ConcatAndDel(&t, PyObject_Str(sh));
-        Py_DECREF(sh);
-        PyUString_ConcatAndDel(&t, PyUString_FromString(")"));
-        sub = t;
     }
-    else if (PyDataType_ISFLEXIBLE(self) || !PyArray_ISNBO(self->byteorder)) {
-        sub = arraydescr_protocol_typestr_get(self);
+    PyUString_ConcatAndDel(&ret, PyUString_FromString("]"));
+
+    return ret;
+}
+
+/*
+ * Returns a string representation of a structured array,
+ * in a dict format.
+ */
+static PyObject *
+arraydescr_struct_dict_str(PyArray_Descr *dtype)
+{
+    PyObject *names, *key, *fields, *ret, *tmp, *tup, *title;
+    Py_ssize_t i, names_size;
+    PyArray_Descr *fld_dtype;
+    int fld_offset, has_titles;
+
+    names = dtype->names;
+    names_size = PyTuple_GET_SIZE(names);
+    fields = dtype->fields;
+    has_titles = 0;
+
+    /* Build up a string to make the dictionary */
+
+    /* First, the names */
+    ret = PyUString_FromString("{'names':[");
+    for (i = 0; i < names_size; ++i) {
+        key = PyTuple_GET_ITEM(names, i);
+        PyUString_ConcatAndDel(&ret, PyObject_Repr(key));
+        if (i != names_size - 1) {
+            PyUString_ConcatAndDel(&ret, PyUString_FromString(","));
+        }
+    }
+    /* Second, the formats */
+    PyUString_ConcatAndDel(&ret, PyUString_FromString("], 'formats':["));
+    for (i = 0; i < names_size; ++i) {
+        key = PyTuple_GET_ITEM(names, i);
+        tup = PyDict_GetItem(fields, key);
+        if (tup == NULL) {
+            return 0;
+        }
+        title = NULL;
+        if (!PyArg_ParseTuple(tup, "Oi|O", &fld_dtype, &fld_offset, &title)) {
+            PyErr_Clear();
+            return 0;
+        }
+        /* Check for whether to do titles as well */
+        if (title != NULL && title != Py_None) {
+            has_titles = 1;
+        }
+        tmp = arraydescr_short_construction_repr(fld_dtype);
+        PyUString_ConcatAndDel(&ret, tmp);
+        if (i != names_size - 1) {
+            PyUString_ConcatAndDel(&ret, PyUString_FromString(","));
+        }
+    }
+    /* Third, the offsets */
+    PyUString_ConcatAndDel(&ret, PyUString_FromString("], 'offsets':["));
+    for (i = 0; i < names_size; ++i) {
+        key = PyTuple_GET_ITEM(names, i);
+        tup = PyDict_GetItem(fields, key);
+        if (tup == NULL) {
+            return 0;
+        }
+        if (!PyArg_ParseTuple(tup, "Oi|O", &fld_dtype, &fld_offset, &title)) {
+            PyErr_Clear();
+            return 0;
+        }
+        PyUString_ConcatAndDel(&ret, PyUString_FromFormat("%d", fld_offset));
+        if (i != names_size - 1) {
+            PyUString_ConcatAndDel(&ret, PyUString_FromString(","));
+        }
+    }
+    /* Fourth, the titles */
+    if (has_titles) {
+        PyUString_ConcatAndDel(&ret, PyUString_FromString("], 'titles':["));
+        for (i = 0; i < names_size; ++i) {
+            key = PyTuple_GET_ITEM(names, i);
+            tup = PyDict_GetItem(fields, key);
+            if (tup == NULL) {
+                return 0;
+            }
+            title = Py_None;
+            if (!PyArg_ParseTuple(tup, "Oi|O", &fld_dtype,
+                                            &fld_offset, &title)) {
+                PyErr_Clear();
+                return 0;
+            }
+            PyUString_ConcatAndDel(&ret, PyObject_Repr(title));
+            if (i != names_size - 1) {
+                PyUString_ConcatAndDel(&ret, PyUString_FromString(","));
+            }
+        }
+    }
+    /* Finally, the itemsize */
+    PyUString_ConcatAndDel(&ret,
+            PyUString_FromFormat("], 'itemsize':%d}", (int)dtype->elsize));
+
+    return ret;
+}
+
+/* Produces a string representation for a structured dtype */
+static PyObject *
+arraydescr_struct_str(PyArray_Descr *dtype)
+{
+    if (is_dtype_struct_simple_unaligned_layout(dtype)) {
+        return arraydescr_struct_list_str(dtype);
     }
     else {
-        sub = arraydescr_typename_get(self);
+        return arraydescr_struct_dict_str(dtype);
+    }
+}
+
+/* Produces a string representation for a subarray dtype */
+static PyObject *
+arraydescr_subarray_str(PyArray_Descr *dtype)
+{
+    PyObject *p, *ret;
+
+    ret = PyUString_FromString("(");
+    p = arraydescr_short_construction_repr(dtype->subarray->base);
+    PyUString_ConcatAndDel(&ret, p);
+    PyUString_ConcatAndDel(&ret, PyUString_FromString(", "));
+    PyUString_ConcatAndDel(&ret, PyObject_Str(dtype->subarray->shape));
+    PyUString_ConcatAndDel(&ret, PyUString_FromString(")"));
+
+    return ret;
+}
+
+static PyObject *
+arraydescr_str(PyArray_Descr *dtype)
+{
+    PyObject *sub;
+
+    if (PyDataType_HASFIELDS(dtype)) {
+        sub = arraydescr_struct_str(dtype);
+    }
+    else if (PyDataType_HASSUBARRAY(dtype)) {
+        sub = arraydescr_subarray_str(dtype);
+    }
+    else if (PyDataType_ISFLEXIBLE(dtype) || !PyArray_ISNBO(dtype->byteorder)) {
+        sub = arraydescr_protocol_typestr_get(dtype);
+    }
+    else {
+        sub = arraydescr_typename_get(dtype);
     }
     return sub;
 }
 
+/*
+ * The dtype repr function specifically for structured arrays.
+ */
 static PyObject *
-arraydescr_repr(PyArray_Descr *self)
+arraydescr_struct_repr(PyArray_Descr *dtype)
 {
     PyObject *sub, *s;
+
     s = PyUString_FromString("dtype(");
-    sub = arraydescr_str(self);
+    sub = arraydescr_struct_str(dtype);
     if (sub == NULL) {
-        return sub;
-    }
-    if (!self->names && !self->subarray) {
-        PyObject *t=PyUString_FromString("'");
-        PyUString_Concat(&sub, t);
-        PyUString_ConcatAndDel(&t, sub);
-        sub = t;
+        return NULL;
     }
+
     PyUString_ConcatAndDel(&s, sub);
-    sub = PyUString_FromString(")");
-    PyUString_ConcatAndDel(&s, sub);
+
+    /* If it's an aligned structure, add the align=True parameter */
+    if (dtype->flags&NPY_ALIGNED_STRUCT) {
+        PyUString_ConcatAndDel(&s, PyUString_FromString(", align=True"));
+    }
+
+    PyUString_ConcatAndDel(&s, PyUString_FromString(")"));
     return s;
 }
 
+/*
+ * This creates a shorter repr using 'kind' and 'itemsize',
+ * instead of the longer type name. This is the object passed
+ * as the first parameter to the dtype constructor, and if no
+ * additional constructor parameters are given, will reproduce
+ * the exact memory layout.
+ *
+ * This does not preserve the 'align=True' parameter or sticky
+ * NPY_ALIGNED_STRUCT flag for struct arrays like the regular
+ * repr does, because the 'align' flag is not part of first
+ * dtype constructor parameter.
+ */
+NPY_NO_EXPORT PyObject *
+arraydescr_short_construction_repr(PyArray_Descr *dtype)
+{
+    PyObject *ret;
+    PyArray_DatetimeMetaData *meta;
+    char byteorder[2];
+
+    if (PyDataType_HASFIELDS(dtype)) {
+        return arraydescr_struct_str(dtype);
+    }
+    else if (PyDataType_HASSUBARRAY(dtype)) {
+        return arraydescr_subarray_str(dtype);
+    }
+
+    /* Normalize byteorder to '<' or '>' */
+    switch (dtype->byteorder) {
+        case NPY_NATIVE:
+            byteorder[0] = NPY_NATBYTE;
+            break;
+        case NPY_SWAP:
+            byteorder[0] = NPY_OPPBYTE;
+            break;
+        case NPY_IGNORE:
+            byteorder[0] = '\0';
+            break;
+        default:
+            byteorder[0] = dtype->byteorder;
+            break;
+    }
+    byteorder[1] = '\0';
+
+    /* Handle booleans, numbers, and custom dtypes */
+    if (dtype->type_num == NPY_BOOL) {
+        return PyUString_FromString("'?'");
+    }
+    else if (PyTypeNum_ISNUMBER(dtype->type_num)) {
+        return PyUString_FromFormat("'%s%c%d'", byteorder, (int)dtype->kind,
+                                                dtype->elsize);
+    }
+    else if (PyTypeNum_ISUSERDEF(dtype->type_num)) {
+        char *s = strrchr(dtype->typeobj->tp_name, '.');
+        if (s == NULL) {
+            return PyUString_FromString(dtype->typeobj->tp_name);
+        }
+        else {
+            return PyUString_FromStringAndSize(s + 1, strlen(s) - 1);
+        }
+    }
+
+    /* All the rest which don't fit in the same pattern */
+    switch (dtype->type_num) {
+        /*
+         * The object reference may be different sizes on different
+         * platforms, so it should never include the itemsize here.
+         */
+        case NPY_OBJECT:
+            return PyUString_FromString("'O'");
+
+        case NPY_STRING:
+            if (dtype->elsize == 0) {
+                return PyUString_FromString("'S'");
+            }
+            else {
+                return PyUString_FromFormat("'S%d'", (int)dtype->elsize);
+            }
+
+        case NPY_UNICODE:
+            if (dtype->elsize == 0) {
+                return PyUString_FromFormat("'%sU'", byteorder);
+            }
+            else {
+                return PyUString_FromFormat("'%sU%d'", byteorder,
+                                                (int)dtype->elsize / 4);
+            }
+
+        case NPY_VOID:
+            if (dtype->elsize == 0) {
+                return PyUString_FromString("'V'");
+            }
+            else {
+                return PyUString_FromFormat("'V%d'", (int)dtype->elsize);
+            }
+
+        case NPY_DATETIME:
+            meta = get_datetime_metadata_from_dtype(dtype);
+            if (meta == NULL) {
+                return NULL;
+            }
+            ret = PyUString_FromFormat("%sM8", byteorder);
+            return append_metastr_to_string(meta, 0, ret);
+
+        case NPY_TIMEDELTA:
+            meta = get_datetime_metadata_from_dtype(dtype);
+            if (meta == NULL) {
+                return NULL;
+            }
+            ret = PyUString_FromFormat("%sm8", byteorder);
+            return append_metastr_to_string(meta, 0, ret);
+
+        default:
+            PyErr_SetString(PyExc_RuntimeError, "Internal error: NumPy dtype "
+                            "unrecognized type number");
+            return NULL;
+    }
+}
+
+/*
+ * The general dtype repr function.
+ */
+static PyObject *
+arraydescr_repr(PyArray_Descr *dtype)
+{
+    PyObject *sub, *s;
+
+    if (PyDataType_HASFIELDS(dtype)) {
+        return arraydescr_struct_repr(dtype);
+    }
+    else {
+        s = PyUString_FromString("dtype(");
+        sub = arraydescr_str(dtype);
+        if (sub == NULL) {
+            return NULL;
+        }
+        if (!PyDataType_HASSUBARRAY(dtype)) {
+            PyObject *t=PyUString_FromString("'");
+            PyUString_Concat(&sub, t);
+            PyUString_ConcatAndDel(&t, sub);
+            sub = t;
+        }
+        PyUString_ConcatAndDel(&s, sub);
+        sub = PyUString_FromString(")");
+        PyUString_ConcatAndDel(&s, sub);
+        return s;
+    }
+}
+
 static PyObject *
 arraydescr_richcompare(PyArray_Descr *self, PyObject *other, int cmp_op)
 {
@@ -2611,7 +3163,7 @@ descr_length(PyObject *self0)
 {
     PyArray_Descr *self = (PyArray_Descr *)self0;
 
-    if (self->names) {
+    if (PyDataType_HASFIELDS(self)) {
         return PyTuple_GET_SIZE(self->names);
     }
     else {
@@ -2642,7 +3194,7 @@ descr_subscript(PyArray_Descr *self, PyObject *op)
 {
     PyObject *retval;
 
-    if (!self->names) {
+    if (!PyDataType_HASFIELDS(self)) {
         PyObject *astr = arraydescr_str(self);
 #if defined(NPY_PY3K)
         PyObject *bstr = PyUnicode_AsUnicodeEscapeString(astr);
diff --git a/numpy/core/src/multiarray/descriptor.h b/numpy/core/src/multiarray/descriptor.h
index acb80eec6..4f8a90582 100644
--- a/numpy/core/src/multiarray/descriptor.h
+++ b/numpy/core/src/multiarray/descriptor.h
@@ -10,6 +10,18 @@ array_set_typeDict(PyObject *NPY_UNUSED(ignored), PyObject *args);
 NPY_NO_EXPORT PyArray_Descr *
 _arraydescr_fromobj(PyObject *obj);
 
+/*
+ * This creates a shorter repr using the 'kind' and 'itemsize',
+ * instead of the longer type name. It also creates the input
+ * for constructing a dtype rather than the full dtype function
+ * call.
+ *
+ * This does not preserve the 'align=True' parameter
+ * for structured arrays like the regular repr does.
+ */
+NPY_NO_EXPORT PyObject *
+arraydescr_short_construction_repr(PyArray_Descr *dtype);
+
 #ifdef NPY_ENABLE_SEPARATE_COMPILATION
 extern NPY_NO_EXPORT char *_datetime_strings[];
 #endif
diff --git a/numpy/core/src/multiarray/dtype_transfer.c b/numpy/core/src/multiarray/dtype_transfer.c
index 445133ebf..88bba189e 100644
--- a/numpy/core/src/multiarray/dtype_transfer.c
+++ b/numpy/core/src/multiarray/dtype_transfer.c
@@ -2310,7 +2310,7 @@ get_subarray_transfer_function(int aligned,
     npy_intp src_size = 1, dst_size = 1;
 
     /* Get the subarray shapes and sizes */
-    if (src_dtype->subarray != NULL) {
+    if (PyDataType_HASSUBARRAY(src_dtype)) {
        if (!(PyArray_IntpConverter(src_dtype->subarray->shape,
                                             &src_shape))) {
             PyErr_SetString(PyExc_ValueError,
@@ -2320,7 +2320,7 @@ get_subarray_transfer_function(int aligned,
         src_size = PyArray_MultiplyList(src_shape.ptr, src_shape.len);
         src_dtype = src_dtype->subarray->base;
     }
-    if (dst_dtype->subarray != NULL) {
+    if (PyDataType_HASSUBARRAY(dst_dtype)) {
        if (!(PyArray_IntpConverter(dst_dtype->subarray->shape,
                                             &dst_shape))) {
             if (src_shape.ptr != NULL) {
@@ -3184,7 +3184,7 @@ get_setdstzero_transfer_function(int aligned,
         *out_transferdata = NULL;
     }
     /* If there are subarrays, need to wrap it */
-    else if (dst_dtype->subarray != NULL) {
+    else if (PyDataType_HASSUBARRAY(dst_dtype)) {
         PyArray_Dims dst_shape = {NULL, -1};
         npy_intp dst_size = 1;
         PyArray_StridedTransferFn *contig_stransfer;
@@ -3297,7 +3297,7 @@ get_decsrcref_transfer_function(int aligned,
         return NPY_SUCCEED;
     }
     /* If there are subarrays, need to wrap it */
-    else if (src_dtype->subarray != NULL) {
+    else if (PyDataType_HASSUBARRAY(src_dtype)) {
         PyArray_Dims src_shape = {NULL, -1};
         npy_intp src_size = 1;
         PyArray_StridedTransferFn *stransfer;
@@ -3496,7 +3496,8 @@ PyArray_GetDTypeTransferFunction(int aligned,
     if (src_itemsize == dst_itemsize && src_dtype->kind == dst_dtype->kind &&
                 !PyDataType_HASFIELDS(src_dtype) &&
                 !PyDataType_HASFIELDS(dst_dtype) &&
-                src_dtype->subarray == NULL && dst_dtype->subarray == NULL &&
+                !PyDataType_HASSUBARRAY(src_dtype) &&
+                !PyDataType_HASSUBARRAY(dst_dtype) &&
                 src_type_num != NPY_DATETIME && src_type_num != NPY_TIMEDELTA) {
         /* A custom data type requires that we use its copy/swap */
         if (src_type_num >= NPY_NTYPES || dst_type_num >= NPY_NTYPES) {
@@ -3575,7 +3576,8 @@ PyArray_GetDTypeTransferFunction(int aligned,
     }
 
     /* Handle subarrays */
-    if (src_dtype->subarray != NULL || dst_dtype->subarray != NULL) {
+    if (PyDataType_HASSUBARRAY(src_dtype) ||
+                                PyDataType_HASSUBARRAY(dst_dtype)) {
         return get_subarray_transfer_function(aligned,
                         src_stride, dst_stride,
                         src_dtype, dst_dtype,
diff --git a/numpy/core/src/multiarray/getset.c b/numpy/core/src/multiarray/getset.c
index 3d2b6975e..e039ed611 100644
--- a/numpy/core/src/multiarray/getset.c
+++ b/numpy/core/src/multiarray/getset.c
@@ -438,7 +438,7 @@ array_descr_set(PyArrayObject *self, PyObject *arg)
 
     if ((newtype->elsize != self->descr->elsize) &&
         (self->nd == 0 || !PyArray_ISONESEGMENT(self) ||
-         newtype->subarray)) {
+         PyDataType_HASSUBARRAY(newtype))) {
         goto fail;
     }
     if (PyArray_ISCONTIGUOUS(self)) {
@@ -474,7 +474,7 @@ array_descr_set(PyArrayObject *self, PyObject *arg)
 
     /* fall through -- adjust type*/
     Py_DECREF(self->descr);
-    if (newtype->subarray) {
+    if (PyDataType_HASSUBARRAY(newtype)) {
         /*
          * create new array object from data and update
          * dimensions, strides and descr from it
@@ -550,7 +550,7 @@ array_struct_get(PyArrayObject *self)
         inter->strides = NULL;
     }
     inter->data = self->data;
-    if (self->descr->names) {
+    if (PyDataType_HASFIELDS(self->descr)) {
         inter->descr = arraydescr_protocol_descr_get(self->descr);
         if (inter->descr == NULL) {
             PyErr_Clear();
diff --git a/numpy/core/src/multiarray/hashdescr.c b/numpy/core/src/multiarray/hashdescr.c
index 60a9a7361..d4dbdf7e8 100644
--- a/numpy/core/src/multiarray/hashdescr.c
+++ b/numpy/core/src/multiarray/hashdescr.c
@@ -55,7 +55,7 @@ static int _is_array_descr_builtin(PyArray_Descr* descr)
         if (descr->fields != NULL && descr->fields != Py_None) {
                 return 0;
         }
-        if (descr->subarray != NULL) {
+        if (PyDataType_HASSUBARRAY(descr)) {
                 return 0;
         }
         return 1;
@@ -223,7 +223,7 @@ static int _array_descr_walk(PyArray_Descr* descr, PyObject *l)
                 return -1;
             }
         }
-        if(descr->subarray != NULL) {
+        if(PyDataType_HASSUBARRAY(descr)) {
             st = _array_descr_walk_subarray(descr->subarray, l);
             if (st) {
                 return -1;
diff --git a/numpy/core/src/multiarray/mapping.c b/numpy/core/src/multiarray/mapping.c
index 31472333d..3f1d2957e 100644
--- a/numpy/core/src/multiarray/mapping.c
+++ b/numpy/core/src/multiarray/mapping.c
@@ -545,7 +545,7 @@ array_subscript(PyArrayObject *self, PyObject *op)
     if (PyString_Check(op) || PyUnicode_Check(op)) {
         PyObject *temp;
 
-        if (self->descr->names) {
+        if (PyDataType_HASFIELDS(self->descr)) {
             obj = PyDict_GetItem(self->descr->fields, op);
             if (obj != NULL) {
                 PyArray_Descr *descr;
@@ -573,7 +573,9 @@ array_subscript(PyArrayObject *self, PyObject *op)
     }
 
     /* Check for multiple field access */
-    if (self->descr->names && PySequence_Check(op) && !PyTuple_Check(op)) {
+    if (PyDataType_HASFIELDS(self->descr) &&
+                        PySequence_Check(op) &&
+                        !PyTuple_Check(op)) {
         int seqlen, i;
         seqlen = PySequence_Size(op);
         for (i = 0; i < seqlen; i++) {
@@ -797,7 +799,7 @@ array_ass_sub(PyArrayObject *self, PyObject *index, PyObject *op)
     }
 
     if (PyString_Check(index) || PyUnicode_Check(index)) {
-        if (self->descr->names) {
+        if (PyDataType_HASFIELDS(self->descr)) {
             PyObject *obj;
 
             obj = PyDict_GetItem(self->descr->fields, index);
diff --git a/numpy/core/src/multiarray/methods.c b/numpy/core/src/multiarray/methods.c
index 2cd4487ac..fe2030f47 100644
--- a/numpy/core/src/multiarray/methods.c
+++ b/numpy/core/src/multiarray/methods.c
@@ -1132,7 +1132,7 @@ array_sort(PyArrayObject *self, PyObject *args, PyObject *kwds)
         PyObject *new_name;
         PyObject *_numpy_internal;
         saved = self->descr;
-        if (saved->names == NULL) {
+        if (!PyDataType_HASFIELDS(saved)) {
             PyErr_SetString(PyExc_ValueError, "Cannot specify " \
                             "order when the array has no fields.");
             return NULL;
@@ -1186,7 +1186,7 @@ array_argsort(PyArrayObject *self, PyObject *args, PyObject *kwds)
         PyObject *new_name;
         PyObject *_numpy_internal;
         saved = self->descr;
-        if (saved->names == NULL) {
+        if (!PyDataType_HASFIELDS(saved)) {
             PyErr_SetString(PyExc_ValueError, "Cannot specify " \
                             "order when the array has no fields.");
             return NULL;
diff --git a/numpy/core/src/multiarray/scalarapi.c b/numpy/core/src/multiarray/scalarapi.c
index d4ccc42c8..4607c2904 100644
--- a/numpy/core/src/multiarray/scalarapi.c
+++ b/numpy/core/src/multiarray/scalarapi.c
@@ -757,7 +757,7 @@ PyArray_Scalar(void *data, PyArray_Descr *descr, PyObject *base)
             Py_SIZE(vobj) = itemsize;
             vobj->flags = BEHAVED | OWNDATA;
             swap = 0;
-            if (descr->names) {
+            if (PyDataType_HASFIELDS(descr)) {
                 if (base) {
                     Py_INCREF(base);
                     vobj->base = base;
diff --git a/numpy/core/src/multiarray/scalartypes.c.src b/numpy/core/src/multiarray/scalartypes.c.src
index 0e7eb5914..f6aa64b3d 100644
--- a/numpy/core/src/multiarray/scalartypes.c.src
+++ b/numpy/core/src/multiarray/scalartypes.c.src
@@ -2008,7 +2008,7 @@ static PyMethodDef @name@type_methods[] = {
 static Py_ssize_t
 voidtype_length(PyVoidScalarObject *self)
 {
-    if (!self->descr->names) {
+    if (!PyDataType_HASFIELDS(self->descr)) {
         return 0;
     }
     else { /* return the number of fields */
diff --git a/numpy/core/tests/test_dtype.py b/numpy/core/tests/test_dtype.py
index c79b755be..ff13dcad6 100644
--- a/numpy/core/tests/test_dtype.py
+++ b/numpy/core/tests/test_dtype.py
@@ -41,6 +41,25 @@ class TestBuiltin(TestCase):
             #print typestr
             assert_raises(TypeError, np.dtype, typestr)
 
+    def test_bad_param(self):
+        # Can't give a size that's too small
+        assert_raises(ValueError, np.dtype,
+                        {'names':['f0','f1'],
+                         'formats':['i4', 'i1'],
+                         'offsets':[0,4],
+                         'itemsize':4})
+        # If alignment is enabled, the alignment (4) must divide the itemsize
+        assert_raises(ValueError, np.dtype,
+                        {'names':['f0','f1'],
+                         'formats':['i4', 'i1'],
+                         'offsets':[0,4],
+                         'itemsize':9}, align=True)
+        # If alignment is enabled, the individual fields must be aligned
+        assert_raises(ValueError, np.dtype,
+                        {'names':['f0','f1'],
+                         'formats':['i1','f4'],
+                         'offsets':[0,2]}, align=True)
+
 class TestRecord(TestCase):
     def test_equivalent_record(self):
         """Test whether equivalent record dtypes hash the same."""
@@ -56,10 +75,12 @@ class TestRecord(TestCase):
 
     def test_different_titles(self):
         # In theory, they may hash the same (collision) ?
-        a = np.dtype({'names': ['r','b'], 'formats': ['u1', 'u1'],
-            'titles': ['Red pixel', 'Blue pixel']})
-        b = np.dtype({'names': ['r','b'], 'formats': ['u1', 'u1'],
-            'titles': ['RRed pixel', 'Blue pixel']})
+        a = np.dtype({'names': ['r','b'],
+                      'formats': ['u1', 'u1'],
+                      'titles': ['Red pixel', 'Blue pixel']})
+        b = np.dtype({'names': ['r','b'],
+                      'formats': ['u1', 'u1'],
+                      'titles': ['RRed pixel', 'Blue pixel']})
         assert_dtype_not_equal(a, b)
 
     def test_not_lists(self):
@@ -71,6 +92,99 @@ class TestRecord(TestCase):
         self.assertRaises(TypeError, np.dtype,
             dict(names=['A', 'B'], formats=set(['f8', 'i4'])))
 
+    def test_aligned_size(self):
+        # Check that structured dtypes get padded to an aligned size
+        dt = np.dtype('i4, i1', align=True)
+        assert_equal(dt.itemsize, 8)
+        dt = np.dtype([('f0', 'i4'), ('f1', 'i1')], align=True)
+        assert_equal(dt.itemsize, 8)
+        dt = np.dtype({'names':['f0','f1'],
+                       'formats':['i4', 'u1'],
+                       'offsets':[0,4]}, align=True)
+        assert_equal(dt.itemsize, 8)
+        dt = np.dtype({'f0': ('i4', 0), 'f1':('u1', 4)}, align=True)
+        assert_equal(dt.itemsize, 8)
+        # Nesting should preserve that alignment
+        dt1 = np.dtype([('f0', 'i4'),
+                       ('f1', [('f1', 'i1'), ('f2', 'i4'), ('f3', 'i1')]),
+                       ('f2', 'i1')], align=True)
+        assert_equal(dt1.itemsize, 20)
+        dt2 = np.dtype({'names':['f0','f1','f2'],
+                       'formats':['i4',
+                                  [('f1', 'i1'), ('f2', 'i4'), ('f3', 'i1')],
+                                  'i1'],
+                       'offsets':[0, 4, 16]}, align=True)
+        assert_equal(dt2.itemsize, 20)
+        dt3 = np.dtype({'f0': ('i4', 0),
+                       'f1': ([('f1', 'i1'), ('f2', 'i4'), ('f3', 'i1')], 4),
+                       'f2': ('i1', 16)}, align=True)
+        assert_equal(dt3.itemsize, 20)
+        assert_equal(dt1, dt2)
+        assert_equal(dt2, dt3)
+        # Nesting should preserve packing
+        dt1 = np.dtype([('f0', 'i4'),
+                       ('f1', [('f1', 'i1'), ('f2', 'i4'), ('f3', 'i1')]),
+                       ('f2', 'i1')], align=False)
+        assert_equal(dt1.itemsize, 11)
+        dt2 = np.dtype({'names':['f0','f1','f2'],
+                       'formats':['i4',
+                                  [('f1', 'i1'), ('f2', 'i4'), ('f3', 'i1')],
+                                  'i1'],
+                       'offsets':[0, 4, 10]}, align=False)
+        assert_equal(dt2.itemsize, 11)
+        dt3 = np.dtype({'f0': ('i4', 0),
+                       'f1': ([('f1', 'i1'), ('f2', 'i4'), ('f3', 'i1')], 4),
+                       'f2': ('i1', 10)}, align=False)
+        assert_equal(dt3.itemsize, 11)
+        assert_equal(dt1, dt2)
+        assert_equal(dt2, dt3)
+
+    def test_union_struct(self):
+        # Should be able to create union dtypes
+        dt = np.dtype({'names':['f0','f1','f2'], 'formats':['<u4', '<u2','<u2'],
+                        'offsets':[0,0,2]}, align=True)
+        assert_equal(dt.itemsize, 4)
+        a = np.array([3], dtype='<u4').view(dt)
+        a['f1'] = 10
+        a['f2'] = 36
+        assert_equal(a['f0'], 10 + 36*256*256)
+        # Should be able to specify fields out of order
+        dt = np.dtype({'names':['f0','f1','f2'], 'formats':['<u4', '<u2','<u2'],
+                        'offsets':[4,0,2]}, align=True)
+        assert_equal(dt.itemsize, 8)
+        dt2 = np.dtype({'names':['f2','f0','f1'],
+                        'formats':['<u2', '<u4','<u2'],
+                        'offsets':[2,4,0]}, align=True)
+        vals = [(0,1,2), (3,-1,4)]
+        vals2 = [(2,0,1), (4,3,-1)]
+        a = np.array(vals, dt)
+        b = np.array(vals2, dt2)
+        assert_equal(a.astype(dt2), b)
+        assert_equal(b.astype(dt), a)
+        assert_equal(a.view(dt2), b)
+        assert_equal(b.view(dt), a)
+        # Should not be able to overlap objects with other types
+        assert_raises(TypeError, np.dtype,
+                {'names':['f0','f1'],
+                 'formats':['O', 'i1'],
+                 'offsets':[0,2]})
+        assert_raises(TypeError, np.dtype,
+                {'names':['f0','f1'],
+                 'formats':['i4', 'O'],
+                 'offsets':[0,3]})
+        assert_raises(TypeError, np.dtype,
+                {'names':['f0','f1'],
+                 'formats':[[('a','O')], 'i1'],
+                 'offsets':[0,2]})
+        assert_raises(TypeError, np.dtype,
+                {'names':['f0','f1'],
+                 'formats':['i4', [('a','O')]],
+                 'offsets':[0,3]})
+        # Out of order should still be ok, however
+        dt = np.dtype({'names':['f0','f1'],
+                       'formats':['i1', 'O'],
+                       'offsets':[np.dtype('intp').itemsize, 0]})
+
 class TestSubarray(TestCase):
     def test_single_subarray(self):
         a = np.dtype((np.int, (2)))
@@ -165,5 +279,92 @@ class TestMetadata(TestCase):
         d = np.dtype([('a', np.dtype(int, metadata={'datum': 1}))])
         self.assertEqual(d['a'].metadata, {'datum': 1})
 
+class TestString(TestCase):
+    def test_complex_dtype_str(self):
+        dt = np.dtype([('top', [('tiles', ('>f4', (64, 64)), (1,)),
+                                ('rtile', '>f4', (64, 36))], (3,)),
+                       ('bottom', [('bleft', ('>f4', (8, 64)), (1,)),
+                                   ('bright', '>f4', (8, 36))])])
+        assert_equal(str(dt),
+                     "[('top', [('tiles', ('>f4', (64, 64)), (1,)), "
+                     "('rtile', '>f4', (64, 36))], (3,)), "
+                     "('bottom', [('bleft', ('>f4', (8, 64)), (1,)), "
+                     "('bright', '>f4', (8, 36))])]")
+
+        dt = np.dtype({'names': ['r','g','b'], 'formats': ['u1', 'u1', 'u1'],
+                        'offsets': [0, 1, 2],
+                        'titles': ['Red pixel', 'Green pixel', 'Blue pixel']})
+        assert_equal(str(dt),
+                    "[(('Red pixel', 'r'), 'u1'), "
+                    "(('Green pixel', 'g'), 'u1'), "
+                    "(('Blue pixel', 'b'), 'u1')]")
+
+        dt = np.dtype({'names': ['rgba', 'r','g','b'],
+                       'formats': ['<u4', 'u1', 'u1', 'u1'],
+                       'offsets': [0, 0, 1, 2],
+                       'titles': ['Color', 'Red pixel',
+                                  'Green pixel', 'Blue pixel']})
+        assert_equal(str(dt),
+                    "{'names':['rgba','r','g','b'],"
+                    " 'formats':['<u4','u1','u1','u1'],"
+                    " 'offsets':[0,0,1,2],"
+                    " 'titles':['Color','Red pixel',"
+                              "'Green pixel','Blue pixel'],"
+                    " 'itemsize':4}")
+
+        dt = np.dtype({'names': ['r','b'], 'formats': ['u1', 'u1'],
+                        'offsets': [0, 2],
+                        'titles': ['Red pixel', 'Blue pixel']})
+        assert_equal(str(dt),
+                    "{'names':['r','b'],"
+                    " 'formats':['u1','u1'],"
+                    " 'offsets':[0,2],"
+                    " 'titles':['Red pixel','Blue pixel'],"
+                    " 'itemsize':3}")
+
+    def test_complex_dtype_repr(self):
+        dt = np.dtype([('top', [('tiles', ('>f4', (64, 64)), (1,)),
+                                ('rtile', '>f4', (64, 36))], (3,)),
+                       ('bottom', [('bleft', ('>f4', (8, 64)), (1,)),
+                                   ('bright', '>f4', (8, 36))])])
+        assert_equal(repr(dt),
+                     "dtype([('top', [('tiles', ('>f4', (64, 64)), (1,)), "
+                     "('rtile', '>f4', (64, 36))], (3,)), "
+                     "('bottom', [('bleft', ('>f4', (8, 64)), (1,)), "
+                     "('bright', '>f4', (8, 36))])])")
+
+        dt = np.dtype({'names': ['r','g','b'], 'formats': ['u1', 'u1', 'u1'],
+                        'offsets': [0, 1, 2],
+                        'titles': ['Red pixel', 'Green pixel', 'Blue pixel']},
+                        align=True)
+        assert_equal(repr(dt),
+                    "dtype([(('Red pixel', 'r'), 'u1'), "
+                    "(('Green pixel', 'g'), 'u1'), "
+                    "(('Blue pixel', 'b'), 'u1')], align=True)")
+
+        dt = np.dtype({'names': ['rgba', 'r','g','b'],
+                       'formats': ['<u4', 'u1', 'u1', 'u1'],
+                       'offsets': [0, 0, 1, 2],
+                       'titles': ['Color', 'Red pixel',
+                                  'Green pixel', 'Blue pixel']}, align=True)
+        assert_equal(repr(dt),
+                    "dtype({'names':['rgba','r','g','b'],"
+                    " 'formats':['<u4','u1','u1','u1'],"
+                    " 'offsets':[0,0,1,2],"
+                    " 'titles':['Color','Red pixel',"
+                              "'Green pixel','Blue pixel'],"
+                    " 'itemsize':4}, align=True)")
+
+        dt = np.dtype({'names': ['r','b'], 'formats': ['u1', 'u1'],
+                        'offsets': [0, 2],
+                        'titles': ['Red pixel', 'Blue pixel'],
+                        'itemsize': 4})
+        assert_equal(repr(dt),
+                    "dtype({'names':['r','b'], "
+                    "'formats':['u1','u1'], "
+                    "'offsets':[0,2], "
+                    "'titles':['Red pixel','Blue pixel'], "
+                    "'itemsize':4})")
+
 if __name__ == "__main__":
     run_module_suite()
diff --git a/numpy/core/tests/test_regression.py b/numpy/core/tests/test_regression.py
index a4cc2d725..1c43189bb 100644
--- a/numpy/core/tests/test_regression.py
+++ b/numpy/core/tests/test_regression.py
@@ -853,17 +853,6 @@ class TestRegression(TestCase):
         assert_almost_equal(fdouble, 1.234)
         assert_almost_equal(flongdouble, 1.234)
 
-    def test_complex_dtype_printing(self, level=rlevel):
-        dt = np.dtype([('top', [('tiles', ('>f4', (64, 64)), (1,)),
-                                ('rtile', '>f4', (64, 36))], (3,)),
-                       ('bottom', [('bleft', ('>f4', (8, 64)), (1,)),
-                                   ('bright', '>f4', (8, 36))])])
-        assert_equal(str(dt),
-                     "[('top', [('tiles', ('>f4', (64, 64)), (1,)), "
-                     "('rtile', '>f4', (64, 36))], (3,)), "
-                     "('bottom', [('bleft', ('>f4', (8, 64)), (1,)), "
-                     "('bright', '>f4', (8, 36))])]")
-
     def test_nonnative_endian_fill(self, level=rlevel):
         """ Non-native endian arrays were incorrectly filled with scalars before
         r5034.