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+
+The ndarray supports records intrinsically.  None of the default
+descriptors have fields defined, but you can create new descriptors
+easily.  The ndarray even supports nested arrays of records inside of
+a record.  Any record that the array protocol can describe can be
+represented.  The ndarray also supports partial field descriptors.
+Not every byte has to be accounted for.
+
+This was done by adding to the established ``PyArray_Descr *`` structure:
+
+1. A PyObject ``*fields`` member which contains a dictionary of "field
+   name" : (``PyArray_Descr`` ``*field-type``, ``offset``, [optional field
+   title]).  If a title is given, then it is also inserted into the
+   dictionary and used to key the same entry.
+
+2. A byteorder member.  By default this is '=' (native), or '|'
+   (not-applicable).
+
+3. An additional ``PyArray_ArrDescr`` ``*member`` of the structure which
+   contains a simple representation of an array of another base-type.
+   types. The ``PyArray_ArrayDescr`` structure has members
+   ``PyArray_Descr *``, ``PyObject *``, for holding a reference to
+   the base-type and the shape of the sub-array.
+
+4. The ``PyArray_Descr *`` as official Python object that fully describes
+   a region of memory for the data
+
+
+Data type conversions
+---------------------
+
+We can support additional data-type
+conversions.  The data-type passed in is converted to a
+``PyArray_Descr *`` object.
+
+New possibilities for the "data-type"
+`````````````````````````````````````
+
+**List [data-type 1, data-type 2, ..., data-type n]**
+  Equivalent to  {'names':['f1','f2',...,'fn'],
+	        'formats': [data-type 1, data-type 2, ..., data-type n]}
+
+  This is a quick way to specify a record format with default field names.
+
+
+**Tuple  (flexible type, itemsize) (fixed type, shape)**
+  Get converted to a new ``PyArray_Descr *`` object with a flexible
+  type. The latter structure also sets the ``PyArray_ArrayDescr`` field of the
+  returned ``PyArray_Descr *``.
+
+
+**Dictionary (keys "names", "titles", and "formats")**
+  This will be converted to a ``PyArray_VOID`` type with corresponding
+  fields parameter (the formats list will be converted to actual
+  ``PyArray_Descr *`` objects).
+
+
+**Objects (anything with an .itemsize and .fields attribute)**
+  If its an instance of (a sub-class of) void type, then a new
+  ``PyArray_Descr*`` structure is created corresponding to its
+  typeobject (and ``PyArray_VOID``) typenumber.  If the type is
+  registered, then the registered type-number is used.
+
+  Otherwise a new ``PyArray_VOID PyArray_Descr*`` structure is created
+  and filled ->elsize and ->fields filled in appropriately.
+
+  The itemsize attribute must return a number > 0. The fields
+  attribute must return a dictionary with at least "names" and
+  "formats" entries.  The "formats" entry will be converted to a
+  "proper" descr->fields entry (all generic data-types converted to
+  ``PyArray_Descr *`` structure).
+
+
+Reference counting for ``PyArray_Descr *`` objects.
+```````````````````````````````````````````````````
+
+Most functions that take ``PyArary_Descr *`` as arguments and return a
+``PyObject *`` steal the reference unless otherwise noted in the code:
+
+Functions that return ``PyArray_Descr *`` objects return a new
+reference.
+
+.. tip::
+
+  There is a new function  and a new method of array objects both labelled
+  dtypescr which can be used to try out the ``PyArray_DescrConverter``.
+