DyND-Python Release Notes
===================

DyND-Python 0.4.1
-----------------

 - Rename nd.arange to nd.range, the "a" prefix is unneeded because
   the nd namespace is always used.
 - Finish the rename of nd.ndobject to nd.array throughout the system.
 - Change string/bytes conversion and assignment to be similar to
   Python 3 on both Python 2 and 3.

DyND-Python 0.4.0
-----------------

 - Updates to notebooks and other documentation
 - Some API tweaks, like adding ndt.make_bytes_dtype
 - Rename nd.ndobject to nd.array
 - Add initial basic datetime type, with 64-bit int storage

DyND-Python 0.3.1
-----------------

 - Add dynd._lowlevel submodule which exposes low level details as
   ctypes function pointers and structures.
 - Rename var_dim from "VarDim" to "var" in dshape parsing/printing.
 - Rename fixedstruct to cstruct dtype, make it follow the C/C++
   layout properly.


DyND-Python 0.3.0
-----------------

 - Support Python 3.3 (Python 2.6, 2.7, 3.3 using one code base).
 - Implement more __*__ methods so ndobject integrates better in Python.
 - Add function nd.fields, which extracts fields from a struct array.
 - Rename cast_udtype to ucast.
 - Functions ndt.replace_udtype and ndt.extract_udtype for manipulating dtypes.
 - Improved var_dim support.
 - Implement a groupby function which produces a ragged array with a
   var_dim type.
 - More sophisticated initialization and assignment from Python objects.

DyND-Python 0.2.0
-----------------

 - Convert from a NumPy-style array/dtype data model to a datashape
   based approach. This unifies the treatment of dimensions and types.
 - Add a prototype computed fields mechanism, based on numpy/scipy expressions
 - Split the dynd.nd namespace into dynd.nd and dynd.ndt
 - Improved conversion to/from native Python types and NumPy arrays.
 - Add datashape to/from dynd types.
 - Add a typed JSON parsing function, that parses into an object of
   specified dtype.

DyND-Python 0.1.0
-----------------

This is the first preview release of dynd-python, a component of
of the Blaze project. Blaze will layer a broader distributed storage and
compute system on top of dynd-python, numpy, and other systems.

DyND-Python is a multi-dimensional array library for Python
which provides functionality augmenting the NumPy/Matplotlib/SciPy
computing stack. It is built using the libdynd library,
a C++ library which is also in preview release.

This initial release includes a basic dtype system, a multi-dimensional
array primitive, interoperability with NumPy, lazy evaluation,
and an early gfunc library supporting kernels provided via ctypes.

As a preview release, there are many bugs, missing features, and
features that will change drastically as development proceeds.
