Post 2.6.3 release actions done

ANNOUNCE.rst

@@ -1,9 +1,4 @@
-=========================
- Announcing Numexpr 2.6.3
-=========================
-
-What's new
-==========
+Hi everyone, 
 
 This is primarily a maintenance release that fixes a number of newly discovered
 bugs. The NumPy requirement has increased from 1.6 to 1.7 due to changes with 
@@ -14,14 +9,27 @@ Project documentation is now available at:
 
 http://numexpr.readthedocs.io/
 
-In case you want to know more in detail what has changed in this
-version, see:
-
-https://github.com/pydata/numexpr/blob/master/RELEASE_NOTES.rst
-
-
-What's Numexpr
-==============
+==========================
+ Announcing Numexpr 2.6.3
+==========================
+
+Changes from 2.6.2 to 2.6.3
+---------------------------
+
+- Documentation now available at numexpr.readthedocs.io
+- Support for floor() and ceil() functions added by Caleb P. Burns.
+- NumPy requirement increased from 1.6 to 1.7 due to changes in iterator
+  flags (#245).
+- Sphinx autodocs support added for documentation on readthedocs.org.
+- Fixed a bug where complex constants would return an error, fixing 
+  problems with `sympy` when using NumExpr as a backend.
+- Fix for #277 whereby arrays of shape (1,...) would be reduced as 
+  if they were full reduction. Behavoir now matches that of NumPy.
+- String literals are automatically encoded into 'ascii' bytes for 
+  convience (see #281).
+
+What's Numexpr?
+---------------
 
 Numexpr is a fast numerical expression evaluator for NumPy.  With it,
 expressions that operate on arrays (like "3*a+4*b") are accelerated
@@ -40,7 +48,7 @@ easy-to-deploy, easy-to-use, computational engine for projects that
 don't want to adopt other solutions requiring more heavy dependencies.
 
 Where I can find Numexpr?
-=========================
+-------------------------
 
 The project is hosted at GitHub in:
 
@@ -50,8 +58,12 @@ You can get the packages from PyPI as well (but not for RC releases):
 
 http://pypi.python.org/pypi/numexpr
 
+Documentation is hosted at:
+
+http://numexpr.readthedocs.io/en/latest/
+
 Share your experience
-=====================
+---------------------
 
 Let us know of any bugs, suggestions, gripes, kudos, etc. you may
 have.

README.rst

@@ -1,5 +1,5 @@
 ======================================================
-Numexpr: Fast numerical expression evaluator for NumPy
+NumExpr: Fast numerical expression evaluator for NumPy
 ======================================================
 
 :Author: David M. Cooke, Francesc Alted and others
@@ -8,25 +8,23 @@ Numexpr: Fast numerical expression evaluator for NumPy
 :Documentation: http://numexpr.readthedocs.io/en/latest/
 :Travis CI: |travis|
 :Appveyor: |appveyor|
-:PyPi: |version| |pypi|
+:PyPi: |version|
 :readthedocs: |docs|
 
 .. |travis| image:: https://travis-ci.org/pydata/numexpr.png?branch=master
         :target: https://travis-ci.org/pydata/numexpr
 .. |appveyor| image:: https://ci.appveyor.com/api/projects/status/github/pydata/numexpr
         :target: https://ci.appveyor.com/project/pydata/numexpr
-.. |pypi| image:: https://img.shields.io/pypi/dm/numexpr.png
-        :target: https://pypi.python.org/pypi/numexpr
 .. |docs| image:: https://media.readthedocs.org/static/projects/badges/passing.svg
         :target: http://numexpr.readthedocs.io/en/latest
 .. |version| image:: https://img.shields.io/pypi/v/numexpr.png
         :target: https://pypi.python.org/pypi/numexpr
 
 
-What it is Numexpr?
--------------------
+What is NumExpr?
+----------------
 
-Numexpr is a fast numerical expression evaluator for NumPy.  With it,
+NumExpr is a fast numerical expression evaluator for NumPy.  With it,
 expressions that operate on arrays (like :code:`'3*a+4*b'`) are accelerated
 and use less memory than doing the same calculation in Python.
 
@@ -39,15 +37,15 @@ Library, normally integrated in its Math Kernel Library, or MKL).
 This allows further acceleration of transcendent expressions.
 
 
-How Numexpr achieves high performance
+How NumExpr achieves high performance
 -------------------------------------
 
-The main reason why Numexpr achieves better performance than NumPy is
+The main reason why NumExpr achieves better performance than NumPy is
 that it avoids allocating memory for intermediate results. This
 results in better cache utilization and reduces memory access in
-general. Due to this, Numexpr works best with large arrays.
+general. Due to this, NumExpr works best with large arrays.
 
-Numexpr parses expressions into its own op-codes that are then used by
+NumExpr parses expressions into its own op-codes that are then used by
 an integrated computing virtual machine. The array operands are split
 into small chunks that easily fit in the cache of the CPU and passed
 to the virtual machine. The virtual machine then applies the
@@ -56,20 +54,20 @@ constants in the expression are also chunked. Chunks are distributed among
 the available cores of the CPU, resulting in highly parallelized code 
 execution.
 
-The result is that Numexpr can get the most of your machine computing
+The result is that NumExpr can get the most of your machine computing
 capabilities for array-wise computations. Common speed-ups with regard
 to NumPy are usually between 0.95x (for very simple expressions like
 :code:`'a + 1'`) and 4x (for relatively complex ones like :code:`'a*b-4.1*a >
 2.5*b'`), although much higher speed-ups can be achieved for some functions 
 and complex math operations (up to 15x in some cases).
 
-Numexpr performs best on matrices that are too large to fit in L1 CPU cache. 
+NumExpr performs best on matrices that are too large to fit in L1 CPU cache. 
 In order to get a better idea on the different speed-ups that can be achieved 
 on your platform, run the provided benchmarks.
 
 
-Examples of use
----------------
+Usage
+-----
 
 ::
 
@@ -105,15 +103,13 @@ Included is a user guide, benchmark results, and the reference API.
 Authors
 -------
 
-.. include:: AUTHORS.TXT
+Please see `AUTHORS.txt <https://github.com/pydata/numexpr/blob/master/AUTHORS.txt>`_.
 
 
 License
 -------
 
-NumExpr is distributed under the MIT_ license.
-
-.. _MIT: http://www.opensource.org/licenses/mit-license.php
+NumExpr is distributed under the `MIT <http://www.opensource.org/licenses/mit-license.php>`_ license.
 
 
 .. Local Variables:

RELEASE_NOTES.rst

@@ -2,6 +2,11 @@
  Release notes for Numexpr 2.6 series
 =====================================
 
+Changes from 2.6.3 to 2.6.4
+---------------------------
+
+  #XXX version-specific blurb XXX#
+
 Changes from 2.6.2 to 2.6.3
 ---------------------------
 

numexpr/version.py

@@ -8,4 +8,4 @@
 #  rights to use.
 ####################################################################
 
-version = '2.6.3'
+version = '2.6.4dev0'