Release 1.52.0

[SVN r81201]

doc/projects.html

@@ -396,33 +396,27 @@
       </blockquote>
     </dd>
 
-    <dt><b><a href="http://pyrap.googlecode.com/">Pyrap</a></b></dt>
-    <dd>
-      <p><a href="diepen@astron.nl"
-        >Ger van Diepen</a> writes:</p>
-
-      <blockquote>
-        <p>Pyrap is the python interface to the Radio-Astronomical Package
-        casacore (<a href="http://casacore.googlecode.com/"
-        >casacore.googlecode.com</a>). Astronomers love pyrap because
-        it makes it easily possible to get their data (observed with
-        radio-astronomical telescopes like LOFAR, ASKAP, and eVLA) in numpy
-        arrays and do basic data inspection and manipulation using the many
-        python packages that are available.</p>
-
-        <p>Boost.Python made it quite easily possible to create converters for
-        the various data types, also for numpy arrays and individual elements
-        of a numpy array. It's nice they work fully recursively. Mapping C++
-        functions to Python was straightforward.</p>
-      </blockquote>
-    </dd>
-
-    <dt><b><a href="http://www.rdkit.org/"
-           >RDKit: Cheminformatics and Machine Learning Software</a></b></dt>
+    <dt><b><a href="http://www.rationaldiscovery.com">Rational Discovery
+    LLC</a></b></dt>
 
     <dd>
-      A collection of cheminformatics and machine-learning software
-      written in C++ and Python.
+      Rational Discovery provides computational modeling, combinatorial
+      library design and custom software development services to the
+      pharmaceutical, biotech and chemical industries. We do a substantial
+      amount of internal research to develop new approaches for applying
+      machine-learning techniques to solve chemical problems. Because we're a
+      small organization and chemistry is a large and complex field, it is
+      essential that we be able to quickly and easily prototype and test new
+      algorithms.
+
+      <p>For our internal software, we implement core data structures in C
+      and expose them to Python using Boost.Python. Algorithm development is
+      done in Python and then translated to C if required (often it's not).
+      This hybrid development approach not only greatly increases our
+      productivity, but it also allows "non-developers" (people without C
+      experience) to take part in method development. Learning C is a
+      daunting task, but "Python fits your brain." (Thanks to Bruce Eckel for
+      the quote.)</p>
     </dd>
   </dl>
 

src/converter/builtin_converters.cpp

@@ -377,8 +377,7 @@ namespace
       static unaryfunc* get_slot(PyObject* obj)
       {
 #if PY_VERSION_HEX >= 0x03000000
-          return (PyUnicode_Check(obj)) ? &py_unicode_as_string_unaryfunc : 
-                  PyBytes_Check(obj) ? &py_object_identity : 0;
+          return (PyUnicode_Check(obj)) ? &py_unicode_as_string_unaryfunc : 0;
 #else
           return (PyString_Check(obj)) ? &obj->ob_type->tp_str : 0;