Used vancestors instead of abcs

4 files changed, 185 insertions, 184 deletions

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diff --git a/documentation.rst b/documentation.rst
index b373586..9ab8b16 100644
--- a/documentation.rst
+++ b/documentation.rst
@@ -16,22 +16,23 @@ Introduction
 -----------------------------------------
 
 The decorator module is over ten years old, but still alive and
-kicking. It is used by several frameworks (IPython, scipy,
-pyramid,...) and has been stable for a *long* time. It is your best
-option if you want to preserve the signature of decorated functions in
-a consistent way across Python releases. Version 4.0 is fully
-compatible with the past, except for one thing: support for Python 2.4
-and 2.5 has been dropped. That decision made it possible to use a
-single code base both for Python 2.X and Python 3.X. This is a *huge*
-bonus, since I could remove over 2,000 lines of duplicated
-documentation/doctests. Having to maintain separate docs for Python 2 and
-Python 3 effectively stopped any development on the module for several
-years. Moreover, it is now trivial to distribute the module as a wheel_
-since 2to3 is no more required. Since Python 2.5 has been released 9
-years ago, I felt that it was reasonable to drop the support for it. If you
-need to support ancient versions of Python, stick with the decorator
-module version 3.4.2.  This version supports all Python releases from
-2.6 up to 3.5, which currently is still in beta status.
+kicking. It is used by several frameworks (IPython, scipy, authkit,
+pylons, repoze, pycuda, sugar, ...) and has been stable for a *long*
+time. It is your best option if you want to preserve the signature of
+decorated functions in a consistent way across Python
+releases. Version 4.0 is fully compatible with the past, except for
+one thing: support for Python 2.4 and 2.5 has been dropped. That
+decision made it possible to use a single code base both for Python
+2.X and Python 3.X. This is a *huge* bonus, since I could remove over
+2,000 lines of duplicated documentation/doctests. Having to maintain
+separate docs for Python 2 and Python 3 effectively stopped any
+development on the module for several years. Moreover, it is now
+trivial to distribute the module as a wheel_ since 2to3 is no more
+required. Since Python 2.5 has been released 9 years ago, I felt that
+it was reasonable to drop the support for it. If you need to support
+ancient versions of Python, stick with the decorator module version
+3.4.2.  This version supports all Python releases from 2.6 up to 3.5,
+which currently is still in beta status.
 
 .. _wheel: http://pythonwheels.com/
 
@@ -41,11 +42,10 @@ What's new
 Since now there is a single manual for all Python versions, I took the
 occasion for overhauling the documentation. Therefore, even if you are
 an old time user, you may want to read the docs again, since several
-examples have been improved. The packaging has been improved and now
-I am also distributing the code in wheel format. The integration
-with setuptools has been improved and now you can use
-``python setup.py test`` to run the tests.
-A new utility function ``decorate(func,
+examples have been improved. The packaging has been improved and now I
+am also distributing the code in wheel format. The integration with
+setuptools has been improved and now you can use ``python setup.py
+test`` to run the tests.  A new utility function ``decorate(func,
 caller)`` has been added, doing the same job that in the past was done
 by ``decorator(caller, func)``. The old functionality is still there
 for compatibility sake, but it is deprecated and not documented
@@ -54,14 +54,14 @@ anymore.
 Apart from that, there is a new experimental feature. The decorator
 module now includes an implementation of generic (multiple dispatch)
 functions. The API is designed to mimic the one of
-`functools.singledispatch` but the implementation is much simpler and
-more general; moreover all the decorators involved preserve the
-signature of the decorated functions. For the moment the facility is
-there mostly to exemplify the power of the module. In the future it
-could change and/or be enhanced/optimized; on the other hand, it could
-even become deprecated. Such is the fate of experimental features. In
-any case it is very short and compact, so you can extract it for
-your own use. Take it as food for thought.
+`functools.singledispatch` but the implementation is much simpler;
+moreover all the decorators involved preserve the signature of the
+decorated functions. For the moment the facility is there mostly to
+exemplify the power of the module. In the future it could change
+and/or be enhanced/optimized; on the other hand, it could even become
+deprecated. Such is the fate of experimental features. In any case it
+is very short and compact, so you can extract it for your own
+use. Take it as food for thought.
 
 Usefulness of decorators
 ------------------------------------------------
@@ -1232,7 +1232,7 @@ would require to change the CPython implementation of functions and
 add an hook to make it possible to change their signature directly.
 That could happen in future versions of Python (see PEP 362_) and
 then the decorator module would become obsolete. However, at present,
-even in Python 3.4 it is impossible to change the function signature
+even in Python 3.5 it is impossible to change the function signature
 directly, therefore the ``decorator`` module is still useful.
 Actually, this is the main reasons why I keep maintaining
 the module and releasing new versions.
@@ -1285,7 +1285,6 @@ a (shallow) copy of the original function dictionary:
  'something else'
 
 .. _function annotations: http://www.python.org/dev/peps/pep-3107/
-.. _distribute: http://packages.python.org/distribute/
 .. _docutils: http://docutils.sourceforge.net/
 .. _pygments: http://pygments.org/
 
diff --git a/src/decorator.py b/src/decorator.py
index 6a40091..a7a5439 100644
--- a/src/decorator.py
+++ b/src/decorator.py
@@ -279,51 +279,51 @@ elif n_args == 4:  # (self, gen, args, kwds) Python 3.5
 contextmanager = decorator(ContextManager)
 
 
-# ######################### dispatch_on ############################ #
+# ############################ dispatch_on ############################ #
 
-class _ABCManager(object):
+class _VAManager(object):
     """
-    Manage a list of ABCs for each dispatch type. The list is partially
-    ordered by the `issubclass` comparison operator.
+    Manage a list of virtual ancestors for each dispatch type.
+    The list is partially ordered by the `issubclass` comparison operator.
     """
     def __init__(self, n):
         self.indices = range(n)
-        self.abcs = [[] for _ in self.indices]
+        self.vancestors = [[] for _ in self.indices]
 
     def insert(self, i, a):
         """
-        For each index `i` insert an ABC `a` in the corresponding list, by
-        keeping the partial ordering.
+        For each index `i` insert a virtual ancestor `a` in the corresponding
+        list, by keeping the partial ordering.
         """
-        abcs = self.abcs[i]
-        for j, abc in enumerate(abcs):
-            if issubclass(a, abc) and a is not abc:
-                abcs.insert(j, a)
+        vancestors = self.vancestors[i]
+        for j, va in enumerate(vancestors):
+            if issubclass(a, va) and a is not va:
+                vancestors.insert(j, a)
                 break
         else:  # less specialized
-            if a not in abcs:
-                abcs.append(a)
+            if a not in vancestors:
+                vancestors.append(a)
 
-    def get_abcs(self, types):
+    def get_vancestors(self, types):
         """
-        For each type get the most specialized ABC available; return a tuple
+        For each type get the most specialized VA available; return a tuple
         """
         class Sentinel(object):
             pass
-        abclist = [Sentinel for _ in self.indices]
-        for i, t, abcs in zip(self.indices, types, self.abcs):
-            for new in abcs:
+        valist = [Sentinel for _ in self.indices]
+        for i, t, vancestors in zip(self.indices, types, self.vancestors):
+            for new in vancestors:
                 if issubclass(t, new):
-                    old = abclist[i]
+                    old = valist[i]
                     if old is Sentinel or issubclass(new, old):
-                        abclist[i] = new
+                        valist[i] = new
                     elif issubclass(old, new):
                         pass
                     else:
                         raise RuntimeError(
                             'Ambiguous dispatch for %s instance: %s or %s?'
                             % (t.__name__, old.__name__, new.__name__))
-        return tuple(abclist)
+        return tuple(valist)
 
 
 # inspired from simplegeneric by P.J. Eby and functools.singledispatch
@@ -344,7 +344,7 @@ def dispatch_on(*dispatch_args):
             raise NameError('Unknown dispatch arguments %s' % dispatch_str)
 
         typemap = {}
-        abcman = _ABCManager(len(dispatch_args))
+        man = _VAManager(len(dispatch_args))
 
         def register(*types):
             "Decorator to register an implementation for the given types"
@@ -358,9 +358,9 @@ def dispatch_on(*dispatch_args):
                     raise TypeError(
                         '%s has not enough arguments (got %d, expected %d)' %
                         (f, n_args, len(dispatch_args)))
-                for i, t, abc in zip(abcman.indices, types, abcman.abcs):
+                for i, t, va in zip(man.indices, types, man.vancestors):
                     if isinstance(t, ABCMeta):
-                        abcman.insert(i, t)
+                        man.insert(i, t)
                 typemap[types] = f
                 return f
             return dec
@@ -369,17 +369,19 @@ def dispatch_on(*dispatch_args):
             "Dispatcher function"
             types = tuple(type(arg) for arg in dispatch_args)
             try:  # fast path
-                return typemap[types](*args, **kw)
+                f = typemap[types]
             except KeyError:
                 pass
+            else:
+                return f(*args, **kw)
             for types_ in itertools.product(*(t.__mro__ for t in types)):
                 f = typemap.get(types_)
                 if f is not None:
                     return f(*args, **kw)
 
-            # else look at the ABCs
-            if abcman.abcs:
-                f = typemap.get(abcman.get_abcs(types))
+            # else look at the virtual ancestors
+            if man.vancestors:
+                f = typemap.get(man.get_vancestors(types))
                 if f is not None:
                     return f(*args, **kw)
 
@@ -389,7 +391,7 @@ def dispatch_on(*dispatch_args):
         return FunctionMaker.create(
             func, 'return _f_(%s, %%(shortsignature)s)' % dispatch_str,
             dict(_f_=dispatch), register=register, default=func,
-            typemap=typemap, abcs=abcman.abcs, __wrapped__=func)
+            typemap=typemap, vancestors=man.vancestors, __wrapped__=func)
 
     gen_func_dec.__name__ = 'dispatch_on' + dispatch_str
     return gen_func_dec
diff --git a/src/tests/test.py b/src/tests/test.py
index 4c1c816..cbb8373 100644
--- a/src/tests/test.py
+++ b/src/tests/test.py
@@ -245,12 +245,12 @@ class TestSingleDispatch(unittest.TestCase):
         self.assertEqual(g(t), "tuple")
         if hasattr(c, 'ChainMap'):
             self.assertEqual(
-                [abc.__name__ for abc in g.abcs[0]],
+                [abc.__name__ for abc in g.vancestors[0]],
                 ['ChainMap', 'MutableMapping', 'MutableSequence', 'MutableSet',
                  'Mapping', 'Sequence', 'Set', 'Sized'])
         else:
             self.assertEqual(
-                [abc.__name__ for abc in g.abcs[0]],
+                [abc.__name__ for abc in g.vancestors[0]],
                 ['MutableMapping', 'MutableSequence', 'MutableSet',
                  'Mapping', 'Sequence', 'Set', 'Sized'])