PEP 209: Resolve dangling hyphens (#3344)

pep-0209.txt

@@ -12,9 +12,9 @@ Post-History:
 Abstract
 ========
 
-This PEP proposes a redesign and re-implementation of the multi-
-dimensional array module, Numeric, to make it easier to add new
-features and functionality to the module.  Aspects of Numeric 2
+This PEP proposes a redesign and re-implementation of the
+multi-dimensional array module, Numeric, to make it easier to add
+new features and functionality to the module.  Aspects of Numeric 2
 that will receive special attention are efficient access to arrays
 exceeding a gigabyte in size and composed of inhomogeneous data
 structures or records.  The proposed design uses four Python
@@ -128,8 +128,8 @@ Some planned features are:
         automatically handle alignment and representational issues
         when data is accessed or operated on.  There are two
         approaches to implementing records; as either a derived array
-        class or a special array type, depending on your point-of-
-        view.  We defer this discussion to the Open Issues section.
+        class or a special array type, depending on your point-of-view.
+        We defer this discussion to the Open Issues section.
 
 
 2.  Additional array types
@@ -265,8 +265,8 @@ The design of Numeric 2 has four primary classes:
         _ufunc.compute(slice, data, func, swap, conv)
 
     The 'func' argument is a CFuncObject, while the 'swap' and 'conv'
-    arguments are lists of CFuncObjects for those arrays needing pre-
-    or post-processing, otherwise None is used.  The data argument is
+    arguments are lists of CFuncObjects for those arrays needing pre- or
+    post-processing, otherwise None is used.  The data argument is
     a list of buffer objects, and the slice argument gives the number
     of iterations for each dimension along with the buffer offset and
     step size for each array and each dimension.