Incorporate measurement results.

pep-0393.txt

@@ -372,6 +372,25 @@ the iobench, stringbench, and json benchmarks see typically
 slowdowns of 1% to 30%; for specific benchmarks, speedups may
 happen as may happen significantly larger slowdowns.
 
+In actual measurements of a Django application ([2]_), significant
+reductions of memory usage could be found. For example, the storage
+for Unicode objects reduced to 2216807 bytes, down from 6378540 bytes
+for a wide Unicode build, and down from 3694694 bytes for a narrow
+Unicode build (all on a 32-bit system). This reduction came from the
+prevalence of ASCII strings in this application; out of 36,000 strings
+(with 1,310,000 chars), 35713 where ASCII strings (with 1,300,000
+chars). The sources for these strings where not further analysed;
+many of them likely originate from identifiers in the library, and
+string constants in Django's source code.
+
+In comparison to Python 2, both Unicode and byte strings need to be
+accounted. In the test application, Unicode and byte strings combined
+had a length of 2,046,000 units (bytes/chars) in 2.x, and 2,200,000
+units in 3.x. On a 32-bit system, where the 2.x build used 32-bit
+wchar_t/Py_UNICODE, the 2.x test used 3,620,000 bytes, and the 3.x
+build 3,340,000 bytes. This reduction in 3.x using the PEP compared
+to 2.x only occurs when comparing with a wide unicode build.
+
 Porting Guidelines
 ==================
 
@@ -435,6 +454,8 @@ References
 
 .. [1] PEP 393 branch
        https://bitbucket.org/t0rsten/pep-393
+.. [2] Django measurement results
+       http://www.dcl.hpi.uni-potsdam.de/home/loewis/djmemprof/
 
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