Antoine Pitrou <pit...@free.fr> added the comment:
Here is a patch. Benchmark numbers:
* dumps():
./python -m timeit -s "import pickle, io; d={(x, 'a'): x for x in
range(10000)}" "pickle.dumps(d)"
-> before: 100 loops, best of 3: 7.47 msec per loop
-> after: 100 loops, best of 3: 2.45 msec per loop
* loads():
./python -m timeit -s "import pickle, io; d={(x, 'a'): x for x in
range(10000)}; d=pickle.dumps(d)" "pickle.loads(d)"
-> before: 100 loops, best of 3: 12.1 msec per loop
-> after: 100 loops, best of 3: 2.62 msec per loop
* dump():
./python -m timeit -s "import pickle, io; d={(x, 'a'): x for x in
range(10000)}" "pickle.dump(d, io.BytesIO())"
-> before: 100 loops, best of 3: 13.2 msec per loop
-> after: 100 loops, best of 3: 2.54 msec per loop
* load():
./python -m timeit -s "import pickle, io; d={(x, 'a'): x for x in
range(10000)}; d=pickle.dumps(d)" "pickle.load(io.BytesIO(d))"
-> before: 100 loops, best of 3: 12.7 msec per loop
-> after: 100 loops, best of 3: 11.6 msec per loop
As you can see, load() doesn't really benefit from the buffering improvements.
The three methods see quite massive speedups.
----------
Added file: http://bugs.python.org/file18778/pickle_optimizations4.diff
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