I don't know this is relating to your case. When I saw Victor's report [1], I researched why Python 3 is slower than Python 2 on unpickle_pure_python benchmark. [1] https://mail.python.org/pipermail/speed/2017-February/000503.html And I found Python 2 and 3 uses different version of pickle format. Current Python 3 uses "framing" format. While unpickling, `read(1)` is very performance critical. Python 2 uses `cStringIO.read` which is implemented in C. On the other hand, Python 3 uses `_Unframer.read` which is implemented in Python. Since this is not relating to "first import time", I don't know this is what you want to optimize. (Since _pickle is used for normal case, pure Python unpickle performance is not a common problem). If you want to optimize it, _Unframer uses BytesIO internally and performance critical part may be able to call BytesIO.read directly instead of _Unframer.read. Regards, INADA Naoki <songofacandy at gmail.com> On Sun, Jul 9, 2017 at 11:08 PM, Bhavishya <bhavishyagopesh at gmail.com> wrote: > Hello, > > 1).I was going through the code of python pickle to search any optimization > possibility.But the only thing that I found very alarming was again the > import time(I tried with lazy-import but it didn't helped much.) > > I found py3 to be ~45 times slower on initial imports(very raw > measure..using "time." ) as compared to py2 on an usual example. > > py3-> > ./python -c ' > favorite_color = { "lion": "yellow", "kitty": "red" } > pickle.dump( favorite_color, open( "save.p", "wb" ) )' > 0.009715557098388672(time taken to do initial imports...measured using > time.time() ) > > py2-> > ./python -c ' > favorite_color = { "lion": "yellow", "kitty": "red" } > pickle.dump( favorite_color, open( "save.p", "wb" ) )' > 0.000236034393311(time taken to do initial imports...measured using > time.time() ) > > Do you have any thought/ideas on improving this? > > > Thank You.
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