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  <songofaca...@gmail.com>


On Sun, Jul 9, 2017 at 11:08 PM, Bhavishya <bhavishyagop...@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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