Thanks for your answer!
I read the link [0] and run such benchmarks, finding that slow performance on
allocate_tuple still exists now. On my cpu, it was 0.65s for cpython3.8, and
7.6s for PyPy 3.9. I am wondering if this could lead to the undesired low
performance on pandas.
As for my code
Hello pypy experts!
What I want to do is to run a performance test on the cpyext module. The
translation procedure took about 1 hour on my computer. After I
modifying some code( just a slight modification under pypy/modules/cpyext), the
whole translation procedure seemed to restart
I found one operation leading to the speed decrement.When inputs are a list
of dictionaries, pandas will firstly convert them to a series of numpy.ndarray.
This conversion might be slow when using PyPy.
I made a small example inside the micro benchmark project like this:
