~~Jupyter ~~Python kernel seriously slower than ~~SageNB~~SageMath kernel

Hi, I just found the ~~Jupyter session ~~Python kernel is seriously slower than the ~~SageNB ~~SageMath one.

This was the snippet to reproduce:

```
# intersection profiling with Python session
from sage.all import *
def run(num):
cube = (polytopes.cube() * 37 / 45).change_ring(QQ)
for i in range(num):
hspace = Polyhedron(ieqs=[[1/2, 1/(i+1), 0, 0]]).change_ring(QQ)
intersection = hspace.intersection(cube)
%timeit run(100)
```

The timing ~~in SageNB ~~for SageMath kernel is `1 loop, best of 5: 186 ms per loop`

, while that ~~in Jupyter ~~for Python is `1 loop, best of 5: 7.07 s per loop`

. With this snippet I think no variable was cached. I also cprofiled a stand-alone .py file with the same lines (expect the `%timeit`

line), whose timing is close to the ~~Jupyter one. ~~Python kernel. Any idea what could cause this huge performance difference?