3 ms·
I would have liked to see PyPy test for the sum function in the comparison. Update: Well this is interesting ;D time python test.py real 0m11.169s user 0m1
by Demiurge 13y ago
I would have liked to see PyPy test for the sum function in the comparison.
Update:
Well this is interesting ;D
time python test.py
real 0m11.169s
user 0m11.141s
sys 0m0.022s
time pypy test.py
real 0m0.259s
user 0m0.239s
sys 0m0.018s
cat test.py
def python_sum(y):
N = len(y)
x = y[0]
for i in xrange(1,N):
x += y[i]
return x
python_sum(xrange(100000000))
- paddy_m 13y agoTo be clear, you are comparing pure pypy vs pure python?
- freyrs3 13y agoYes, it is well known that allocating 100000000 PyObjects is slow.
- onalark 13y agoHi. I was reluctant to publish any results with PyPy because I am not an expert in working with their code base. If you'd like to look at the GrowCut benchmark being run on my Mac (Intel iCore 7 2.7 GHz) on PyPy vs. Anaconda Python (or even better, download and run it yourself), the gist is [here](https://gist.github.com/ahmadia/5638980 https://gist.github.com/ahmadia/5638980).