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The author complains about CPU-bound performance and then mentions PyPy but claims it's ecosystem is barren enough that the point stands. This claim is presente
by lvh 8y ago
The author complains about CPU-bound performance and then mentions PyPy but claims it's ecosystem is barren enough that the point stands. This claim is presented without evidence.
In practice it doesn't really show up: the cases where code is actually CPython-specific usually imply all the work is being done in highly optimized C bits. Hence, those programs, despite being run on CPython, aren't CPU-bound.
Finally: while this FUD is really pernicious because it used to be hard/impossible to get scientific code like numpy to run on PyPy, that hasn't been the case in a long time. Right now you can just pip install numpy and it'll just work.
- dnautics 8y agoIt will bite you when you don't expect it. When i work, we had a dev write a IO trace playback engine in Python to do some IO performance testing. We then deployed it on various platforms and got very strange results - eventually I noticed when TOPing the node, the CPU was pegged at 100%, so this wasted about 2 months time of about ~4 developers