I have found PyPy wins if the wall time is over about 1.5 seconds, making it my goto Python environment for 1GB+ ETLs.
Everything you say is true, but under the systems I use/write I am able to test for correctness pretty quickly. The nice thing about switching from CPython to PyPy is that everything get faster. I have also found that using PyPy has removed lots of cases where I would want to drop down to native code.
Changing platforms can make one's designs simpler and more robust. When it comes to structured storage, I'll start with sqlite, then when it starts to get slow I'll switch to PostgreSQL. It takes almost no work to port from one to the other.
You really should give PyPy another shot. It supports more of numpy every day and the startup time is excellent. Maybe give jitpy a try if you are not likely to move off of CPython.
Everything you say is true, but under the systems I use/write I am able to test for correctness pretty quickly. The nice thing about switching from CPython to PyPy is that everything get faster. I have also found that using PyPy has removed lots of cases where I would want to drop down to native code.
Changing platforms can make one's designs simpler and more robust. When it comes to structured storage, I'll start with sqlite, then when it starts to get slow I'll switch to PostgreSQL. It takes almost no work to port from one to the other.
You really should give PyPy another shot. It supports more of numpy every day and the startup time is excellent. Maybe give jitpy a try if you are not likely to move off of CPython.