Through some back & forth in conda and pip (fighting dependencies), I have been able to get PyPy 3.9 running with my ARM64 Debian system. So far I am seeing a performance decrease up to 2x. I have a series of REST API calls that encapsulate a single DB transaction - a mix of reads and writes. Most of it is leaning on SQL Alchemy, but we have been reaching for psycopg2 for some of the larger insert statements.
I was hoping to see some improvement in ORM performance (SQLAlchemy 1.3) - mainly in the bookkeeping side. Currently the app is about 60% Python app wait time and 40% DB wait time. We have a handful noisy areas which emit a lot of statements (Update 1 row at a time, 10000 times via ORM for example).
I also tried cProfiler to drill down, but as I've seen in Stack Overflow notes that profiler has a larger impact in PyPy over CPython.
What is the compatibility of PyPy with a typical web server deployment? I am currently looking at testing compatibility with Tornado -> SQL Alchemy -> psycopg2. It seems like the C-extensions are a common tripping point. I see the recommendation to use psycopg2cffi, but it seems that package's last release was 2019 :(
I was hoping to see some improvement in ORM performance (SQLAlchemy 1.3) - mainly in the bookkeeping side. Currently the app is about 60% Python app wait time and 40% DB wait time. We have a handful noisy areas which emit a lot of statements (Update 1 row at a time, 10000 times via ORM for example).
I also tried cProfiler to drill down, but as I've seen in Stack Overflow notes that profiler has a larger impact in PyPy over CPython.