Cuni: Tracing JITs in the real world @ CPython Core Dev Sprint
Date:
Thu, 25 Sep 2025 19:13:19 +0000
Description:
Longtime PyPy developer Antonio Cuni has a lengthy
blog post that describes his talk at the recently completed 2025
CPython
Core Dev Sprint , held at Arm in Cambridge, UK.  The talk, entitled
"Tracing JIT and real world Python  aka: what we can learn from PyPy" was
meant to try to pass on some of his experiences " optimizing existing
code for PyPy at a high-frequency trading firm " to the
developers working on the CPython JIT compiler .  His goal was
to raise awareness of some of the problems he encountered: Until now 
CPython's performance has been particularly predictable, there are well  established "performance tricks" to make code faster, and generally speaking  you can mostly reason about the speed of a given piece of code "locally".  Adding a JIT completely changes how we reason about performance of a given  program, for two reasons: JITted code can be very fast if your code conforms  to the heuristics applied by the JIT compiler, but unexpectedly slow(-ish)  otherwise; the speed of a given piece of code might depend heavily on what
    happens elsewhere in the program, making it much harder to reason about
    performance locally. The end result is that modifying a line of code can  significantly impact seemingly unrelated code. This effect becomes more  pronounced as the JIT becomes more sophisticated. Cuni also gave a talk on  Python performance, which LWN covered , at
EuroPython 2025 in July.
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Link to news story:
https://lwn.net/Articles/1039612/
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