Cuni: Tracing JITs in the real world @ CPython Core Dev Sprint

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:

  1. JITted code can be very fast if your code conforms to the heuristics applied by the JIT compiler, but unexpectedly slow(-ish) otherwise;
  2. 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.

[$] The phaseout of the mmap() file operation

The file_operations
structure in the kernel is a set of function pointers implementing, as the
name would suggest, operations on files. A subsystem that manages objects
which can be represented by a file descriptor will provide a
file_operations structure providing implementations of the various
operations that a user of the file descriptor may want to carry out. The
mmap() method, in particular, is invoked when user space calls the
mmap()
system call to map the object behind a file descriptor into its address
space. That method, though, is currently on its way out in a multi-release
process that started in 6.17.

Fedora considers an AI-tool policy

The Fedora project has posted a
proposal
for a policy regarding the use of AI tools when developing for
the distribution.

You are responsible for your contributions. AI-generated
content must be treated as a suggestion, not as final code or
text. It is your responsibility to review, test, and understand
everything you submit. Submitting unverified or low-quality
machine-generated content (sometimes called “AI slop”) creates an
unfair review burden on the community and is not an acceptable
contribution.

Intel Posts New Linux Patches To Reduce Overhead Of VMSCAPE Mitigation

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Qualcomm Begins Posting Linux Patches For Snapdragon X2 Elite, 8 Elite Gen 5 SoCs

Yesterday at the Snapdragon Summit in Hawaii Qualcomm announced the Snapdragon X2 Elite SoCs for upcoming laptops. In addition Qualcomm announced the Snapdragon 8 Elite Gen 5 mobile platform too. With those announcements out there, the Qualcomm open-source engineers have been busy in rolling out their latest patches for beginning to enable these new platforms with the Linux kernel…