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SUMMARY:Immutability: Safe and Fast Sharing of Data Across Threads - Fridt
 jof Stoldt
DTSTART;TZID=Europe/Stockholm:20261119T113000
DTEND;TZID=Europe/Stockholm:20261119T120000
DTSTAMP:20261111T055034Z
UID:pretalx-pycon-sweden-2026-3HZ7NE@pretalx.com
DESCRIPTION:Python is becoming more parallel with Free-Threading and Subin
 terpreters. Both approaches allow threads to run in parallel without the r
 estriction of a single GIL. The downside is that parallelization comes wit
 h a safety tax: Free-threading adds a lock per object and subinterpreters 
 typically involve pickling and copying data between interpreters to ensure
  isolation. This has a negative impact on performance with both CPU and me
 mory overheads. This talk is about PEP795\, which proposes to add immutabi
 lity to Python. It allows threads to share data without the risk of data r
 aces. This enables different optimisations: on free-threaded Python\, inte
 rpreter-level synchronisation is no longer needed to ensure safe access to
  shared data structures (think PEP frozendict but for any type)\, it allow
 s multiple subinterpreters to directly share objects without copying\, and
  it improves GC performance by simplifying cycle detection.\n\nWe will pre
 sent the design and rationale for immutability in Python\, the API for cre
 ating and managing immutable state\, decorators for communicating immutabi
 lity in code\, as well as opting out of immutability where necessary. We w
 ill also discuss our prototype implementation on-top of Python 3.15 and de
 monstrate how immutable sharing across sub-interpreters improves performan
 ce and compare the speed of freezing (the act of making objects immutable)
  to pickling and unpickling.\n\nThis is an updated version of our immutabi
 lity talk at EuroPython'26 based on feedback from the Python community.
LOCATION:Auditorium
URL:https://pretalx.com/pycon-sweden-2026/talk/3HZ7NE/
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