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UID:pretalx-2025-9WUFNR@cfp.in.pycon.org
DTSTART;TZID=IST:20250913T121000
DTEND;TZID=IST:20250913T124000
DESCRIPTION:Memory management in Python is mostly automatic - but not invis
 ible. From reference cycles and unexpected leaks to costly object growth a
 nd GC pauses\, memory issues still affect real-world Python applications. 
 Understanding how Python allocates\, tracks\, and reclaims memory is key t
 o writing efficient and predictable programs - especially for long-running
  services\, data-heavy scripts\, or performance-sensitive tools.\n\nThis t
 alk starts from first principles - how reference counting and garbage coll
 ection work - then builds up to real-world issues like circular references
 \, hidden object retention\, and finalizer behavior. We’ll explore moder
 n tools like tracemalloc and pympler for memory diagnostics\, and cover pr
 actical techniques like using __slots__\, generators\, and object reuse pa
 tterns. A live demo will walk through detecting and fixing a subtle memory
  leak. The goal is to make memory behavior in Python understandable\, meas
 urable\, and improvable.
DTSTAMP:20260317T120000Z
LOCATION:Track 3
SUMMARY:Memory Management in Python: Foundations\, Problems\, and Modern Te
 chniques - Jithu Sunny
URL:https://cfp.in.pycon.org/2025/talk/9WUFNR/
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