BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//pretalx//talks.python-summit.ch//swiss-python-summit-2026//speak
 er//KNSPQL
BEGIN:VTIMEZONE
TZID:Europe/Zurich
BEGIN:DAYLIGHT
DTSTART:20251022T000000
TZNAME:CEST
TZOFFSETFROM:+0200
TZOFFSETTO:+0200
END:DAYLIGHT
BEGIN:STANDARD
DTSTART:20251026T030000
RDATE:20261025T030000
TZNAME:CET
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
END:STANDARD
BEGIN:DAYLIGHT
DTSTART:20260329T030000
RDATE:20270328T030000
TZNAME:CEST
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
END:DAYLIGHT
END:VTIMEZONE
BEGIN:VEVENT
SUMMARY:Your Code Is Slower Than Expected - Hidden Performance Traps - Mic
 hael Inden
DTSTART;TZID=Europe/Zurich:20261022T091000
DTEND;TZID=Europe/Zurich:20261022T094000
DTSTAMP:20261111T040113Z
UID:pretalx-swiss-python-summit-2026-TLBGRU@talks.python-summit.ch
DESCRIPTION:Python makes it easy to write clean and expressive code — bu
 t it also makes it easy to write code that is unexpectedly slow.\n\nIn thi
 s talk\, we’ll look at everyday Python patterns that seem harmless but c
 an have serious performance implications. Why is x in list sometimes drama
 tically slower than expected? What’s the real difference between append(
 )\, +=\, and +? And when does a simple data structure choice turn an O(n) 
 solution into O(n²)?\n\nInstead of focusing on micro-optimizations\, we
 ’ll go one level deeper: how Python’s core data structures (lists\, se
 ts\, dictionaries) actually work under the hood — and how that directly 
 impacts runtime behavior.\n\nYou’ll leave with a practical mental model 
 and a small set of rules of thumb that help you write code that is not jus
 t correct and readable\, but also efficient — without premature optimiza
 tion.
LOCATION:Aula 4.101
URL:https://talks.python-summit.ch/swiss-python-summit-2026/talk/TLBGRU/
END:VEVENT
END:VCALENDAR