The document discusses performance profiling tools for Python applications, highlighting tools such as py-spy and repoze.profile for analyzing performance issues. It details improvements made in Plone versions 5.2.1 to 5.2.3, including optimizations in caching and memory consumption. Future considerations include optimizing plone.restapi and reducing unnecessary calls to plone.registry.

1. Performance
https://www.deviantart.com/cannikin1701/art/Discovery-sSpore-Jump-719880707

8. How to find
the performance problem?
Tools

9. Tools mainly used
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py-spy
runtime profiler for Python programs
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repoze.profile
Python profiler integration with WSGI
●
dis
Disassembler for Python bytecode

10. py-spy
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Overall mix of the whole application performance
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Unix „top“ like output of running python program
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recording mode: for later analyzing
●
Able to attach to live process w/o slowing down
Plone

11. repoze.profile
●
Python profiler integration as WSGI
middleware
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Slows down the application
●
Ability to profile a single request and
analyse its call stack by count/ single call
time, accumulated time/ callee/ caller

12. Plone 5.2.0 to 5.2.3
plone.dexterity
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avoid early providedBy calls
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__getattr__ early exit on common attrs
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caches optimized: assignable, schema cache
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removal of superfluos threadlocal sync

13. Plone 5.2.1 to 5.2.2
zope.interface
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~1.25x -1.5x __hash__ override removals on
Implementer leftover
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~1.25x __hash__ improvement InterfaceClass
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~5x lookup/lookupAll/subscriptions
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memory consumption reduced (jmadden)

14. DEMO TIME

15. Future Todo‘s
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plone.restapi has optimization potential
→ all navigation related
●
plone.registry is called too often
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Use „python:“ expressions in all page
templates
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More introspection

16. Advice:
Start introspecting your performance!
Virtual hugs and stay healthy!
(Q&A at Jitsi face2face as announced)