The webinar by Felix Zumstein on xlwings performance covers strategies to optimize Python calls within Excel, including minimizing cross-border calls using arrays, using raw values for faster data writing, and implementing a UDF server for Windows. It also discusses caching methods and application properties to improve performance. Code samples are provided on GitHub to illustrate these concepts.

1. xlwings Performance
Felix Zumstein, 25 June 2020
Webinar

2. Agenda
1. MinimizeCross Border Calls
2. Raw Values
3. UDF Server (Win only)
4. Caching
5. App Properties
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3. Code Samples
https://github.com/xlwings/xlwings-demo/tree/master/performance
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4. 1. Minimize Cross Border Calls

5. Minimize Cross Border Calls
• Use arrays (both in scriptsand UDFs)
– Nested lists, NumPy arrays, pandas DataFrames
• A goodworkflow is:
– read the data
– do the magic in Python
– write the results back
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6. 2. Raw Values

7. Raw Values
• Faster, especiallyfor writingbig DataFrames
• sheet['A1:B1'].raw_value = arr
• @xw.ret('raw') / @xw.arg('x', 'raw')
• Uses the platform-specificlow-level librarieswithoutthe convenience
layer, i.e. datacleaning!(pywin32 andappscript)
• Requires you to calculatethe dimension
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8. 3. UDF Server (Win only)

9. Use UDF Server
• Keeps Python sessionalive
• UsingRunPythonwill make it cross-platformcompatible,butyouneed to
”Restart UDF server” after each code change
• Windows-only:Use @xw.subdecorator andImport Subs like you import
UDFs
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10. 4. Caching

11. Caching
• Built-in:functools.lru_cache (leastrecently used)
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@lru_cache()
@xw.func
def slow():
time.sleep(5)
return 'done'
• Third-partypackages, e.g. cachetools

12. 5. App Properties

13. App Properties
• myapp.screen_updating = False
• myapp.calculation = 'manual'
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14. Thank You
Let’s connect: https://www.linkedin.com/in/felix-
zumstein