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This advice seems to really highlight the difference between high level managed memory languages languages: those that fallback to native functions for perform
by joncampbelldev 9y ago
This advice seems to really highlight the difference between high level managed memory languages languages:
those that fallback to native functions for performance Vs those that work on a fast VM / compilation to native code.
it seems like the former gets some quick performance wins but results in being unable to use the language as intended in any remotely hot spots.
- fnord123 9y agoAn almost free FFI to C is one of python's best features. Using this great feature is definitely using it as intended.
- joncampbelldev 9y agoOnly if every python programmer can easily implement and distribute their own c functions for every performance hotspot they find in their program. This is the trade-off I was talking about, you cannot trust the language itself to be performant, you have to rely on others or jump through extra hoops. It's certainly one way to ensure you won't spend the time to fix performance issues until they're really biting you (premature optimisation quote goes here).