generally O(1), which means they generally are rather fast
O(1) != fast. Roughly speaking big-o notation says how well a given operation scales based on the size of the input. So, it speaks to the realative speed of say an input of size 1000 vs input of size 10000. That having been said, I'd say that opening a file is not O(1), but probably O(n); opening n files takes n times as long as opening one file. Granted, each one is really fast, but it takes a finite amount of time. There can be operations that are O(1) that are slow. But such operations will be equally slow regardless of whether they're operating on one million. I'll end my pedantary now.

thor

Feel the white light, the light within
Be your own disciple, fan the sparks of will
For all of us waiting, your kingdom will come


In reply to Re^2: Intelligent logging by thor
in thread Intelligent logging by Muoyo

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