Re: cProfile, timed call tree

On 2018-05-30 07:45:07 +0200, dieter wrote: > "Peter J. Holzer" writes: > > On 2018-05-26 07:38:09 +0200, dieter wrote: > >> But, in general, you are right: you cannot reconstruct complete > >> call trees. The reason is quite simple: maintaining information > >> for the complete caller ancestry

Re: cProfile, timed call tree

"Peter J. Holzer" writes: > On 2018-05-26 07:38:09 +0200, dieter wrote: >> But, in general, you are right: you cannot reconstruct complete >> call trees. The reason is quite simple: maintaining information >> for the complete caller ancestry (rather than just the immediate >> caller) is

Re: cProfile, timed call tree

On 2018-05-26 07:38:09 +0200, dieter wrote: > But, in general, you are right: you cannot reconstruct complete > call trees. The reason is quite simple: maintaining information > for the complete caller ancestry (rather than just the immediate > caller) is expensive (both in terms of runtime and

Re: cProfile, timed call tree

Thanks, Dieter, for the concise answer. Cheers, Nico On Sat, May 26, 2018 at 7:42 AM dieter wrote: > Nico Schlömer writes: > > > From what I understand about the Python profilers, the type of > information > > you get from a stats object is > > >

Re: cProfile, timed call tree

Nico Schlömer writes: > From what I understand about the Python profilers, the type of information > you get from a stats object is > > * How much time was spent in function X, > * what the callers and callees of function X are, and > * and bunch of meta info

cProfile, timed call tree

Hi everyone, >From what I understand about the Python profilers, the type of information you get from a stats object is * How much time was spent in function X, * what the callers and callees of function X are, and * and bunch of meta info about function X. With the program ``` def