Well, then. I think I'm going to have some fun with this. :) Thank you!
On Thu, Jun 27, 2019 at 4:17 PM Victor Stinner <vstin...@redhat.com> wrote: > Le ven. 28 juin 2019 à 01:03, Yonatan Zunger <zun...@humu.com> a écrit : > > Although while I have you hear, I do have a further question about how > tracemalloc works: If I'm reading the code correctly, traces get removed by > tracemalloc when objects are free, which means that at equilibrium (e.g. at > the end of a function) the trace would show just the data which leaked. > That's very useful in most cases, but I'm trying to hunt down a situation > where memory usage is transiently spiking -- which might be due to > something being actively used, or to something building up and overwhelming > the GC, or to evil elves in the CPU for all I can tell so far. Would it be > completely insane for tracemalloc to have a mode where it either records > frees separately (e.g. as a malloc of negative space, at the trace where > the free is happening), or where it simply ignores frees altogether? > > My very first implementation of tracemalloc produced a log of malloc > and free calls. Problem: transferring the log from a slow set top box > to a desktop computer was slow, and parsing the log was very slow. > Parsing complexity is in O(n) where n is the number of malloc or free > calls, knowning that Python calls malloc(), realloc() or free() > 270,000 times per second in average: > https://www.python.org/dev/peps/pep-0454/#log-calls-to-the-memory-allocator > > tracemalloc is built on top of PEP 445 -- Add new APIs to customize > Python memory allocators: > https://www.python.org/dev/peps/pep-0445/ > > Using these PEP 445 hooks, you should be able to do whatever you want > on Python memory allocations and free :-) > > Example of toy project to inject memory allocation failures: > https://github.com/vstinner/pyfailmalloc > > Victor >
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