- Notifications
You must be signed in to change notification settings - Fork384
Conversation
…umber of children; refactor the profile file reading functions
fabianp commentedApr 7, 2017
Thanks for the pull request!. This looks good, but give me a couple of days to look into it as I'm currently travelling |
fabianp commentedApr 11, 2017
Why is pandas needed? Does this change the quality of the plots? I would like to maintain dependencies to the strict minimum ... |
fabianp commentedApr 11, 2017
(numpy is fine since its required by matplotlib anyway) |
rokroskar commentedApr 12, 2017
Right, pandas is not strictly needed and I also hesitate making another dependency. IMO the usability of the results is improved by putting them into a DataFrame. The user can then select only the PIDs they want, they can get averages, etc. It's a simple way to allow for a bit more customization. On the other hand, it's not really a dependency, since the only function that needs pandas is |
rokroskar commentedApr 12, 2017
oh oops, I guess I already added the try/except in my last commit... |
fabianp commentedApr 12, 2017 via email
I've seen the try block. However I would like to be able to plot withoutpandas.Also, add your name and contribution to the Readme if you want.Cheers …On Apr 12, 2017 9:59 AM, "Rok Roškar" ***@***.***> wrote: oh oops, I guess I already added the try/except in my last commit... — You are receiving this because you commented. Reply to this email directly, view it on GitHub <https://github.com/fabianp/memory_profiler/pull/140#issuecomment-293503093>, or mute the thread <https://github.com/notifications/unsubscribe-auth/AAQ8h3hgdhSAr4RuOoCEmW8r2xCPIfARks5rvIRtgaJpZM4M1qBd> . |
eamars commentedFeb 14, 2019 • edited
Loading Uh oh!
There was an error while loading.Please reload this page.
edited
Uh oh!
There was an error while loading.Please reload this page.
Hello Guys |
This pull request is an extension to#118 and#134 and tries to improve the ability to analyze child process memory consumption.
Changes/additions:
pidinstead of sequentially -- this is to ensure that we can properly track children of processes where the parent might continuously spawn many short-lived childrenconvert_mem_usage_to_dffunction which produces apandas.DataFramefrom a list returned bymemory_usagefor easier plotting and slicingmprofto monitor an existing process by providing a pidSide-effects:
read_mprofile_filefunction tomemory_profilerso that it can be used programaticallyread_mprofile_file_multiprocessfunction that reads a mprofile file and returns a list of timings identical to what you expect frommemory_usagememory_usage#139plot_filewhere plotting would fail when number of children > 6timeoutflag tomprof