https://rushter.com/blog/python-memory-managment/
https://rushter.com/blog/python-garbage-collector/
https://dzone.com/articles/python-memory-issues-tips-and-tricks
Main features:
Line by line memory usage. By decorating a function you can get information about the memory usage in each line of code.
Time based memory usage. mprof run run_service --app-ini= export. It will execute the export service and analyze the memory usage. To plot it: mprof plot
This profiler helps you find the peak memory usage of the application. It will generate a waterfall style graph where you can see the stack trace of the most memory consuming parts of the application. Run like this: fil-profile run run_service --app-ini= export
Dumping or Diffing memory object status - https://pythonhosted.org/Pympler/muppy.html
https://medium.com/zendesk-engineering/hunting-for-memory-leaks-in-python-applications-6824d0518774
http://tech.labs.oliverwyman.com/blog/2008/11/14/tracing-python-memory-leaks/
https://pythonspeed.com/articles/python-server-memory-leaks/
https://pythonhosted.org/Pympler/muppy.html
https://github.com/P403n1x87/austin - Connect to preview