... | ... | @@ -13,7 +13,7 @@ Related issue: #8837. |
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* (2013) [From the creator of memory_profiler ](http://fa.bianp.net/blog/2013/different-ways-to-get-memory-consumption-or-lessons-learned-from-memory_profiler/), resource is a bit faster than psutil, but possibly less accurate. Spawning `ps` is some orders of magnitude slower.
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* (2014) In a [comment about memory_profiler](http://www.marinamele.com/7-tips-to-time-python-scripts-and-control-memory-and-cpu-usage), this person says 2 important things: (1) that memory_profiler is faster if psutil is installed, and (2) that measuring memory influences time. *Maybe tests that measure memory and cpu should be run separatelly from tests that measure time.*
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* [This person says that](http://www.marinamele.com/7-tips-to-time-python-scripts-and-control-memory-and-cpu-usage) "[memory_profiler] is extremelly useful if you're wanting to profile a section of memory-intensive code, but it won't help much if you have no idea where the biggest memory usage is. In that case, a higher-level approach of profiling is needed first". Also, "memory_profiler comes with a script called *mprof*, which can show you memory usage over the lifetime of your application. This can be useful if you want to see if your memory is getting cleaned up and released periodically".
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* [This person says that](https://www.pluralsight.com/guides/python/profiling-memory-usage-in-python) "[memory_profiler] is extremelly useful if you're wanting to profile a section of memory-intensive code, but it won't help much if you have no idea where the biggest memory usage is. In that case, a higher-level approach of profiling is needed first". Also, "memory_profiler comes with a script called *mprof*, which can show you memory usage over the lifetime of your application. This can be useful if you want to see if your memory is getting cleaned up and released periodically".
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## Scenarios
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