mprof run mem_profiled.py
mprof plot
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September 14, 2018 18:46
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Using memory_profiler in Python
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| @profile | |
| def benchmark_memory(): | |
| sum=0 | |
| a=[] | |
| for n in list(range(100000)): | |
| sum +=1 | |
| a.append(n) | |
| if __name__ == '__main__': | |
| benchmark_memory() |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| def benchmark_memory(): | |
| sum=0 | |
| a=[] | |
| for n in list(range(100000)): | |
| sum +=1 | |
| a.append(n) | |
| if __name__ == '__main__': | |
| benchmark_memory() |
pip -m install memory_profiler
from memrun import benchmark_memory
%load_ext memory_profiler
%mprun -f benchmark_memory benchmark_memory()
Filename: memrun.py
Line # Mem usage Increment Line Contents
================================================
3 30.0 MiB 30.0 MiB def benchmark_memory():
4 30.0 MiB 0.0 MiB sum=0
5 30.0 MiB 0.0 MiB a=[]
6 32.3 MiB 1.5 MiB for n in list(range(100000)):
7 32.3 MiB 0.1 MiB sum +=1
8 32.3 MiB 0.8 MiB a.append(n)
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