Example of using tracemalloc in Python

tracemalloc_example.py

>>> import tracemalloc
>>> import numpy as np

>>> def create_array(x, y):
>>>     x = x**2
>>>     y = y**3
>>>     return np.ones((x, y, 1024, 3), dtype=np.uint8)

>>> tracemalloc.start()
>>> ### Run application
>>> arr = create_array(30,10)
>>> ### take memory usage snapshot
>>> snapshot = tracemalloc.take_snapshot()
>>> top_stats = snapshot.statistics('lineno')

>>> ### Print top 10 files allocating the most memory
>>> print("[ Top 10 ]")
>>> for stat in top_stats[:10]:
>>>     print(stat)


[ Top 10 ]
/usr/local/lib/python3.7/dist-packages/numpy/core/numeric.py:192: size=2637 MiB, count=2, average=1318 MiB
/usr/lib/python3.7/threading.py:289: size=216 B, count=6, average=36 B
/usr/lib/python3.7/codeop.py:141: size=189 B, count=2, average=94 B
/usr/local/lib/python3.7/dist-packages/debugpy/_vendored/pydevd/pydevd.py:1532: size=144 B, count=2, average=72 B
/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py:2820: size=112 B, count=3, average=37 B
/usr/lib/python3.7/queue.py:182: size=80 B, count=1, average=80 B
/usr/lib/python3.7/queue.py:107: size=80 B, count=1, average=80 B
/usr/lib/python3.7/threading.py:1264: size=72 B, count=1, average=72 B
    
## ==================================================================================
##### Explanation #####
## count: Number of memory blocks (int)
## size: Total size of memory blocks in bytes (int)
## traceback: Traceback where the memory block was allocated, Traceback instance