Sometimes, we want to profile memory usage in Python.
In this article, we’ll look at how to profile memory usage in Python.
How to profile memory usage in Python?
To profile memory usage in Python, we can use the guppy module.
For instance, we write:
from guppy import hpy
h = hpy()
heap = h.heap()
print(heap)
We call hpy to return an object with the heap method.
heap returns a string with the memory usage data in a string.
Therefore, heap is something like:
Partition of a set of 35781 objects. Total size = 4143541 bytes.
Index Count % Size % Cumulative % Kind (class / dict of class)
0 10581 30 946824 23 946824 23 str
1 7115 20 494688 12 1441512 35 tuple
2 2534 7 447560 11 1889072 46 types.CodeType
3 5001 14 354149 9 2243221 54 bytes
4 449 1 349104 8 2592325 63 type
5 2337 7 317832 8 2910157 70 function
6 449 1 245120 6 3155277 76 dict of type
7 101 0 179024 4 3334301 80 dict of module
8 264 1 112296 3 3446597 83 dict (no owner)
9 1101 3 79272 2 3525869 85 types.WrapperDescriptorType
<121 more rows. Type e.g. '_.more' to view.>
Size and cumulative are memory usage in bytes.
Conclusion
To profile memory usage in Python, we can use the guppy module.
