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Python and Memory

Author(s): 

Peter Norton

I found myself thinking about an interesting problem I ran into a few years ago. I was wondering why an open source metrics collection system seemed to have a relatively low performance ceiling when relaying metrics.

After much troubleshooting, I found that the performance issue resided in attempts at splitting a list: when it had thousands of messages, it would pull off some messages from the front of a list, then split the list, and the way it was doing this was inefficient. In the end I found some improvement in using a deque, but the problem has left me with continuing questions about some of these oddities in how Python does its memory management.

Download Article: 
PDF icon Python and Memory
Article Section: 
COLUMNS
;login: issue: 
Spring 2020, Vol. 45, No. 1
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