I built a small application using PyQt4 and pyqtgraph to visualize some data. The app has 32 graphs that plot deques of size 512. The plots are updated when 200 ints are cycled through each deque.
The plotting slows down in a linear manner with respect to time. In other words after cycling through 100,000 data points the time between calls to process events is much longer than it was at T0. I have done a little memory profiling. Watching the process on top, it's clear that there is some memory leak. I also tried invoking objgraph.show_most_common_types(). This test reveals that the number of objects being created plateaus, except for weakref objects, which keep growing and growing. I have come to believe that the growing number of weakrefs is slowing down execution. Is my analysis misguided? How can I introspect further? If the slowdown can be attributed to weakref escalation, what are some next steps? Thanks, Kevin
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