Monitoring Jupyter

As with the earlier discussions in this chapter on optimization, you can also use programming tools to monitor the overall interactions of your notebook. The predominant tool for Linux/Mac environments is memory_profiler. If you start this tool then your notebook, the profiler will keep track of memory use of your notebook.

With this record of information points you may be able to adjust your programmatic memory allocation to be smaller in profile if you find a large memory use occurring. For example, the profiler may highlight that you are creating (and dropping) a large memory item continuously inside of a loop. When you go back to your coding you realize this memory access could be pulled out of the loop and just done once or that size of the allocation could be minimized easily.