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You're reading from  Jupyter for Data Science

Product typeBook
Published inOct 2017
Reading LevelBeginner
PublisherPackt
ISBN-139781785880070
Edition1st Edition
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Dan Toomey
Dan Toomey
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Dan Toomey

Dan Toomey has been developing application software for over 20 years. He has worked in a variety of industries and companies, in roles from sole contributor to VP/CTO-level. For the last few years, he has been contracting for companies in the eastern Massachusetts area. Dan has been contracting under Dan Toomey Software Corp. Dan has also written R for Data Science, Jupyter for Data Sciences, and the Jupyter Cookbook, all with Packt.
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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.

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Jupyter for Data Science
Published in: Oct 2017Publisher: PacktISBN-13: 9781785880070

Author (1)

author image
Dan Toomey

Dan Toomey has been developing application software for over 20 years. He has worked in a variety of industries and companies, in roles from sole contributor to VP/CTO-level. For the last few years, he has been contracting for companies in the eastern Massachusetts area. Dan has been contracting under Dan Toomey Software Corp. Dan has also written R for Data Science, Jupyter for Data Sciences, and the Jupyter Cookbook, all with Packt.
Read more about Dan Toomey