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Making your code faster: Cython and parallel processing in the Jupyter Notebook


PyData DC 2016

Github: Slides:

As the complexity and scope of applications grow, it is very common to run into slow performance issues. In Python, it is possible to improve the speed of execution with the use of parallel processing and the Cython compiler. The Jupyter Notebook makes the implementation of both of them a relatively simple task, which will be the focus of this session.

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