In this book we have explored various topics of scientific and technical computing using Python and its ecosystem of libraries. As touched upon in the very first chapter of this book, the Python environment for scientific computing generally strikes a good balance between a high-level environment that is suitable for exploratory computing and rapid prototyping – which minimizes development efforts – and high-performance numerics, which minimize application runtimes. High-performance numerics is achieved not through the Python language itself, but rather through leveraging libraries ...
© Robert Johansson 2019
Robert JohanssonNumerical Python https://doi.org/10.1007/978-1-4842-4246-9_1919. Code Optimization
Robert Johansson1
(1)
Urayasu-shi, Chiba, Japan
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