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NumPy Essentials

You're reading from  NumPy Essentials

Product type Book
Published in Apr 2016
Publisher
ISBN-13 9781784393670
Pages 156 pages
Edition 1st Edition
Languages
Authors (3):
Leo (Liang-Huan) Chin Leo (Liang-Huan) Chin
Profile icon Leo (Liang-Huan) Chin
Tanmay Dutta Tanmay Dutta
Profile icon Tanmay Dutta
Shane Holloway Shane Holloway
Profile icon Shane Holloway
View More author details

Table of Contents (16) Chapters

NumPy Essentials
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. An Introduction to NumPy 2. The NumPy ndarray Object 3. Using NumPy Arrays 4. NumPy Core and Libs Submodules 5. Linear Algebra in NumPy 6. Fourier Analysis in NumPy 7. Building and Distributing NumPy Code 8. Speeding Up NumPy with Cython 9. Introduction to the NumPy C-API 10. Further Reading

The Python and NumPy C-API


The Python implementation that we are using is a C-based implementation of the Python interpreter. NumPy is specifically for this C-based Python implementation. This implementation of Python comes with a C-API, which is the backbone of the interpreter and provides low-level control to its user. NumPy has further augmented this by providing a rich C-API.

Writing functions in C/C++ can provide developers with the flexibility to leverage some of the advanced libraries available in these languages. However, the cost is apparent in terms of having to write too much boilerplate code around parsing input in order to construct return values. Additionally, developers have to take care while referencing/dereferencing objects since this could eventually create nasty bugs and memory leaks. There is also the problem of future compatibility of the code as the C-API keeps on evolving; hence, if a developer wants to migrate to a later version of Python, they may be up for a lot...

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