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Cython, by Kurt W. Smith
Ebook Cython, by Kurt W. Smith
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Build software that combines Python’s expressivity with the performance and control of C (and C++). It’s possible with Cython, the compiler and hybrid programming language used by foundational packages such as NumPy, and prominent in projects including Pandas, h5py, and scikits-learn. In this practical guide, you’ll learn how to use Cython to improve Python’s performance—up to 3000x— and to wrap C and C++ libraries in Python with ease.
Author Kurt Smith takes you through Cython’s capabilities, with sample code and in-depth practice exercises. If you’re just starting with Cython, or want to go deeper, you’ll learn how this language is an essential part of any performance-oriented Python programmer’s arsenal.
- Use Cython’s static typing to speed up Python code
- Gain hands-on experience using Cython features to boost your numeric-heavy Python
- Create new types with Cython—and see how fast object-oriented programming in Python can be
- Effectively organize Cython code into separate modules and packages without sacrificing performance
- Use Cython to give Pythonic interfaces to C and C++ libraries
- Optimize code with Cython’s runtime and compile-time profiling tools
- Use Cython’s prange function to parallelize loops transparently with OpenMP
- Sales Rank: #164552 in Books
- Published on: 2015-01-31
- Released on: 2015-01-21
- Original language: English
- Number of items: 1
- Dimensions: 9.19" h x .58" w x 7.00" l, .0 pounds
- Binding: Paperback
- 254 pages
About the Author
Kurt Smith has been using Python in scientific computing ever since his college days, looking for any opportunity to incorporate it into his computational physics classes. He has contributed to the Cython project as part of the 2009 Google Summer of Code, implementing the initial version of typed memoryviews and native cython arrays. He uses Cython extensively in his consulting work at Enthought, training hundreds of scientists, engineers, and researchers in Python, NumPy, Cython, and parallel and high-performance computing.
Most helpful customer reviews
16 of 17 people found the following review helpful.
Super Charge Python with Cython
By James Saturn
This is an excellent book. The written style is clean and easy to understand. The author makes a good point about what Cython can and cannot do, and discusses the difference between CPU, memory, and I/O bound operations. There is a comprehensive treatment of Cython and how to optimize Python code that is CPU bound. I've used Cython on and off for several years, but this is by far the best book written about Cython to date.
11 of 11 people found the following review helpful.
Exceptionally written, helpful and concise - highly recommended!
By Alex T
With such a need for ways to improve the performance of a very popular programming language, this rare book on Cython feels long overdue. As someone who develops in Python, this might be the first great learning material on the compiler. Cython by Kurt W. Smith is thankfully well-written, and is a definite recommendation for anyone curious about speeding up Python. Of course, it helps to have some intermediate programming experience in both Python and C (and maybe even some C++, but I'll get to that later).
I will caution those who start to read the book and notice the immediate introduction of compiling Cython code (Chapter 2) even before going in-depth into syntax. Don't be discouraged, as this is actually a very clever organization by the author, whose comprehensible writing proves his knowledgeability in every topic here. Smith is starting off readers with a more conceptual, macroscopic look into how Cython code is ran - in multiple ways, as he explains in the chapter - so that way they're not constantly asking themselves that same question in the later chapters.
Which is to say, this book is meant to be read chronologically, and is not intended to be just a reference source on the subject. For that, you'll want to go to docs.cython.org or github.com/cython/cython/wiki. At roughly 220 pages of content, this book is incredibly dense for what it covers. It's definitely amazing how lean it is without being too overwhelming. Some key topics Smith covers includes organizing Cython code (Chapter 6), making a C library accessible to Python (Chapter 7), doing the same with C++ (Chapter 8), and using cProfile (Chapter 9). The entire text certainly comes off as a project that took years to pile all together.
As someone who's gone through the book page for page, I can assure others that there's at least something that even existing users of Cython are bound to learn. With that all said, my only gripe about Cython by Kurt Smith is what he doesn't cover: debugging and testing. I can understand the omissions for the reason of keeping it all concise, but it would've still been worthwhile to mention that Cython comes with a GDB extension called cygdb for when your project acts up. Still, these are ultimately minor complaints for what is easily the best learning resource on taking full advantage of Cython. Kudos to the computational plasma physicist himself, Kurt W. Smith.
Some other helpful notes:
-You should wait to install Cython before reading this book; Smith has helpful info on installing it for Linux, Mac OS X, and Windows in Chapter 2.
-Some topics make use of IPython and using Python decorators, so get acquainted with both.
-Know what pointers are!
-Be mindful of using C++ with Cython when reading Chapter 9, as the pairing of the two is (as of this writing) still a work in progress, something that even the author acknowledges at the end of the chapter. This is worth mentioning because, to my knowledge, it's hard to know for sure that all of the newer features of C++11 and C++14 are stable with Cython.
-There's a 4-part YouTube tutorial called "Cython: Speed up Python and NumPy, Pythonize C, C++, and Fortran, SciPy2013 Tutorial", presented by Kurt W. Smith himself, and it covers a lot of the same material in the book. It's specifically located in the Enthought YouTube Channel (if you have trouble finding it, its logo looks just like the icon used for the Nintendo Gamecube). [UPDATE 9-10-15: It's come to my attention that Smith has another tutorial in the same channel but much newer; look up "Cython: Blend the Best of Python and C++ | SciPy 2015 Tutorial | Kurt Smith". As a heads up, the tutorial is 3 hours and 45 minutes long.]
-https://github.com/cythonbook/examples is where all of the code examples from this book is stored. As a helpful gesture, Smith cites this URL as a footnote within the text from time to time.
1 of 1 people found the following review helpful.
Great Writing About A Facinating Technology
By William P Ross
I purchased this book without much prior knowledge of Cython, but was interested in learning how to create performant Python code. This book did a great job of explaining why Cython is the go to choice for speeding up Python.
Cython allows you to speed up Python code by translating it to C (or C++), and it also allows you to create wrappers for C code to be called in Python.
The book assumes you know Python and C somewhat well. It is a niche book for experienced users. The author took a bold step in assuming the reader will be up to speed, and I appreciated that.
Chapter three did a great job explaining how Python and C are fundamentally different languages, but also how they are complementary. Cython acts an interface between the two languages allowing you to pick and choose where you want C level performance, or where you want ease of use functionality of Python.
The writing is excellent and the author assumes you are familiar with modern software techniques.
I will leave it to the author to explain it best with the last sentence from the book: "With this one multifaceted tool [Cython] in hand, we can confidently bring Python's dynamism to C and C++, and bring the performance of C and C++ to Python".
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