Book Image

Python High Performance, Second Edition - Second Edition

By : Dr. Gabriele Lanaro
Book Image

Python High Performance, Second Edition - Second Edition

By: Dr. Gabriele Lanaro

Overview of this book

Python is a versatile language that has found applications in many industries. The clean syntax, rich standard library, and vast selection of third-party libraries make Python a wildly popular language. Python High Performance is a practical guide that shows how to leverage the power of both native and third-party Python libraries to build robust applications. The book explains how to use various profilers to find performance bottlenecks and apply the correct algorithm to fix them. The reader will learn how to effectively use NumPy and Cython to speed up numerical code. The book explains concepts of concurrent programming and how to implement robust and responsive applications using Reactive programming. Readers will learn how to write code for parallel architectures using Tensorflow and Theano, and use a cluster of computers for large-scale computations using technologies such as Dask and PySpark. By the end of the book, readers will have learned to achieve performance and scale from their Python applications.
Table of Contents (10 chapters)

Sharing declarations

When writing your Cython modules, you may want to reorganize your most used functions and classes declaration in a separate file so that they can be reused in different modules. Cython allows you to put these components in a definition file and access them with cimport statements.

Let's say that we have a module with the max and min functions, and we want to reuse those functions in multiple Cython programs. If we simply write a bunch of functions in a .pyx file, the declarations will be confined to the same file.

Definition files are also used to interface Cython with external C code. The idea is to copy (or, more accurately, translate) the types and function prototypes in the definition file and leave the implementation in the external C code that will be compiled and linked in a separate step.

To share the max and min functions, we need to write a definition file with a .pxd extension...