Book Image

Advanced Python Programming

By : Dr. Gabriele Lanaro, Quan Nguyen, Sakis Kasampalis
Book Image

Advanced Python Programming

By: Dr. Gabriele Lanaro, Quan Nguyen, Sakis Kasampalis

Overview of this book

This Learning Path shows you how to leverage the power of both native and third-party Python libraries for building robust and responsive applications. You will learn about profilers and reactive programming, concurrency and parallelism, as well as tools for making your apps quick and efficient. You will discover 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. With the knowledge of how Python design patterns work, you will be able to clone objects, secure interfaces, dynamically choose algorithms, and accomplish much more in high performance computing. By the end of this Learning Path, you will have the skills and confidence to build engaging models that quickly offer efficient solutions to your problems. This Learning Path includes content from the following Packt products: • Python High Performance - Second Edition by Gabriele Lanaro • Mastering Concurrency in Python by Quan Nguyen • Mastering Python Design Patterns by Sakis Kasampalis
Table of Contents (41 chapters)
Title Page
Copyright
About Packt
Contributors
Preface
Index

What is concurrency?


It is estimated that the amount of data that needs to be processed by computer programs doubles every two years. The International Data Corporation (IDC), for example, estimates that, by 2020, there will be 5,200 GB of data for every person on earth. With this staggering volume of data come insatiable demands for computing power, and, while numerous computing techniques are being developed and utilized every day, concurrent programming remains one of the most prominent ways to effectively and accurately process data.

While some might be intimidated when the word concurrency appears, the notion behind it is quite intuitive, and it is very common, even in a non-programming context. However, this is not to say that concurrent programs are as simple as sequential ones; they are indeed more difficult to write and understand. Yet, once a correct and effective concurrent structure is achieved, significant improvement in execution time will follow, as you will see later on.

Concurrent...