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
About Packt


You have now been introduced to the concept of concurrent and parallel programming. It is about designing and structuring programming commands and instructions, so that different sections of the program can be executed in an efficient order, while sharing the same resources. Since time is saved when some commands and instructions are executed at the same time, concurrent programming provides significant improvements in program execution time, as compared to traditional sequential programming.

However, various factors need to be taken into consideration while designing a concurrent program. While there are specific tasks that can easily be broken down into independent sections that can be executed in parallel (embarrassingly parallel tasks), others require different forms of coordination between the program commands, so that shared resources are used correctly and efficiently. There are also inherently sequential tasks, in which no concurrency and parallelism can be applied to achieve...