Book Image

Hands-On Software Engineering with Python

By : Brian Allbee, Nimesh Verma
Book Image

Hands-On Software Engineering with Python

By: Brian Allbee, Nimesh Verma

Overview of this book

Software Engineering is about more than just writing code—it includes a host of soft skills that apply to almost any development effort, no matter what the language, development methodology, or scope of the project. Being a senior developer all but requires awareness of how those skills, along with their expected technical counterparts, mesh together through a project's life cycle. This book walks you through that discovery by going over the entire life cycle of a multi-tier system and its related software projects. You'll see what happens before any development takes place, and what impact the decisions and designs made at each step have on the development process. The development of the entire project, over the course of several iterations based on real-world Agile iterations, will be executed, sometimes starting from nothing, in one of the fastest growing languages in the world—Python. Application of practices in Python will be laid out, along with a number of Python-specific capabilities that are often overlooked. Finally, the book will implement a high-performance computing solution, from first principles through complete foundation.
Table of Contents (21 chapters)
Free Chapter
1
Programming versus Software Engineering

Multiprocessing and HPC in Python

High-performance computing (HPC), quite simply, is the use of parallel processing during the execution of an application to spread the computational load across multiple processors, often across multiple machines. There are several MPC strategies to choose from, ranging from custom applications that leverage local multiprocessor computer architecture through to dedicated MPC systems, such as Hadoop or Apache Spark.

In this chapter, we will explore and apply different Python capabilities, building from executing a baseline algorithm against elements in a dataset one element at a time, and look at the following topics:

  • Building parallel processing approaches that exploit locally available multiprocessor architectures, and the limitations of those approaches using Python's multiprocessing module
  • Defining and implementing an approach across...