What this book covers

Chapter 1, Contextualizing Parallel, Concurrent, and Distributed Programming, covers the concepts, advantages, disadvantages, and implications of parallel programming models. In addition, this chapter exposes some Python libraries to implement parallel solutions.

Chapter 2, Designing Parallel Algorithms, introduces a discussion about some techniques to design parallel algorithms.

Chapter 3, Identifying a Parallelizable Problem, introduces some examples of problems, and analyzes if these problems can be divided into parallel pieces.

Chapter 4, Using the threading and concurrent.futures Modules, explains how to implement each problem presented in Chapter 3, Identifying a Parallelizable Problem, using the threading and concurrent.futures modules.

Chapter 5, Using Multiprocessing and ProcessPoolExecutor, covers how to implement each problem presented in Chapter 3, Identifying a Parallelizable Problem, using multiprocessing and ProcessPoolExecutor.

Chapter 6, Utilizing Parallel Python, covers how to implement each problem presented in Chapter 3, Identifying a Parallelizable Problem, using the parallel Python module.

Chapter 7, Distributing Tasks with Celery, explains how to implement each problem presented in Chapter 3, Identifying a Parallelizable Problem, using the Celery distributed task queue.

Chapter 8, Doing Things Asynchronously, explains how to use the asyncio module and concepts about asynchronous programming.