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

Chapter 19. Deadlocks

Deadlocks, one of the most common concurrency problems, will be the first problem that we analyze in this book. In this chapter, we will discuss the theoretical causes of deadlocks in concurrent programming. We will cover a classical synchronization problem in concurrency, called the Dining Philosophers problem, as a real-life example of deadlock. We will also illustrate an actual implementation of deadlock in Python. We will discuss several methods to address the problem. This chapter will also cover the concept of livelock, which is relevant to deadlock and is a relatively common problem in concurrent programming.

The following topics will be covered in this chapter:

  • The idea behind deadlock, and how to simulate it in Python
  • Common solutions to deadlock, and how to implement them in Python
  • The concept of livelock, and its connection to deadlock