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

Locks as a solution to race conditions


In this section, we will discuss the most common solution to race conditions: locks. Intuitively, since the race conditions that we observed arose when multiple threads or processes accessed and wrote to a shared resource simultaneously, the key idea to solving race conditions is to isolate the executions of different threads/processes, especially when interacting with a shared resource. Specifically, we need to make sure that a thread/process can only access the shared resource after any other threads/processes interacting with the resource have finished their interactions with that resource.

The effectiveness of locks

With locks, we can turn a shared resource in a concurrent program into a critical section, whose integrity of data is guaranteed to be protected. A critical section guarantees the mutual exclusion of a shared resource, and cannot be accessed concurrently by multiple processes or threads; this will prevent any protected data from being...