Python Concurrency Books. Python provides thread-based concurrency in the threading module, as well as process-based concurrency in the multiprocessing module and coroutine-based concurrency in the asyncio module. Choosing the right type of …

Understand the idea of concurrency in programming and relevant concepts such as queues, threads, parallelism. Explore the core syntax and language features that enable concurrency in simple Python problems, namely through concurrent, multiprocessing, asyncio.

Mastering Concurrency in Python starts by introducing the concepts and principles in concurrency, right from Amdahl's Law to multithreading programming, followed by elucidating multiprocessing programming, web scraping, and asynchronous I/O, together with common problems that engineers and programmers face in concurrent programming.

Unlock concurrency with Python threads (and run 100s or 1,000s of tasks simultaneously). The threading module provides easy-to-use thread-based concurrency in Python. Unlike Python multiprocessing, the threading module is limited by the infamous Global Interpreter Lock (GIL).

Python 3 handles threads by using the threading library. It includes several methods and objects to manipulate threads. Figure 7.1: Diagram of a threading-based application . We can create a new thread using the Thread class from the Threading library. This class requires three arguments: target arguments.

Python supports real concurrency with first-class native support for threads and processes. It always has. ...on all recent Python versions, like Python v2.6+ and v3.0+. ...on all major platforms, like Windows, macOS, and Linux. ...with all major hardware, like …

This book covers the following exciting features: Synchronize multiple threads and processes to manage parallel tasks; Use message passing techniques to establish communication between processes to build parallel applications; Program your own GPU cards to address complex problems; Manage computing entities to execute distributed computational task