Python in a Nutshell, 3rd Edition

Chapter 14. Threads and Processes

A thread is a flow of control that shares global state (memory) with other threads; all threads appear to execute simultaneously, although they are usually “taking turns” on a single processor/core. Threads are not easy to master, and multithreaded programs are often hard to test, and to debug; however, as covered in “Use Threading, Multiprocessing, or async Programming?”, when used appropriately, multithreading may sometimes improve program performance in comparison to traditional “single-threaded” programming. This chapter covers the facilities that Python provides for dealing with threads, including the threading, queue, and concurrent modules.

A process is an instance of a running program. The operating system protects processes from one another. Processes that want to communicate must explicitly arrange to do so via inter-process communication (IPC) mechanisms. Processes may communicate via files (covered in Chapter 10) and databases (covered in Chapter 11). The general way in which processes communicate using data storage mechanisms, such as files and databases, is that one process writes data, and another process later reads that data back. This chapter covers the Python standard library modules subprocess and multiprocessing; the process-related parts of the module os, including simple IPC by means of pipes; and a cross-platform IPC mechanism known as memory-mapped files, which is supplied to Python programs by the module mmap.

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