Chapter 14. Threads and Processes

A thread is a flow of control that shares global state with other threads; all threads appear to execute simultaneously. Threads are not easy to master, but once you do master them, they may let you tackle some problems with a simpler architecture, and sometimes better performance, in comparison to traditional "single-thread" programming. This chapter covers the facilities that Python provides for dealing with threads, including the thread, threading, and Queue modules.

A process is an instance of a running program. Sometimes, particularly on Unix-like operating systems or on multiprocessor computers, you can get better results with multiple processes than with threads. The operating system protects processes from one another. Processes that want to communicate must explicitly arrange to do so via local inter-process communication (IPC). Processes may communicate via files (covered in Chapter 10) or via databases (covered in Chapter 11). In both cases, the general way in which processes communicate using such data storage mechanisms is that one process can write data, and another process can later read that data back. This chapter covers Python standard library module process; the process-related parts of 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 module mmap.

Network mechanisms are well suited for IPC, as they work between processes that run on different nodes of a network as well as those that run on the same node. (Chapter 20 covers low-level network mechanisms that provide a flexible basis for IPC.) Other, higher-level mechanisms, known as distributed computing, such as CORBA, DCOM/COM+, EJB, SOAP, XML-RPC, and .NET, make IPC easier, whether locally or remotely. However, distributed computing is not covered in this book.