Threads are another way to start activities running at the same time. In short, they run a function call in parallel with the rest of the program. Threads are sometimes called “lightweight processes,” because they run in parallel like forked processes, but all of them run within the same single process. While processes are commonly used to start independent programs, threads are commonly used for tasks such as nonblocking input calls and long-running tasks in a GUI. They also provide a natural model for algorithms that can be expressed as independently running tasks. For applications that can benefit from parallel processing, some developers consider threads to offer a number of advantages:


Because all threads run within the same process, they don’t generally incur a big startup cost to copy the process itself. The costs of both copying forked processes and running threads can vary per platform, but threads are usually considered less expensive in terms of performance overhead.


Threads can be noticeably simpler to program too, especially when some of the more complex aspects of processes enter the picture (e.g., process exits, communication schemes, and zombie processes, covered in Chapter 13).

Shared global memory

Also because threads run in a single process, every thread shares the same global memory space of the process. This provides a natural and easy way for threads to communicate—by fetching and setting data in global memory. To the Python ...

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