Concurrency and parallelism are concepts related to achieving efficient execution of multiple tasks in a program. In Python, they play a crucial role in improving performance and responsiveness, especially in scenarios where tasks can be executed simultaneously.
Concurrency refers to the ability of a program to execute multiple tasks concurrently. It allows different tasks to make progress independently, even if they are not executing simultaneously. In Python, concurrency is often achieved through the use of threads. Threads are lightweight and can be managed by the operating system's scheduler, which allocates CPU time to different threads.
Parallelism, on the other hand, involves executing multiple tasks simultaneously, utilizing multiple processors or CPU cores. It enables tasks to be executed in parallel, where each task is allocated its own processing unit and executes independently. Parallelism can provide significant performance improvements for computationally intensive tasks. In Python, parallelism can be achieved through multiprocessing, which involves spawning multiple processes that can execute in parallel.
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