multiprocessing python lock
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in python, the multiprocessing module allows you to create parallel processes, enabling concurrent execution of tasks and taking advantage of multi-core processors. however, when multiple processes access shared resources simultaneously, it can lead to race conditions and data corruption. to address this issue, the multiprocessing.lock class can be used to synchronize access to shared resources among multiple processes.
in this tutorial, we'll cover the basics of using multiprocessing.lock to ensure safe access to shared resources in a multiprocessing environment with a practical code example.
this tutorial assumes you have a basic understanding of python programming and multiprocessing concepts.
ensure you have python installed on your system. if not, download and install it from python.org.
multiprocessing.lock is a synchronization primitive used to enforce mutual exclusion. it allows only one process to acquire the lock at a time. other processes that attempt to acquire the lock while it's held by another process will block until the lock is released.
here's a basic workflow of using multiprocessing.lock:
now let's see how this works with a code example.
in this tutorial, you've learned how to use multiprocessing.lock to ensure safe access to shared resources in a multiprocessing environment in python. by properly synchronizing access to shared resources, you can prevent race conditions and data corruption, enabling efficient parallel processing.
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