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Threads/Multithreading Python Multithreading in Python Multithreading in Python is used to run multiple threads (smaller units of a process) concurrently to improve performance, especially in ...

1. Global Interpreter Lock (GIL): The number one disadvantage of Python's multithreading is the GIL—it doesn't allow multiple threads to execute Python bytecode simultaneously in one process. 2.

Python lets you parallelize workloads using threads, subprocesses, or both. Here's what you need to know about Python's thread and process pools and Python threads after Python 3.13.

Thread Safety Issues: Multithreading can introduce complex issues such as race conditions, deadlocks, and resource contention, which require careful handling using locks or semaphores. Higher Memory ...