Python provides two ways to work around this issue: threading and multiprocessing. Each approach allows you to break a long-running job into parallel batches, which you can work on side-by-side.

However, Python has a limitation known as the Global Interpreter Lock (GIL). The GIL ensures that only one thread executes Python bytecode at any given time, which prevents true parallelism in ...

Code Interpreter is the latest feature in OpenAI ChatGPT (specifically, with the GPT-4 model) that allows you to run Python code in a live working environment. It’s basically a sandboxed Python ...

The multiprocessing module, for instance, makes it possible to run concurrent instances of the Python interpreter (each on its own physical thread) and share work between them.

The main thread just waits all the time inside the multiprocessing implementation for the threading.Event that signals that the result has arrived. It does not spend significant CPU time. There are ...

The GIL is controversial because it only allows one thread at a time to access the Python interpreter. This means that it’s often not possible for threads to take advantage of multi-core systems.