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Overview Threads and locks are a software-defined formalization of the hardware underneath, and as such comprise the simplest possible concurrency model. It forms the basis of other concurrency abstractions built on top of it, so it’s important to understand in this regards. However, it’s difficult or impossible to build reliable, scalable systems directly on these primitives. While most every language has support for threads and locks, CPython remains special in its use of a global interpreter lock that prevents threads from concurrently accessing shared memory, because CPython’s memory management is not thread-safe.
A common technique to debug in Python is to add this line at a place which you want to observe: When you run the Python code and the interpreter hits this line, it drops you into a Python debugger prompt. You can inspect local variables and step through code from here. An irritating problem here…