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As you probably know, the GIL stands for the Global Interpreter Lock, and its job is to make the CPython interpreter thread-safe. The GIL allows only one OS thread to execute Python bytecode at any given time, and the consequence of this is that it's not possible to speed up CPU-intensive Python code by distributing the work among multiple threads. This is, however, not the only negative effect of

If you ask me to name the most misunderstood aspect of Python, I will answer without a second thought: the Python import system. Just remember how many times you used relative imports and got something like ImportError: attempted relative import with no known parent package; or tried to figure out how to structure a project so that all the imports work correctly; or hacked sys.path when you couldn

As we know from the previous parts of this series, the execution of a Python program consists of two major steps: The CPython compiler translates Python code to bytecode. The CPython VM executes the bytecode. We've been focusing on the second step for quite a while. In part 4 we've looked at the evaluation loop, a place where Python bytecode gets executed. And in part 5 we've studied how the VM ex

We started this series with an overview of the CPython VM. We learned that to run a Python program, CPython first compiles it to bytecode, and we studied how the compiler works in part two. Last time we stepped through the CPython source code starting with the main() function until we reached the evaluation loop, a place where Python bytecode gets executed. The main reason why we spent time studyi