Cool concept. Right off the bat I see some big issues with the generated CPython documentation:<p>> This provides a register-based virtual machine that executes the bytecode through simple opcodes.<p>Python's VM is stack-based, not register-based.<p>> The tiered interpreter in …/ceval.c can compile bytecode sequences into "traces" of optimized microoperations.<p>No such functionality exists in CPython, as far as I know.<p>> The dispatch loop switches on opcodes, calling functions to manipulate the operand stack. It implements stack manipulation with macros.<p>No it doesn't. If you look at the bytecode interpreter, it's full of plain old statements like `stack_pointer += 1;`.<p>> The tiered interpreter is entered from a label. It compiles the bytecode sequence into a trace of "micro-operations" stored in the code object. These micro-ops are then executed in a tight loop in the trace for faster interpretation.<p>As mentioned above, this seems to be a complete hallucination.<p>> During initialization, …/pylifecycle.c performs several important steps: [...] It creates the main interpreter object and thread<p>No, the code in this file creates an internal thread <i>state</i> object, corresponding to the already-running thread that calls it.<p>> References: Python/clinic/import.c.h The module implements finding and loading modules from the file system and cached bytecode.<p>This is kinda sorta technically correct, but the description never mentions the crucial fact that most of this C code only exists to bootstrap and support the <i>real</i> import machinery, which is written in Python, not C. (Also, the listed source file is the wrong one: it just contains auto-generated function <i>wrappers</i>, not the actual implementations.)<p>> Core data structure modules like …/arraymodule.c provide efficient implementations of homogeneous multidimensional arrays<p>Python's built-in array module provides only one-dimensional arrays.<p>And so on.