GIL may and does get released in the interpreter (on I/O) and C extensions such as regex, lxml, numpy. Performance sensitive extensions may even use multiple CPU cores implicitly e.g., as numpy.dot() can do for large enough input without changing the code in any way.

Yes, leading to C extensions that are not thread safe and so can't be used in multi-threaded code at all. An example I'm familiar with is pylibmc.

Wrong. GIL does NOT necessarily make your Python/C code thread-safe and in reverse releasing GIL does not prevent you from writing a thread-safe code.

True, though this is not the kind of speed this article was talking about. You can get around that limitation somewhat by using multiprocessing module.

I'm not saying Python is the best language of all, but dissecting Python bytecode is kind of missing the point. Python's strong point is its ease of use.