This is a common misconception! It is true that, of the Smalltalk descendants, Python was not designed for speed like Self or Java; but it was not designed to be slow or difficult to compile. The main technique required to implement a Python JIT is virtualizable objects, which allows the JIT to temporarily desynchronize the contents of registers from the contents of the heap; it’s not obvious and wasn’t in the first few iterations of PyPy. Additionally, it turns out that tracing the meta-level (see docs or the paper) is a key trick: instead of JIT’ing the Python program, the JIT operates on the interpreter, on the Python VM itself!
python is a language explicitly designed to resist any form of proper optimization. It just can’t be made fast
This is a common misconception! It is true that, of the Smalltalk descendants, Python was not designed for speed like Self or Java; but it was not designed to be slow or difficult to compile. The main technique required to implement a Python JIT is virtualizable objects, which allows the JIT to temporarily desynchronize the contents of registers from the contents of the heap; it’s not obvious and wasn’t in the first few iterations of PyPy. Additionally, it turns out that tracing the meta-level (see docs or the paper) is a key trick: instead of JIT’ing the Python program, the JIT operates on the interpreter, on the Python VM itself!