This is all problem spectific, but I have found C code integrated via ctypes, cffi, or by a C extension is over 100x Python alone. Interestingly Python, Numba, and Numpy together which is a more pythonic solution can get to those speeds too.
Of course you did. Those are changing the semantics of the language. For example, things like Numpy store arrays more like how C does it than Python. That makes all the difference, not merely compiling to native code.
You can get about 10x by compiling Python using PyPy. So compiling is not nothing. Using Numpy alone is about 5x which surprised me. There is a lot of missleading stuff out there about how to make Python fast. Lot of people say CPython is pretty fast or that using a binary library like numpy is fast. No CPython is very slow and libraries are not always that fast.
Edit: Another compiler is Numba which is more specialized. It can get 30x on some code without numpy. Again compiling can help.
Of course you did. Those are changing the semantics of the language. For example, things like Numpy store arrays more like how C does it than Python. That makes all the difference, not merely compiling to native code.
You can get about 10x by compiling Python using PyPy. So compiling is not nothing. Using Numpy alone is about 5x which surprised me. There is a lot of missleading stuff out there about how to make Python fast. Lot of people say CPython is pretty fast or that using a binary library like numpy is fast. No CPython is very slow and libraries are not always that fast.
Edit: Another compiler is Numba which is more specialized. It can get 30x on some code without numpy. Again compiling can help.