| >the dynamic nature of the language means many optimizing techniques just aren't available. This is something that seems like it should be true, but counter evidence exists that proves that it's not the case. The first example would be V8, the JavaScript JIT compiler used in Chrome and NodeJs (and probably other things). V8 is many times faster than CPython in pretty much every situation. The second, and even better example is SBCL, a Common Lisp compiler. SBCL is quite a bit faster than CPython and V8, it's closer to the JVM in terms of performance in benchmarks that I have saw. The third example would be some of the Scheme compilers, like Chez and Gambit, which are not far off from SBCL. Maybe you could argue that JavaScript is not as dynamic as Python. I don't know JavaScript at all so maybe that is the case. I'm pretty sure that Common Lisp and Scheme are not less dynamic though. I think Common Lisp is actually more dynamic but I don't have any way to measure this, so it's just my opinion. So assuming these languages are as or more dynamic than Python, this seems to be proof that Pythons dynamic-ness is not the reason for it's poor performance! The Lisp compilers are also much less widely used and have much less engineering power available! I think these counter examples are pretty interesting and don't know exactly what to make of it. Python has more funding and more users to contribute to it (except in the case of V8), I guess until now they just haven't put any of that into performance. |