On 9/2/07, Diez B. Roggisch <[EMAIL PROTECTED]> wrote: > Wildemar Wildenburger schrieb: > > Martin v. Löwis wrote: > >>>> (2) it is a interpretation language > >>> Not quite. It's compiled to byte-code - just like Java (would you call > >>> Java an 'interpreted language' ?) > >> > >> Python is not implemented like Java. In Java (at least in HotSpot), > >> the byte code is further compiled to machine code before execution; > >> in Python, the byte code is interpreted. > >> > > OK, good. Naive question now comming to mind: Why doesn't Python do the > > latter as well? > > because of the dynamic nature of it. Java is statically typed, so the > JIT can heavily optimize. > > OTH psyco IS a JIT-compiler to optimize certain calculations which are > mostly of a numerical nature. But this can't be done to the extend it is > possible in java. >
Original code: 3 min, 9 seconds Original code with psyco: 30.28 seconds Original code, compiled with Pyrex: 1min 39 seconds (moves the for loops into C) Same, with a,b,c declared with cdef int: 20 seconds (uses c pow() instead of going through Python). Same, with the for..xrange loops rewritten to use C integer loops: 13 seconds (saves xrange use, but since the python loop was already gone, not too much savings). With a small amount of work, you should be able to implement the C algorithm in Pyrex (or even just use the C algorithm, in a wrapper that converts the return value to an int) and get the same speed as the C version + a constant marshalling factor. Adding pysco took all of 20 seconds (half that because I needed to move the module scope code into a function), and re-writing with pyrex took a minute or two. So, as a demonstration of numeric optmization, both of them can give you quite good rewards with minimal effort. -- http://mail.python.org/mailman/listinfo/python-list
