Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
Bearophile wrote: Was this link, shown by William, not enough? http://hg.flibuste.net/libre/games/cheval/file/46797c3a5136/chevalx.pyx#l1 Yes, sorry, I posted too soon. -- Greg -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
William Dode': I updated the script (python, c and java) with your unrolled version + somes litle thinks. [...] c 1.85s gcj 2.15s java 2.8s python2.5 + psyco 3.1s unladen-2009Q2 145s (2m45) python2.5 254s (4m14s) python3.1 300s (5m) ironpython1.1.1 680s (11m20) Sorry for being late, I was away. In your last C version this code is useless because the C compiler is able to perform such simple optimization by itself (but probably Python isn't able, so if you want the code to be the similar in all versions it may be better to keep it): shift_0=shift[0]; shift_1=shift[1]; shift_2=shift[2]; shift_3=shift[3]; shift_4=shift[4]; shift_5=shift[5]; shift_6=shift[6]; shift_7=shift[7]; This part in the Python code is useless: shift_0 = shift[0] shift_1 = shift[1] shift_2 = shift[2] shift_3 = shift[3] shift_4 = shift[4] shift_5 = shift[5] shift_6 = shift[6] shift_7 = shift[7] Because later you copy values locally anyway: def solve(nb, x, y, SIDE=SIDE, SQR_SIDE=SQR_SIDE, circuit=circuit, shift_0=shift_0, shift_1=shift_1, shift_2=shift_2, shift_3=shift_3, shift_4=shift_4, shift_5=shift_5, shift_6=shift_6, shift_7=shift_7, ): So doing something like this is probably enough: def solve(nb, x, y, SIDE=SIDE, SQR_SIDE=SQR_SIDE, circuit=circuit, shift_0=shift[0], shift_1=shift[1], shift_2=shift[2], shift_3=shift[3], shift_4=shift[4], shift_5=shift[5], shift_6=shift[6], shift_7=shift[7], ): In low-level languages like C unrolling has to be done with care, to avoid slowing down the code. I have tried your latest C version using your compiler options, my MinGW based on GCC 4.3.2 produces a crash at runtime. Using LLVM-GCC it runs in 1.31 seconds. The D version is a bit less optimized than your last C versions, yet using DMD it runs in 1.08-1.10 seconds. Let's see if someone is able to write a C version faster than that D code :-) Have you have compiled/read my D version? In the D version you may have missed that I did use an extra trick: unsigned integers, so it needs just two tests to see if a number is in the 0-5, 0-5 square :-) Note that Pyd, the Python-D bridge, may work with the latest DMD version still (and it works if you use a bit older DMD compiler): http://pyd.dsource.org/ Bye, bearophile -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
On 23-07-2009, Kurt Smith wrote: On Wed, Jul 22, 2009 at 2:48 AM, Bearophilebearophileh...@lycos.com wrote: greg: Posting benchmark times for Pyrex or Cython is pretty meaningless without showing the exact code that was used, since times can vary enormously depending on how much you C-ify things. Was this link, shown by William, not enough? http://hg.flibuste.net/libre/games/cheval/file/46797c3a5136/chevalx.pyx#l1 I took a stab at converting the recent psyco-optimized code to cython, and got a speedup. thanks, i updated my repo with litle more tips. -- William Dodé - http://flibuste.net Informaticien Indépendant -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
srepmub mark.duf...@gmail.com wrote: please send any program that doesn't work with shedskin (it still is experimental after all) to me, or create an issue at shedskin.googlecode.com, and I will have a look at the problem. I divided and conquered the program as suggested and eventually I got it to compile and run correctly :-) I learnt that if you have lots of variables with indeterminate type then shedskin takes a very long time indeed before blowing up! I also learnt that shedskin doesn't support the idiom I'd been using for creating shallow copies, namely the Board.__new__(Board) below. shedskin compiles it ok, but the C++ won't compile complaning about not being able to find __init__ methods Producing these warnings *WARNING* rush_hour_solver_cut_down.py:71: class 'Vehicle' has no method '__new__' *WARNING* rush_hour_solver_cut_down.py:72: variable 'new' has no type *WARNING* rush_hour_solver_cut_down.py:236: variable 'new_vehicle' has no type And these compile errors rush_hour_solver_cut_down.cpp:94: error: ‘__new__’ is not a member of ‘__rush_hour_solver_cut_down__::Vehicle’ rush_hour_solver_cut_down.cpp:95: error: expected type-specifier before ‘;’ token rush_hour_solver_cut_down.cpp: In member function ‘void* __rush_hour_solver_cut_down__::Board::move(int, int)’: rush_hour_solver_cut_down.cpp:276: error: ‘void*’ is not a pointer-to-object type rush_hour_solver_cut_down.cpp:276: error: ‘void*’ is not a pointer-to-object type rush_hour_solver_cut_down.cpp:279: error: ‘void*’ is not a pointer-to-object type rush_hour_solver_cut_down.cpp:279: error: ‘void*’ is not a pointer-to-object type rush_hour_solver_cut_down.cpp:281: error: invalid conversion from ‘void*’ to ‘__rush_hour_solver_cut_down__::Vehicle*’ def copy(self): new = Board.__new__(Board) new.me_x = self.me_x new.me_y = self.me_y new.depth = self.depth new.parent = self new.best_child = None new.board = [self.board[i][:] for i in range(WIDTH)] new.rep = self.rep[:] new.vehicles = self.vehicles[:] return new I changed to using copy.copy which did work, but I couldn't name my copy methods copy otherwise I got this error from the C++ compile rush_hour_solver_cut_down.cpp: In member function '__rush_hour_solver_cut_down__::Vehicle* __rush_hour_solver_cut_down__::Vehicle::copy()': rush_hour_solver_cut_down.cpp:94: error: no matching function for call to '__rush_hour_solver_cut_down__::Vehicle::copy(__rush_hour_solver_cut_down__::Vehicle* const)' rush_hour_solver_cut_down.cpp:89: note: candidates are: __rush_hour_solver_cut_down__::Vehicle* __rush_hour_solver_cut_down__::Vehicle::copy() rush_hour_solver_cut_down.cpp: In member function '__rush_hour_solver_cut_down__::Board* __rush_hour_solver_cut_down__::Board::copy()': rush_hour_solver_cut_down.cpp:135: error: no matching function for call to '__rush_hour_solver_cut_down__::Board::copy(__rush_hour_solver_cut_down__::Board* const)' rush_hour_solver_cut_down.cpp:129: note: candidates are: __rush_hour_solver_cut_down__::Board* __rush_hour_solver_cut_down__::Board::copy() So I renamed them to pycopy, and they ended up looking like def pycopy(self): new = copy(self) new.parent = self new.best_child = None new.board = [self.board[i][:] for i in range(WIDTH)] new.rep = self.rep[:] new.vehicles = self.vehicles[:] return new After all that - some timing results! Python: 9.3 seconds Psyco:5.8 seconds ShedSkin: 1.0 seconds Impressive! I put the code http://www.craig-wood.com/nick/pub/rush_hour_solver_cut_down.py I left in the commented out bits of code I had to change. This is only part of the project (375 lines) - it solves Rush Hour boards. There is another part which I haven't attempted to compile yet which finds the most difficult possible boards using a combination of back tracking and a genetic algorithm. -- Nick Craig-Wood n...@craig-wood.com -- http://www.craig-wood.com/nick -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
greg: Posting benchmark times for Pyrex or Cython is pretty meaningless without showing the exact code that was used, since times can vary enormously depending on how much you C-ify things. Was this link, shown by William, not enough? http://hg.flibuste.net/libre/games/cheval/file/46797c3a5136/chevalx.pyx#l1 Bye, bearophile -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
I updated the script (python, c and java) with your unrolled version + somes litle thinks. I also tried with python3.1, unladen Q2, ironpython1.1.1 Unfortunately it doesn't work more with shedskin, i'll see on the shedskin group... c 1.85s gcj 2.15s java 2.8s python2.5 + psyco 3.1s unladen-2009Q2 145s (2m45) python2.5 254s (4m14s) python3.1 300s (5m) ironpython1.1.1 680s (11m20) -- William Dodé - http://flibuste.net Informaticien Indépendant -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
please send any program that doesn't work with shedskin (it still is experimental after all) to me, or create an issue at shedskin.googlecode.com, and I will have a look at the problem. thanks, mark. -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
On 22-07-2009, srepmub wrote: please send any program that doesn't work with shedskin (it still is experimental after all) to me, or create an issue at shedskin.googlecode.com, and I will have a look at the problem. I did it, on the discussion group http://groups.google.com/group/shedskin-discuss/browse_thread/thread/c1f47a7c21897b44 -- William Dodé - http://flibuste.net Informaticien Indépendant -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
On Jul 22, 7:38 am, William Dode w...@flibuste.net wrote: I updated the script (python, c and java) with your unrolled version + somes litle thinks. I also tried with python3.1, unladen Q2, ironpython1.1.1 Unfortunately it doesn't work more with shedskin, i'll see on the shedskin group... c 1.85s gcj 2.15s java 2.8s python2.5 + psyco 3.1s unladen-2009Q2 145s (2m45) python2.5 254s (4m14s) python3.1 300s (5m) ironpython1.1.1 680s (11m20) Cool; it would be interesting to see the numbers for Jython and Boo as well if it's not too much effort. George -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
On 22-07-2009, George Sakkis wrote: On Jul 22, 7:38 am, William Dode w...@flibuste.net wrote: I updated the script (python, c and java) with your unrolled version + somes litle thinks. I also tried with python3.1, unladen Q2, ironpython1.1.1 Unfortunately it doesn't work more with shedskin, i'll see on the shedskin group... c 1.85s gcj 2.15s java 2.8s python2.5 + psyco 3.1s unladen-2009Q2 145s (2m45) python2.5 254s (4m14s) python3.1 300s (5m) ironpython1.1.1 680s (11m20) Cool; it would be interesting to see the numbers for Jython and Boo as well if it's not too much effort. I just tried with jython, but oddly it's faster without array. Thanks to Mark, i could compile to shedskin again. And add somes little improvements... c 1.65s gcj 1.9s java 2.4s python2.5 + psyco 2.9s shedskin 3.4s unladen-2009Q2 125s (2m05) Jython 2.2.1 on java1.6.0_12 176s (without array, like shedskin) Jython 2.2.1 on java1.6.0_12 334s (with array) python2.5 215s (3m35s) python3.1 246s (4m06s) ironpython1.1.1 512 (8m32s) -- William Dodé - http://flibuste.net Informaticien Indépendant -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
On 22-07-2009, William Dode wrote: c 1.65s gcj 1.9s java 2.4s python2.5 + psyco 2.9s shedskin 3.4s with -bw i have 2.6s unladen-2009Q2 125s (2m05) Jython 2.2.1 on java1.6.0_12 176s (without array, like shedskin) Jython 2.2.1 on java1.6.0_12 334s (with array) python2.5 215s (3m35s) python3.1 246s (4m06s) ironpython1.1.1 512 (8m32s) somebody can test with ironpython on windows ? Anyway, it's very impressive. I wonder if unladen will be so close in the futur. -- William Dodé - http://flibuste.net Informaticien Indépendant -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
On Jul 22, 12:45 pm, William Dode w...@flibuste.net wrote: On 22-07-2009, George Sakkis wrote: On Jul 22, 7:38 am, William Dode w...@flibuste.net wrote: I updated the script (python, c and java) with your unrolled version + somes litle thinks. I also tried with python3.1, unladen Q2, ironpython1.1.1 Unfortunately it doesn't work more with shedskin, i'll see on the shedskin group... c 1.85s gcj 2.15s java 2.8s python2.5 + psyco 3.1s unladen-2009Q2 145s (2m45) python2.5 254s (4m14s) python3.1 300s (5m) ironpython1.1.1 680s (11m20) Cool; it would be interesting to see the numbers for Jython and Boo as well if it's not too much effort. I just tried with jython, but oddly it's faster without array. FYI Jython 2.5 was released last month, you may want to try this instead of 2.2. George -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
On Wed, Jul 22, 2009 at 11:55 AM, William Dode w...@flibuste.net wrote: On 22-07-2009, William Dode wrote: c 1.65s gcj 1.9s java 2.4s python2.5 + psyco 2.9s shedskin 3.4s with -bw i have 2.6s unladen-2009Q2 125s (2m05) Jython 2.2.1 on java1.6.0_12 176s (without array, like shedskin) Jython 2.2.1 on java1.6.0_12 334s (with array) python2.5 215s (3m35s) python3.1 246s (4m06s) ironpython1.1.1 512 (8m32s) somebody can test with ironpython on windows ? Anyway, it's very impressive. I wonder if unladen will be so close in the futur. -- William Dodé - http://flibuste.net Informaticien Indépendant I had time to run a few tests. Since psyco doesn't work on 64 bit and the developer now works on pypy I used that. Intel Core i7 920 @ 2.66GHz Kubuntu Jaunty Jackal c gcc4.3.3 0.77s gcj 4.3.3 0.81s java 1.6 0.99s shedskin 1.63s jython 2.2.1 85.37s cpython 2.6.2 93.26s pypy 1.1.0 1612.15s http://mail.python.org/mailman/listinfo/python-list -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
On Wed, Jul 22, 2009 at 2:48 AM, Bearophilebearophileh...@lycos.com wrote: greg: Posting benchmark times for Pyrex or Cython is pretty meaningless without showing the exact code that was used, since times can vary enormously depending on how much you C-ify things. Was this link, shown by William, not enough? http://hg.flibuste.net/libre/games/cheval/file/46797c3a5136/chevalx.pyx#l1 I took a stab at converting the recent psyco-optimized code to cython, and got a speedup. gcj4.3.31.39s gcc4.3.31.55s cython 11.2 1.91s psyco 1.94s javac 1.5.0_19 2.00s python 2.5.4168.37s It was just a matter of cdef-ing all the arrays integers -- bearophile already did the hard work :-) Here's the cython code; all the others are from the repo. # DEF NMOVES = 8 DEF SIDE = 5 DEF SQR_SIDE = SIDE * SIDE cdef int circuit[SQR_SIDE] cdef int nsolutions = 0 cdef int movex[NMOVES] cdef int movey[NMOVES] py_movex = [-1,-2,-2,-1,+1,+2,+2,+1] py_movey = [-2,-1,+1,+2,+2,+1,-1,-2] for i in range(NMOVES): movex[i] = py_movex[i] movey[i] = py_movey[i] shift = [x * SIDE + y for x,y in zip(py_movex, py_movey)] cdef int shift_0 = shift[0] cdef int shift_1 = shift[1] cdef int shift_2 = shift[2] cdef int shift_3 = shift[3] cdef int shift_4 = shift[4] cdef int shift_5 = shift[5] cdef int shift_6 = shift[6] cdef int shift_7 = shift[7] def showCircuit(): print for x in xrange(SIDE): x_SIDE = x * SIDE for y in xrange(SIDE): if SQR_SIDE 100: print %02d % circuit[x_SIDE + y], else: print %03d % circuit[x_SIDE + y], print cdef void solve(int nb, int x, int y, int SIDE=SIDE, int SQR_SIDE=SQR_SIDE, int *circuit=circuit, int shift_0=shift_0, int shift_1=shift_1, int shift_2=shift_2, int shift_3=shift_3, int shift_4=shift_4, int shift_5=shift_5, int shift_6=shift_6, int shift_7=shift_7, ): global nsolutions cdef int newx, newy cdef int pos = x * SIDE + y circuit[pos] = nb if nb == SQR_SIDE: #showCircuit() nsolutions += 1 circuit[pos] = 0 return newx = x + -1 if newx = 0 and newx SIDE: newy = y + -2 if newy = 0 and newy SIDE and not circuit[pos + shift_0]: solve(nb+1, newx, newy) newx = x + -2 if newx = 0 and newx SIDE: newy = y + -1 if newy = 0 and newy SIDE and not circuit[pos + shift_1]: solve(nb+1, newx, newy) newx = x + -2 if newx = 0 and newx SIDE: newy = y + 1 if newy = 0 and newy SIDE and not circuit[pos + shift_2]: solve(nb+1, newx, newy) newx = x + -1 if newx = 0 and newx SIDE: newy = y + 2 if newy = 0 and newy SIDE and not circuit[pos + shift_3]: solve(nb+1, newx, newy) newx = x + 1 if newx = 0 and newx SIDE: newy = y + 2 if newy = 0 and newy SIDE and not circuit[pos + shift_4]: solve(nb+1, newx, newy) newx = x + 2 if newx = 0 and newx SIDE: newy = y + 1 if newy = 0 and newy SIDE and not circuit[pos + shift_5]: solve(nb+1, newx, newy) newx = x + 2 if newx = 0 and newx SIDE: newy = y + -1 if newy = 0 and newy SIDE and not circuit[pos + shift_6]: solve(nb+1, newx, newy) newx = x + 1 if newx = 0 and newx SIDE: newy = y + -2 if newy = 0 and newy SIDE and not circuit[pos + shift_7]: solve(nb+1, newx, newy) circuit[pos] = 0 def main(): print Search for side=%d % SIDE cdef int x,y for x in range(SIDE): for y in range(SIDE): solve(1, x, y); print \n%dx%d case, %d solutions. % (SIDE, SIDE, nsolutions) def run(): import time s=time.time() main() print time.time()-s # -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
On 20-07-2009, srepmub wrote: Nice timings, can you please show me the Python, Java and C code versions? I may do more tests. Of course, the codes are here : http://hg.flibuste.net/libre/games/cheval Like you'll see, i tried to use exactly the same code for each langage. also, which shedskin options did you use? did you use -bw, to disable bounds and wrap-around checking? this can make quite a difference for code that does a lot of indexing. if the code uses random numbers, then -r can also make a big difference, to use C rand(), instead of Python compatible random numbers. and which C++ compiler flags did you use? the default -O2, or something like -O3 -fomit-frame-pointer -msse2..? I used the default, shedksin cheval.py; make shedskin 0.2 With -bw and -O3 -fomit-frame-pointer -msse2 i have 5.5s (instead of 8) Let me know if you find better. -- William Dodé - http://flibuste.net Informaticien Indépendant -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
On 20-07-2009, Bearophile wrote: Skip Montanaro: I read just enough French to know that avec means with, but I don't understand the difference between avec malloc *int and avec []. Can you explain please? Maybe it's the time difference between using a Python list from Cython and using a C array allocated with a malloc from Cython. yes, it's this -- William Dodé - http://flibuste.net Informaticien Indépendant -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
With -bw and -O3 -fomit-frame-pointer -msse2 i have 5.5s (instead of 8) Let me know if you find better. thanks. now I'm wondering how fast does the C version become with these flags..? :-) mark. -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
Mark Dufour mark.duf...@gmail.com wrote: I have just released version 0.2 of Shed Skin, an experimental (restricted) Python-to-C++ compiler (http://shedskin.googlecode.com). It comes with 7 new example programs (for a total of 40 example programs, at over 12,000 lines) and several important improvements/bug fixes. See http://code.google.com/p/shedskin/wiki/ReleaseNotes for the full changelog. Cool! I tried it on a program I wrote to solve a puzzle (Rush Hour). (Actually it solves the meta-puzzle - trying to make the hardest possible Rush Hour puzzle.) After a bit of twiddling (remove psyco and profiling) I got it to start compiling, but unfortunately it compiled for about an hour (in iterative type analysis..) used up 600 MB of RAM printing an '*' every 10 minutes or so then gave an error message and gave up. Unfortunately I shut the window by accident, but the error message was something about not being able to resolve types I think with a list of 20 or so unresolved types. Can you give a hint as to how I debug this? I presume my program has some instances of non static types which is causing the problem, but it is going to be a very long debugging session if it takes me an hour each cycle ;-) The program is about 700 lines of python (excluding comments). Thanks Nick -- Nick Craig-Wood n...@craig-wood.com -- http://www.craig-wood.com/nick -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
On 21-07-2009, srepmub wrote: With -bw and -O3 -fomit-frame-pointer -msse2 i have 5.5s (instead of 8) Let me know if you find better. thanks. now I'm wondering how fast does the C version become with these flags..? :-) I don't see any difference... -- William Dodé - http://flibuste.net Informaticien Indépendant -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
Nick Craig-Wood: Can you give a hint as to how I debug this? I presume my program has some instances of non static types which is causing the problem, but it is going to be a very long debugging session if it takes me an hour each cycle ;-) The program is about 700 lines of python (excluding comments). You can show us the Python (SSPython) code, and we can try to find the problem. Sometimes there's no simple ways to solve such problems. Generally for not very large progrograms if SS doesn't compile in about a minute or so then it's gone in infinite loop (there's a compilation flag that avoids some infinite loops, try it). Bye, bearophile -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
William Dode': http://hg.flibuste.net/libre/games/cheval Like you'll see, i tried to use exactly the same code for each langage. It's a cute solver. Few more versions of mine: #1, a Psyco version of mine: http://codepad.org/9m5rf7kX #2, unrolled Psyco version: http://codepad.org/gKFLu34M #3, a quick D (D1) version: http://codepad.org/Tk9FL7Xk Timings (no printing), seconds, best of 3: #1: 4.79 #2: 3.67 #3: 1.10 Your Psyco version: 13.37 Your C version, compiled with GCC 4.3.2, -s -O3 -fomit-frame-pointer: 3.79 I have timed the whole running time of the programs, with an external timer, so my timings include the start of the PythonVM and the final cleanup of the GC. Please, feel free to time my code again, so we can compare with your other timings (Java, etc) better. I have used Psyco 1.6 final and Python 2.6.2 on a Core2 CPU at 2 GHz. To compile the D1 code you can use the free DMD compiler for D1, I have used version 1.042, www.digitalmars.com/d/download.html ). In such benchmarks it's often better to start from the fastest low level code (written in an imperative language as C/D/C++, or a version in a functional language like Clean or OCaML) and then use it to create higher level versions (in Python, etc). This offers you a baseline timing, and usually the small differences of the higher level code compared to the original C/Clean code don't invalidate the test. I have changed only small things in the program, as you can see the Psyco program #2 is faster than your C code :-) If you learn how to use it well, Psyco1.6 can often lead to very good performance. But lot of people don't know how to use Psyco well (I too am ignorant: I don't know how to profile Python programs yet). Bye, bearophile -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
Nick Craig-Wood wrote: I tried it on a program I wrote to solve a puzzle (Rush Hour). (Actually it solves the meta-puzzle - trying to make the hardest possible Rush Hour puzzle.) After a bit of twiddling (remove psyco and profiling) I got it to start compiling, but unfortunately it compiled for about an hour (in iterative type analysis..) used up 600 MB of RAM printing an '*' every 10 minutes or so then gave an error message and gave up. Unfortunately I shut the window by accident, but the error message was something about not being able to resolve types I think with a list of 20 or so unresolved types. Can you give a hint as to how I debug this? I presume my program has some instances of non static types which is causing the problem, but it is going to be a very long debugging session if it takes me an hour each cycle ;-) The program is about 700 lines of python (excluding comments). Split it into pieces and compile each separately. Recurse. tjr -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
William Dode wrote: I just tested it with a litle game, to find the places of horse on a board 5x5. The result is : cython avec malloc *int 18s Posting benchmark times for Pyrex or Cython is pretty meaningless without showing the exact code that was used, since times can vary enormously depending on how much you C-ify things. -- Greg -- http://mail.python.org/mailman/listinfo/python-list
ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
Hi all, I have just released version 0.2 of Shed Skin, an experimental (restricted) Python-to-C++ compiler (http://shedskin.googlecode.com). It comes with 7 new example programs (for a total of 40 example programs, at over 12,000 lines) and several important improvements/bug fixes. See http://code.google.com/p/shedskin/wiki/ReleaseNotes for the full changelog. The new example programs consist of Disco, an elegant go player (see http://shed-skin.blogspot.com/2009/07/disco-elegant-python-go-player.html), a larger Voronoi implementation at 800 lines, a TSP algorithm simulating ant colonies, a nicer neural network algorithm and three compressors (Lempel-Ziv, huffman block, and arithmetic). Other than bug fixes for these programs, this release adds some important optimizations. First and foremost, inlining was greatly improved, resulting in potential speedups across the board. Second, loops such as 'for a, b in enumerate/zip(sequence[, sequence])' should now be dramatically faster (also inside list comprehensions), by avoiding allocation of intermediate tuples. Finally, basic list slicing should now be much faster. Please try it out! Mark Dufour. -- One of my most productive days was throwing away 1000 lines of code - Ken Thompson -- http://mail.python.org/mailman/listinfo/python-announce-list Support the Python Software Foundation: http://www.python.org/psf/donations/
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
On 19-07-2009, Mark Dufour wrote: Hi all, I have just released version 0.2 of Shed Skin, an experimental (restricted) Python-to-C++ compiler (http://shedskin.googlecode.com). I just tested it with a litle game, to find the places of horse on a board 5x5. The result is : c 5s gcj 7s java 7s shedskin 8s python + psyco 18s cython avec malloc *int 18s cython 55s avec [] python python 303s (5m3s) -- William Dodé - http://flibuste.net Informaticien Indépendant -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
William Dode wrote: On 19-07-2009, Mark Dufour wrote: I have just released version 0.2 of Shed Skin, an experimental (restricted) Python-to-C++ compiler (http://shedskin.googlecode.com). I just tested it with a litle game, to find the places of horse on a board 5x5. The result is : [...] shedskin 8s python + psyco 18s cython avec malloc *int 18s cython 55s avec [] python python 303s (5m3s) Note that both Psyco and Cython make a lot less assumptions about Python code than Shed Skin does. Psyco has the advantage of just needing to jump in when it finds out that it can help, so it's the most broadly compatible of the three. But Cython also supports quite a large corpus of dynamic Python code by now. Shed Skin has a lot of restrictions, many of which are by design. It's not intended to compile dynamic code, and I think that's a good thing, because that's what makes it fast for the code that it supports. Getting the same speed in Cython requires a bit more explicit typing, simply because Cython does not assume these restrictions. I think that all three have their raison d'être, and it currently looks like all three are there to stay and to keep growing better. And I'm also happy to read that some optimisations jump from one to the other. ;) Stefan -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
William Dode': I just tested it with a litle game, to find the places of horse on a board 5x5. The result is : c 5s gcj 7s java 7s shedskin 8s python + psyco 18s cython avec malloc *int 18s cython 55s avec [] python python 303s (5m3s) Nice timings, can you please show me the Python, Java and C code versions? I may do more tests. The purpose of all those example programs in ShedSkin is to find bugs and to find details to speedup. Bye, bearophile -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
William c 5s William gcj 7s William java 7s William shedskin 8s William python + psyco 18s William cython avec malloc *int 18s William cython 55s avec [] python William python 303s (5m3s) I read just enough French to know that avec means with, but I don't understand the difference between avec malloc *int and avec []. Can you explain please? Thx, -- Skip Montanaro - s...@pobox.com - http://www.smontanaro.net/ That's more than a dress. That's an Audrey Hepburn movie. -- Jerry Maguire -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
Skip Montanaro: I read just enough French to know that avec means with, but I don't understand the difference between avec malloc *int and avec []. Can you explain please? Maybe it's the time difference between using a Python list from Cython and using a C array allocated with a malloc from Cython. Bye, bearophile -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
Nice timings, can you please show me the Python, Java and C code versions? I may do more tests. also, which shedskin options did you use? did you use -bw, to disable bounds and wrap-around checking? this can make quite a difference for code that does a lot of indexing. if the code uses random numbers, then -r can also make a big difference, to use C rand(), instead of Python compatible random numbers. and which C++ compiler flags did you use? the default -O2, or something like -O3 -fomit-frame-pointer -msse2..? thanks, mark. -- http://mail.python.org/mailman/listinfo/python-list
Re: ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
I like this, I am going to run this as a test. I also want to see the source code on how they compile the dynamic variables. On Mon, Jul 20, 2009 at 10:20 PM, srepmub mark.duf...@gmail.com wrote: Nice timings, can you please show me the Python, Java and C code versions? I may do more tests. also, which shedskin options did you use? did you use -bw, to disable bounds and wrap-around checking? this can make quite a difference for code that does a lot of indexing. if the code uses random numbers, then -r can also make a big difference, to use C rand(), instead of Python compatible random numbers. and which C++ compiler flags did you use? the default -O2, or something like -O3 -fomit-frame-pointer -msse2..? thanks, mark. -- http://mail.python.org/mailman/listinfo/python-list -- http://www.jewelerslounge.com -- http://mail.python.org/mailman/listinfo/python-list
ANN: Shed Skin 0.2, an experimental (restricted) Python-to-C++ compiler
Hi all, I have just released version 0.2 of Shed Skin, an experimental (restricted) Python-to-C++ compiler (http://shedskin.googlecode.com). It comes with 7 new example programs (for a total of 40 example programs, at over 12,000 lines) and several important improvements/bug fixes. See http://code.google.com/p/shedskin/wiki/ReleaseNotes for the full changelog. The new example programs consist of Disco, an elegant go player (see http://shed-skin.blogspot.com/2009/07/disco-elegant-python-go-player.html), a larger Voronoi implementation at 800 lines, a TSP algorithm simulating ant colonies, a nicer neural network algorithm and three compressors (Lempel-Ziv, huffman block, and arithmetic). Other than bug fixes for these programs, this release adds some important optimizations. First and foremost, inlining was greatly improved, resulting in potential speedups across the board. Second, loops such as 'for a, b in enumerate/zip(sequence[, sequence])' should now be dramatically faster (also inside list comprehensions), by avoiding allocation of intermediate tuples. Finally, basic list slicing should now be much faster. Please try it out! Mark Dufour. -- One of my most productive days was throwing away 1000 lines of code - Ken Thompson -- http://mail.python.org/mailman/listinfo/python-list