Convert Python program to C C code

Question

is it possible to convert a Python program to C C     I need to implement a couple of algorithms  and I m not sure if the performance gap is big enough to justify all the pain I d go through when doing it in C C    which I m not good at   I thought about writing one simple algorithm and benchmark it against such a converted solution  If that alone is significantly faster than the Python version  then I ll have no other choice than doing it in C C

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If the C variant needs x hours less  then I d invest that time in letting the algorithms run longer again    invest  isn t the right word here    Build a working implementation in Python   You ll finish this long before you d finish a C version  Measure performance with the Python profiler   Fix any problems you find   Change data structures and algorithms as necessary to really do this properly   You ll finish this long before you finish the first version in C   If it s still too slow  manually translate the well-designed and carefully constructed Python into C   Because of the way hindsight works  doing the second version from existing Python  with existing unit tests  and with existing profiling data  will still be faster than trying to do the C code from scratch    This quote is important      Thompson s Rule for First-Time Telescope Makers   It is faster to make a four-inch mirror and then a six-inch mirror than to make a six-inch mirror       Bill McKeenan   Wang Institute

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Shed Skin is  a  restricted  Python-to-C   compiler

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http   code google com p py2c  looks like a possibility - they also mention on their site  Cython  Shedskin and RPython and confirm that they are converting Python code to pure C C   which is much faster than C C   riddled with Python API calls  Note  I haven   t tried it but I am going to

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I know this is an older thread but I wanted to give what I think to be helpful information   I personally use PyPy which is really easy to install using pip  I interchangeably use Python PyPy interpreter  you don t need to change your code at all and I ve found it to be roughly 40x faster than the standard python interpreter  Either Python 2x or 3x   I use pyCharm Community Edition to manage my code and I love it    I like writing code in python as I think it lets you focus more on the task than the language  which is a huge plus for me  And if you need it to be even faster  you can always compile to a binary for Windows  Linux  or Mac  not straight forward but possible with other tools   From my experience  I get about 3 5x speedup over PyPy when compiling  meaning 140x faster than python  PyPy is available for Python 3x and 2x code and again if you use an IDE like PyCharm you can interchange between say PyPy  Cython  and Python very easily  takes a little of initial learning and setup though     Some people may argue with me on this one  but I find PyPy to be faster than Cython  But they re both great choices though   Edit  I d like to make another quick note about compiling  when you compile  the resulting binary is much bigger than your python script as it builds all dependencies into it  etc  But then you get a few distinct benefits  speed   now the app will work on any machine  depending on which OS you compiled for  if not all  lol  without Python or libraries  it also obfuscates your code and is technically  production  ready  to a degree   Some compilers also generate C code  which I haven t really looked at or seen if it s useful or just gibberish  Good luck   Hope that helps

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Another option - to convert to C   besides Shed Skin - is Pythran   To quote High Performance Python by Micha Gorelick and Ian Ozsvald      Pythran is a Python-to-C   compiler for a subset of Python that   includes partial numpy support  It acts a little like Numba and   Cython   you annotate a function   s arguments  and then it takes over   with further type annotation and code specialization  It takes   advantage of vectorization possibilities and of OpenMP-based   parallelization possibilities  It runs using Python 2 7 only       One very interesting feature of Pythran is that it will attempt to   automatically spot parallelization opportunities  e g   if you   re   using a map   and turn this into parallel code without requiring extra   effort from you  You can also specify parallel sections using pragma omp              directives  in this respect  it feels very similar to Cython   s   OpenMP support       Behind the scenes  Pythran will take both normal Python and numpy code   and attempt to aggressively compile them into very fast C     even   faster than the results of Cython       You should note that this project is young  and you may encounter   bugs  you should also note that the development team are very friendly   and tend to fix bugs in a matter of hours

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Yes  Look at Cython  It does just that  Converts Python to C for speedups

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Just came across this new tool in hacker news   From their page -  Nuitka is a good replacement for the Python interpreter and compiles every construct that CPython 2 6  2 7  3 2 and 3 3 offer  It translates the Python into a C   program that then uses  libpython  to execute in the same way as CPython does  in a very compatible way

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I realize that an answer on a quite new solution is missing  If Numpy is used in the code  I would advice to try Pythran   http   pythran readthedocs io   For the functions I tried  Pythran gives extremely good results  The resulting functions are as fast as well written Fortran code  or only slightly slower  and a little bit faster than the  quite optimized  Cython solution   The advantage compared to Cython is that you just have to use Pythran on the Python function optimized for Numpy  meaning that you do not have to expand the loops and add types for all variables in the loop  Pythran takes its time to analyse the code so it understands the operations on numpy ndarray   It is also a huge advantage compared to Numba or other projects based on just-in-time compilation for which  to my knowledge   you have to expand the loops to be really efficient  And then the code with the loops becomes very very inefficient using only CPython and Numpy     A drawback of Pythran  no classes  But since only the functions that really need to be optimized have to be compiled  it is not very annoying   Another point  Pythran supports well  and very easily  OpenMP parallelism  But I don t think mpi4py is supported

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