Are you using Linux? Linux has lazy allocation of memory. The underlying calls to malloc and calloc in numpy always ‘succeed’. No memory is actually allocated until the memory is first accessed. The zeros function will use calloc which zeros any allocated memory before it is first accessed. Therfore, numpy need not explicitly zero the … Read more
Contrary to what Adam Matan and others assert, you can in fact create a single executable binary file using Cython, from a pure Python (.py) file. Yes, Cython is intended to be used as stated – as a way of simplifying writing C/C++ extension modules for the CPython python runtime. But, as nudzo alludes to … Read more
After further research (I tried in an empty Win 7 x64 bit VM, without any VCredist previously installed), it seems that these files are enough: the program itself, test.exe (produced by cython –embed and compilation with cl.exe) python37.dll python37.zip coming from packages named “Windows x86-64 embeddable zip file” in https://www.python.org/downloads/windows/ vcruntime140.dll, as mentioned in Can … Read more
You just have some minor errors in the interface definition. The following worked for me: from libc.stdlib cimport malloc import numpy as np cimport numpy as np np.import_array() ctypedef np.int32_t DTYPE_t cdef extern from “numpy/arrayobject.h”: void PyArray_ENABLEFLAGS(np.ndarray arr, int flags) cdef data_to_numpy_array_with_spec(void * ptr, np.npy_intp N, int t): cdef np.ndarray[DTYPE_t, ndim=1] arr = np.PyArray_SimpleNewFromData(1, &N, … Read more
Usually, a Python-interpreter isn’t “standalone” and in order to work it needs its standard libraries (for example ctypes (compiled) or site.py (interpreted)) and also path to other site-packages (for example numpy) must be set. Albeit it is possible to make a Python-interpter fully standalone by freezing the py-modules and merging all c-extensions (see for example … Read more
Calling BLAS bundled with Scipy is “fairly” straightforward, here’s one example for calling DGEMM to compute matrix multiplication: https://gist.github.com/pv/5437087 Note that BLAS and LAPACK expect all arrays to be Fortran-contiguous (modulo the lda/b/c parameters), hence order=”F” and double[::1,:] which are required for correct functioning. Computing inverses can be similarly done by applying the LAPACK function … Read more
Try setting the “CC” environment variable from inside the setup.py with os.environ.
What you want is the –embed flag for the Cython compiler. There isn’t a ton of documentation on it, but this is what I was able to find. It does link to a simple working example. To compile the Cython source code to a C file that can then be compiled to an executable you … Read more
In your setup.py, the Extension should have the argument include_dirs=[numpy.get_include()]. Also, you are missing np.import_array() in your code. — Example setup.py: from distutils.core import setup, Extension from Cython.Build import cythonize import numpy setup( ext_modules=[ Extension(“my_module”, [“my_module.c”], include_dirs=[numpy.get_include()]), ], ) # Or, if you use cythonize() to make the ext_modules list, # include_dirs can be passed … Read more
Here’s the wiki page on embedding cython Assuming you installed python to C:\Python31 and you want to use Microsoft Compiler. smalltest1.py – is the file you want to compile. test.exe – name of the executable. You need to set the environmental variables for cl. C:\Python31\python.exe C:\Python31\Scripts\cython.py smalltest1.py –embed cl.exe /nologo /Ox /MD /W3 /GS- /DNDEBUG … Read more