Fixed-size Sequence Of Bytestrings In Cython
Solution 1:
You are definitely close! There appears to be two issues.
First, we need to change the declaration of obj
so that it reads that we are trying to create an array of char*
objects, fixed to a size of 3. To do this, you need to put the type, then the variable name, and only then the size of the array. This will give you the desired array of char*
on the stack.
Second, when you declare char* a, b, c
, only a
is a char*
, while b
and c
are just char
! This is made clear in cython during the compilation phase, which outputs the following warning for me:
Non-trivial type declarators in shared declaration (e.g. mix of pointers and values). Each pointer declaration should be on its own line.
So you should do this instead:
cdef char* obj[3]
cdef char* a
cdef char* b
cdef char* c
a = b'abc'
b = b'1234'
c = b'^&$#%'
obj = [a, b, c]
As a side note, you can minimize typing cdef
by doing this for your code:
cdef:
char* obj[3]
char* a
char* b
char* c
a = b'abc'
b = b'1234'
c = b'^&$#%'
obj = [a, b, c]
Bonus:
Based on your level of experience with C and pointers in general, I think I will just show the more newbie-friendly approach using C++ data structures. C++ has simple built-in data structures like vector
, which is the equivalent of a python list. The C alternative would be to have a pointer to a struct, signifying an "array" of triplets
. You would then be personally in charge of managing the memory of this using functions like malloc
, free
, realloc
, etc.
Here is something to get you started; I strongly suggest you follow some online C or C++ tutorials on your own and adapt them to cython, which should be fairly trivial after some practice. I am showing both a test.pyx
file as well as the setup.py
file that shows how you can compile this with c++ support.
test.pyx
from libcpp.vector cimport vector
"""
While it can be discouraged to mix raw char* C "strings" wth C++ data types,
the code here is pretty simple.
Fixed arrays cannot be used directly for vector type, so we use a struct.
Ideally, you would use an std::array of std::string, but std::array does not
exist in cython's libcpp. It should be easy to add support for this with an
extern statement though (out of the scope of this mini-tutorial).
"""
ctypedef struct triplet:
char* data[3]
cdef:
vector[triplet] obj
triplet abc
triplet xyz
abc.data = ["abc", "1234", "^&$#%"]
xyz.data = ["xyz", "5678", "%#$&^"]
obj.push_back(abc)#pretty much like python's list.append
obj.push_back(xyz)
"""
Loops through the vector.
Cython can automagically print structs so long as their members can be
converted trivially to python types.
"""
for o in obj:
print(o)
setup.py
from distutils.core import setup
from Cython.Build import cythonize
from distutils.core import Extension
def create_extension(ext_name):
global language, libs, args, link_args
path_parts = ext_name.split(".")
path = "./{0}.pyx".format("/".join(path_parts))
ext = Extension(ext_name, sources=[path], libraries=libs, language=language,
extra_compile_args=args, extra_link_args=link_args)
return ext
if __name__ == "__main__":
libs = []#no external c libraries in this case
language = "c++"#chooses c++ rather than c since STL is used
args = ["-w", "-O3", "-ffast-math", "-march=native", "-fopenmp"]#assumes gcc is the compiler
link_args = ["-fopenmp"]#none here, could use -fopenmp for parallel code
annotate = True#autogenerates .html files per .pyx
directives = {#saves typing @cython decorators and applies them globally
"boundscheck": False,
"wraparound": False,
"initializedcheck": False,
"cdivision": True,
"nonecheck": False,
}
ext_names = [
"test",
]
extensions = [create_extension(ext_name) for ext_name in ext_names]
setup(ext_modules = cythonize(
extensions,
annotate=annotate,
compiler_directives=directives,
)
)
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