The following code works on arbitrary lists:
import ctypes
py_values = [1, 2, 3, 4]
arr = (ctypes.c_int * len(py_values))(*py_values)
Python
docs.python.org › 3 › library › ctypes.html
ctypes — A foreign function library for Python
The recommended way to create array types is by multiplying a data type with a positive integer: ... Here is an example of a somewhat artificial data type, a structure containing 4 POINTs among other stuff: >>> from ctypes import * >>> class ...
CodersLegacy
coderslegacy.com › home › python › using arrays with python ctypes
Using Arrays with Python Ctypes - CodersLegacy
March 10, 2023 - In ctypes, the way to do this is to multiply a normal datatype (like c_int) by the number of elements you want in the array. The empty () brackets count as a constructor of sorts.
Using ctypes in Python - arrays and structures
Hello Folks! I try to call from Python several routines contained in a .so library generated from some Fortran 90 routines. All the objects in the library are resolved using the -fPIC flag when compiling the .so. I have a sample code which looks like #!/usr/bin/env python3 from numpy import... More on thecodingforums.com
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December 7, 2011Using array.array in Python ctypes - Stack Overflow
I have to interface a Python program with a C library. The particular function I need to call takes an array and returns a double. The following function has the same signature and is easier to More on stackoverflow.com
python ctypes arrays - Stack Overflow
I would like to have an array of variable length arrays in ctypes. I know the size of the outer array and all of the inner arrays, too. I found an interesting thread here: How do I emulate a dynam... More on stackoverflow.com
Passing long double array to C function with ctypes
I dont know why i got downvoted :( but it wasnt working because ctypes isnt good with long double apparently. changing from long double to double worked. More on reddit.com
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1
November 14, 2023Using arrays with python ctypes
Wrap C Function returning array of unknown size using ctypes ...
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Convert Array pointer to List in Python Ctypes - YouTube
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Ctypes vs regular Python: Performance comparison - YouTube
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Using Structs and Classes with Python Ctypes - YouTube
Top answer 1 of 4
120
The following code works on arbitrary lists:
import ctypes
py_values = [1, 2, 3, 4]
arr = (ctypes.c_int * len(py_values))(*py_values)
2 of 4
25
This is an explanation of the accepted answer.
ctypes.c_int * len(pyarr) creates an array (sequence) of type c_int of length 4 (python3, python 2). Since c_int is an object whose constructor takes one argument, (ctypes.c_int * len(pyarr)(*pyarr) does a one shot init of each c_int instance from pyarr. An easier to read form is:
pyarr = [1, 2, 3, 4]
seq = ctypes.c_int * len(pyarr)
arr = seq(*pyarr)
Use type function to see the difference between seq and arr.
Rip Tutorial
riptutorial.com › ctypes arrays
Python Language Tutorial => ctypes arrays
Now arr is an actual array that contains the numbers from 0 to 15. They can be accessed just like any list: >>> arr[5] 5 >>> arr[5] = 20 >>> arr[5] 20 · And just like any other ctypes object, it also has a size and a location: >>> sizeof(arr) 64 # sizeof(c_int) * 16 >>> hex(addressof(arr)) '0xc000l0ff' PDF - Download Python Language for free ·
Fz-juelich
pgi-jcns.fz-juelich.de › portal › pages › using-c-from-python.html
Using C from Python: How to create a ctypes wrapper - Scientific IT-Systems
The type expects each array element as an argument, so we use the asterisk notation with numbers. The result has the type ctypes.c_int and we want to return a python integer, therefore int(result) is returned.
NumPy
numpy.org › doc › stable › reference › generated › numpy.ndarray.ctypes.html
numpy.ndarray.ctypes — NumPy v2.5 Manual
The ctypes array contains the shape of the underlying array.
SciPy
scipy.github.io › old-wiki › pages › Cookbook › Ctypes.html
Cookbook/Ctypes - SciPy wiki dump
In addition to dimension and shape, this allocator function takes a char indicating what type of array to allocate. You can get these typecodes from the ndarrayobject.h header, in the NPY_TYPECHAR enum. 1 from ctypes import * 2 import numpy as N 3 4 class Allocator: 5 CFUNCTYPE = CFUNCTYPE(c_long, c_int, POINTER(c_int), c_char) 6 7 def __init__(self): 8 self.allocated_arrays = [] 9 10 def __call__(self, dims, shape, dtype): 11 x = N.empty(shape[:dims], N.dtype(dtype)) 12 self.allocated_arrays.append(x) 13 return x.ctypes.data_as(c_void_p).value 14 15 def getcfunc(self): 16 return self.CFUNCTYPE(self) 17 cfunc = property(getcfunc)
NumPy
numpy.org › devdocs › reference › generated › numpy.ndarray.ctypes.html
numpy.ndarray.ctypes — NumPy v2.6.dev0 Manual
The ctypes array contains the shape of the underlying array.
ProgramCreek
programcreek.com › python › example › 51331 › ctypes.Array
Python Examples of ctypes.Array
def __init__(self, *args, **kwds): super(Array, self).__init__(*args, **kwds) try: if self.flags & PAI_NOTSWAPPED: ct = self._ctypes[self.typekind, self.itemsize] elif c_int.__ctype_le__ is c_int: ct = self._ctypes[self.typekind, self.itemsize].__ctype_be__ else: ct = self._ctypes[self.typekind, self.itemsize].__ctype_le__ except KeyError: ct = c_uint8 * self.itemsize self._ctype = ct self._ctype_p = POINTER(ct) ... def _convert_ctype_to_python(x): if isinstance(x, ctypes.Structure): return [_convert_ctype_to_python(getattr(x, field_name)) for field_name, _ in x._fields_] if isinstance(x, ctypes.Array): return [_convert_ctype_to_python(num) for num in x] if isinstance(x, ctypes.c_double): return x.value if isinstance(x, (float, int)): return x assert False, "Don't know how to convert: {}".format(x)
SageMath
doc.sagemath.org › html › en › thematic_tutorials › numerical_sage › ctypes.html
Ctypes - Thematic Tutorials
Note that actually there are other ways to pass in the required array of doubles. For example · a=(c_double*10)() for i in range(10): a[i]=i my_sum.sum(a,int(10)) This example only uses ctypes. Ctypes has wrappers for C data types so for example ... would create a ctypes double object which could be passed to a C function. Note that there is a byref function that lets you pass parameters by reference. This is used in the next example. c double*10, is a python object that represents an array of 10 doubles and
Medium
stephenscotttucker.medium.com › interfacing-python-with-c-using-ctypes-classes-and-arrays-42534d562ce7
Interfacing Python with C++ using ctypes: classes and arrays | by Stephen Tucker | Medium
March 2, 2023 - Whatever the case may be, we’ll need to wrap C/C++ functions in Python code that allows arguments and return types to be shared. Luckily, the ctypes module (included in the Standard Library) makes this simple. Even arrays can be easily passed to and returned from wrapped functions with a little help from NumPy.
GitHub
gist.github.com › nicolamontecchio › 3277840
python ctypes - array conversion · GitHub
May 25, 2019 - Hi, how to convert an address of array into array with ctypes ?
YouTube
youtube.com › coderslegacy
Using Arrays with Python Ctypes - YouTube
In this Video we will discuss how to pass Arrays back and forth between our C and Python programs using the ctypes library.C File Compilation Command:gcc -fP...
Published: November 16, 2022
Views: 4K
The Coding Forums
thecodingforums.com › programming languages › python
Using ctypes in Python - arrays and structures | Python | Coding Forums
December 7, 2011 - NumNodes = zeros(NumElems, dtype=int, order="Fortran") method(byref(c_int(NumElems)), NumNodes.ctypes.data_as(POINTER(c_int)), Length.ctypes.data_as(POINTER(c_double)), RBMass.ctypes.data_as(POINTER(c_double)) ) In this second case, the array NumNodes is equal to array([8589934594, 0]), whereas both elements of NumNodes should be equal to 2. I haven't said earlier, but NumNodes is only initialized in Python and it gets the values in the Fortran90 where they are computed in correct way.
NumPy
numpy.org › doc › 2.1 › reference › generated › numpy.ndarray.ctypes.html
numpy.ndarray.ctypes — NumPy v2.1 Manual
The ctypes array contains the shape of the underlying array.
Top answer 1 of 2
4
use array.buffer_info() to get the address and length, and cast() the address to POINTER(c_double):
from array import array
buf = array("d", range(101))
addr, count = buf.buffer_info()
print lib.sum(cast(addr, POINTER(c_double)), count)
2 of 2
0
Not that this is a better answer but for completeness if you are using numpy it is just a bit different as numpy can handle the cast part for you.
import numpy as np
data = np.arange(101, dtype=ctypes.c_double) # making this match seems important sometimes
print lib.sum(data.ctypes.data_as(ctypes.POINTER(ctypes.c_double)), len(data))
Reddit
reddit.com › r/learnprogramming › need help with python ctypes array and splat operator on bytesarray object
r/learnprogramming on Reddit: Need help with Python ctypes array and splat operator on bytesarray object
May 22, 2024 - import ctypes import pathlib r = ctypes.CDLL(pathlib.Path().absolute() / "renderer.dll") settings = {} def init(map, **kwargs): global settings settings.update({ "size": ctypes.c_uint64(map.size.width()*map.size.height()), "map": (ctypes.c_uint32 * map.size.width() * map.size.height())(*(map.map)), "background": map.model.background }) settings.update(kwargs) r.test() class initMapStruct(ctypes.Structure): _fields_ = [ ('r', ctypes.c_uint8), ('g', ctypes.c_uint8), ('b', ctypes.c_uint8), ('a', ctypes.c_uint8), ('length', ctypes.c_size_t), ('map', ctypes.POINTER(ctypes.c_uint32)) ] def __init__(
NumPy
numpy.org › doc › stable › reference › generated › numpy.recarray.ctypes.html
numpy.recarray.ctypes — NumPy v2.3 Manual
June 29, 2020 - The ctypes array contains the shape of the underlying array.
NumPy
numpy.org › doc › 2.2 › reference › generated › numpy.ndarray.ctypes.html
numpy.ndarray.ctypes — NumPy v2.2 Manual
The ctypes array contains the shape of the underlying array.