Pep 3118 Warning When Using Ctypes Array As Numpy Array
Solution 1:
It's a bug in Python. ctypes currently produces invalid PEP 3118 type codes, which Numpy notices: http://bugs.python.org/issue10746http://bugs.python.org/issue10744
When such an inconsistency is present, Numpy skips using the PEP 3118 buffer interface, and falls back to the old (obsolete) buffer interface. This should work properly.
You can silence the warning using Python's warnings
module. However, the warning may have a performance impact.
You can also try working around the issue by wrapping the ctypes object in buffer()
.
Solution 2:
There is a more convenient way of doing this, which avoids the warning altogether:
Instead of creating the data as a ctypes array first and then converting it to a NumPy array, just create it as a NumPy array right away, and then use numpy.ctypeslib.ndpointer
as type specifier in your ctypes prototype. As an example, let's say you have a C function called f
which takes a char*
and a size_t
as arguments:
voidf(char* buf, size_t len);
Your ctypes prototype would be
from numpy.ctypeslib import ndpointer
some_dll = ctypes.CDLL(...)
some_dll.f.argtypes = [ndpointer(numpy.uint8, flags="C_CONTIGUOUS"),
ctypes.c_size_t]
some_dll.f.restype = None
and you can call this function as
a = numpy.zeros(10, numpy.uint8)
f(a, a.size)
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