- class numba.pycc.CC(extension_name, source_module=None)
An object used to generate compiled extensions from Numba-compiled Python functions. extension_name is the name of the extension to be generated. source_module is the Python module containing the functions; if
None, it is inferred by examining the call stack.
CCinstances have the following attributes and methods:
(read-only attribute) The name of the extension module to be generated.
(read-write attribute) The directory the extension module will be written into. By default it is the directory the source_module is located in.
(read-write attribute) The name of the file the extension module will be written to. By default this follows the Python naming convention for the current platform.
(read-write attribute) The name of the CPU model to generate code for. This will select the appropriate instruction set extensions. By default, a generic CPU is selected in order to produce portable code.
Recognized names for this attribute depend on the current architecture and LLVM version. If you have LLVM installed,
llc -mcpu=helpwill give you a list. Examples on x86-64 are
"broadwell". You can also give the value
"host"which will select the current host CPU.
(read-write attribute) If true, print out information while compiling the extension. False by default.
- @export(exported_name, sig)
Mark the decorated function for compilation with the signature sig. The compiled function will be exposed as exported_name in the generated extension module.
All exported names within a given
CCinstance must be distinct, otherwise an exception is raised.
distutils.core.Extensioninstance allowing to integrate generation of the extension module in a conventional
setup.py-driven build process. The optional kwargs let you pass optional parameters to the