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Function descriptors.
from collections import defaultdict
import importlib
from numba.core import types, itanium_mangler
from numba.core.utils import _dynamic_modname, _dynamic_module
def default_mangler(name, argtypes, *, abi_tags=()):
return itanium_mangler.mangle(name, argtypes, abi_tags=abi_tags)
def qualifying_prefix(modname, qualname):
Returns a new string that is used for the first half of the mangled name.
# XXX choose a different convention for object mode
return '{}.{}'.format(modname, qualname) if modname else qualname
class FunctionDescriptor(object):
Base class for function descriptors: an object used to carry
useful metadata about a natively callable function.
Note that while `FunctionIdentity` denotes a Python function
which is being concretely compiled by Numba, `FunctionDescriptor`
may be more "abstract": e.g. a function decorated with `@generated_jit`.
__slots__ = ('native', 'modname', 'qualname', 'doc', 'typemap',
'calltypes', 'args', 'kws', 'restype', 'argtypes',
'mangled_name', 'unique_name', 'env_name', 'global_dict',
'inline', 'noalias', 'abi_tags')
def __init__(self, native, modname, qualname, unique_name, doc,
typemap, restype, calltypes, args, kws, mangler=None,
argtypes=None, inline=False, noalias=False, env_name=None,
global_dict=None, abi_tags=()):
self.native = native
self.modname = modname
self.global_dict = global_dict
self.qualname = qualname
self.unique_name = unique_name
self.doc = doc
# XXX typemap and calltypes should be on the compile result,
# not the FunctionDescriptor
self.typemap = typemap
self.calltypes = calltypes
self.args = args
self.kws = kws
self.restype = restype
# Argument types
if argtypes is not None:
assert isinstance(argtypes, tuple), argtypes
self.argtypes = argtypes
# Get argument types from the type inference result
# (note the "arg.FOO" convention as used in typeinfer
self.argtypes = tuple(self.typemap['arg.' + a] for a in args)
mangler = default_mangler if mangler is None else mangler
# The mangled name *must* be unique, else the wrong function can
# be chosen at link time.
qualprefix = qualifying_prefix(self.modname, self.unique_name)
self.mangled_name = mangler(
qualprefix, self.argtypes, abi_tags=abi_tags,
if env_name is None:
env_name = mangler(".NumbaEnv.{}".format(qualprefix),
self.argtypes, abi_tags=abi_tags)
self.env_name = env_name
self.inline = inline
self.noalias = noalias
self.abi_tags = abi_tags
def lookup_globals(self):
Return the global dictionary of the function.
It may not match the Module's globals if the function is created
dynamically (i.e. exec)
return self.global_dict or self.lookup_module().__dict__
def lookup_module(self):
Return the module in which this function is supposed to exist.
This may be a dummy module if the function was dynamically
generated. Raise exception if the module can't be found.
if self.modname == _dynamic_modname:
return _dynamic_module
# ensure module exist
return importlib.import_module(self.modname)
except ImportError:
raise ModuleNotFoundError(
f"can't compile {self.qualname}: "
f"import of module {self.modname} failed") from None
def lookup_function(self):
Return the original function object described by this object.
return getattr(self.lookup_module(), self.qualname)
def llvm_func_name(self):
The LLVM-registered name for the raw function.
return self.mangled_name
# XXX refactor this
def llvm_cpython_wrapper_name(self):
The LLVM-registered name for a CPython-compatible wrapper of the
raw function (i.e. a PyCFunctionWithKeywords).
return itanium_mangler.prepend_namespace(self.mangled_name,
def llvm_cfunc_wrapper_name(self):
The LLVM-registered name for a C-compatible wrapper of the
raw function.
return 'cfunc.' + self.mangled_name
def __repr__(self):
return "<function descriptor %r>" % (self.unique_name)
def _get_function_info(cls, func_ir):
qualname, unique_name, modname, doc, args, kws, globals
``unique_name`` must be a unique name.
func = func_ir.func_id.func
qualname = func_ir.func_id.func_qualname
# XXX to func_id
modname = func.__module__
doc = func.__doc__ or ''
args = tuple(func_ir.arg_names)
kws = () # TODO
global_dict = None
if modname is None:
# Dynamically generated function.
modname = _dynamic_modname
# Retain a reference to the dictionary of the function.
# This disables caching, serialization and pickling.
global_dict = func_ir.func_id.func.__globals__
unique_name = func_ir.func_id.unique_name
return qualname, unique_name, modname, doc, args, kws, global_dict
def _from_python_function(cls, func_ir, typemap, restype,
calltypes, native, mangler=None,
inline=False, noalias=False, abi_tags=()):
(qualname, unique_name, modname, doc, args, kws, global_dict,
) = cls._get_function_info(func_ir)
self = cls(native, modname, qualname, unique_name, doc,
typemap, restype, calltypes,
args, kws, mangler=mangler, inline=inline, noalias=noalias,
global_dict=global_dict, abi_tags=abi_tags)
return self
class PythonFunctionDescriptor(FunctionDescriptor):
A FunctionDescriptor subclass for Numba-compiled functions.
__slots__ = ()
def from_specialized_function(cls, func_ir, typemap, restype, calltypes,
mangler, inline, noalias, abi_tags):
Build a FunctionDescriptor for a given specialization of a Python
function (in nopython mode).
return cls._from_python_function(func_ir, typemap, restype, calltypes,
native=True, mangler=mangler,
inline=inline, noalias=noalias,
def from_object_mode_function(cls, func_ir):
Build a FunctionDescriptor for an object mode variant of a Python
typemap = defaultdict(lambda: types.pyobject)
calltypes = typemap.copy()
restype = types.pyobject
return cls._from_python_function(func_ir, typemap, restype, calltypes,
class ExternalFunctionDescriptor(FunctionDescriptor):
A FunctionDescriptor subclass for opaque external functions
(e.g. raw C functions).
__slots__ = ()
def __init__(self, name, restype, argtypes):
args = ["arg%d" % i for i in range(len(argtypes))]
super(ExternalFunctionDescriptor, self
).__init__(native=True, modname=None, qualname=name,
unique_name=name, doc='', typemap=None,
restype=restype, calltypes=None, args=args,
mangler=lambda a, x, abi_tags: a, argtypes=argtypes)