# Buggy code
def _arange_dtype(*args):
    bounds = [a for a in args if not isinstance(a, types.NoneType)]

    if any(isinstance(a, types.Complex) for a in bounds):
        dtype = types.complex128
    elif any(isinstance(a, types.Float) for a in bounds):
        dtype = types.float64
    else:
        # It's not possible for the dtype to replicate NumPy as integer literals
        # are intp size in Numba but np.dtype(int) (i.e. intc) in NumPy. The
        # NumPy logic is to basically do max(np.long, *[type(x) for x in args]).
        # On windows 64, in NumPy, that would mean:
        # * np.arange(1, 10) -> max(np.long, np.intc, np.intc) -> int32
        # but in Numba:
        # * np.arange(1, 10) -> max(np.long, np.intp, np.intp) -> int64
        #
        # It's therefore not possible to replicate the case where integer
        # literals are supplied, however best effort is made to correctly handle
        # cases like:
        # * np.arange(np.int8(10)) -> max(np.long, np.int8) -> np.long
        #
        # Alg ref:
        # https://github.com/numpy/numpy/blob/maintenance/1.17.x/numpy/core/src/multiarray/ctors.c#L3376-L3377    # noqa: E501
        #
        # Also not Py2.7 on 32 bit linux as a 32bit np.long where as Py3 has a
        # 64bit, numba is not replicating this!
        dtype = max(
            bounds
            + [
                types.long_,
            ]
        )

    return dtype


# Traceback (IndexError)
Traceback (most recent call last):
File "/home/ibutygin/miniconda3/envs/NUMBA_CUSTOM/lib/python3.7/site-packages/llvmlite/ir/instructions.py", line 619, in __init__
typ = typ.elements[i]
IndexError: tuple index out of range

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "/home/ibutygin/src/numba/numba/numba/errors.py", line 717, in new_error_context
yield
File "/home/ibutygin/src/numba/numba/numba/lowering.py", line 260, in lower_block
self.lower_inst(inst)
File "/home/ibutygin/src/numba/numba/numba/lowering.py", line 303, in lower_inst
val = self.lower_assign(ty, inst)
File "/home/ibutygin/src/numba/numba/numba/lowering.py", line 467, in lower_assign
return self.lower_expr(ty, value)
File "/home/ibutygin/src/numba/numba/numba/lowering.py", line 932, in lower_expr
res = self.lower_call(resty, expr)
File "/home/ibutygin/src/numba/numba/numba/lowering.py", line 724, in lower_call
res = self._lower_call_normal(fnty, expr, signature)
File "/home/ibutygin/src/numba/numba/numba/lowering.py", line 903, in _lower_call_normal
res = impl(self.builder, argvals, self.loc)
File "/home/ibutygin/src/numba/numba/numba/targets/base.py", line 1132, in __call__
res = self._imp(self._context, builder, self._sig, args, loc=loc)
File "/home/ibutygin/src/numba/numba/numba/targets/base.py", line 1157, in wrapper
return fn(*args, **kwargs)
File "/home/ibutygin/src/numba/numba/numba/typing/templates.py", line 778, in method_impl
return call(builder, args)
File "/home/ibutygin/src/numba/numba/numba/targets/base.py", line 1132, in __call__
res = self._imp(self._context, builder, self._sig, args, loc=loc)
File "/home/ibutygin/src/numba/numba/numba/targets/base.py", line 1157, in wrapper
return fn(*args, **kwargs)
File "/home/ibutygin/src/numba/numba/numba/targets/imputils.py", line 193, in imp
builder, func, fndesc.restype, fndesc.argtypes, args)
File "/home/ibutygin/src/numba/numba/numba/targets/callconv.py", line 477, in call_function
args = list(arginfo.as_arguments(builder, args))
File "/home/ibutygin/src/numba/numba/numba/datamodel/packer.py", line 100, in as_arguments
for dm, val in zip(self._dm_args, values)
File "/home/ibutygin/src/numba/numba/numba/datamodel/packer.py", line 100, in <listcomp>
for dm, val in zip(self._dm_args, values)
File "/home/ibutygin/src/numba/numba/numba/datamodel/models.py", line 447, in as_argument
v = builder.extract_value(value, [i])
File "/home/ibutygin/miniconda3/envs/NUMBA_CUSTOM/lib/python3.7/site-packages/llvmlite/ir/builder.py", line 927, in extract_value
instr = instructions.ExtractValue(self.block, agg, idx, name=name)
File "/home/ibutygin/miniconda3/envs/NUMBA_CUSTOM/lib/python3.7/site-packages/llvmlite/ir/instructions.py", line 622, in __init__
% (list(indices), agg.type))
TypeError: Can't index at [0] in {}

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "test.py", line 73, in <module>
print(bar(Dummy()))
File "/home/ibutygin/src/numba/numba/numba/dispatcher.py", line 420, in _compile_for_args
raise e
File "/home/ibutygin/src/numba/numba/numba/dispatcher.py", line 353, in _compile_for_args
return self.compile(tuple(argtypes))
File "/home/ibutygin/src/numba/numba/numba/compiler_lock.py", line 32, in _acquire_compile_lock
return func(*args, **kwargs)
File "/home/ibutygin/src/numba/numba/numba/dispatcher.py", line 768, in compile
cres = self._compiler.compile(args, return_type)
File "/home/ibutygin/src/numba/numba/numba/dispatcher.py", line 77, in compile
status, retval = self._compile_cached(args, return_type)
File "/home/ibutygin/src/numba/numba/numba/dispatcher.py", line 91, in _compile_cached
retval = self._compile_core(args, return_type)
File "/home/ibutygin/src/numba/numba/numba/dispatcher.py", line 109, in _compile_core
pipeline_class=self.pipeline_class)
File "/home/ibutygin/src/numba/numba/numba/compiler.py", line 543, in compile_extra
return pipeline.compile_extra(func)
File "/home/ibutygin/src/numba/numba/numba/compiler.py", line 328, in compile_extra
return self._compile_bytecode()
File "/home/ibutygin/src/numba/numba/numba/compiler.py", line 389, in _compile_bytecode
return self._compile_core()
File "/home/ibutygin/src/numba/numba/numba/compiler.py", line 368, in _compile_core
raise e
File "/home/ibutygin/src/numba/numba/numba/compiler.py", line 359, in _compile_core
pm.run(self.state)
File "/home/ibutygin/src/numba/numba/numba/compiler_machinery.py", line 331, in run
raise patched_exception
File "/home/ibutygin/src/numba/numba/numba/compiler_machinery.py", line 322, in run
self._runPass(idx, pass_inst, state)
File "/home/ibutygin/src/numba/numba/numba/compiler_lock.py", line 32, in _acquire_compile_lock
return func(*args, **kwargs)
File "/home/ibutygin/src/numba/numba/numba/compiler_machinery.py", line 281, in _runPass
mutated |= check(pss.run_pass, internal_state)
File "/home/ibutygin/src/numba/numba/numba/compiler_machinery.py", line 268, in check
mangled = func(compiler_state)
File "/home/ibutygin/src/numba/numba/numba/typed_passes.py", line 391, in run_pass
NativeLowering().run_pass(state)
File "/home/ibutygin/src/numba/numba/numba/typed_passes.py", line 333, in run_pass
lower.lower()
File "/home/ibutygin/src/numba/numba/numba/lowering.py", line 179, in lower
self.lower_normal_function(self.fndesc)
File "/home/ibutygin/src/numba/numba/numba/lowering.py", line 220, in lower_normal_function
entry_block_tail = self.lower_function_body()
File "/home/ibutygin/src/numba/numba/numba/lowering.py", line 245, in lower_function_body
self.lower_block(block)
File "/home/ibutygin/src/numba/numba/numba/lowering.py", line 260, in lower_block
self.lower_inst(inst)
File "/home/ibutygin/miniconda3/envs/NUMBA_CUSTOM/lib/python3.7/contextlib.py", line 130, in __exit__
self.gen.throw(type, value, traceback)
File "/home/ibutygin/src/numba/numba/numba/errors.py", line 725, in new_error_context
six.reraise(type(newerr), newerr, tb)
File "/home/ibutygin/src/numba/numba/numba/six.py", line 669, in reraise
raise value
numba.errors.LoweringError: Failed in nopython mode pipeline (step: nopython mode backend)
Can't index at [0] in {}

File "test.py", line 71:
def bar(obj):
return obj.inline_method(123,456)
^

[1] During: lowering "$10call_method.4 = call $4load_method.1($const6.2, $const8.3, func=$4load_method.1, args=[Var($const6.2, test.py:71), Var($const8.3, test.py:71)], kws=(), vararg=None)" at test.py (71)

# Fixed code
def _arange_dtype(*args):
    bounds = [a for a in args if not isinstance(a, types.NoneType)]

    if any(isinstance(a, types.Complex) for a in bounds):
        dtype = types.complex128
    elif any(isinstance(a, types.Float) for a in bounds):
        dtype = types.float64
    else:
        # numerous attempts were made at guessing this type from the NumPy
        # source but it turns out on running `np.arange(10).dtype` on pretty
        # much all platform and python combinations that it matched np.int?!
        # Windows 64 is broken by default here because Numba (as of 0.47) does
        # not differentiate between Python and NumPy integers, so a `typeof(1)`
        # on w64 is `int64`, i.e. `intp`. This means an arange(<some int>) will
        # be typed as arange(int64) and the following will yield int64 opposed
        # to int32. Example: without a load of analysis to work out of the args
        # were wrapped in NumPy int*() calls it's not possible to detect the
        # difference between `np.arange(10)` and `np.arange(np.int64(10)`.
        NPY_TY = getattr(types, "int%s" % (8 * np.dtype(np.int).itemsize))
        dtype = max(
            bounds
            + [
                NPY_TY,
            ]
        )

    return dtype