def test_type_parameter_equality(self):
param1 = abstract.TypeParameter("S", self._ctx)
param2 = abstract.TypeParameter("T", self._ctx)
cls = abstract.InterpreterClass("S", [], {}, None, self._ctx)
self.assertEqual(param1, param1)
self.assertNotEqual(param1, param2)
self.assertNotEqual(param1, cls)
def test_type_parameter_official_name(self):
param = abstract.TypeParameter("T", self._ctx)
self._ctx.vm.frame = frame_state.SimpleFrame() # for error logging
param.update_official_name("T")
self.assertFalse(self._ctx.errorlog.has_error())
param.update_official_name("Q")
self.assertTrue(self._ctx.errorlog.has_error())
def test_type_parameter_instance_bad_attribute(self):
t = abstract.TypeParameter(abstract_utils.T, self._ctx)
t_instance = abstract.TypeParameterInstance(
t, self._ctx.convert.primitive_class_instances[str], self._ctx)
node, var = self._ctx.attribute_handler.get_attribute(
self._ctx.root_node, t_instance, "rumpelstiltskin")
self.assertIs(node, self._ctx.root_node)
self.assertIsNone(var)
def test_instantiate_type_parameter_type(self):
params = {
abstract_utils.T: abstract.TypeParameter(abstract_utils.T, self._ctx)
}
cls = abstract.ParameterizedClass(self._ctx.convert.type_type, params,
self._ctx)
self.assertListEqual(
cls.instantiate(self._node).data, [self._ctx.convert.unsolvable])
def test_type_parameter_instance(self):
t = abstract.TypeParameter(abstract_utils.T, self._ctx)
t_instance = abstract.TypeParameterInstance(
t, self._ctx.convert.primitive_class_instances[str], self._ctx)
node, var = self._ctx.attribute_handler.get_attribute(
self._ctx.root_node, t_instance, "upper")
self.assertIs(node, self._ctx.root_node)
attr, = var.data
self.assertIsInstance(attr, abstract.PyTDFunction)
def test_call_with_type_parameter(self):
ret_cls = abstract.ParameterizedClass(
self._ctx.convert.list_type,
{abstract_utils.T: abstract.TypeParameter(abstract_utils.T, self._ctx)},
self._ctx)
f = self._make_func(
param_names=("test",),
annotations={
"test": abstract.TypeParameter(abstract_utils.T, self._ctx),
"return": ret_cls
})
args = function.Args(
posargs=(self._ctx.convert.build_int(self._ctx.root_node),))
_, ret = f.call(self._ctx.root_node, f, args)
# ret is an Instance(ParameterizedClass(list, {abstract_utils.T: int}))
# but we really only care about T.
self.assertIs(ret.data[0].cls.formal_type_parameters[abstract_utils.T],
self._ctx.convert.int_type)
def test_call_empty_type_parameter_instance(self):
instance = abstract.Instance(self._ctx.convert.list_type, self._ctx)
t = abstract.TypeParameter(abstract_utils.T, self._ctx)
t_instance = abstract.TypeParameterInstance(t, instance, self._ctx)
node, ret = t_instance.call(self._node, t_instance.to_binding(self._node),
function.Args(posargs=()))
self.assertIs(node, self._node)
retval, = ret.data
self.assertIs(retval, self._ctx.convert.empty)
def test_empty_type_parameter_instance(self):
t = abstract.TypeParameter(
abstract_utils.T, self._ctx, bound=self._ctx.convert.int_type)
instance = abstract.Instance(self._ctx.convert.list_type, self._ctx)
t_instance = abstract.TypeParameterInstance(t, instance, self._ctx)
node, var = self._ctx.attribute_handler.get_attribute(
self._ctx.root_node, t_instance, "real")
self.assertIs(node, self._ctx.root_node)
attr, = var.data
self.assertIs(attr, self._ctx.convert.primitive_class_instances[int])
def test_type_parameter_instance_set_attribute(self):
t = abstract.TypeParameter(abstract_utils.T, self._ctx)
t_instance = abstract.TypeParameterInstance(
t, self._ctx.convert.primitive_class_instances[str], self._ctx)
node = self._ctx.attribute_handler.set_attribute(
self._ctx.root_node, t_instance, "rumpelstiltskin",
self._ctx.new_unsolvable(self._ctx.root_node))
self.assertIs(node, self._ctx.root_node)
self.assertEqual(
str(self._ctx.errorlog).strip(),
"Can't assign attribute 'rumpelstiltskin' on str [not-writable]")
def test_call_type_parameter_instance(self):
instance = abstract.Instance(self._ctx.convert.list_type, self._ctx)
instance.merge_instance_type_parameter(
self._ctx.root_node, abstract_utils.T,
self._ctx.convert.int_type.to_variable(self._ctx.root_node))
t = abstract.TypeParameter(abstract_utils.T, self._ctx)
t_instance = abstract.TypeParameterInstance(t, instance, self._ctx)
node, ret = t_instance.call(self._node, t_instance.to_binding(self._node),
function.Args(posargs=()))
self.assertIs(node, self._node)
retval, = ret.data
self.assertEqual(retval.cls, self._ctx.convert.int_type)
def test_call_type_parameter_instance_with_wrong_args(self):
instance = abstract.Instance(self._ctx.convert.list_type, self._ctx)
instance.merge_instance_type_parameter(
self._ctx.root_node, abstract_utils.T,
self._ctx.convert.int_type.to_variable(self._ctx.root_node))
t = abstract.TypeParameter(abstract_utils.T, self._ctx)
t_instance = abstract.TypeParameterInstance(t, instance, self._ctx)
posargs = (self._ctx.new_unsolvable(self._node),) * 3
node, ret = t_instance.call(self._node, t_instance.to_binding(self._node),
function.Args(posargs=posargs))
self.assertIs(node, self._node)
self.assertTrue(ret.bindings)
error, = self._ctx.errorlog
self.assertEqual(error.name, "wrong-arg-count")
def test_instantiate_tuple_class_for_sub(self):
type_param = abstract.TypeParameter(abstract_utils.K, self._ctx)
cls = abstract.TupleClass(self._ctx.convert.tuple_type, {
0: type_param,
abstract_utils.T: type_param
}, self._ctx)
# Instantiate the tuple class.
subst_value = cls.instantiate(self._ctx.root_node,
abstract_utils.DUMMY_CONTAINER)
# Recover the class from the instance.
subbed_cls = self._ctx.annotation_utils.sub_one_annotation(
self._ctx.root_node, type_param, [{
abstract_utils.K: subst_value
}])
self.assertEqual(cls, subbed_cls)
def make_replace_method(ctx, node, cls, *, kwargs_name="kwargs"):
"""Create a replace() method for a dataclass."""
# This is used by several packages that extend dataclass.
# The signature is
# def replace(self: T, **kwargs) -> T
typevar = abstract.TypeParameter(abstract_utils.T + cls.name,
ctx,
bound=cls)
return overlay_utils.make_method(
ctx=ctx,
node=node,
name="replace",
return_type=typevar,
self_param=overlay_utils.Param("self", typevar),
kwargs=overlay_utils.Param(kwargs_name),
)
def _get_typeparam(self, node, args):
args = args.simplify(node, self.ctx)
try:
self.match_args(node, args)
except function.InvalidParameters as e:
raise TypeVarError("wrong arguments", e.bad_call) from e
except function.FailedFunctionCall as e:
# It is currently impossible to get here, since the only
# FailedFunctionCall that is not an InvalidParameters is NotCallable.
raise TypeVarError("initialization failed") from e
name = self._get_constant(args.posargs[0],
"name",
str,
arg_type_desc="a constant str")
constraints = tuple(
self._get_annotation(node, c, "constraint")
for c in args.posargs[1:])
if len(constraints) == 1:
raise TypeVarError(
"the number of constraints must be 0 or more than 1")
bound = self._get_namedarg(node, args, "bound", None)
covariant = self._get_namedarg(node, args, "covariant", False)
contravariant = self._get_namedarg(node, args, "contravariant", False)
if constraints and bound:
raise TypeVarError(
"constraints and a bound are mutually exclusive")
extra_kwargs = set(
args.namedargs) - {"bound", "covariant", "contravariant"}
if extra_kwargs:
raise TypeVarError("extra keyword arguments: " +
", ".join(extra_kwargs))
if args.starargs:
raise TypeVarError("*args must be a constant tuple")
if args.starstarargs:
raise TypeVarError("ambiguous **kwargs not allowed")
return abstract.TypeParameter(name,
self.ctx,
constraints=constraints,
bound=bound,
covariant=covariant,
contravariant=contravariant)
def _constant_to_value(self, pyval, subst, get_node):
"""Create a BaseValue that represents a python constant.
This supports both constant from code constant pools and PyTD constants such
as classes. This also supports builtin python objects such as int and float.
Args:
pyval: The python or PyTD value to convert.
subst: The current type parameters.
get_node: A getter function for the current node.
Returns:
A Value that represents the constant, or None if we couldn't convert.
Raises:
NotImplementedError: If we don't know how to convert a value.
TypeParameterError: If we can't find a substitution for a type parameter.
"""
if isinstance(pyval, str):
return abstract.ConcreteValue(pyval, self.str_type, self.ctx)
elif isinstance(pyval, bytes):
return abstract.ConcreteValue(pyval, self.bytes_type, self.ctx)
elif isinstance(pyval, bool):
return self.true if pyval else self.false
elif isinstance(pyval, int) and -1 <= pyval <= _MAX_IMPORT_DEPTH:
# For small integers, preserve the actual value (for things like the
# level in IMPORT_NAME).
return abstract.ConcreteValue(pyval, self.int_type, self.ctx)
elif pyval.__class__ in self.primitive_classes:
return self.primitive_class_instances[pyval.__class__]
elif pyval.__class__ is frozenset:
instance = abstract.Instance(self.frozenset_type, self.ctx)
for element in pyval:
instance.merge_instance_type_parameter(
self.ctx.root_node, abstract_utils.T,
self.constant_to_var(element, subst, self.ctx.root_node))
return instance
elif isinstance(pyval, (loadmarshal.CodeType, blocks.OrderedCode)):
return abstract.ConcreteValue(pyval,
self.primitive_classes[types.CodeType],
self.ctx)
elif pyval is super:
return special_builtins.Super(self.ctx)
elif pyval is object:
return special_builtins.Object(self.ctx)
elif pyval.__class__ is type:
try:
return self.name_to_value(self._type_to_name(pyval), subst)
except (KeyError, AttributeError):
log.debug("Failed to find pytd", exc_info=True)
raise
elif isinstance(pyval, pytd.LateType):
actual = self._load_late_type(pyval)
return self._constant_to_value(actual, subst, get_node)
elif isinstance(pyval, pytd.TypeDeclUnit):
return self._create_module(pyval)
elif isinstance(pyval, pytd.Module):
mod = self.ctx.loader.import_name(pyval.module_name)
return self._create_module(mod)
elif isinstance(pyval, pytd.Class):
if pyval.name == "builtins.super":
return self.ctx.special_builtins["super"]
elif pyval.name == "builtins.object":
return self.object_type
elif pyval.name == "types.ModuleType":
return self.module_type
elif pyval.name == "_importlib_modulespec.ModuleType":
# Python 3's typeshed uses a stub file indirection to define ModuleType
# even though it is exported via types.pyi.
return self.module_type
elif pyval.name == "types.FunctionType":
return self.function_type
else:
module, dot, base_name = pyval.name.rpartition(".")
# typing.TypingContainer intentionally loads the underlying pytd types.
if (module not in ("typing", "typing_extensions") and
module in overlay_dict.overlays):
overlay = self.ctx.vm.import_module(module, module, 0)
if overlay.get_module(base_name) is overlay:
overlay.load_lazy_attribute(base_name)
return abstract_utils.get_atomic_value(overlay.members[base_name])
try:
cls = abstract.PyTDClass.make(base_name, pyval, self.ctx)
except mro.MROError as e:
self.ctx.errorlog.mro_error(self.ctx.vm.frames, base_name, e.mro_seqs)
cls = self.unsolvable
else:
if dot:
cls.module = module
cls.call_metaclass_init(get_node())
return cls
elif isinstance(pyval, pytd.Function):
signatures = [
abstract.PyTDSignature(pyval.name, sig, self.ctx)
for sig in pyval.signatures
]
type_new = self.ctx.loader.lookup_builtin("builtins.type").Lookup(
"__new__")
if pyval is type_new:
f_cls = special_builtins.TypeNew
else:
f_cls = abstract.PyTDFunction
f = f_cls(pyval.name, signatures, pyval.kind, self.ctx)
f.is_abstract = pyval.is_abstract
return f
elif isinstance(pyval, pytd.ClassType):
if pyval.cls:
cls = pyval.cls
else:
# If pyval is a reference to a class in builtins or typing, we can fill
# in the class ourselves. lookup_builtin raises a KeyError if the name
# is not found.
cls = self.ctx.loader.lookup_builtin(pyval.name)
assert isinstance(cls, pytd.Class)
return self.constant_to_value(cls, subst, self.ctx.root_node)
elif isinstance(pyval, pytd.NothingType):
return self.empty
elif isinstance(pyval, pytd.AnythingType):
return self.unsolvable
elif (isinstance(pyval, pytd.Constant) and
isinstance(pyval.type, pytd.AnythingType)):
# We allow "X = ... # type: Any" to declare X as a type.
return self.unsolvable
elif (isinstance(pyval, pytd.Constant) and
isinstance(pyval.type, pytd.GenericType) and
pyval.type.name == "builtins.type"):
# `X: Type[other_mod.X]` is equivalent to `X = other_mod.X`.
param, = pyval.type.parameters
return self.constant_to_value(param, subst, self.ctx.root_node)
elif isinstance(pyval, pytd.UnionType):
options = [
self.constant_to_value(t, subst, self.ctx.root_node)
for t in pyval.type_list
]
if len(options) > 1:
return abstract.Union(options, self.ctx)
else:
return options[0]
elif isinstance(pyval, pytd.TypeParameter):
constraints = tuple(
self.constant_to_value(c, {}, self.ctx.root_node)
for c in pyval.constraints)
bound = (
pyval.bound and
self.constant_to_value(pyval.bound, {}, self.ctx.root_node))
return abstract.TypeParameter(
pyval.name,
self.ctx,
constraints=constraints,
bound=bound,
module=pyval.scope)
elif isinstance(pyval, abstract_utils.AsInstance):
cls = pyval.cls
if isinstance(cls, pytd.LateType):
actual = self._load_late_type(cls)
if not isinstance(actual, pytd.ClassType):
return self.unsolvable
cls = actual.cls
if isinstance(cls, pytd.ClassType):
cls = cls.cls
if isinstance(cls, pytd.GenericType) and cls.name == "typing.ClassVar":
param, = cls.parameters
return self.constant_to_value(
abstract_utils.AsInstance(param), subst, self.ctx.root_node)
elif isinstance(cls, pytd.GenericType) or (isinstance(cls, pytd.Class) and
cls.template):
# If we're converting a generic Class, need to create a new instance of
# it. See test_classes.testGenericReinstantiated.
if isinstance(cls, pytd.Class):
params = tuple(t.type_param.upper_value for t in cls.template)
cls = pytd.GenericType(base_type=pytd.ClassType(cls.name, cls),
parameters=params)
if isinstance(cls.base_type, pytd.LateType):
actual = self._load_late_type(cls.base_type)
if not isinstance(actual, pytd.ClassType):
return self.unsolvable
base_cls = actual.cls
else:
base_type = cls.base_type
assert isinstance(base_type, pytd.ClassType)
base_cls = base_type.cls
assert isinstance(base_cls, pytd.Class), base_cls
if base_cls.name == "builtins.type":
c, = cls.parameters
if isinstance(c, pytd.TypeParameter):
if not subst or c.full_name not in subst:
raise self.TypeParameterError(c.full_name)
# deformalize gets rid of any unexpected TypeVars, which can appear
# if something is annotated as Type[T].
return self.ctx.annotation_utils.deformalize(
self.merge_classes(subst[c.full_name].data))
else:
return self.constant_to_value(c, subst, self.ctx.root_node)
elif isinstance(cls, pytd.TupleType):
content = tuple(self.constant_to_var(abstract_utils.AsInstance(p),
subst, get_node())
for p in cls.parameters)
return self.tuple_to_value(content)
elif isinstance(cls, pytd.CallableType):
clsval = self.constant_to_value(cls, subst, self.ctx.root_node)
return abstract.Instance(clsval, self.ctx)
else:
clsval = self.constant_to_value(base_cls, subst, self.ctx.root_node)
instance = abstract.Instance(clsval, self.ctx)
num_params = len(cls.parameters)
assert num_params <= len(base_cls.template)
for i, formal in enumerate(base_cls.template):
if i < num_params:
node = get_node()
p = self.constant_to_var(
abstract_utils.AsInstance(cls.parameters[i]), subst, node)
else:
# An omitted type parameter implies `Any`.
node = self.ctx.root_node
p = self.unsolvable.to_variable(node)
instance.merge_instance_type_parameter(node, formal.name, p)
return instance
elif isinstance(cls, pytd.Class):
assert not cls.template
# This key is also used in __init__
key = (abstract.Instance, cls)
if key not in self._convert_cache:
if cls.name in ["builtins.type", "builtins.property"]:
# An instance of "type" or of an anonymous property can be anything.
instance = self._create_new_unknown_value("type")
else:
mycls = self.constant_to_value(cls, subst, self.ctx.root_node)
instance = abstract.Instance(mycls, self.ctx)
log.info("New pytd instance for %s: %r", cls.name, instance)
self._convert_cache[key] = instance
return self._convert_cache[key]
elif isinstance(cls, pytd.Literal):
return self.constant_to_value(
self._get_literal_value(cls.value), subst, self.ctx.root_node)
else:
return self.constant_to_value(cls, subst, self.ctx.root_node)
elif (isinstance(pyval, pytd.GenericType) and
pyval.name == "typing.ClassVar"):
param, = pyval.parameters
return self.constant_to_value(param, subst, self.ctx.root_node)
elif isinstance(pyval, pytd.GenericType):
if isinstance(pyval.base_type, pytd.LateType):
actual = self._load_late_type(pyval.base_type)
if not isinstance(actual, pytd.ClassType):
return self.unsolvable
base = actual.cls
else:
assert isinstance(pyval.base_type, pytd.ClassType), pyval
base = pyval.base_type.cls
assert isinstance(base, pytd.Class), base
base_cls = self.constant_to_value(base, subst, self.ctx.root_node)
if not isinstance(base_cls, abstract.Class):
# base_cls can be, e.g., an unsolvable due to an mro error.
return self.unsolvable
if isinstance(pyval, pytd.TupleType):
abstract_class = abstract.TupleClass
template = list(range(len(pyval.parameters))) + [abstract_utils.T]
combined_parameter = pytd_utils.JoinTypes(pyval.parameters)
parameters = pyval.parameters + (combined_parameter,)
elif isinstance(pyval, pytd.CallableType):
abstract_class = abstract.CallableClass
template = list(range(len(pyval.args))) + [abstract_utils.ARGS,
abstract_utils.RET]
parameters = pyval.args + (pytd_utils.JoinTypes(pyval.args), pyval.ret)
else:
abstract_class = abstract.ParameterizedClass
if pyval.name == "typing.Generic":
pyval_template = pyval.parameters
else:
pyval_template = base.template
template = tuple(t.name for t in pyval_template)
parameters = pyval.parameters
assert (pyval.name in ("typing.Generic", "typing.Protocol") or
len(parameters) <= len(template))
# Delay type parameter loading to handle recursive types.
# See the ParameterizedClass.formal_type_parameters() property.
type_parameters = abstract_utils.LazyFormalTypeParameters(
template, parameters, subst)
return abstract_class(base_cls, type_parameters, self.ctx)
elif isinstance(pyval, pytd.Literal):
value = self.constant_to_value(
self._get_literal_value(pyval.value), subst, self.ctx.root_node)
return abstract.LiteralClass(value, self.ctx)
elif isinstance(pyval, pytd.Annotated):
typ = self.constant_to_value(pyval.base_type, subst, self.ctx.root_node)
if pyval.annotations[0] == "'pytype_metadata'":
try:
md = metadata.from_string(pyval.annotations[1])
if md["tag"] == "attr.ib":
ret = attr_overlay.AttribInstance.from_metadata(
self.ctx, self.ctx.root_node, typ, md)
return ret
elif md["tag"] == "attr.s":
ret = attr_overlay.Attrs.from_metadata(self.ctx, md)
return ret
except (IndexError, ValueError, TypeError, KeyError):
details = "Wrong format for pytype_metadata."
self.ctx.errorlog.invalid_annotation(self.ctx.vm.frames,
pyval.annotations[1], details)
return typ
else:
return typ
elif pyval.__class__ is tuple: # only match raw tuple, not namedtuple/Node
return self.tuple_to_value([
self.constant_to_var(item, subst, self.ctx.root_node)
for i, item in enumerate(pyval)
])
else:
raise NotImplementedError("Can't convert constant %s %r" %
(type(pyval), pyval))
def _build_namedtuple(self, name, field_names, field_types, node, bases):
# Build an InterpreterClass representing the namedtuple.
if field_types:
# TODO(mdemello): Fix this to support late types.
field_types_union = abstract.Union(field_types, self.ctx)
else:
field_types_union = self.ctx.convert.none_type
members = {n: t.instantiate(node) for n, t in zip(field_names, field_types)}
# collections.namedtuple has: __dict__, __slots__ and _fields.
# typing.NamedTuple adds: _field_types, __annotations__ and _field_defaults.
# __slots__ and _fields are tuples containing the names of the fields.
slots = tuple(self.ctx.convert.build_string(node, f) for f in field_names)
members["__slots__"] = self.ctx.convert.build_tuple(node, slots)
members["_fields"] = self.ctx.convert.build_tuple(node, slots)
# __dict__ and _field_defaults are both collections.OrderedDicts that map
# field names (strings) to objects of the field types.
ordered_dict_cls = self.ctx.convert.name_to_value(
"collections.OrderedDict", ast=self.collections_ast)
# Normally, we would use abstract_utils.K and abstract_utils.V, but
# collections.pyi doesn't conform to that standard.
field_dict_cls = abstract.ParameterizedClass(ordered_dict_cls, {
"K": self.ctx.convert.str_type,
"V": field_types_union
}, self.ctx)
members["__dict__"] = field_dict_cls.instantiate(node)
members["_field_defaults"] = field_dict_cls.instantiate(node)
# _field_types and __annotations__ are both collections.OrderedDicts
# that map field names (strings) to the types of the fields. Note that
# ctx.make_class will take care of adding the __annotations__ member.
field_types_cls = abstract.ParameterizedClass(ordered_dict_cls, {
"K": self.ctx.convert.str_type,
"V": self.ctx.convert.type_type
}, self.ctx)
members["_field_types"] = field_types_cls.instantiate(node)
# __new__
# We set the bound on this TypeParameter later. This gives __new__ the
# signature: def __new__(cls: Type[_Tname], ...) -> _Tname, i.e. the same
# signature that visitor.CreateTypeParametersForSignatures would create.
# This allows subclasses of the NamedTuple to get the correct type from
# their constructors.
cls_type_param = abstract.TypeParameter(
visitors.CreateTypeParametersForSignatures.PREFIX + name,
self.ctx,
bound=None)
cls_type = abstract.ParameterizedClass(self.ctx.convert.type_type,
{abstract_utils.T: cls_type_param},
self.ctx)
params = [Param(n, t) for n, t in zip(field_names, field_types)]
members["__new__"] = overlay_utils.make_method(
self.ctx,
node,
name="__new__",
self_param=Param("cls", cls_type),
params=params,
return_type=cls_type_param,
)
# __init__
members["__init__"] = overlay_utils.make_method(
self.ctx,
node,
name="__init__",
varargs=Param("args"),
kwargs=Param("kwargs"))
heterogeneous_tuple_type_params = dict(enumerate(field_types))
heterogeneous_tuple_type_params[abstract_utils.T] = field_types_union
# Representation of the to-be-created NamedTuple as a typing.Tuple.
heterogeneous_tuple_type = abstract.TupleClass(
self.ctx.convert.tuple_type, heterogeneous_tuple_type_params, self.ctx)
# _make
# _make is a classmethod, so it needs to be wrapped by
# special_builtins.ClassMethodInstance.
# Like __new__, it uses the _Tname TypeVar.
sized_cls = self.ctx.convert.name_to_value("typing.Sized")
iterable_type = abstract.ParameterizedClass(
self.ctx.convert.name_to_value("typing.Iterable"),
{abstract_utils.T: field_types_union}, self.ctx)
cls_type = abstract.ParameterizedClass(self.ctx.convert.type_type,
{abstract_utils.T: cls_type_param},
self.ctx)
len_type = abstract.CallableClass(
self.ctx.convert.name_to_value("typing.Callable"), {
0: sized_cls,
abstract_utils.ARGS: sized_cls,
abstract_utils.RET: self.ctx.convert.int_type
}, self.ctx)
params = [
Param("iterable", iterable_type),
Param("new").unsolvable(self.ctx, node),
Param("len", len_type).unsolvable(self.ctx, node)
]
make = overlay_utils.make_method(
self.ctx,
node,
name="_make",
params=params,
self_param=Param("cls", cls_type),
return_type=cls_type_param)
make_args = function.Args(posargs=(make,))
_, members["_make"] = self.ctx.special_builtins["classmethod"].call(
node, None, make_args)
# _replace
# Like __new__, it uses the _Tname TypeVar. We have to annotate the `self`
# param to make sure the TypeVar is substituted correctly.
members["_replace"] = overlay_utils.make_method(
self.ctx,
node,
name="_replace",
self_param=Param("self", cls_type_param),
return_type=cls_type_param,
kwargs=Param("kwds", field_types_union))
# __getnewargs__
members["__getnewargs__"] = overlay_utils.make_method(
self.ctx,
node,
name="__getnewargs__",
return_type=heterogeneous_tuple_type)
# __getstate__
members["__getstate__"] = overlay_utils.make_method(
self.ctx, node, name="__getstate__")
# _asdict
members["_asdict"] = overlay_utils.make_method(
self.ctx, node, name="_asdict", return_type=field_dict_cls)
# Finally, make the class.
cls_dict = abstract.Dict(self.ctx)
cls_dict.update(node, members)
if self.ctx.options.strict_namedtuple_checks:
# Enforces type checking like Tuple[...]
superclass_of_new_type = heterogeneous_tuple_type.to_variable(node)
else:
superclass_of_new_type = self.ctx.convert.tuple_type.to_variable(node)
if bases:
final_bases = []
for base in bases:
if any(b.full_name == "typing.NamedTuple" for b in base.data):
final_bases.append(superclass_of_new_type)
else:
final_bases.append(base)
else:
final_bases = [superclass_of_new_type]
# This NamedTuple is being created via a function call. We manually
# construct an annotated_locals entry for it so that __annotations__ is
# initialized properly for the generated class.
self.ctx.vm.annotated_locals[name] = {
field: abstract_utils.Local(node, None, typ, None, self.ctx)
for field, typ in zip(field_names, field_types)
}
node, cls_var = self.ctx.make_class(
node=node,
name_var=self.ctx.convert.build_string(node, name),
bases=final_bases,
class_dict_var=cls_dict.to_variable(node),
cls_var=None)
cls = cls_var.data[0]
# Now that the class has been made, we can complete the TypeParameter used
# by __new__, _make and _replace.
cls_type_param.bound = cls
return node, cls_var
