# Licensed under the LGPL: https://www.gnu.org/licenses/old-licenses/lgpl-2.1.en.html # For details: https://github.com/pylint-dev/astroid/blob/main/LICENSE # Copyright (c) https://github.com/pylint-dev/astroid/blob/main/CONTRIBUTORS.txt """This module contains a set of functions to handle python protocols for nodes where it makes sense. """ from __future__ import annotations import collections import itertools import operator as operator_mod from collections.abc import Callable, Generator, Iterator, Sequence from typing import Any, TypeVar from astroid import arguments, bases, decorators, helpers, nodes, objects, util from astroid.const import Context from astroid.context import InferenceContext, copy_context from astroid.exceptions import ( AstroidIndexError, AstroidTypeError, AttributeInferenceError, InferenceError, NoDefault, ) from astroid.nodes import node_classes from astroid.typing import ( ConstFactoryResult, InferenceResult, SuccessfulInferenceResult, ) _TupleListNodeT = TypeVar("_TupleListNodeT", nodes.Tuple, nodes.List) def _reflected_name(name) -> str: return "__r" + name[2:] def _augmented_name(name) -> str: return "__i" + name[2:] _CONTEXTLIB_MGR = "contextlib.contextmanager" BIN_OP_METHOD = { "+": "__add__", "-": "__sub__", "/": "__truediv__", "//": "__floordiv__", "*": "__mul__", "**": "__pow__", "%": "__mod__", "&": "__and__", "|": "__or__", "^": "__xor__", "<<": "__lshift__", ">>": "__rshift__", "@": "__matmul__", } REFLECTED_BIN_OP_METHOD = { key: _reflected_name(value) for (key, value) in BIN_OP_METHOD.items() } AUGMENTED_OP_METHOD = { key + "=": _augmented_name(value) for (key, value) in BIN_OP_METHOD.items() } UNARY_OP_METHOD = { "+": "__pos__", "-": "__neg__", "~": "__invert__", "not": None, # XXX not '__nonzero__' } _UNARY_OPERATORS: dict[str, Callable[[Any], Any]] = { "+": operator_mod.pos, "-": operator_mod.neg, "~": operator_mod.invert, "not": operator_mod.not_, } def _infer_unary_op(obj: Any, op: str) -> ConstFactoryResult: """Perform unary operation on `obj`, unless it is `NotImplemented`. Can raise TypeError if operation is unsupported. """ if obj is NotImplemented: value = obj else: func = _UNARY_OPERATORS[op] value = func(obj) return nodes.const_factory(value) nodes.Tuple.infer_unary_op = lambda self, op: _infer_unary_op(tuple(self.elts), op) nodes.List.infer_unary_op = lambda self, op: _infer_unary_op(self.elts, op) nodes.Set.infer_unary_op = lambda self, op: _infer_unary_op(set(self.elts), op) nodes.Const.infer_unary_op = lambda self, op: _infer_unary_op(self.value, op) nodes.Dict.infer_unary_op = lambda self, op: _infer_unary_op(dict(self.items), op) # Binary operations BIN_OP_IMPL = { "+": lambda a, b: a + b, "-": lambda a, b: a - b, "/": lambda a, b: a / b, "//": lambda a, b: a // b, "*": lambda a, b: a * b, "**": lambda a, b: a**b, "%": lambda a, b: a % b, "&": lambda a, b: a & b, "|": lambda a, b: a | b, "^": lambda a, b: a ^ b, "<<": lambda a, b: a << b, ">>": lambda a, b: a >> b, "@": operator_mod.matmul, } for _KEY, _IMPL in list(BIN_OP_IMPL.items()): BIN_OP_IMPL[_KEY + "="] = _IMPL @decorators.yes_if_nothing_inferred def const_infer_binary_op( self: nodes.Const, opnode: nodes.AugAssign | nodes.BinOp, operator: str, other: InferenceResult, context: InferenceContext, _: SuccessfulInferenceResult, ) -> Generator[ConstFactoryResult | util.UninferableBase, None, None]: not_implemented = nodes.Const(NotImplemented) if isinstance(other, nodes.Const): if ( operator == "**" and isinstance(self.value, (int, float)) and isinstance(other.value, (int, float)) and (self.value > 1e5 or other.value > 1e5) ): yield not_implemented return try: impl = BIN_OP_IMPL[operator] try: yield nodes.const_factory(impl(self.value, other.value)) except TypeError: # ArithmeticError is not enough: float >> float is a TypeError yield not_implemented except Exception: # pylint: disable=broad-except yield util.Uninferable except TypeError: yield not_implemented elif isinstance(self.value, str) and operator == "%": # TODO(cpopa): implement string interpolation later on. yield util.Uninferable else: yield not_implemented nodes.Const.infer_binary_op = const_infer_binary_op def _multiply_seq_by_int( self: _TupleListNodeT, opnode: nodes.AugAssign | nodes.BinOp, other: nodes.Const, context: InferenceContext, ) -> _TupleListNodeT: node = self.__class__(parent=opnode) filtered_elts = ( helpers.safe_infer(elt, context) or util.Uninferable for elt in self.elts if not isinstance(elt, util.UninferableBase) ) node.elts = list(filtered_elts) * other.value return node def _filter_uninferable_nodes( elts: Sequence[InferenceResult], context: InferenceContext ) -> Iterator[SuccessfulInferenceResult]: for elt in elts: if isinstance(elt, util.UninferableBase): yield nodes.Unknown() else: for inferred in elt.infer(context): if not isinstance(inferred, util.UninferableBase): yield inferred else: yield nodes.Unknown() @decorators.yes_if_nothing_inferred def tl_infer_binary_op( self: _TupleListNodeT, opnode: nodes.AugAssign | nodes.BinOp, operator: str, other: InferenceResult, context: InferenceContext, method: SuccessfulInferenceResult, ) -> Generator[_TupleListNodeT | nodes.Const | util.UninferableBase, None, None]: """Infer a binary operation on a tuple or list. The instance on which the binary operation is performed is a tuple or list. This refers to the left-hand side of the operation, so: 'tuple() + 1' or '[] + A()' """ # For tuples and list the boundnode is no longer the tuple or list instance context.boundnode = None not_implemented = nodes.Const(NotImplemented) if isinstance(other, self.__class__) and operator == "+": node = self.__class__(parent=opnode) node.elts = list( itertools.chain( _filter_uninferable_nodes(self.elts, context), _filter_uninferable_nodes(other.elts, context), ) ) yield node elif isinstance(other, nodes.Const) and operator == "*": if not isinstance(other.value, int): yield not_implemented return yield _multiply_seq_by_int(self, opnode, other, context) elif isinstance(other, bases.Instance) and operator == "*": # Verify if the instance supports __index__. as_index = helpers.class_instance_as_index(other) if not as_index: yield util.Uninferable else: yield _multiply_seq_by_int(self, opnode, as_index, context) else: yield not_implemented nodes.Tuple.infer_binary_op = tl_infer_binary_op nodes.List.infer_binary_op = tl_infer_binary_op @decorators.yes_if_nothing_inferred def instance_class_infer_binary_op( self: bases.Instance | nodes.ClassDef, opnode: nodes.AugAssign | nodes.BinOp, operator: str, other: InferenceResult, context: InferenceContext, method: SuccessfulInferenceResult, ) -> Generator[InferenceResult, None, None]: return method.infer_call_result(self, context) bases.Instance.infer_binary_op = instance_class_infer_binary_op nodes.ClassDef.infer_binary_op = instance_class_infer_binary_op # assignment ################################################################## """The assigned_stmts method is responsible to return the assigned statement (e.g. not inferred) according to the assignment type. The `assign_path` argument is used to record the lhs path of the original node. For instance if we want assigned statements for 'c' in 'a, (b,c)', assign_path will be [1, 1] once arrived to the Assign node. The `context` argument is the current inference context which should be given to any intermediary inference necessary. """ def _resolve_looppart(parts, assign_path, context): """Recursive function to resolve multiple assignments on loops.""" assign_path = assign_path[:] index = assign_path.pop(0) for part in parts: if isinstance(part, util.UninferableBase): continue if not hasattr(part, "itered"): continue try: itered = part.itered() except TypeError: continue try: if isinstance(itered[index], (nodes.Const, nodes.Name)): itered = [part] except IndexError: pass for stmt in itered: index_node = nodes.Const(index) try: assigned = stmt.getitem(index_node, context) except (AttributeError, AstroidTypeError, AstroidIndexError): continue if not assign_path: # we achieved to resolved the assignment path, # don't infer the last part yield assigned elif isinstance(assigned, util.UninferableBase): break else: # we are not yet on the last part of the path # search on each possibly inferred value try: yield from _resolve_looppart( assigned.infer(context), assign_path, context ) except InferenceError: break @decorators.raise_if_nothing_inferred def for_assigned_stmts( self: nodes.For | nodes.Comprehension, node: node_classes.AssignedStmtsPossibleNode = None, context: InferenceContext | None = None, assign_path: list[int] | None = None, ) -> Any: if isinstance(self, nodes.AsyncFor) or getattr(self, "is_async", False): # Skip inferring of async code for now return { "node": self, "unknown": node, "assign_path": assign_path, "context": context, } if assign_path is None: for lst in self.iter.infer(context): if isinstance(lst, (nodes.Tuple, nodes.List)): yield from lst.elts else: yield from _resolve_looppart(self.iter.infer(context), assign_path, context) return { "node": self, "unknown": node, "assign_path": assign_path, "context": context, } nodes.For.assigned_stmts = for_assigned_stmts nodes.Comprehension.assigned_stmts = for_assigned_stmts def sequence_assigned_stmts( self: nodes.Tuple | nodes.List, node: node_classes.AssignedStmtsPossibleNode = None, context: InferenceContext | None = None, assign_path: list[int] | None = None, ) -> Any: if assign_path is None: assign_path = [] try: index = self.elts.index(node) # type: ignore[arg-type] except ValueError as exc: raise InferenceError( "Tried to retrieve a node {node!r} which does not exist", node=self, assign_path=assign_path, context=context, ) from exc assign_path.insert(0, index) return self.parent.assigned_stmts( node=self, context=context, assign_path=assign_path ) nodes.Tuple.assigned_stmts = sequence_assigned_stmts nodes.List.assigned_stmts = sequence_assigned_stmts def assend_assigned_stmts( self: nodes.AssignName | nodes.AssignAttr, node: node_classes.AssignedStmtsPossibleNode = None, context: InferenceContext | None = None, assign_path: list[int] | None = None, ) -> Any: return self.parent.assigned_stmts(node=self, context=context) nodes.AssignName.assigned_stmts = assend_assigned_stmts nodes.AssignAttr.assigned_stmts = assend_assigned_stmts def _arguments_infer_argname( self, name: str | None, context: InferenceContext ) -> Generator[InferenceResult, None, None]: # arguments information may be missing, in which case we can't do anything # more if not (self.arguments or self.vararg or self.kwarg): yield util.Uninferable return functype = self.parent.type # first argument of instance/class method if ( self.arguments and getattr(self.arguments[0], "name", None) == name and functype != "staticmethod" ): cls = self.parent.parent.scope() is_metaclass = isinstance(cls, nodes.ClassDef) and cls.type == "metaclass" # If this is a metaclass, then the first argument will always # be the class, not an instance. if context.boundnode and isinstance(context.boundnode, bases.Instance): cls = context.boundnode._proxied if is_metaclass or functype == "classmethod": yield cls return if functype == "method": yield cls.instantiate_class() return if context and context.callcontext: callee = context.callcontext.callee while hasattr(callee, "_proxied"): callee = callee._proxied if getattr(callee, "name", None) == self.parent.name: call_site = arguments.CallSite(context.callcontext, context.extra_context) yield from call_site.infer_argument(self.parent, name, context) return if name == self.vararg: vararg = nodes.const_factory(()) vararg.parent = self if not self.arguments and self.parent.name == "__init__": cls = self.parent.parent.scope() vararg.elts = [cls.instantiate_class()] yield vararg return if name == self.kwarg: kwarg = nodes.const_factory({}) kwarg.parent = self yield kwarg return # if there is a default value, yield it. And then yield Uninferable to reflect # we can't guess given argument value try: context = copy_context(context) yield from self.default_value(name).infer(context) yield util.Uninferable except NoDefault: yield util.Uninferable def arguments_assigned_stmts( self: nodes.Arguments, node: node_classes.AssignedStmtsPossibleNode = None, context: InferenceContext | None = None, assign_path: list[int] | None = None, ) -> Any: try: node_name = node.name # type: ignore[union-attr] except AttributeError: # Added to handle edge cases where node.name is not defined. # https://github.com/pylint-dev/astroid/pull/1644#discussion_r901545816 node_name = None # pragma: no cover if context and context.callcontext: callee = context.callcontext.callee while hasattr(callee, "_proxied"): callee = callee._proxied else: return _arguments_infer_argname(self, node_name, context) if node and getattr(callee, "name", None) == node.frame(future=True).name: # reset call context/name callcontext = context.callcontext context = copy_context(context) context.callcontext = None args = arguments.CallSite(callcontext, context=context) return args.infer_argument(self.parent, node_name, context) return _arguments_infer_argname(self, node_name, context) nodes.Arguments.assigned_stmts = arguments_assigned_stmts @decorators.raise_if_nothing_inferred def assign_assigned_stmts( self: nodes.AugAssign | nodes.Assign | nodes.AnnAssign, node: node_classes.AssignedStmtsPossibleNode = None, context: InferenceContext | None = None, assign_path: list[int] | None = None, ) -> Any: if not assign_path: yield self.value return None yield from _resolve_assignment_parts( self.value.infer(context), assign_path, context ) return { "node": self, "unknown": node, "assign_path": assign_path, "context": context, } def assign_annassigned_stmts( self: nodes.AnnAssign, node: node_classes.AssignedStmtsPossibleNode = None, context: InferenceContext | None = None, assign_path: list[int] | None = None, ) -> Any: for inferred in assign_assigned_stmts(self, node, context, assign_path): if inferred is None: yield util.Uninferable else: yield inferred nodes.Assign.assigned_stmts = assign_assigned_stmts nodes.AnnAssign.assigned_stmts = assign_annassigned_stmts nodes.AugAssign.assigned_stmts = assign_assigned_stmts def _resolve_assignment_parts(parts, assign_path, context): """Recursive function to resolve multiple assignments.""" assign_path = assign_path[:] index = assign_path.pop(0) for part in parts: assigned = None if isinstance(part, nodes.Dict): # A dictionary in an iterating context try: assigned, _ = part.items[index] except IndexError: return elif hasattr(part, "getitem"): index_node = nodes.Const(index) try: assigned = part.getitem(index_node, context) except (AstroidTypeError, AstroidIndexError): return if not assigned: return if not assign_path: # we achieved to resolved the assignment path, don't infer the # last part yield assigned elif isinstance(assigned, util.UninferableBase): return else: # we are not yet on the last part of the path search on each # possibly inferred value try: yield from _resolve_assignment_parts( assigned.infer(context), assign_path, context ) except InferenceError: return @decorators.raise_if_nothing_inferred def excepthandler_assigned_stmts( self: nodes.ExceptHandler, node: node_classes.AssignedStmtsPossibleNode = None, context: InferenceContext | None = None, assign_path: list[int] | None = None, ) -> Any: for assigned in node_classes.unpack_infer(self.type): if isinstance(assigned, nodes.ClassDef): assigned = objects.ExceptionInstance(assigned) yield assigned return { "node": self, "unknown": node, "assign_path": assign_path, "context": context, } nodes.ExceptHandler.assigned_stmts = excepthandler_assigned_stmts def _infer_context_manager(self, mgr, context): try: inferred = next(mgr.infer(context=context)) except StopIteration as e: raise InferenceError(node=mgr) from e if isinstance(inferred, bases.Generator): # Check if it is decorated with contextlib.contextmanager. func = inferred.parent if not func.decorators: raise InferenceError( "No decorators found on inferred generator %s", node=func ) for decorator_node in func.decorators.nodes: decorator = next(decorator_node.infer(context=context), None) if isinstance(decorator, nodes.FunctionDef): if decorator.qname() == _CONTEXTLIB_MGR: break else: # It doesn't interest us. raise InferenceError(node=func) try: yield next(inferred.infer_yield_types()) except StopIteration as e: raise InferenceError(node=func) from e elif isinstance(inferred, bases.Instance): try: enter = next(inferred.igetattr("__enter__", context=context)) except (InferenceError, AttributeInferenceError, StopIteration) as exc: raise InferenceError(node=inferred) from exc if not isinstance(enter, bases.BoundMethod): raise InferenceError(node=enter) yield from enter.infer_call_result(self, context) else: raise InferenceError(node=mgr) @decorators.raise_if_nothing_inferred def with_assigned_stmts( self: nodes.With, node: node_classes.AssignedStmtsPossibleNode = None, context: InferenceContext | None = None, assign_path: list[int] | None = None, ) -> Any: """Infer names and other nodes from a *with* statement. This enables only inference for name binding in a *with* statement. For instance, in the following code, inferring `func` will return the `ContextManager` class, not whatever ``__enter__`` returns. We are doing this intentionally, because we consider that the context manager result is whatever __enter__ returns and what it is binded using the ``as`` keyword. class ContextManager(object): def __enter__(self): return 42 with ContextManager() as f: pass # ContextManager().infer() will return ContextManager # f.infer() will return 42. Arguments: self: nodes.With node: The target of the assignment, `as (a, b)` in `with foo as (a, b)`. context: Inference context used for caching already inferred objects assign_path: A list of indices, where each index specifies what item to fetch from the inference results. """ try: mgr = next(mgr for (mgr, vars) in self.items if vars == node) except StopIteration: return None if assign_path is None: yield from _infer_context_manager(self, mgr, context) else: for result in _infer_context_manager(self, mgr, context): # Walk the assign_path and get the item at the final index. obj = result for index in assign_path: if not hasattr(obj, "elts"): raise InferenceError( "Wrong type ({targets!r}) for {node!r} assignment", node=self, targets=node, assign_path=assign_path, context=context, ) try: obj = obj.elts[index] except IndexError as exc: raise InferenceError( "Tried to infer a nonexistent target with index {index} " "in {node!r}.", node=self, targets=node, assign_path=assign_path, context=context, ) from exc except TypeError as exc: raise InferenceError( "Tried to unpack a non-iterable value in {node!r}.", node=self, targets=node, assign_path=assign_path, context=context, ) from exc yield obj return { "node": self, "unknown": node, "assign_path": assign_path, "context": context, } nodes.With.assigned_stmts = with_assigned_stmts @decorators.raise_if_nothing_inferred def named_expr_assigned_stmts( self: nodes.NamedExpr, node: node_classes.AssignedStmtsPossibleNode, context: InferenceContext | None = None, assign_path: list[int] | None = None, ) -> Any: """Infer names and other nodes from an assignment expression.""" if self.target == node: yield from self.value.infer(context=context) else: raise InferenceError( "Cannot infer NamedExpr node {node!r}", node=self, assign_path=assign_path, context=context, ) nodes.NamedExpr.assigned_stmts = named_expr_assigned_stmts @decorators.yes_if_nothing_inferred def starred_assigned_stmts( # noqa: C901 self: nodes.Starred, node: node_classes.AssignedStmtsPossibleNode = None, context: InferenceContext | None = None, assign_path: list[int] | None = None, ) -> Any: """ Arguments: self: nodes.Starred node: a node related to the current underlying Node. context: Inference context used for caching already inferred objects assign_path: A list of indices, where each index specifies what item to fetch from the inference results. """ # pylint: disable=too-many-locals,too-many-statements def _determine_starred_iteration_lookups( starred: nodes.Starred, target: nodes.Tuple, lookups: list[tuple[int, int]] ) -> None: # Determine the lookups for the rhs of the iteration itered = target.itered() for index, element in enumerate(itered): if ( isinstance(element, nodes.Starred) and element.value.name == starred.value.name ): lookups.append((index, len(itered))) break if isinstance(element, nodes.Tuple): lookups.append((index, len(element.itered()))) _determine_starred_iteration_lookups(starred, element, lookups) stmt = self.statement(future=True) if not isinstance(stmt, (nodes.Assign, nodes.For)): raise InferenceError( "Statement {stmt!r} enclosing {node!r} must be an Assign or For node.", node=self, stmt=stmt, unknown=node, context=context, ) if context is None: context = InferenceContext() if isinstance(stmt, nodes.Assign): value = stmt.value lhs = stmt.targets[0] if not isinstance(lhs, nodes.BaseContainer): yield util.Uninferable return if sum(1 for _ in lhs.nodes_of_class(nodes.Starred)) > 1: raise InferenceError( "Too many starred arguments in the assignment targets {lhs!r}.", node=self, targets=lhs, unknown=node, context=context, ) try: rhs = next(value.infer(context)) except (InferenceError, StopIteration): yield util.Uninferable return if isinstance(rhs, util.UninferableBase) or not hasattr(rhs, "itered"): yield util.Uninferable return try: elts = collections.deque(rhs.itered()) # type: ignore[union-attr] except TypeError: yield util.Uninferable return # Unpack iteratively the values from the rhs of the assignment, # until the find the starred node. What will remain will # be the list of values which the Starred node will represent # This is done in two steps, from left to right to remove # anything before the starred node and from right to left # to remove anything after the starred node. for index, left_node in enumerate(lhs.elts): if not isinstance(left_node, nodes.Starred): if not elts: break elts.popleft() continue lhs_elts = collections.deque(reversed(lhs.elts[index:])) for right_node in lhs_elts: if not isinstance(right_node, nodes.Starred): if not elts: break elts.pop() continue # We're done unpacking. packed = nodes.List( ctx=Context.Store, parent=self, lineno=lhs.lineno, col_offset=lhs.col_offset, ) packed.postinit(elts=list(elts)) yield packed break if isinstance(stmt, nodes.For): try: inferred_iterable = next(stmt.iter.infer(context=context)) except (InferenceError, StopIteration): yield util.Uninferable return if isinstance(inferred_iterable, util.UninferableBase) or not hasattr( inferred_iterable, "itered" ): yield util.Uninferable return try: itered = inferred_iterable.itered() # type: ignore[union-attr] except TypeError: yield util.Uninferable return target = stmt.target if not isinstance(target, nodes.Tuple): raise InferenceError( "Could not make sense of this, the target must be a tuple", context=context, ) lookups: list[tuple[int, int]] = [] _determine_starred_iteration_lookups(self, target, lookups) if not lookups: raise InferenceError( "Could not make sense of this, needs at least a lookup", context=context ) # Make the last lookup a slice, since that what we want for a Starred node last_element_index, last_element_length = lookups[-1] is_starred_last = last_element_index == (last_element_length - 1) lookup_slice = slice( last_element_index, None if is_starred_last else (last_element_length - last_element_index), ) last_lookup = lookup_slice for element in itered: # We probably want to infer the potential values *for each* element in an # iterable, but we can't infer a list of all values, when only a list of # step values are expected: # # for a, *b in [...]: # b # # *b* should now point to just the elements at that particular iteration step, # which astroid can't know about. found_element = None for index, lookup in enumerate(lookups): if not hasattr(element, "itered"): break if index + 1 is len(lookups): cur_lookup: slice | int = last_lookup else: # Grab just the index, not the whole length cur_lookup = lookup[0] try: itered_inner_element = element.itered() element = itered_inner_element[cur_lookup] except IndexError: break except TypeError: # Most likely the itered() call failed, cannot make sense of this yield util.Uninferable return else: found_element = element unpacked = nodes.List( ctx=Context.Store, parent=self, lineno=self.lineno, col_offset=self.col_offset, ) unpacked.postinit(elts=found_element or []) yield unpacked return yield util.Uninferable nodes.Starred.assigned_stmts = starred_assigned_stmts @decorators.yes_if_nothing_inferred def match_mapping_assigned_stmts( self: nodes.MatchMapping, node: nodes.AssignName, context: InferenceContext | None = None, assign_path: None = None, ) -> Generator[nodes.NodeNG, None, None]: """Return empty generator (return -> raises StopIteration) so inferred value is Uninferable. """ return yield nodes.MatchMapping.assigned_stmts = match_mapping_assigned_stmts @decorators.yes_if_nothing_inferred def match_star_assigned_stmts( self: nodes.MatchStar, node: nodes.AssignName, context: InferenceContext | None = None, assign_path: None = None, ) -> Generator[nodes.NodeNG, None, None]: """Return empty generator (return -> raises StopIteration) so inferred value is Uninferable. """ return yield nodes.MatchStar.assigned_stmts = match_star_assigned_stmts @decorators.yes_if_nothing_inferred def match_as_assigned_stmts( self: nodes.MatchAs, node: nodes.AssignName, context: InferenceContext | None = None, assign_path: None = None, ) -> Generator[nodes.NodeNG, None, None]: """Infer MatchAs as the Match subject if it's the only MatchCase pattern else raise StopIteration to yield Uninferable. """ if ( isinstance(self.parent, nodes.MatchCase) and isinstance(self.parent.parent, nodes.Match) and self.pattern is None ): yield self.parent.parent.subject nodes.MatchAs.assigned_stmts = match_as_assigned_stmts