# 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 from __future__ import annotations from collections import defaultdict from collections.abc import Callable from typing import TYPE_CHECKING, List, Optional, Tuple, TypeVar, Union, cast, overload from astroid.context import _invalidate_cache from astroid.typing import SuccessfulInferenceResult, TransformFn if TYPE_CHECKING: from astroid import nodes _SuccessfulInferenceResultT = TypeVar( "_SuccessfulInferenceResultT", bound=SuccessfulInferenceResult ) _Predicate = Optional[Callable[[_SuccessfulInferenceResultT], bool]] _Vistables = Union[ "nodes.NodeNG", List["nodes.NodeNG"], Tuple["nodes.NodeNG", ...], str, None ] _VisitReturns = Union[ SuccessfulInferenceResult, List[SuccessfulInferenceResult], Tuple[SuccessfulInferenceResult, ...], str, None, ] class TransformVisitor: """A visitor for handling transforms. The standard approach of using it is to call :meth:`~visit` with an *astroid* module and the class will take care of the rest, walking the tree and running the transforms for each encountered node. Based on its usage in AstroidManager.brain, it should not be reinstantiated. """ def __init__(self) -> None: # The typing here is incorrect, but it's the best we can do # Refer to register_transform and unregister_transform for the correct types self.transforms: defaultdict[ type[SuccessfulInferenceResult], list[ tuple[ TransformFn[SuccessfulInferenceResult], _Predicate[SuccessfulInferenceResult], ] ], ] = defaultdict(list) def _transform(self, node: SuccessfulInferenceResult) -> SuccessfulInferenceResult: """Call matching transforms for the given node if any and return the transformed node. """ cls = node.__class__ for transform_func, predicate in self.transforms[cls]: if predicate is None or predicate(node): ret = transform_func(node) # if the transformation function returns something, it's # expected to be a replacement for the node if ret is not None: _invalidate_cache() node = ret if ret.__class__ != cls: # Can no longer apply the rest of the transforms. break return node def _visit(self, node: nodes.NodeNG) -> SuccessfulInferenceResult: for name in node._astroid_fields: value = getattr(node, name) value = cast(_Vistables, value) visited = self._visit_generic(value) if visited != value: setattr(node, name, visited) return self._transform(node) @overload def _visit_generic(self, node: None) -> None: ... @overload def _visit_generic(self, node: str) -> str: ... @overload def _visit_generic( self, node: list[nodes.NodeNG] ) -> list[SuccessfulInferenceResult]: ... @overload def _visit_generic( self, node: tuple[nodes.NodeNG, ...] ) -> tuple[SuccessfulInferenceResult, ...]: ... @overload def _visit_generic(self, node: nodes.NodeNG) -> SuccessfulInferenceResult: ... def _visit_generic(self, node: _Vistables) -> _VisitReturns: if isinstance(node, list): return [self._visit_generic(child) for child in node] if isinstance(node, tuple): return tuple(self._visit_generic(child) for child in node) if not node or isinstance(node, str): return node return self._visit(node) def register_transform( self, node_class: type[_SuccessfulInferenceResultT], transform: TransformFn[_SuccessfulInferenceResultT], predicate: _Predicate[_SuccessfulInferenceResultT] | None = None, ) -> None: """Register `transform(node)` function to be applied on the given node. The transform will only be applied if `predicate` is None or returns true when called with the node as argument. The transform function may return a value which is then used to substitute the original node in the tree. """ self.transforms[node_class].append((transform, predicate)) # type: ignore[index, arg-type] def unregister_transform( self, node_class: type[_SuccessfulInferenceResultT], transform: TransformFn[_SuccessfulInferenceResultT], predicate: _Predicate[_SuccessfulInferenceResultT] | None = None, ) -> None: """Unregister the given transform.""" self.transforms[node_class].remove((transform, predicate)) # type: ignore[index, arg-type] def visit(self, node: nodes.NodeNG) -> SuccessfulInferenceResult: """Walk the given astroid *tree* and transform each encountered node. Only the nodes which have transforms registered will actually be replaced or changed. """ return self._visit(node)