# 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 """Various context related utilities, including inference and call contexts.""" from __future__ import annotations import contextlib import pprint from collections.abc import Iterator from typing import TYPE_CHECKING, Dict, Optional, Sequence, Tuple from astroid.typing import InferenceResult, SuccessfulInferenceResult if TYPE_CHECKING: from astroid import constraint, nodes from astroid.nodes.node_classes import Keyword, NodeNG _InferenceCache = Dict[ Tuple["NodeNG", Optional[str], Optional[str], Optional[str]], Sequence["NodeNG"] ] _INFERENCE_CACHE: _InferenceCache = {} def _invalidate_cache() -> None: _INFERENCE_CACHE.clear() class InferenceContext: """Provide context for inference. Store already inferred nodes to save time Account for already visited nodes to stop infinite recursion """ __slots__ = ( "path", "lookupname", "callcontext", "boundnode", "extra_context", "constraints", "_nodes_inferred", ) max_inferred = 100 def __init__( self, path: set[tuple[nodes.NodeNG, str | None]] | None = None, nodes_inferred: list[int] | None = None, ) -> None: if nodes_inferred is None: self._nodes_inferred = [0] else: self._nodes_inferred = nodes_inferred self.path = path or set() """Path of visited nodes and their lookupname. Currently this key is ``(node, context.lookupname)`` """ self.lookupname: str | None = None """The original name of the node. e.g. foo = 1 The inference of 'foo' is nodes.Const(1) but the lookup name is 'foo' """ self.callcontext: CallContext | None = None """The call arguments and keywords for the given context.""" self.boundnode: SuccessfulInferenceResult | None = None """The bound node of the given context. e.g. the bound node of object.__new__(cls) is the object node """ self.extra_context: dict[SuccessfulInferenceResult, InferenceContext] = {} """Context that needs to be passed down through call stacks for call arguments.""" self.constraints: dict[str, dict[nodes.If, set[constraint.Constraint]]] = {} """The constraints on nodes.""" @property def nodes_inferred(self) -> int: """ Number of nodes inferred in this context and all its clones/descendents. Wrap inner value in a mutable cell to allow for mutating a class variable in the presence of __slots__ """ return self._nodes_inferred[0] @nodes_inferred.setter def nodes_inferred(self, value: int) -> None: self._nodes_inferred[0] = value @property def inferred(self) -> _InferenceCache: """ Inferred node contexts to their mapped results. Currently the key is ``(node, lookupname, callcontext, boundnode)`` and the value is tuple of the inferred results """ return _INFERENCE_CACHE def push(self, node: nodes.NodeNG) -> bool: """Push node into inference path. Allows one to see if the given node has already been looked at for this inference context """ name = self.lookupname if (node, name) in self.path: return True self.path.add((node, name)) return False def clone(self) -> InferenceContext: """Clone inference path. For example, each side of a binary operation (BinOp) starts with the same context but diverge as each side is inferred so the InferenceContext will need be cloned """ # XXX copy lookupname/callcontext ? clone = InferenceContext(self.path.copy(), nodes_inferred=self._nodes_inferred) clone.callcontext = self.callcontext clone.boundnode = self.boundnode clone.extra_context = self.extra_context clone.constraints = self.constraints.copy() return clone @contextlib.contextmanager def restore_path(self) -> Iterator[None]: path = set(self.path) yield self.path = path def is_empty(self) -> bool: return ( not self.path and not self.nodes_inferred and not self.callcontext and not self.boundnode and not self.lookupname and not self.callcontext and not self.extra_context and not self.constraints ) def __str__(self) -> str: state = ( f"{field}={pprint.pformat(getattr(self, field), width=80 - len(field))}" for field in self.__slots__ ) return "{}({})".format(type(self).__name__, ",\n ".join(state)) class CallContext: """Holds information for a call site.""" __slots__ = ("args", "keywords", "callee") def __init__( self, args: list[NodeNG], keywords: list[Keyword] | None = None, callee: InferenceResult | None = None, ): self.args = args # Call positional arguments if keywords: arg_value_pairs = [(arg.arg, arg.value) for arg in keywords] else: arg_value_pairs = [] self.keywords = arg_value_pairs # Call keyword arguments self.callee = callee # Function being called def copy_context(context: InferenceContext | None) -> InferenceContext: """Clone a context if given, or return a fresh context.""" if context is not None: return context.clone() return InferenceContext() def bind_context_to_node( context: InferenceContext | None, node: SuccessfulInferenceResult ) -> InferenceContext: """Give a context a boundnode to retrieve the correct function name or attribute value with from further inference. Do not use an existing context since the boundnode could then be incorrectly propagated higher up in the call stack. """ context = copy_context(context) context.boundnode = node return context