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# Licensed under the LGPL: https://www.gnu.org/licenses/old-licenses/lgpl-2.1.en.html
# For details: https://github.com/PyCQA/astroid/blob/main/LICENSE
# Copyright (c) https://github.com/PyCQA/astroid/blob/main/CONTRIBUTORS.txt
"""Various context related utilities, including inference and call contexts."""
from __future__ import annotations
import contextlib
import pprint
from typing import TYPE_CHECKING, Dict, Optional, Sequence, Tuple
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=None,
nodes_inferred: list[int] | None = None,
):
if nodes_inferred is None:
self._nodes_inferred = [0]
else:
self._nodes_inferred = nodes_inferred
self.path = path or set()
"""
:type: set(tuple(NodeNG, optional(str)))
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 = None
"""
:type: optional[NodeNG]
The bound node of the given context
e.g. the bound node of object.__new__(cls) is the object node
"""
self.extra_context = {}
"""
:type: dict(NodeNG, Context)
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) -> bool:
"""Push node into inference path.
:return: Whether node is already in context 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):
path = set(self.path)
yield
self.path = path
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: NodeNG | 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) -> 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.
:param node: Node to do name lookups from
:type node NodeNG:
:returns: A new context
:rtype: InferenceContext
"""
context = copy_context(context)
context.boundnode = node
return context
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