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Direktori : /opt/cloudlinux/venv/lib/python3.11/site-packages/astroid/ |
Current File : //opt/cloudlinux/venv/lib/python3.11/site-packages/astroid/inference_tip.py |
# 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 """Transform utilities (filters and decorator).""" from __future__ import annotations import typing from collections.abc import Iterator import wrapt from astroid.exceptions import InferenceOverwriteError, UseInferenceDefault from astroid.nodes import NodeNG from astroid.typing import InferenceResult, InferFn _cache: dict[tuple[InferFn, NodeNG], list[InferenceResult] | None] = {} def clear_inference_tip_cache() -> None: """Clear the inference tips cache.""" _cache.clear() @wrapt.decorator def _inference_tip_cached( func: InferFn, instance: None, args: typing.Any, kwargs: typing.Any ) -> Iterator[InferenceResult]: """Cache decorator used for inference tips.""" node = args[0] try: result = _cache[func, node] # If through recursion we end up trying to infer the same # func + node we raise here. if result is None: raise UseInferenceDefault() except KeyError: _cache[func, node] = None result = _cache[func, node] = list(func(*args, **kwargs)) assert result return iter(result) def inference_tip(infer_function: InferFn, raise_on_overwrite: bool = False) -> InferFn: """Given an instance specific inference function, return a function to be given to AstroidManager().register_transform to set this inference function. :param bool raise_on_overwrite: Raise an `InferenceOverwriteError` if the inference tip will overwrite another. Used for debugging Typical usage .. sourcecode:: python AstroidManager().register_transform(Call, inference_tip(infer_named_tuple), predicate) .. Note:: Using an inference tip will override any previously set inference tip for the given node. Use a predicate in the transform to prevent excess overwrites. """ def transform(node: NodeNG, infer_function: InferFn = infer_function) -> NodeNG: if ( raise_on_overwrite and node._explicit_inference is not None and node._explicit_inference is not infer_function ): raise InferenceOverwriteError( "Inference already set to {existing_inference}. " "Trying to overwrite with {new_inference} for {node}".format( existing_inference=infer_function, new_inference=node._explicit_inference, node=node, ) ) # pylint: disable=no-value-for-parameter node._explicit_inference = _inference_tip_cached(infer_function) return node return transform