diff options
Diffstat (limited to 'venv/Lib/site-packages/astroid/brain/brain_functools.py')
| -rw-r--r-- | venv/Lib/site-packages/astroid/brain/brain_functools.py | 158 |
1 files changed, 0 insertions, 158 deletions
diff --git a/venv/Lib/site-packages/astroid/brain/brain_functools.py b/venv/Lib/site-packages/astroid/brain/brain_functools.py deleted file mode 100644 index 8b594ef..0000000 --- a/venv/Lib/site-packages/astroid/brain/brain_functools.py +++ /dev/null @@ -1,158 +0,0 @@ -# Copyright (c) 2016, 2018 Claudiu Popa <pcmanticore@gmail.com> -# Copyright (c) 2018 Bryce Guinta <bryce.paul.guinta@gmail.com> - -"""Astroid hooks for understanding functools library module.""" -from functools import partial -from itertools import chain - -import astroid -from astroid import arguments -from astroid import BoundMethod -from astroid import extract_node -from astroid import helpers -from astroid.interpreter import objectmodel -from astroid import MANAGER -from astroid import objects - - -LRU_CACHE = "functools.lru_cache" - - -class LruWrappedModel(objectmodel.FunctionModel): - """Special attribute model for functions decorated with functools.lru_cache. - - The said decorators patches at decoration time some functions onto - the decorated function. - """ - - @property - def attr___wrapped__(self): - return self._instance - - @property - def attr_cache_info(self): - cache_info = extract_node( - """ - from functools import _CacheInfo - _CacheInfo(0, 0, 0, 0) - """ - ) - - class CacheInfoBoundMethod(BoundMethod): - def infer_call_result(self, caller, context=None): - yield helpers.safe_infer(cache_info) - - return CacheInfoBoundMethod(proxy=self._instance, bound=self._instance) - - @property - def attr_cache_clear(self): - node = extract_node("""def cache_clear(self): pass""") - return BoundMethod(proxy=node, bound=self._instance.parent.scope()) - - -def _transform_lru_cache(node, context=None): - # TODO: this is not ideal, since the node should be immutable, - # but due to https://github.com/PyCQA/astroid/issues/354, - # there's not much we can do now. - # Replacing the node would work partially, because, - # in pylint, the old node would still be available, leading - # to spurious false positives. - node.special_attributes = LruWrappedModel()(node) - return - - -def _functools_partial_inference(node, context=None): - call = arguments.CallSite.from_call(node) - number_of_positional = len(call.positional_arguments) - if number_of_positional < 1: - raise astroid.UseInferenceDefault( - "functools.partial takes at least one argument" - ) - if number_of_positional == 1 and not call.keyword_arguments: - raise astroid.UseInferenceDefault( - "functools.partial needs at least to have some filled arguments" - ) - - partial_function = call.positional_arguments[0] - try: - inferred_wrapped_function = next(partial_function.infer(context=context)) - except astroid.InferenceError as exc: - raise astroid.UseInferenceDefault from exc - if inferred_wrapped_function is astroid.Uninferable: - raise astroid.UseInferenceDefault("Cannot infer the wrapped function") - if not isinstance(inferred_wrapped_function, astroid.FunctionDef): - raise astroid.UseInferenceDefault("The wrapped function is not a function") - - # Determine if the passed keywords into the callsite are supported - # by the wrapped function. - function_parameters = chain( - inferred_wrapped_function.args.args or (), - inferred_wrapped_function.args.posonlyargs or (), - inferred_wrapped_function.args.kwonlyargs or (), - ) - parameter_names = set( - param.name - for param in function_parameters - if isinstance(param, astroid.AssignName) - ) - if set(call.keyword_arguments) - parameter_names: - raise astroid.UseInferenceDefault( - "wrapped function received unknown parameters" - ) - - partial_function = objects.PartialFunction( - call, - name=inferred_wrapped_function.name, - doc=inferred_wrapped_function.doc, - lineno=inferred_wrapped_function.lineno, - col_offset=inferred_wrapped_function.col_offset, - parent=inferred_wrapped_function.parent, - ) - partial_function.postinit( - args=inferred_wrapped_function.args, - body=inferred_wrapped_function.body, - decorators=inferred_wrapped_function.decorators, - returns=inferred_wrapped_function.returns, - type_comment_returns=inferred_wrapped_function.type_comment_returns, - type_comment_args=inferred_wrapped_function.type_comment_args, - ) - return iter((partial_function,)) - - -def _looks_like_lru_cache(node): - """Check if the given function node is decorated with lru_cache.""" - if not node.decorators: - return False - for decorator in node.decorators.nodes: - if not isinstance(decorator, astroid.Call): - continue - if _looks_like_functools_member(decorator, "lru_cache"): - return True - return False - - -def _looks_like_functools_member(node, member): - """Check if the given Call node is a functools.partial call""" - if isinstance(node.func, astroid.Name): - return node.func.name == member - elif isinstance(node.func, astroid.Attribute): - return ( - node.func.attrname == member - and isinstance(node.func.expr, astroid.Name) - and node.func.expr.name == "functools" - ) - - -_looks_like_partial = partial(_looks_like_functools_member, member="partial") - - -MANAGER.register_transform( - astroid.FunctionDef, _transform_lru_cache, _looks_like_lru_cache -) - - -MANAGER.register_transform( - astroid.Call, - astroid.inference_tip(_functools_partial_inference), - _looks_like_partial, -) |