name : brain_namedtuple_enum.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 """Astroid hooks for the Python standard library.""" from __future__ import annotations import functools import keyword import sys from collections.abc import Iterator from textwrap import dedent import astroid from astroid import arguments, bases, inference_tip, nodes, util from astroid.builder import AstroidBuilder, _extract_single_node, extract_node from astroid.context import InferenceContext from astroid.exceptions import ( AstroidTypeError, AstroidValueError, InferenceError, MroError, UseInferenceDefault, ) from astroid.manager import AstroidManager if sys.version_info >= (3, 8): from typing import Final else: from typing_extensions import Final ENUM_BASE_NAMES = { "Enum", "IntEnum", "enum.Enum", "enum.IntEnum", "IntFlag", "enum.IntFlag", } ENUM_QNAME: Final[str] = "enum.Enum" TYPING_NAMEDTUPLE_QUALIFIED: Final = { "typing.NamedTuple", "typing_extensions.NamedTuple", } TYPING_NAMEDTUPLE_BASENAMES: Final = { "NamedTuple", "typing.NamedTuple", "typing_extensions.NamedTuple", } def _infer_first(node, context): if isinstance(node, util.UninferableBase): raise UseInferenceDefault try: value = next(node.infer(context=context)) except StopIteration as exc: raise InferenceError from exc if isinstance(value, util.UninferableBase): raise UseInferenceDefault() return value def _find_func_form_arguments(node, context): def _extract_namedtuple_arg_or_keyword( # pylint: disable=inconsistent-return-statements position, key_name=None ): if len(args) > position: return _infer_first(args[position], context) if key_name and key_name in found_keywords: return _infer_first(found_keywords[key_name], context) args = node.args keywords = node.keywords found_keywords = ( {keyword.arg: keyword.value for keyword in keywords} if keywords else {} ) name = _extract_namedtuple_arg_or_keyword(position=0, key_name="typename") names = _extract_namedtuple_arg_or_keyword(position=1, key_name="field_names") if name and names: return name.value, names raise UseInferenceDefault() def infer_func_form( node: nodes.Call, base_type: list[nodes.NodeNG], context: InferenceContext | None = None, enum: bool = False, ) -> tuple[nodes.ClassDef, str, list[str]]: """Specific inference function for namedtuple or Python 3 enum.""" # node is a Call node, class name as first argument and generated class # attributes as second argument # namedtuple or enums list of attributes can be a list of strings or a # whitespace-separate string try: name, names = _find_func_form_arguments(node, context) try: attributes: list[str] = names.value.replace(",", " ").split() except AttributeError as exc: # Handle attributes of NamedTuples if not enum: attributes = [] fields = _get_namedtuple_fields(node) if fields: fields_node = extract_node(fields) attributes = [ _infer_first(const, context).value for const in fields_node.elts ] # Handle attributes of Enums else: # Enums supports either iterator of (name, value) pairs # or mappings. if hasattr(names, "items") and isinstance(names.items, list): attributes = [ _infer_first(const[0], context).value for const in names.items if isinstance(const[0], nodes.Const) ] elif hasattr(names, "elts"): # Enums can support either ["a", "b", "c"] # or [("a", 1), ("b", 2), ...], but they can't # be mixed. if all(isinstance(const, nodes.Tuple) for const in names.elts): attributes = [ _infer_first(const.elts[0], context).value for const in names.elts if isinstance(const, nodes.Tuple) ] else: attributes = [ _infer_first(const, context).value for const in names.elts ] else: raise AttributeError from exc if not attributes: raise AttributeError from exc except (AttributeError, InferenceError) as exc: raise UseInferenceDefault from exc if not enum: # namedtuple maps sys.intern(str()) over over field_names attributes = [str(attr) for attr in attributes] # XXX this should succeed *unless* __str__/__repr__ is incorrect or throws # in which case we should not have inferred these values and raised earlier attributes = [attr for attr in attributes if " " not in attr] # If we can't infer the name of the class, don't crash, up to this point # we know it is a namedtuple anyway. name = name or "Uninferable" # we want to return a Class node instance with proper attributes set class_node = nodes.ClassDef(name) # A typical ClassDef automatically adds its name to the parent scope, # but doing so causes problems, so defer setting parent until after init # see: https://github.com/PyCQA/pylint/issues/5982 class_node.parent = node.parent class_node.postinit( # set base class=tuple bases=base_type, body=[], decorators=None, ) # XXX add __init__(*attributes) method for attr in attributes: fake_node = nodes.EmptyNode() fake_node.parent = class_node fake_node.attrname = attr class_node.instance_attrs[attr] = [fake_node] return class_node, name, attributes def _has_namedtuple_base(node): """Predicate for class inference tip. :type node: ClassDef :rtype: bool """ return set(node.basenames) & TYPING_NAMEDTUPLE_BASENAMES def _looks_like(node, name) -> bool: func = node.func if isinstance(func, nodes.Attribute): return func.attrname == name if isinstance(func, nodes.Name): return func.name == name return False _looks_like_namedtuple = functools.partial(_looks_like, name="namedtuple") _looks_like_enum = functools.partial(_looks_like, name="Enum") _looks_like_typing_namedtuple = functools.partial(_looks_like, name="NamedTuple") def infer_named_tuple( node: nodes.Call, context: InferenceContext | None = None ) -> Iterator[nodes.ClassDef]: """Specific inference function for namedtuple Call node.""" tuple_base_name: list[nodes.NodeNG] = [nodes.Name(name="tuple", parent=node.root())] class_node, name, attributes = infer_func_form( node, tuple_base_name, context=context ) call_site = arguments.CallSite.from_call(node, context=context) node = extract_node("import collections; collections.namedtuple") try: func = next(node.infer()) except StopIteration as e: raise InferenceError(node=node) from e try: rename = next(call_site.infer_argument(func, "rename", context)).bool_value() except (InferenceError, StopIteration): rename = False try: attributes = _check_namedtuple_attributes(name, attributes, rename) except AstroidTypeError as exc: raise UseInferenceDefault("TypeError: " + str(exc)) from exc except AstroidValueError as exc: raise UseInferenceDefault("ValueError: " + str(exc)) from exc replace_args = ", ".join(f"{arg}=None" for arg in attributes) field_def = ( " {name} = property(lambda self: self[{index:d}], " "doc='Alias for field number {index:d}')" ) field_defs = "\n".join( field_def.format(name=name, index=index) for index, name in enumerate(attributes) ) fake = AstroidBuilder(AstroidManager()).string_build( f""" class {name}(tuple): __slots__ = () _fields = {attributes!r} def _asdict(self): return self.__dict__ @classmethod def _make(cls, iterable, new=tuple.__new__, len=len): return new(cls, iterable) def _replace(self, {replace_args}): return self def __getnewargs__(self): return tuple(self) {field_defs} """ ) class_node.locals["_asdict"] = fake.body[0].locals["_asdict"] class_node.locals["_make"] = fake.body[0].locals["_make"] class_node.locals["_replace"] = fake.body[0].locals["_replace"] class_node.locals["_fields"] = fake.body[0].locals["_fields"] for attr in attributes: class_node.locals[attr] = fake.body[0].locals[attr] # we use UseInferenceDefault, we can't be a generator so return an iterator return iter([class_node]) def _get_renamed_namedtuple_attributes(field_names): names = list(field_names) seen = set() for i, name in enumerate(field_names): if ( not all(c.isalnum() or c == "_" for c in name) or keyword.iskeyword(name) or not name or name[0].isdigit() or name.startswith("_") or name in seen ): names[i] = "_%d" % i seen.add(name) return tuple(names) def _check_namedtuple_attributes(typename, attributes, rename=False): attributes = tuple(attributes) if rename: attributes = _get_renamed_namedtuple_attributes(attributes) # The following snippet is derived from the CPython Lib/collections/__init__.py sources # <snippet> for name in (typename,) + attributes: if not isinstance(name, str): raise AstroidTypeError("Type names and field names must be strings") if not name.isidentifier(): raise AstroidValueError( "Type names and field names must be valid" + f"identifiers: {name!r}" ) if keyword.iskeyword(name): raise AstroidValueError( f"Type names and field names cannot be a keyword: {name!r}" ) seen = set() for name in attributes: if name.startswith("_") and not rename: raise AstroidValueError( f"Field names cannot start with an underscore: {name!r}" ) if name in seen: raise AstroidValueError(f"Encountered duplicate field name: {name!r}") seen.add(name) # </snippet> return attributes def infer_enum( node: nodes.Call, context: InferenceContext | None = None ) -> Iterator[bases.Instance]: """Specific inference function for enum Call node.""" # Raise `UseInferenceDefault` if `node` is a call to a a user-defined Enum. try: inferred = node.func.infer(context) except (InferenceError, StopIteration) as exc: raise UseInferenceDefault from exc if not any( isinstance(item, nodes.ClassDef) and item.qname() == ENUM_QNAME for item in inferred ): raise UseInferenceDefault enum_meta = _extract_single_node( """ class EnumMeta(object): 'docstring' def __call__(self, node): class EnumAttribute(object): name = '' value = 0 return EnumAttribute() def __iter__(self): class EnumAttribute(object): name = '' value = 0 return [EnumAttribute()] def __reversed__(self): class EnumAttribute(object): name = '' value = 0 return (EnumAttribute, ) def __next__(self): return next(iter(self)) def __getitem__(self, attr): class Value(object): @property def name(self): return '' @property def value(self): return attr return Value() __members__ = [''] """ ) class_node = infer_func_form(node, [enum_meta], context=context, enum=True)[0] return iter([class_node.instantiate_class()]) INT_FLAG_ADDITION_METHODS = """ def __or__(self, other): return {name}(self.value | other.value) def __and__(self, other): return {name}(self.value & other.value) def __xor__(self, other): return {name}(self.value ^ other.value) def __add__(self, other): return {name}(self.value + other.value) def __div__(self, other): return {name}(self.value / other.value) def __invert__(self): return {name}(~self.value) def __mul__(self, other): return {name}(self.value * other.value) """ def infer_enum_class(node: nodes.ClassDef) -> nodes.ClassDef: """Specific inference for enums.""" for basename in (b for cls in node.mro() for b in cls.basenames): if node.root().name == "enum": # Skip if the class is directly from enum module. break dunder_members = {} target_names = set() for local, values in node.locals.items(): if any(not isinstance(value, nodes.AssignName) for value in values): continue stmt = values[0].statement(future=True) if isinstance(stmt, nodes.Assign): if isinstance(stmt.targets[0], nodes.Tuple): targets = stmt.targets[0].itered() else: targets = stmt.targets elif isinstance(stmt, nodes.AnnAssign): targets = [stmt.target] else: continue inferred_return_value = None if stmt.value is not None: if isinstance(stmt.value, nodes.Const): if isinstance(stmt.value.value, str): inferred_return_value = repr(stmt.value.value) else: inferred_return_value = stmt.value.value else: inferred_return_value = stmt.value.as_string() new_targets = [] for target in targets: if isinstance(target, nodes.Starred): continue target_names.add(target.name) # Replace all the assignments with our mocked class. classdef = dedent( """ class {name}({types}): @property def value(self): return {return_value} @property def name(self): return "{name}" """.format( name=target.name, types=", ".join(node.basenames), return_value=inferred_return_value, ) ) if "IntFlag" in basename: # Alright, we need to add some additional methods. # Unfortunately we still can't infer the resulting objects as # Enum members, but once we'll be able to do that, the following # should result in some nice symbolic execution classdef += INT_FLAG_ADDITION_METHODS.format(name=target.name) fake = AstroidBuilder( AstroidManager(), apply_transforms=False ).string_build(classdef)[target.name] fake.parent = target.parent for method in node.mymethods(): fake.locals[method.name] = [method] new_targets.append(fake.instantiate_class()) dunder_members[local] = fake node.locals[local] = new_targets # The undocumented `_value2member_map_` member: node.locals["_value2member_map_"] = [nodes.Dict(parent=node)] members = nodes.Dict(parent=node) members.postinit( [ (nodes.Const(k, parent=members), nodes.Name(v.name, parent=members)) for k, v in dunder_members.items() ] ) node.locals["__members__"] = [members] # The enum.Enum class itself defines two @DynamicClassAttribute data-descriptors # "name" and "value" (which we override in the mocked class for each enum member # above). When dealing with inference of an arbitrary instance of the enum # class, e.g. in a method defined in the class body like: # class SomeEnum(enum.Enum): # def method(self): # self.name # <- here # In the absence of an enum member called "name" or "value", these attributes # should resolve to the descriptor on that particular instance, i.e. enum member. # For "value", we have no idea what that should be, but for "name", we at least # know that it should be a string, so infer that as a guess. if "name" not in target_names: code = dedent( """ @property def name(self): return '' """ ) name_dynamicclassattr = AstroidBuilder(AstroidManager()).string_build(code)[ "name" ] node.locals["name"] = [name_dynamicclassattr] break return node def infer_typing_namedtuple_class(class_node, context: InferenceContext | None = None): """Infer a subclass of typing.NamedTuple.""" # Check if it has the corresponding bases annassigns_fields = [ annassign.target.name for annassign in class_node.body if isinstance(annassign, nodes.AnnAssign) ] code = dedent( """ from collections import namedtuple namedtuple({typename!r}, {fields!r}) """ ).format(typename=class_node.name, fields=",".join(annassigns_fields)) node = extract_node(code) try: generated_class_node = next(infer_named_tuple(node, context)) except StopIteration as e: raise InferenceError(node=node, context=context) from e for method in class_node.mymethods(): generated_class_node.locals[method.name] = [method] for body_node in class_node.body: if isinstance(body_node, nodes.Assign): for target in body_node.targets: attr = target.name generated_class_node.locals[attr] = class_node.locals[attr] elif isinstance(body_node, nodes.ClassDef): generated_class_node.locals[body_node.name] = [body_node] return iter((generated_class_node,)) def infer_typing_namedtuple_function(node, context: InferenceContext | None = None): """ Starting with python3.9, NamedTuple is a function of the typing module. The class NamedTuple is build dynamically through a call to `type` during initialization of the `_NamedTuple` variable. """ klass = extract_node( """ from typing import _NamedTuple _NamedTuple """ ) return klass.infer(context) def infer_typing_namedtuple( node: nodes.Call, context: InferenceContext | None = None ) -> Iterator[nodes.ClassDef]: """Infer a typing.NamedTuple(...) call.""" # This is essentially a namedtuple with different arguments # so we extract the args and infer a named tuple. try: func = next(node.func.infer()) except (InferenceError, StopIteration) as exc: raise UseInferenceDefault from exc if func.qname() not in TYPING_NAMEDTUPLE_QUALIFIED: raise UseInferenceDefault if len(node.args) != 2: raise UseInferenceDefault if not isinstance(node.args[1], (nodes.List, nodes.Tuple)): raise UseInferenceDefault return infer_named_tuple(node, context) def _get_namedtuple_fields(node: nodes.Call) -> str: """Get and return fields of a NamedTuple in code-as-a-string. Because the fields are represented in their code form we can extract a node from them later on. """ names = [] container = None try: container = next(node.args[1].infer()) except (InferenceError, StopIteration) as exc: raise UseInferenceDefault from exc # We pass on IndexError as we'll try to infer 'field_names' from the keywords except IndexError: pass if not container: for keyword_node in node.keywords: if keyword_node.arg == "field_names": try: container = next(keyword_node.value.infer()) except (InferenceError, StopIteration) as exc: raise UseInferenceDefault from exc break if not isinstance(container, nodes.BaseContainer): raise UseInferenceDefault for elt in container.elts: if isinstance(elt, nodes.Const): names.append(elt.as_string()) continue if not isinstance(elt, (nodes.List, nodes.Tuple)): raise UseInferenceDefault if len(elt.elts) != 2: raise UseInferenceDefault names.append(elt.elts[0].as_string()) if names: field_names = f"({','.join(names)},)" else: field_names = "" return field_names def _is_enum_subclass(cls: astroid.ClassDef) -> bool: """Return whether cls is a subclass of an Enum.""" try: return any( klass.name in ENUM_BASE_NAMES and getattr(klass.root(), "name", None) == "enum" for klass in cls.mro() ) except MroError: return False AstroidManager().register_transform( nodes.Call, inference_tip(infer_named_tuple), _looks_like_namedtuple ) AstroidManager().register_transform( nodes.Call, inference_tip(infer_enum), _looks_like_enum ) AstroidManager().register_transform( nodes.ClassDef, infer_enum_class, predicate=_is_enum_subclass ) AstroidManager().register_transform( nodes.ClassDef, inference_tip(infer_typing_namedtuple_class), _has_namedtuple_base ) AstroidManager().register_transform( nodes.FunctionDef, inference_tip(infer_typing_namedtuple_function), lambda node: node.name == "NamedTuple" and getattr(node.root(), "name", None) == "typing", ) AstroidManager().register_transform( nodes.Call, inference_tip(infer_typing_namedtuple), _looks_like_typing_namedtuple )