Current File : //opt/cloudlinux/venv/lib/python3.11/site-packages/astroid/brain/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
)
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