path: root/venv/Lib/site-packages/astroid/objects.py

# Copyright (c) 2015-2016, 2018 Claudiu Popa <pcmanticore@gmail.com>
# Copyright (c) 2015-2016 Ceridwen <ceridwenv@gmail.com>
# Copyright (c) 2015 Florian Bruhin <me@the-compiler.org>
# Copyright (c) 2016 Derek Gustafson <degustaf@gmail.com>
# Copyright (c) 2018 Bryce Guinta <bryce.paul.guinta@gmail.com>

# Licensed under the LGPL: https://www.gnu.org/licenses/old-licenses/lgpl-2.1.en.html
# For details: https://github.com/PyCQA/astroid/blob/master/COPYING.LESSER


"""
Inference objects are a way to represent composite AST nodes,
which are used only as inference results, so they can't be found in the
original AST tree. For instance, inferring the following frozenset use,
leads to an inferred FrozenSet:

    Call(func=Name('frozenset'), args=Tuple(...))
"""

import builtins

from astroid import bases
from astroid import decorators
from astroid import exceptions
from astroid import MANAGER
from astroid import node_classes
from astroid import scoped_nodes
from astroid import util


BUILTINS = builtins.__name__
objectmodel = util.lazy_import("interpreter.objectmodel")


class FrozenSet(node_classes._BaseContainer):
    """class representing a FrozenSet composite node"""

    def pytype(self):
        return "%s.frozenset" % BUILTINS

    def _infer(self, context=None):
        yield self

    @decorators.cachedproperty
    def _proxied(self):  # pylint: disable=method-hidden
        ast_builtins = MANAGER.builtins_module
        return ast_builtins.getattr("frozenset")[0]


class Super(node_classes.NodeNG):
    """Proxy class over a super call.

    This class offers almost the same behaviour as Python's super,
    which is MRO lookups for retrieving attributes from the parents.

    The *mro_pointer* is the place in the MRO from where we should
    start looking, not counting it. *mro_type* is the object which
    provides the MRO, it can be both a type or an instance.
    *self_class* is the class where the super call is, while
    *scope* is the function where the super call is.
    """

    # pylint: disable=unnecessary-lambda
    special_attributes = util.lazy_descriptor(lambda: objectmodel.SuperModel())

    # pylint: disable=super-init-not-called
    def __init__(self, mro_pointer, mro_type, self_class, scope):
        self.type = mro_type
        self.mro_pointer = mro_pointer
        self._class_based = False
        self._self_class = self_class
        self._scope = scope

    def _infer(self, context=None):
        yield self

    def super_mro(self):
        """Get the MRO which will be used to lookup attributes in this super."""
        if not isinstance(self.mro_pointer, scoped_nodes.ClassDef):
            raise exceptions.SuperError(
                "The first argument to super must be a subtype of "
                "type, not {mro_pointer}.",
                super_=self,
            )

        if isinstance(self.type, scoped_nodes.ClassDef):
            # `super(type, type)`, most likely in a class method.
            self._class_based = True
            mro_type = self.type
        else:
            mro_type = getattr(self.type, "_proxied", None)
            if not isinstance(mro_type, (bases.Instance, scoped_nodes.ClassDef)):
                raise exceptions.SuperError(
                    "The second argument to super must be an "
                    "instance or subtype of type, not {type}.",
                    super_=self,
                )

        if not mro_type.newstyle:
            raise exceptions.SuperError(
                "Unable to call super on old-style classes.", super_=self
            )

        mro = mro_type.mro()
        if self.mro_pointer not in mro:
            raise exceptions.SuperError(
                "The second argument to super must be an "
                "instance or subtype of type, not {type}.",
                super_=self,
            )

        index = mro.index(self.mro_pointer)
        return mro[index + 1 :]

    @decorators.cachedproperty
    def _proxied(self):
        ast_builtins = MANAGER.builtins_module
        return ast_builtins.getattr("super")[0]

    def pytype(self):
        return "%s.super" % BUILTINS

    def display_type(self):
        return "Super of"

    @property
    def name(self):
        """Get the name of the MRO pointer."""
        return self.mro_pointer.name

    def qname(self):
        return "super"

    def igetattr(self, name, context=None):
        """Retrieve the inferred values of the given attribute name."""

        if name in self.special_attributes:
            yield self.special_attributes.lookup(name)
            return

        try:
            mro = self.super_mro()
        # Don't let invalid MROs or invalid super calls
        # leak out as is from this function.
        except exceptions.SuperError as exc:
            raise exceptions.AttributeInferenceError(
                (
                    "Lookup for {name} on {target!r} because super call {super!r} "
                    "is invalid."
                ),
                target=self,
                attribute=name,
                context=context,
                super_=exc.super_,
            ) from exc
        except exceptions.MroError as exc:
            raise exceptions.AttributeInferenceError(
                (
                    "Lookup for {name} on {target!r} failed because {cls!r} has an "
                    "invalid MRO."
                ),
                target=self,
                attribute=name,
                context=context,
                mros=exc.mros,
                cls=exc.cls,
            ) from exc
        found = False
        for cls in mro:
            if name not in cls.locals:
                continue

            found = True
            for inferred in bases._infer_stmts([cls[name]], context, frame=self):
                if not isinstance(inferred, scoped_nodes.FunctionDef):
                    yield inferred
                    continue

                # We can obtain different descriptors from a super depending
                # on what we are accessing and where the super call is.
                if inferred.type == "classmethod":
                    yield bases.BoundMethod(inferred, cls)
                elif self._scope.type == "classmethod" and inferred.type == "method":
                    yield inferred
                elif self._class_based or inferred.type == "staticmethod":
                    yield inferred
                elif bases._is_property(inferred):
                    # TODO: support other descriptors as well.
                    try:
                        yield from inferred.infer_call_result(self, context)
                    except exceptions.InferenceError:
                        yield util.Uninferable
                else:
                    yield bases.BoundMethod(inferred, cls)

        if not found:
            raise exceptions.AttributeInferenceError(
                target=self, attribute=name, context=context
            )

    def getattr(self, name, context=None):
        return list(self.igetattr(name, context=context))


class ExceptionInstance(bases.Instance):
    """Class for instances of exceptions

    It has special treatment for some of the exceptions's attributes,
    which are transformed at runtime into certain concrete objects, such as
    the case of .args.
    """

    @decorators.cachedproperty
    def special_attributes(self):
        qname = self.qname()
        instance = objectmodel.BUILTIN_EXCEPTIONS.get(
            qname, objectmodel.ExceptionInstanceModel
        )
        return instance()(self)


class DictInstance(bases.Instance):
    """Special kind of instances for dictionaries

    This instance knows the underlying object model of the dictionaries, which means
    that methods such as .values or .items can be properly inferred.
    """

    # pylint: disable=unnecessary-lambda
    special_attributes = util.lazy_descriptor(lambda: objectmodel.DictModel())


# Custom objects tailored for dictionaries, which are used to
# disambiguate between the types of Python 2 dict's method returns
# and Python 3 (where they return set like objects).
class DictItems(bases.Proxy):
    __str__ = node_classes.NodeNG.__str__
    __repr__ = node_classes.NodeNG.__repr__


class DictKeys(bases.Proxy):
    __str__ = node_classes.NodeNG.__str__
    __repr__ = node_classes.NodeNG.__repr__


class DictValues(bases.Proxy):
    __str__ = node_classes.NodeNG.__str__
    __repr__ = node_classes.NodeNG.__repr__


class PartialFunction(scoped_nodes.FunctionDef):
    """A class representing partial function obtained via functools.partial"""

    def __init__(
        self, call, name=None, doc=None, lineno=None, col_offset=None, parent=None
    ):
        super().__init__(name, doc, lineno, col_offset, parent)
        self.filled_positionals = len(call.positional_arguments[1:])
        self.filled_args = call.positional_arguments[1:]
        self.filled_keywords = call.keyword_arguments

    def infer_call_result(self, caller=None, context=None):
        if context:
            current_passed_keywords = {
                keyword for (keyword, _) in context.callcontext.keywords
            }
            for keyword, value in self.filled_keywords.items():
                if keyword not in current_passed_keywords:
                    context.callcontext.keywords.append((keyword, value))

            call_context_args = context.callcontext.args or []
            context.callcontext.args = self.filled_args + call_context_args

        return super().infer_call_result(caller=caller, context=context)

    def qname(self):
        return self.__class__.__name__


# TODO: Hack to solve the circular import problem between node_classes and objects
# This is not needed in 2.0, which has a cleaner design overall
node_classes.Dict.__bases__ = (node_classes.NodeNG, DictInstance)