Tipragot
628be439b8
Cela permet de ne pas avoir de problèmes de compatibilité car python est dans le git.
1115 lines
43 KiB
Python
1115 lines
43 KiB
Python
"""Plugin for supporting the attrs library (http://www.attrs.org)"""
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from __future__ import annotations
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from collections import defaultdict
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from functools import reduce
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from typing import Final, Iterable, List, Mapping, cast
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from typing_extensions import Literal
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import mypy.plugin # To avoid circular imports.
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from mypy.applytype import apply_generic_arguments
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from mypy.errorcodes import LITERAL_REQ
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from mypy.expandtype import expand_type, expand_type_by_instance
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from mypy.exprtotype import TypeTranslationError, expr_to_unanalyzed_type
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from mypy.meet import meet_types
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from mypy.messages import format_type_bare
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from mypy.nodes import (
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ARG_NAMED,
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ARG_NAMED_OPT,
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ARG_OPT,
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ARG_POS,
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MDEF,
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Argument,
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AssignmentStmt,
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CallExpr,
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Context,
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Decorator,
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Expression,
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FuncDef,
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IndexExpr,
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JsonDict,
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LambdaExpr,
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ListExpr,
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MemberExpr,
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NameExpr,
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OverloadedFuncDef,
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PlaceholderNode,
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RefExpr,
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SymbolTableNode,
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TempNode,
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TupleExpr,
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TypeApplication,
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TypeInfo,
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TypeVarExpr,
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Var,
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is_class_var,
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)
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from mypy.plugin import SemanticAnalyzerPluginInterface
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from mypy.plugins.common import (
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_get_argument,
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_get_bool_argument,
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_get_decorator_bool_argument,
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add_attribute_to_class,
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add_method,
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deserialize_and_fixup_type,
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)
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from mypy.server.trigger import make_wildcard_trigger
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from mypy.typeops import get_type_vars, make_simplified_union, map_type_from_supertype
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from mypy.types import (
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AnyType,
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CallableType,
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FunctionLike,
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Instance,
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LiteralType,
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NoneType,
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Overloaded,
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ProperType,
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TupleType,
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Type,
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TypeOfAny,
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TypeType,
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TypeVarType,
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UninhabitedType,
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UnionType,
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get_proper_type,
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)
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from mypy.typevars import fill_typevars
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from mypy.util import unmangle
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# The names of the different functions that create classes or arguments.
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attr_class_makers: Final = {"attr.s", "attr.attrs", "attr.attributes"}
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attr_dataclass_makers: Final = {"attr.dataclass"}
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attr_frozen_makers: Final = {"attr.frozen", "attrs.frozen"}
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attr_define_makers: Final = {"attr.define", "attr.mutable", "attrs.define", "attrs.mutable"}
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attr_attrib_makers: Final = {"attr.ib", "attr.attrib", "attr.attr", "attr.field", "attrs.field"}
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attr_optional_converters: Final = {"attr.converters.optional", "attrs.converters.optional"}
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SELF_TVAR_NAME: Final = "_AT"
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MAGIC_ATTR_NAME: Final = "__attrs_attrs__"
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MAGIC_ATTR_CLS_NAME_TEMPLATE: Final = "__{}_AttrsAttributes__" # The tuple subclass pattern.
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ATTRS_INIT_NAME: Final = "__attrs_init__"
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class Converter:
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"""Holds information about a `converter=` argument"""
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def __init__(self, init_type: Type | None = None, ret_type: Type | None = None) -> None:
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self.init_type = init_type
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self.ret_type = ret_type
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class Attribute:
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"""The value of an attr.ib() call."""
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def __init__(
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self,
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name: str,
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info: TypeInfo,
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has_default: bool,
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init: bool,
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kw_only: bool,
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converter: Converter | None,
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context: Context,
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init_type: Type | None,
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) -> None:
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self.name = name
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self.info = info
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self.has_default = has_default
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self.init = init
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self.kw_only = kw_only
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self.converter = converter
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self.context = context
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self.init_type = init_type
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def argument(self, ctx: mypy.plugin.ClassDefContext) -> Argument:
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"""Return this attribute as an argument to __init__."""
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assert self.init
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init_type: Type | None = None
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if self.converter:
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if self.converter.init_type:
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init_type = self.converter.init_type
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if init_type and self.init_type and self.converter.ret_type:
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# The converter return type should be the same type as the attribute type.
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# Copy type vars from attr type to converter.
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converter_vars = get_type_vars(self.converter.ret_type)
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init_vars = get_type_vars(self.init_type)
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if converter_vars and len(converter_vars) == len(init_vars):
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variables = {
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binder.id: arg for binder, arg in zip(converter_vars, init_vars)
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}
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init_type = expand_type(init_type, variables)
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else:
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ctx.api.fail("Cannot determine __init__ type from converter", self.context)
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init_type = AnyType(TypeOfAny.from_error)
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else: # There is no converter, the init type is the normal type.
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init_type = self.init_type or self.info[self.name].type
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unannotated = False
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if init_type is None:
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unannotated = True
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# Convert type not set to Any.
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init_type = AnyType(TypeOfAny.unannotated)
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else:
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proper_type = get_proper_type(init_type)
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if isinstance(proper_type, AnyType):
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if proper_type.type_of_any == TypeOfAny.unannotated:
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unannotated = True
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if unannotated and ctx.api.options.disallow_untyped_defs:
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# This is a compromise. If you don't have a type here then the
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# __init__ will be untyped. But since the __init__ is added it's
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# pointing at the decorator. So instead we also show the error in the
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# assignment, which is where you would fix the issue.
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node = self.info[self.name].node
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assert node is not None
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ctx.api.msg.need_annotation_for_var(node, self.context)
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if self.kw_only:
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arg_kind = ARG_NAMED_OPT if self.has_default else ARG_NAMED
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else:
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arg_kind = ARG_OPT if self.has_default else ARG_POS
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# Attrs removes leading underscores when creating the __init__ arguments.
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return Argument(Var(self.name.lstrip("_"), init_type), init_type, None, arg_kind)
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def serialize(self) -> JsonDict:
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"""Serialize this object so it can be saved and restored."""
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return {
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"name": self.name,
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"has_default": self.has_default,
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"init": self.init,
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"kw_only": self.kw_only,
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"has_converter": self.converter is not None,
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"converter_init_type": self.converter.init_type.serialize()
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if self.converter and self.converter.init_type
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else None,
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"context_line": self.context.line,
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"context_column": self.context.column,
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"init_type": self.init_type.serialize() if self.init_type else None,
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}
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@classmethod
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def deserialize(
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cls, info: TypeInfo, data: JsonDict, api: SemanticAnalyzerPluginInterface
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) -> Attribute:
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"""Return the Attribute that was serialized."""
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raw_init_type = data["init_type"]
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init_type = deserialize_and_fixup_type(raw_init_type, api) if raw_init_type else None
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raw_converter_init_type = data["converter_init_type"]
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converter_init_type = (
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deserialize_and_fixup_type(raw_converter_init_type, api)
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if raw_converter_init_type
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else None
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)
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return Attribute(
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data["name"],
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info,
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data["has_default"],
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data["init"],
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data["kw_only"],
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Converter(converter_init_type) if data["has_converter"] else None,
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Context(line=data["context_line"], column=data["context_column"]),
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init_type,
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)
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def expand_typevar_from_subtype(self, sub_type: TypeInfo) -> None:
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"""Expands type vars in the context of a subtype when an attribute is inherited
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from a generic super type."""
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if self.init_type:
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self.init_type = map_type_from_supertype(self.init_type, sub_type, self.info)
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else:
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self.init_type = None
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def _determine_eq_order(ctx: mypy.plugin.ClassDefContext) -> bool:
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"""
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Validate the combination of *cmp*, *eq*, and *order*. Derive the effective
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value of order.
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"""
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cmp = _get_decorator_optional_bool_argument(ctx, "cmp")
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eq = _get_decorator_optional_bool_argument(ctx, "eq")
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order = _get_decorator_optional_bool_argument(ctx, "order")
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if cmp is not None and any((eq is not None, order is not None)):
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ctx.api.fail('Don\'t mix "cmp" with "eq" and "order"', ctx.reason)
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# cmp takes precedence due to bw-compatibility.
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if cmp is not None:
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return cmp
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# If left None, equality is on and ordering mirrors equality.
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if eq is None:
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eq = True
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if order is None:
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order = eq
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if eq is False and order is True:
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ctx.api.fail("eq must be True if order is True", ctx.reason)
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return order
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def _get_decorator_optional_bool_argument(
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ctx: mypy.plugin.ClassDefContext, name: str, default: bool | None = None
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) -> bool | None:
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"""Return the Optional[bool] argument for the decorator.
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This handles both @decorator(...) and @decorator.
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"""
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if isinstance(ctx.reason, CallExpr):
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attr_value = _get_argument(ctx.reason, name)
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if attr_value:
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if isinstance(attr_value, NameExpr):
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if attr_value.fullname == "builtins.True":
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return True
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if attr_value.fullname == "builtins.False":
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return False
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if attr_value.fullname == "builtins.None":
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return None
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ctx.api.fail(
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f'"{name}" argument must be a True, False, or None literal',
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ctx.reason,
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code=LITERAL_REQ,
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)
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return default
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return default
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else:
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return default
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def attr_tag_callback(ctx: mypy.plugin.ClassDefContext) -> None:
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"""Record that we have an attrs class in the main semantic analysis pass.
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The later pass implemented by attr_class_maker_callback will use this
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to detect attrs classes in base classes.
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"""
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# The value is ignored, only the existence matters.
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ctx.cls.info.metadata["attrs_tag"] = {}
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def attr_class_maker_callback(
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ctx: mypy.plugin.ClassDefContext,
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auto_attribs_default: bool | None = False,
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frozen_default: bool = False,
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slots_default: bool = False,
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) -> bool:
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"""Add necessary dunder methods to classes decorated with attr.s.
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attrs is a package that lets you define classes without writing dull boilerplate code.
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At a quick glance, the decorator searches the class body for assignments of `attr.ib`s (or
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annotated variables if auto_attribs=True), then depending on how the decorator is called,
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it will add an __init__ or all the compare methods.
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For frozen=True it will turn the attrs into properties.
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See https://www.attrs.org/en/stable/how-does-it-work.html for information on how attrs works.
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If this returns False, some required metadata was not ready yet and we need another
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pass.
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"""
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info = ctx.cls.info
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init = _get_decorator_bool_argument(ctx, "init", True)
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frozen = _get_frozen(ctx, frozen_default)
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order = _determine_eq_order(ctx)
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slots = _get_decorator_bool_argument(ctx, "slots", slots_default)
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auto_attribs = _get_decorator_optional_bool_argument(ctx, "auto_attribs", auto_attribs_default)
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kw_only = _get_decorator_bool_argument(ctx, "kw_only", False)
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match_args = _get_decorator_bool_argument(ctx, "match_args", True)
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for super_info in ctx.cls.info.mro[1:-1]:
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if "attrs_tag" in super_info.metadata and "attrs" not in super_info.metadata:
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# Super class is not ready yet. Request another pass.
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return False
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attributes = _analyze_class(ctx, auto_attribs, kw_only)
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# Check if attribute types are ready.
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for attr in attributes:
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node = info.get(attr.name)
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if node is None:
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# This name is likely blocked by some semantic analysis error that
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# should have been reported already.
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_add_empty_metadata(info)
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return True
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_add_attrs_magic_attribute(ctx, [(attr.name, info[attr.name].type) for attr in attributes])
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if slots:
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_add_slots(ctx, attributes)
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if match_args and ctx.api.options.python_version[:2] >= (3, 10):
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# `.__match_args__` is only added for python3.10+, but the argument
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# exists for earlier versions as well.
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_add_match_args(ctx, attributes)
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# Save the attributes so that subclasses can reuse them.
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ctx.cls.info.metadata["attrs"] = {
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"attributes": [attr.serialize() for attr in attributes],
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"frozen": frozen,
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}
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adder = MethodAdder(ctx)
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# If __init__ is not being generated, attrs still generates it as __attrs_init__ instead.
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_add_init(ctx, attributes, adder, "__init__" if init else ATTRS_INIT_NAME)
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if order:
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_add_order(ctx, adder)
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if frozen:
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_make_frozen(ctx, attributes)
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return True
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def _get_frozen(ctx: mypy.plugin.ClassDefContext, frozen_default: bool) -> bool:
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"""Return whether this class is frozen."""
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if _get_decorator_bool_argument(ctx, "frozen", frozen_default):
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return True
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# Subclasses of frozen classes are frozen so check that.
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for super_info in ctx.cls.info.mro[1:-1]:
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if "attrs" in super_info.metadata and super_info.metadata["attrs"]["frozen"]:
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return True
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return False
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def _analyze_class(
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ctx: mypy.plugin.ClassDefContext, auto_attribs: bool | None, kw_only: bool
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) -> list[Attribute]:
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"""Analyze the class body of an attr maker, its parents, and return the Attributes found.
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auto_attribs=True means we'll generate attributes from type annotations also.
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auto_attribs=None means we'll detect which mode to use.
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kw_only=True means that all attributes created here will be keyword only args in __init__.
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"""
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own_attrs: dict[str, Attribute] = {}
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if auto_attribs is None:
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auto_attribs = _detect_auto_attribs(ctx)
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# Walk the body looking for assignments and decorators.
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for stmt in ctx.cls.defs.body:
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if isinstance(stmt, AssignmentStmt):
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for attr in _attributes_from_assignment(ctx, stmt, auto_attribs, kw_only):
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# When attrs are defined twice in the same body we want to use the 2nd definition
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# in the 2nd location. So remove it from the OrderedDict.
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# Unless it's auto_attribs in which case we want the 2nd definition in the
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# 1st location.
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if not auto_attribs and attr.name in own_attrs:
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del own_attrs[attr.name]
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own_attrs[attr.name] = attr
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elif isinstance(stmt, Decorator):
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_cleanup_decorator(stmt, own_attrs)
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for attribute in own_attrs.values():
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# Even though these look like class level assignments we want them to look like
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# instance level assignments.
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if attribute.name in ctx.cls.info.names:
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node = ctx.cls.info.names[attribute.name].node
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if isinstance(node, PlaceholderNode):
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# This node is not ready yet.
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continue
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assert isinstance(node, Var)
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node.is_initialized_in_class = False
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# Traverse the MRO and collect attributes from the parents.
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taken_attr_names = set(own_attrs)
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super_attrs = []
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for super_info in ctx.cls.info.mro[1:-1]:
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if "attrs" in super_info.metadata:
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# Each class depends on the set of attributes in its attrs ancestors.
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ctx.api.add_plugin_dependency(make_wildcard_trigger(super_info.fullname))
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for data in super_info.metadata["attrs"]["attributes"]:
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# Only add an attribute if it hasn't been defined before. This
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# allows for overwriting attribute definitions by subclassing.
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if data["name"] not in taken_attr_names:
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a = Attribute.deserialize(super_info, data, ctx.api)
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a.expand_typevar_from_subtype(ctx.cls.info)
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super_attrs.append(a)
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taken_attr_names.add(a.name)
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attributes = super_attrs + list(own_attrs.values())
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# Check the init args for correct default-ness. Note: This has to be done after all the
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# attributes for all classes have been read, because subclasses can override parents.
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last_default = False
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for i, attribute in enumerate(attributes):
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if not attribute.init:
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continue
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if attribute.kw_only:
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# Keyword-only attributes don't care whether they are default or not.
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continue
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# If the issue comes from merging different classes, report it
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# at the class definition point.
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context = attribute.context if i >= len(super_attrs) else ctx.cls
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if not attribute.has_default and last_default:
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ctx.api.fail("Non-default attributes not allowed after default attributes.", context)
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last_default |= attribute.has_default
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return attributes
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def _add_empty_metadata(info: TypeInfo) -> None:
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"""Add empty metadata to mark that we've finished processing this class."""
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info.metadata["attrs"] = {"attributes": [], "frozen": False}
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def _detect_auto_attribs(ctx: mypy.plugin.ClassDefContext) -> bool:
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"""Return whether auto_attribs should be enabled or disabled.
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It's disabled if there are any unannotated attribs()
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"""
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for stmt in ctx.cls.defs.body:
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if isinstance(stmt, AssignmentStmt):
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for lvalue in stmt.lvalues:
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lvalues, rvalues = _parse_assignments(lvalue, stmt)
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if len(lvalues) != len(rvalues):
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# This means we have some assignment that isn't 1 to 1.
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# It can't be an attrib.
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continue
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for lhs, rvalue in zip(lvalues, rvalues):
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# Check if the right hand side is a call to an attribute maker.
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if (
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isinstance(rvalue, CallExpr)
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and isinstance(rvalue.callee, RefExpr)
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and rvalue.callee.fullname in attr_attrib_makers
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and not stmt.new_syntax
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):
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# This means we have an attrib without an annotation and so
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# we can't do auto_attribs=True
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return False
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|
return True
|
|
|
|
|
|
def _attributes_from_assignment(
|
|
ctx: mypy.plugin.ClassDefContext, stmt: AssignmentStmt, auto_attribs: bool, kw_only: bool
|
|
) -> Iterable[Attribute]:
|
|
"""Return Attribute objects that are created by this assignment.
|
|
|
|
The assignments can look like this:
|
|
x = attr.ib()
|
|
x = y = attr.ib()
|
|
x, y = attr.ib(), attr.ib()
|
|
or if auto_attribs is enabled also like this:
|
|
x: type
|
|
x: type = default_value
|
|
"""
|
|
for lvalue in stmt.lvalues:
|
|
lvalues, rvalues = _parse_assignments(lvalue, stmt)
|
|
|
|
if len(lvalues) != len(rvalues):
|
|
# This means we have some assignment that isn't 1 to 1.
|
|
# It can't be an attrib.
|
|
continue
|
|
|
|
for lhs, rvalue in zip(lvalues, rvalues):
|
|
# Check if the right hand side is a call to an attribute maker.
|
|
if (
|
|
isinstance(rvalue, CallExpr)
|
|
and isinstance(rvalue.callee, RefExpr)
|
|
and rvalue.callee.fullname in attr_attrib_makers
|
|
):
|
|
attr = _attribute_from_attrib_maker(ctx, auto_attribs, kw_only, lhs, rvalue, stmt)
|
|
if attr:
|
|
yield attr
|
|
elif auto_attribs and stmt.type and stmt.new_syntax and not is_class_var(lhs):
|
|
yield _attribute_from_auto_attrib(ctx, kw_only, lhs, rvalue, stmt)
|
|
|
|
|
|
def _cleanup_decorator(stmt: Decorator, attr_map: dict[str, Attribute]) -> None:
|
|
"""Handle decorators in class bodies.
|
|
|
|
`x.default` will set a default value on x
|
|
`x.validator` and `x.default` will get removed to avoid throwing a type error.
|
|
"""
|
|
remove_me = []
|
|
for func_decorator in stmt.decorators:
|
|
if (
|
|
isinstance(func_decorator, MemberExpr)
|
|
and isinstance(func_decorator.expr, NameExpr)
|
|
and func_decorator.expr.name in attr_map
|
|
):
|
|
if func_decorator.name == "default":
|
|
attr_map[func_decorator.expr.name].has_default = True
|
|
|
|
if func_decorator.name in ("default", "validator"):
|
|
# These are decorators on the attrib object that only exist during
|
|
# class creation time. In order to not trigger a type error later we
|
|
# just remove them. This might leave us with a Decorator with no
|
|
# decorators (Emperor's new clothes?)
|
|
# TODO: It would be nice to type-check these rather than remove them.
|
|
# default should be Callable[[], T]
|
|
# validator should be Callable[[Any, 'Attribute', T], Any]
|
|
# where T is the type of the attribute.
|
|
remove_me.append(func_decorator)
|
|
for dec in remove_me:
|
|
stmt.decorators.remove(dec)
|
|
|
|
|
|
def _attribute_from_auto_attrib(
|
|
ctx: mypy.plugin.ClassDefContext,
|
|
kw_only: bool,
|
|
lhs: NameExpr,
|
|
rvalue: Expression,
|
|
stmt: AssignmentStmt,
|
|
) -> Attribute:
|
|
"""Return an Attribute for a new type assignment."""
|
|
name = unmangle(lhs.name)
|
|
# `x: int` (without equal sign) assigns rvalue to TempNode(AnyType())
|
|
has_rhs = not isinstance(rvalue, TempNode)
|
|
sym = ctx.cls.info.names.get(name)
|
|
init_type = sym.type if sym else None
|
|
return Attribute(name, ctx.cls.info, has_rhs, True, kw_only, None, stmt, init_type)
|
|
|
|
|
|
def _attribute_from_attrib_maker(
|
|
ctx: mypy.plugin.ClassDefContext,
|
|
auto_attribs: bool,
|
|
kw_only: bool,
|
|
lhs: NameExpr,
|
|
rvalue: CallExpr,
|
|
stmt: AssignmentStmt,
|
|
) -> Attribute | None:
|
|
"""Return an Attribute from the assignment or None if you can't make one."""
|
|
if auto_attribs and not stmt.new_syntax:
|
|
# auto_attribs requires an annotation on *every* attr.ib.
|
|
assert lhs.node is not None
|
|
ctx.api.msg.need_annotation_for_var(lhs.node, stmt)
|
|
return None
|
|
|
|
if len(stmt.lvalues) > 1:
|
|
ctx.api.fail("Too many names for one attribute", stmt)
|
|
return None
|
|
|
|
# This is the type that belongs in the __init__ method for this attrib.
|
|
init_type = stmt.type
|
|
|
|
# Read all the arguments from the call.
|
|
init = _get_bool_argument(ctx, rvalue, "init", True)
|
|
# Note: If the class decorator says kw_only=True the attribute is ignored.
|
|
# See https://github.com/python-attrs/attrs/issues/481 for explanation.
|
|
kw_only |= _get_bool_argument(ctx, rvalue, "kw_only", False)
|
|
|
|
# TODO: Check for attr.NOTHING
|
|
attr_has_default = bool(_get_argument(rvalue, "default"))
|
|
attr_has_factory = bool(_get_argument(rvalue, "factory"))
|
|
|
|
if attr_has_default and attr_has_factory:
|
|
ctx.api.fail('Can\'t pass both "default" and "factory".', rvalue)
|
|
elif attr_has_factory:
|
|
attr_has_default = True
|
|
|
|
# If the type isn't set through annotation but is passed through `type=` use that.
|
|
type_arg = _get_argument(rvalue, "type")
|
|
if type_arg and not init_type:
|
|
try:
|
|
un_type = expr_to_unanalyzed_type(type_arg, ctx.api.options, ctx.api.is_stub_file)
|
|
except TypeTranslationError:
|
|
ctx.api.fail("Invalid argument to type", type_arg)
|
|
else:
|
|
init_type = ctx.api.anal_type(un_type)
|
|
if init_type and isinstance(lhs.node, Var) and not lhs.node.type:
|
|
# If there is no annotation, add one.
|
|
lhs.node.type = init_type
|
|
lhs.is_inferred_def = False
|
|
|
|
# Note: convert is deprecated but works the same as converter.
|
|
converter = _get_argument(rvalue, "converter")
|
|
convert = _get_argument(rvalue, "convert")
|
|
if convert and converter:
|
|
ctx.api.fail('Can\'t pass both "convert" and "converter".', rvalue)
|
|
elif convert:
|
|
ctx.api.fail("convert is deprecated, use converter", rvalue)
|
|
converter = convert
|
|
converter_info = _parse_converter(ctx, converter)
|
|
|
|
name = unmangle(lhs.name)
|
|
return Attribute(
|
|
name, ctx.cls.info, attr_has_default, init, kw_only, converter_info, stmt, init_type
|
|
)
|
|
|
|
|
|
def _parse_converter(
|
|
ctx: mypy.plugin.ClassDefContext, converter_expr: Expression | None
|
|
) -> Converter | None:
|
|
"""Return the Converter object from an Expression."""
|
|
# TODO: Support complex converters, e.g. lambdas, calls, etc.
|
|
if not converter_expr:
|
|
return None
|
|
converter_info = Converter()
|
|
if (
|
|
isinstance(converter_expr, CallExpr)
|
|
and isinstance(converter_expr.callee, RefExpr)
|
|
and converter_expr.callee.fullname in attr_optional_converters
|
|
and converter_expr.args
|
|
and converter_expr.args[0]
|
|
):
|
|
# Special handling for attr.converters.optional(type)
|
|
# We extract the type and add make the init_args Optional in Attribute.argument
|
|
converter_expr = converter_expr.args[0]
|
|
is_attr_converters_optional = True
|
|
else:
|
|
is_attr_converters_optional = False
|
|
|
|
converter_type: Type | None = None
|
|
if isinstance(converter_expr, RefExpr) and converter_expr.node:
|
|
if isinstance(converter_expr.node, FuncDef):
|
|
if converter_expr.node.type and isinstance(converter_expr.node.type, FunctionLike):
|
|
converter_type = converter_expr.node.type
|
|
else: # The converter is an unannotated function.
|
|
converter_info.init_type = AnyType(TypeOfAny.unannotated)
|
|
return converter_info
|
|
elif isinstance(converter_expr.node, OverloadedFuncDef) and is_valid_overloaded_converter(
|
|
converter_expr.node
|
|
):
|
|
converter_type = converter_expr.node.type
|
|
elif isinstance(converter_expr.node, TypeInfo):
|
|
from mypy.checkmember import type_object_type # To avoid import cycle.
|
|
|
|
converter_type = type_object_type(converter_expr.node, ctx.api.named_type)
|
|
elif (
|
|
isinstance(converter_expr, IndexExpr)
|
|
and isinstance(converter_expr.analyzed, TypeApplication)
|
|
and isinstance(converter_expr.base, RefExpr)
|
|
and isinstance(converter_expr.base.node, TypeInfo)
|
|
):
|
|
# The converter is a generic type.
|
|
from mypy.checkmember import type_object_type # To avoid import cycle.
|
|
|
|
converter_type = type_object_type(converter_expr.base.node, ctx.api.named_type)
|
|
if isinstance(converter_type, CallableType):
|
|
converter_type = apply_generic_arguments(
|
|
converter_type,
|
|
converter_expr.analyzed.types,
|
|
ctx.api.msg.incompatible_typevar_value,
|
|
converter_type,
|
|
)
|
|
else:
|
|
converter_type = None
|
|
|
|
if isinstance(converter_expr, LambdaExpr):
|
|
# TODO: should we send a fail if converter_expr.min_args > 1?
|
|
converter_info.init_type = AnyType(TypeOfAny.unannotated)
|
|
return converter_info
|
|
|
|
if not converter_type:
|
|
# Signal that we have an unsupported converter.
|
|
ctx.api.fail(
|
|
"Unsupported converter, only named functions, types and lambdas are currently "
|
|
"supported",
|
|
converter_expr,
|
|
)
|
|
converter_info.init_type = AnyType(TypeOfAny.from_error)
|
|
return converter_info
|
|
|
|
converter_type = get_proper_type(converter_type)
|
|
if isinstance(converter_type, CallableType) and converter_type.arg_types:
|
|
converter_info.init_type = converter_type.arg_types[0]
|
|
if not is_attr_converters_optional:
|
|
converter_info.ret_type = converter_type.ret_type
|
|
elif isinstance(converter_type, Overloaded):
|
|
types: list[Type] = []
|
|
for item in converter_type.items:
|
|
# Walk the overloads looking for methods that can accept one argument.
|
|
num_arg_types = len(item.arg_types)
|
|
if not num_arg_types:
|
|
continue
|
|
if num_arg_types > 1 and any(kind == ARG_POS for kind in item.arg_kinds[1:]):
|
|
continue
|
|
types.append(item.arg_types[0])
|
|
# Make a union of all the valid types.
|
|
if types:
|
|
converter_info.init_type = make_simplified_union(types)
|
|
|
|
if is_attr_converters_optional and converter_info.init_type:
|
|
# If the converter was attr.converter.optional(type) then add None to
|
|
# the allowed init_type.
|
|
converter_info.init_type = UnionType.make_union([converter_info.init_type, NoneType()])
|
|
|
|
return converter_info
|
|
|
|
|
|
def is_valid_overloaded_converter(defn: OverloadedFuncDef) -> bool:
|
|
return all(
|
|
(not isinstance(item, Decorator) or isinstance(item.func.type, FunctionLike))
|
|
for item in defn.items
|
|
)
|
|
|
|
|
|
def _parse_assignments(
|
|
lvalue: Expression, stmt: AssignmentStmt
|
|
) -> tuple[list[NameExpr], list[Expression]]:
|
|
"""Convert a possibly complex assignment expression into lists of lvalues and rvalues."""
|
|
lvalues: list[NameExpr] = []
|
|
rvalues: list[Expression] = []
|
|
if isinstance(lvalue, (TupleExpr, ListExpr)):
|
|
if all(isinstance(item, NameExpr) for item in lvalue.items):
|
|
lvalues = cast(List[NameExpr], lvalue.items)
|
|
if isinstance(stmt.rvalue, (TupleExpr, ListExpr)):
|
|
rvalues = stmt.rvalue.items
|
|
elif isinstance(lvalue, NameExpr):
|
|
lvalues = [lvalue]
|
|
rvalues = [stmt.rvalue]
|
|
return lvalues, rvalues
|
|
|
|
|
|
def _add_order(ctx: mypy.plugin.ClassDefContext, adder: MethodAdder) -> None:
|
|
"""Generate all the ordering methods for this class."""
|
|
bool_type = ctx.api.named_type("builtins.bool")
|
|
object_type = ctx.api.named_type("builtins.object")
|
|
# Make the types be:
|
|
# AT = TypeVar('AT')
|
|
# def __lt__(self: AT, other: AT) -> bool
|
|
# This way comparisons with subclasses will work correctly.
|
|
tvd = TypeVarType(
|
|
SELF_TVAR_NAME,
|
|
ctx.cls.info.fullname + "." + SELF_TVAR_NAME,
|
|
id=-1,
|
|
values=[],
|
|
upper_bound=object_type,
|
|
default=AnyType(TypeOfAny.from_omitted_generics),
|
|
)
|
|
self_tvar_expr = TypeVarExpr(
|
|
SELF_TVAR_NAME,
|
|
ctx.cls.info.fullname + "." + SELF_TVAR_NAME,
|
|
[],
|
|
object_type,
|
|
AnyType(TypeOfAny.from_omitted_generics),
|
|
)
|
|
ctx.cls.info.names[SELF_TVAR_NAME] = SymbolTableNode(MDEF, self_tvar_expr)
|
|
|
|
args = [Argument(Var("other", tvd), tvd, None, ARG_POS)]
|
|
for method in ["__lt__", "__le__", "__gt__", "__ge__"]:
|
|
adder.add_method(method, args, bool_type, self_type=tvd, tvd=tvd)
|
|
|
|
|
|
def _make_frozen(ctx: mypy.plugin.ClassDefContext, attributes: list[Attribute]) -> None:
|
|
"""Turn all the attributes into properties to simulate frozen classes."""
|
|
for attribute in attributes:
|
|
if attribute.name in ctx.cls.info.names:
|
|
# This variable belongs to this class so we can modify it.
|
|
node = ctx.cls.info.names[attribute.name].node
|
|
if not isinstance(node, Var):
|
|
# The superclass attribute was overridden with a non-variable.
|
|
# No need to do anything here, override will be verified during
|
|
# type checking.
|
|
continue
|
|
node.is_property = True
|
|
else:
|
|
# This variable belongs to a super class so create new Var so we
|
|
# can modify it.
|
|
var = Var(attribute.name, attribute.init_type)
|
|
var.info = ctx.cls.info
|
|
var._fullname = f"{ctx.cls.info.fullname}.{var.name}"
|
|
ctx.cls.info.names[var.name] = SymbolTableNode(MDEF, var)
|
|
var.is_property = True
|
|
|
|
|
|
def _add_init(
|
|
ctx: mypy.plugin.ClassDefContext,
|
|
attributes: list[Attribute],
|
|
adder: MethodAdder,
|
|
method_name: Literal["__init__", "__attrs_init__"],
|
|
) -> None:
|
|
"""Generate an __init__ method for the attributes and add it to the class."""
|
|
# Convert attributes to arguments with kw_only arguments at the end of
|
|
# the argument list
|
|
pos_args = []
|
|
kw_only_args = []
|
|
sym_table = ctx.cls.info.names
|
|
for attribute in attributes:
|
|
if not attribute.init:
|
|
continue
|
|
if attribute.kw_only:
|
|
kw_only_args.append(attribute.argument(ctx))
|
|
else:
|
|
pos_args.append(attribute.argument(ctx))
|
|
|
|
# If the attribute is Final, present in `__init__` and has
|
|
# no default, make sure it doesn't error later.
|
|
if not attribute.has_default and attribute.name in sym_table:
|
|
sym_node = sym_table[attribute.name].node
|
|
if isinstance(sym_node, Var) and sym_node.is_final:
|
|
sym_node.final_set_in_init = True
|
|
args = pos_args + kw_only_args
|
|
if all(
|
|
# We use getattr rather than instance checks because the variable.type
|
|
# might be wrapped into a Union or some other type, but even non-Any
|
|
# types reliably track the fact that the argument was not annotated.
|
|
getattr(arg.variable.type, "type_of_any", None) == TypeOfAny.unannotated
|
|
for arg in args
|
|
):
|
|
# This workaround makes --disallow-incomplete-defs usable with attrs,
|
|
# but is definitely suboptimal as a long-term solution.
|
|
# See https://github.com/python/mypy/issues/5954 for discussion.
|
|
for a in args:
|
|
a.variable.type = AnyType(TypeOfAny.implementation_artifact)
|
|
a.type_annotation = AnyType(TypeOfAny.implementation_artifact)
|
|
adder.add_method(method_name, args, NoneType())
|
|
|
|
|
|
def _add_attrs_magic_attribute(
|
|
ctx: mypy.plugin.ClassDefContext, attrs: list[tuple[str, Type | None]]
|
|
) -> None:
|
|
any_type = AnyType(TypeOfAny.explicit)
|
|
attributes_types: list[Type] = [
|
|
ctx.api.named_type_or_none("attr.Attribute", [attr_type or any_type]) or any_type
|
|
for _, attr_type in attrs
|
|
]
|
|
fallback_type = ctx.api.named_type(
|
|
"builtins.tuple", [ctx.api.named_type_or_none("attr.Attribute", [any_type]) or any_type]
|
|
)
|
|
|
|
attr_name = MAGIC_ATTR_CLS_NAME_TEMPLATE.format(ctx.cls.fullname.replace(".", "_"))
|
|
ti = ctx.api.basic_new_typeinfo(attr_name, fallback_type, 0)
|
|
for (name, _), attr_type in zip(attrs, attributes_types):
|
|
var = Var(name, attr_type)
|
|
var._fullname = name
|
|
var.is_property = True
|
|
proper_type = get_proper_type(attr_type)
|
|
if isinstance(proper_type, Instance):
|
|
var.info = proper_type.type
|
|
ti.names[name] = SymbolTableNode(MDEF, var, plugin_generated=True)
|
|
attributes_type = Instance(ti, [])
|
|
|
|
# We need to stash the type of the magic attribute so it can be
|
|
# loaded on cached runs.
|
|
ctx.cls.info.names[attr_name] = SymbolTableNode(MDEF, ti, plugin_generated=True)
|
|
|
|
add_attribute_to_class(
|
|
ctx.api,
|
|
ctx.cls,
|
|
MAGIC_ATTR_NAME,
|
|
TupleType(attributes_types, fallback=attributes_type),
|
|
fullname=f"{ctx.cls.fullname}.{MAGIC_ATTR_NAME}",
|
|
override_allow_incompatible=True,
|
|
is_classvar=True,
|
|
)
|
|
|
|
|
|
def _add_slots(ctx: mypy.plugin.ClassDefContext, attributes: list[Attribute]) -> None:
|
|
# Unlike `@dataclasses.dataclass`, `__slots__` is rewritten here.
|
|
ctx.cls.info.slots = {attr.name for attr in attributes}
|
|
|
|
# Also, inject `__slots__` attribute to class namespace:
|
|
slots_type = TupleType(
|
|
[ctx.api.named_type("builtins.str") for _ in attributes],
|
|
fallback=ctx.api.named_type("builtins.tuple"),
|
|
)
|
|
add_attribute_to_class(api=ctx.api, cls=ctx.cls, name="__slots__", typ=slots_type)
|
|
|
|
|
|
def _add_match_args(ctx: mypy.plugin.ClassDefContext, attributes: list[Attribute]) -> None:
|
|
if (
|
|
"__match_args__" not in ctx.cls.info.names
|
|
or ctx.cls.info.names["__match_args__"].plugin_generated
|
|
):
|
|
str_type = ctx.api.named_type("builtins.str")
|
|
match_args = TupleType(
|
|
[
|
|
str_type.copy_modified(last_known_value=LiteralType(attr.name, fallback=str_type))
|
|
for attr in attributes
|
|
if not attr.kw_only and attr.init
|
|
],
|
|
fallback=ctx.api.named_type("builtins.tuple"),
|
|
)
|
|
add_attribute_to_class(api=ctx.api, cls=ctx.cls, name="__match_args__", typ=match_args)
|
|
|
|
|
|
class MethodAdder:
|
|
"""Helper to add methods to a TypeInfo.
|
|
|
|
ctx: The ClassDefCtx we are using on which we will add methods.
|
|
"""
|
|
|
|
# TODO: Combine this with the code build_namedtuple_typeinfo to support both.
|
|
|
|
def __init__(self, ctx: mypy.plugin.ClassDefContext) -> None:
|
|
self.ctx = ctx
|
|
self.self_type = fill_typevars(ctx.cls.info)
|
|
|
|
def add_method(
|
|
self,
|
|
method_name: str,
|
|
args: list[Argument],
|
|
ret_type: Type,
|
|
self_type: Type | None = None,
|
|
tvd: TypeVarType | None = None,
|
|
) -> None:
|
|
"""Add a method: def <method_name>(self, <args>) -> <ret_type>): ... to info.
|
|
|
|
self_type: The type to use for the self argument or None to use the inferred self type.
|
|
tvd: If the method is generic these should be the type variables.
|
|
"""
|
|
self_type = self_type if self_type is not None else self.self_type
|
|
add_method(self.ctx, method_name, args, ret_type, self_type, tvd)
|
|
|
|
|
|
def _get_attrs_init_type(typ: Instance) -> CallableType | None:
|
|
"""
|
|
If `typ` refers to an attrs class, get the type of its initializer method.
|
|
"""
|
|
magic_attr = typ.type.get(MAGIC_ATTR_NAME)
|
|
if magic_attr is None or not magic_attr.plugin_generated:
|
|
return None
|
|
init_method = typ.type.get_method("__init__") or typ.type.get_method(ATTRS_INIT_NAME)
|
|
if not isinstance(init_method, FuncDef) or not isinstance(init_method.type, CallableType):
|
|
return None
|
|
return init_method.type
|
|
|
|
|
|
def _fail_not_attrs_class(ctx: mypy.plugin.FunctionSigContext, t: Type, parent_t: Type) -> None:
|
|
t_name = format_type_bare(t, ctx.api.options)
|
|
if parent_t is t:
|
|
msg = (
|
|
f'Argument 1 to "evolve" has a variable type "{t_name}" not bound to an attrs class'
|
|
if isinstance(t, TypeVarType)
|
|
else f'Argument 1 to "evolve" has incompatible type "{t_name}"; expected an attrs class'
|
|
)
|
|
else:
|
|
pt_name = format_type_bare(parent_t, ctx.api.options)
|
|
msg = (
|
|
f'Argument 1 to "evolve" has type "{pt_name}" whose item "{t_name}" is not bound to an attrs class'
|
|
if isinstance(t, TypeVarType)
|
|
else f'Argument 1 to "evolve" has incompatible type "{pt_name}" whose item "{t_name}" is not an attrs class'
|
|
)
|
|
|
|
ctx.api.fail(msg, ctx.context)
|
|
|
|
|
|
def _get_expanded_attr_types(
|
|
ctx: mypy.plugin.FunctionSigContext,
|
|
typ: ProperType,
|
|
display_typ: ProperType,
|
|
parent_typ: ProperType,
|
|
) -> list[Mapping[str, Type]] | None:
|
|
"""
|
|
For a given type, determine what attrs classes it can be: for each class, return the field types.
|
|
For generic classes, the field types are expanded.
|
|
If the type contains Any or a non-attrs type, returns None; in the latter case, also reports an error.
|
|
"""
|
|
if isinstance(typ, AnyType):
|
|
return None
|
|
elif isinstance(typ, UnionType):
|
|
ret: list[Mapping[str, Type]] | None = []
|
|
for item in typ.relevant_items():
|
|
item = get_proper_type(item)
|
|
item_types = _get_expanded_attr_types(ctx, item, item, parent_typ)
|
|
if ret is not None and item_types is not None:
|
|
ret += item_types
|
|
else:
|
|
ret = None # but keep iterating to emit all errors
|
|
return ret
|
|
elif isinstance(typ, TypeVarType):
|
|
return _get_expanded_attr_types(
|
|
ctx, get_proper_type(typ.upper_bound), display_typ, parent_typ
|
|
)
|
|
elif isinstance(typ, Instance):
|
|
init_func = _get_attrs_init_type(typ)
|
|
if init_func is None:
|
|
_fail_not_attrs_class(ctx, display_typ, parent_typ)
|
|
return None
|
|
init_func = expand_type_by_instance(init_func, typ)
|
|
# [1:] to skip the self argument of AttrClass.__init__
|
|
field_names = cast(List[str], init_func.arg_names[1:])
|
|
field_types = init_func.arg_types[1:]
|
|
return [dict(zip(field_names, field_types))]
|
|
else:
|
|
_fail_not_attrs_class(ctx, display_typ, parent_typ)
|
|
return None
|
|
|
|
|
|
def _meet_fields(types: list[Mapping[str, Type]]) -> Mapping[str, Type]:
|
|
"""
|
|
"Meet" the fields of a list of attrs classes, i.e. for each field, its new type will be the lower bound.
|
|
"""
|
|
field_to_types = defaultdict(list)
|
|
for fields in types:
|
|
for name, typ in fields.items():
|
|
field_to_types[name].append(typ)
|
|
|
|
return {
|
|
name: get_proper_type(reduce(meet_types, f_types))
|
|
if len(f_types) == len(types)
|
|
else UninhabitedType()
|
|
for name, f_types in field_to_types.items()
|
|
}
|
|
|
|
|
|
def evolve_function_sig_callback(ctx: mypy.plugin.FunctionSigContext) -> CallableType:
|
|
"""
|
|
Generate a signature for the 'attr.evolve' function that's specific to the call site
|
|
and dependent on the type of the first argument.
|
|
"""
|
|
if len(ctx.args) != 2:
|
|
# Ideally the name and context should be callee's, but we don't have it in FunctionSigContext.
|
|
ctx.api.fail(f'"{ctx.default_signature.name}" has unexpected type annotation', ctx.context)
|
|
return ctx.default_signature
|
|
|
|
if len(ctx.args[0]) != 1:
|
|
return ctx.default_signature # leave it to the type checker to complain
|
|
|
|
inst_arg = ctx.args[0][0]
|
|
inst_type = get_proper_type(ctx.api.get_expression_type(inst_arg))
|
|
inst_type_str = format_type_bare(inst_type, ctx.api.options)
|
|
|
|
attr_types = _get_expanded_attr_types(ctx, inst_type, inst_type, inst_type)
|
|
if attr_types is None:
|
|
return ctx.default_signature
|
|
fields = _meet_fields(attr_types)
|
|
|
|
return CallableType(
|
|
arg_names=["inst", *fields.keys()],
|
|
arg_kinds=[ARG_POS] + [ARG_NAMED_OPT] * len(fields),
|
|
arg_types=[inst_type, *fields.values()],
|
|
ret_type=inst_type,
|
|
fallback=ctx.default_signature.fallback,
|
|
name=f"{ctx.default_signature.name} of {inst_type_str}",
|
|
)
|
|
|
|
|
|
def fields_function_sig_callback(ctx: mypy.plugin.FunctionSigContext) -> CallableType:
|
|
"""Provide the signature for `attrs.fields`."""
|
|
if len(ctx.args) != 1 or len(ctx.args[0]) != 1:
|
|
return ctx.default_signature
|
|
|
|
proper_type = get_proper_type(ctx.api.get_expression_type(ctx.args[0][0]))
|
|
|
|
# fields(Any) -> Any, fields(type[Any]) -> Any
|
|
if (
|
|
isinstance(proper_type, AnyType)
|
|
or isinstance(proper_type, TypeType)
|
|
and isinstance(proper_type.item, AnyType)
|
|
):
|
|
return ctx.default_signature
|
|
|
|
cls = None
|
|
arg_types = ctx.default_signature.arg_types
|
|
|
|
if isinstance(proper_type, TypeVarType):
|
|
inner = get_proper_type(proper_type.upper_bound)
|
|
if isinstance(inner, Instance):
|
|
# We need to work arg_types to compensate for the attrs stubs.
|
|
arg_types = [proper_type]
|
|
cls = inner.type
|
|
elif isinstance(proper_type, CallableType):
|
|
cls = proper_type.type_object()
|
|
|
|
if cls is not None and MAGIC_ATTR_NAME in cls.names:
|
|
# This is a proper attrs class.
|
|
ret_type = cls.names[MAGIC_ATTR_NAME].type
|
|
assert ret_type is not None
|
|
return ctx.default_signature.copy_modified(arg_types=arg_types, ret_type=ret_type)
|
|
|
|
ctx.api.fail(
|
|
f'Argument 1 to "fields" has incompatible type "{format_type_bare(proper_type, ctx.api.options)}"; expected an attrs class',
|
|
ctx.context,
|
|
)
|
|
|
|
return ctx.default_signature
|