"""Mypy type checker.""" from __future__ import annotations import itertools from collections import defaultdict from collections.abc import Iterable, Iterator, Mapping, Sequence, Set as AbstractSet from contextlib import ExitStack, contextmanager from typing import Callable, Final, Generic, NamedTuple, Optional, TypeVar, Union, cast, overload from typing_extensions import TypeAlias as _TypeAlias, TypeGuard import mypy.checkexpr from mypy import errorcodes as codes, join, message_registry, nodes, operators from mypy.binder import ConditionalTypeBinder, Frame, get_declaration from mypy.checker_shared import CheckerScope, TypeCheckerSharedApi, TypeRange from mypy.checkmember import ( MemberContext, analyze_class_attribute_access, analyze_instance_member_access, analyze_member_access, is_instance_var, ) from mypy.checkpattern import PatternChecker from mypy.constraints import SUPERTYPE_OF from mypy.erasetype import erase_type, erase_typevars, remove_instance_last_known_values from mypy.errorcodes import TYPE_VAR, UNUSED_AWAITABLE, UNUSED_COROUTINE, ErrorCode from mypy.errors import Errors, ErrorWatcher, report_internal_error from mypy.expandtype import expand_type from mypy.literals import Key, extract_var_from_literal_hash, literal, literal_hash from mypy.maptype import map_instance_to_supertype from mypy.meet import is_overlapping_erased_types, is_overlapping_types, meet_types from mypy.message_registry import ErrorMessage from mypy.messages import ( SUGGESTED_TEST_FIXTURES, MessageBuilder, append_invariance_notes, append_union_note, format_type, format_type_bare, format_type_distinctly, make_inferred_type_note, pretty_seq, ) from mypy.mro import MroError, calculate_mro from mypy.nodes import ( ARG_NAMED, ARG_POS, ARG_STAR, CONTRAVARIANT, COVARIANT, FUNC_NO_INFO, GDEF, IMPLICITLY_ABSTRACT, INVARIANT, IS_ABSTRACT, LDEF, LITERAL_TYPE, MDEF, NOT_ABSTRACT, SYMBOL_FUNCBASE_TYPES, AssertStmt, AssignmentExpr, AssignmentStmt, Block, BreakStmt, BytesExpr, CallExpr, ClassDef, ComparisonExpr, Context, ContinueStmt, Decorator, DelStmt, EllipsisExpr, Expression, ExpressionStmt, FloatExpr, ForStmt, FuncBase, FuncDef, FuncItem, GlobalDecl, IfStmt, Import, ImportAll, ImportBase, ImportFrom, IndexExpr, IntExpr, LambdaExpr, ListExpr, Lvalue, MatchStmt, MemberExpr, MypyFile, NameExpr, Node, NonlocalDecl, OperatorAssignmentStmt, OpExpr, OverloadedFuncDef, PassStmt, PromoteExpr, RaiseStmt, RefExpr, ReturnStmt, StarExpr, Statement, StrExpr, SymbolNode, SymbolTable, SymbolTableNode, TempNode, TryStmt, TupleExpr, TypeAlias, TypeAliasStmt, TypeInfo, TypeVarExpr, UnaryExpr, Var, WhileStmt, WithStmt, YieldExpr, is_final_node, ) from mypy.operators import flip_ops, int_op_to_method, neg_ops from mypy.options import PRECISE_TUPLE_TYPES, Options from mypy.patterns import AsPattern, StarredPattern from mypy.plugin import Plugin from mypy.plugins import dataclasses as dataclasses_plugin from mypy.scope import Scope from mypy.semanal import is_trivial_body, refers_to_fullname, set_callable_name from mypy.semanal_enum import ENUM_BASES, ENUM_SPECIAL_PROPS from mypy.sharedparse import BINARY_MAGIC_METHODS from mypy.state import state from mypy.subtypes import ( find_member, infer_class_variances, is_callable_compatible, is_equivalent, is_more_precise, is_proper_subtype, is_same_type, is_subtype, restrict_subtype_away, unify_generic_callable, ) from mypy.traverser import TraverserVisitor, all_return_statements, has_return_statement from mypy.treetransform import TransformVisitor from mypy.typeanal import check_for_explicit_any, has_any_from_unimported_type, make_optional_type from mypy.typeops import ( bind_self, coerce_to_literal, custom_special_method, erase_def_to_union_or_bound, erase_to_bound, erase_to_union_or_bound, false_only, fixup_partial_type, function_type, is_literal_type_like, is_singleton_type, make_simplified_union, true_only, try_expanding_sum_type_to_union, try_getting_int_literals_from_type, try_getting_str_literals, try_getting_str_literals_from_type, tuple_fallback, type_object_type, ) from mypy.types import ( ANY_STRATEGY, MYPYC_NATIVE_INT_NAMES, OVERLOAD_NAMES, AnyType, BoolTypeQuery, CallableType, DeletedType, ErasedType, FunctionLike, Instance, LiteralType, NoneType, Overloaded, PartialType, ProperType, TupleType, Type, TypeAliasType, TypedDictType, TypeGuardedType, TypeOfAny, TypeTranslator, TypeType, TypeVarId, TypeVarLikeType, TypeVarTupleType, TypeVarType, UnboundType, UninhabitedType, UnionType, UnpackType, find_unpack_in_list, flatten_nested_unions, get_proper_type, get_proper_types, is_literal_type, is_named_instance, ) from mypy.types_utils import is_overlapping_none, remove_optional, store_argument_type, strip_type from mypy.typetraverser import TypeTraverserVisitor from mypy.typevars import fill_typevars, fill_typevars_with_any, has_no_typevars from mypy.util import is_dunder, is_sunder from mypy.visitor import NodeVisitor T = TypeVar("T") DEFAULT_LAST_PASS: Final = 2 # Pass numbers start at 0 # Maximum length of fixed tuple types inferred when narrowing from variadic tuples. MAX_PRECISE_TUPLE_SIZE: Final = 8 DeferredNodeType: _TypeAlias = Union[FuncDef, OverloadedFuncDef, Decorator] FineGrainedDeferredNodeType: _TypeAlias = Union[FuncDef, MypyFile, OverloadedFuncDef] # A node which is postponed to be processed during the next pass. # In normal mode one can defer functions and methods (also decorated and/or overloaded) # but not lambda expressions. Nested functions can't be deferred -- only top-level functions # and methods of classes not defined within a function can be deferred. class DeferredNode(NamedTuple): node: DeferredNodeType # And its TypeInfo (for semantic analysis self type handling) active_typeinfo: TypeInfo | None # Same as above, but for fine-grained mode targets. Only top-level functions/methods # and module top levels are allowed as such. class FineGrainedDeferredNode(NamedTuple): node: FineGrainedDeferredNodeType active_typeinfo: TypeInfo | None # Data structure returned by find_isinstance_check representing # information learned from the truth or falsehood of a condition. The # dict maps nodes representing expressions like 'a[0].x' to their # refined types under the assumption that the condition has a # particular truth value. A value of None means that the condition can # never have that truth value. # NB: The keys of this dict are nodes in the original source program, # which are compared by reference equality--effectively, being *the # same* expression of the program, not just two identical expressions # (such as two references to the same variable). TODO: it would # probably be better to have the dict keyed by the nodes' literal_hash # field instead. TypeMap: _TypeAlias = Optional[dict[Expression, Type]] # Keeps track of partial types in a single scope. In fine-grained incremental # mode partial types initially defined at the top level cannot be completed in # a function, and we use the 'is_function' attribute to enforce this. class PartialTypeScope(NamedTuple): map: dict[Var, Context] is_function: bool is_local: bool class TypeChecker(NodeVisitor[None], TypeCheckerSharedApi): """Mypy type checker. Type check mypy source files that have been semantically analyzed. You must create a separate instance for each source file. """ # Are we type checking a stub? is_stub = False # Error message reporter errors: Errors # Utility for generating messages msg: MessageBuilder # Types of type checked nodes. The first item is the "master" type # map that will store the final, exported types. Additional items # are temporary type maps used during type inference, and these # will be eventually popped and either discarded or merged into # the master type map. # # Avoid accessing this directly, but prefer the lookup_type(), # has_type() etc. helpers instead. _type_maps: list[dict[Expression, Type]] # Helper for managing conditional types binder: ConditionalTypeBinder # Helper for type checking expressions _expr_checker: mypy.checkexpr.ExpressionChecker pattern_checker: PatternChecker tscope: Scope scope: CheckerScope # Stack of function return types return_types: list[Type] # Flags; true for dynamically typed functions dynamic_funcs: list[bool] # Stack of collections of variables with partial types partial_types: list[PartialTypeScope] # Vars for which partial type errors are already reported # (to avoid logically duplicate errors with different error context). partial_reported: set[Var] # Short names of Var nodes whose previous inferred type has been widened via assignment. # NOTE: The names might not be unique, they are only for debugging purposes. widened_vars: list[str] globals: SymbolTable modules: dict[str, MypyFile] # Nodes that couldn't be checked because some types weren't available. We'll run # another pass and try these again. deferred_nodes: list[DeferredNode] # Type checking pass number (0 = first pass) pass_num = 0 # Last pass number to take last_pass = DEFAULT_LAST_PASS # Have we deferred the current function? If yes, don't infer additional # types during this pass within the function. current_node_deferred = False # Is this file a typeshed stub? is_typeshed_stub = False options: Options # Used for collecting inferred attribute types so that they can be checked # for consistency. inferred_attribute_types: dict[Var, Type] | None = None # Don't infer partial None types if we are processing assignment from Union no_partial_types: bool = False # The set of all dependencies (suppressed or not) that this module accesses, either # directly or indirectly. module_refs: set[str] # A map from variable nodes to a snapshot of the frame ids of the # frames that were active when the variable was declared. This can # be used to determine nearest common ancestor frame of a variable's # declaration and the current frame, which lets us determine if it # was declared in a different branch of the same `if` statement # (if that frame is a conditional_frame). var_decl_frames: dict[Var, set[int]] # Plugin that provides special type checking rules for specific library # functions such as open(), etc. plugin: Plugin def __init__( self, errors: Errors, modules: dict[str, MypyFile], options: Options, tree: MypyFile, path: str, plugin: Plugin, per_line_checking_time_ns: dict[int, int], ) -> None: """Construct a type checker. Use errors to report type check errors. """ self.errors = errors self.modules = modules self.options = options self.tree = tree self.path = path self.msg = MessageBuilder(errors, modules) self.plugin = plugin self.tscope = Scope() self.scope = CheckerScope(tree) self.binder = ConditionalTypeBinder(options) self.globals = tree.names self.return_types = [] self.dynamic_funcs = [] self.partial_types = [] self.partial_reported = set() self.var_decl_frames = {} self.deferred_nodes = [] self.widened_vars = [] self._type_maps = [{}] self.module_refs = set() self.pass_num = 0 self.current_node_deferred = False self.is_stub = tree.is_stub self.is_typeshed_stub = tree.is_typeshed_file(options) self.inferred_attribute_types = None # If True, process function definitions. If False, don't. This is used # for processing module top levels in fine-grained incremental mode. self.recurse_into_functions = True # This internal flag is used to track whether we a currently type-checking # a final declaration (assignment), so that some errors should be suppressed. # Should not be set manually, use get_final_context/enter_final_context instead. # NOTE: we use the context manager to avoid "threading" an additional `is_final_def` # argument through various `checker` and `checkmember` functions. self._is_final_def = False # This flag is set when we run type-check or attribute access check for the purpose # of giving a note on possibly missing "await". It is used to avoid infinite recursion. self.checking_missing_await = False # While this is True, allow passing an abstract class where Type[T] is expected. # although this is technically unsafe, this is desirable in some context, for # example when type-checking class decorators. self.allow_abstract_call = False # Child checker objects for specific AST node types self._expr_checker = mypy.checkexpr.ExpressionChecker( self, self.msg, self.plugin, per_line_checking_time_ns ) self.pattern_checker = PatternChecker(self, self.msg, self.plugin, options) @property def expr_checker(self) -> mypy.checkexpr.ExpressionChecker: return self._expr_checker @property def type_context(self) -> list[Type | None]: return self._expr_checker.type_context def reset(self) -> None: """Cleanup stale state that might be left over from a typechecking run. This allows us to reuse TypeChecker objects in fine-grained incremental mode. """ # TODO: verify this is still actually worth it over creating new checkers self.partial_reported.clear() self.module_refs.clear() self.binder = ConditionalTypeBinder(self.options) self._type_maps[1:] = [] self._type_maps[0].clear() self.temp_type_map = None self.expr_checker.reset() self.deferred_nodes = [] self.partial_types = [] self.inferred_attribute_types = None self.scope = CheckerScope(self.tree) def check_first_pass(self) -> None: """Type check the entire file, but defer functions with unresolved references. Unresolved references are forward references to variables whose types haven't been inferred yet. They may occur later in the same file or in a different file that's being processed later (usually due to an import cycle). Deferred functions will be processed by check_second_pass(). """ self.recurse_into_functions = True with state.strict_optional_set(self.options.strict_optional): self.errors.set_file( self.path, self.tree.fullname, scope=self.tscope, options=self.options ) with self.tscope.module_scope(self.tree.fullname): with self.enter_partial_types(), self.binder.top_frame_context(): for d in self.tree.defs: if self.binder.is_unreachable(): if not self.should_report_unreachable_issues(): break if not self.is_noop_for_reachability(d): self.msg.unreachable_statement(d) break else: self.accept(d) assert not self.current_node_deferred all_ = self.globals.get("__all__") if all_ is not None and all_.type is not None: all_node = all_.node assert all_node is not None seq_str = self.named_generic_type( "typing.Sequence", [self.named_type("builtins.str")] ) if not is_subtype(all_.type, seq_str): str_seq_s, all_s = format_type_distinctly( seq_str, all_.type, options=self.options ) self.fail( message_registry.ALL_MUST_BE_SEQ_STR.format(str_seq_s, all_s), all_node ) def check_second_pass( self, todo: Sequence[DeferredNode | FineGrainedDeferredNode] | None = None ) -> bool: """Run second or following pass of type checking. This goes through deferred nodes, returning True if there were any. """ self.recurse_into_functions = True with state.strict_optional_set(self.options.strict_optional): if not todo and not self.deferred_nodes: return False self.errors.set_file( self.path, self.tree.fullname, scope=self.tscope, options=self.options ) with self.tscope.module_scope(self.tree.fullname): self.pass_num += 1 if not todo: todo = self.deferred_nodes else: assert not self.deferred_nodes self.deferred_nodes = [] done: set[DeferredNodeType | FineGrainedDeferredNodeType] = set() for node, active_typeinfo in todo: if node in done: continue # This is useful for debugging: # print("XXX in pass %d, class %s, function %s" % # (self.pass_num, type_name, node.fullname or node.name)) done.add(node) with ExitStack() as stack: if active_typeinfo: stack.enter_context(self.tscope.class_scope(active_typeinfo)) stack.enter_context(self.scope.push_class(active_typeinfo)) self.check_partial(node) return True def check_partial(self, node: DeferredNodeType | FineGrainedDeferredNodeType) -> None: self.widened_vars = [] if isinstance(node, MypyFile): self.check_top_level(node) else: self.recurse_into_functions = True with self.binder.top_frame_context(): self.accept(node) def check_top_level(self, node: MypyFile) -> None: """Check only the top-level of a module, skipping function definitions.""" self.recurse_into_functions = False with self.enter_partial_types(): with self.binder.top_frame_context(): for d in node.defs: d.accept(self) assert not self.current_node_deferred # TODO: Handle __all__ def defer_node(self, node: DeferredNodeType, enclosing_class: TypeInfo | None) -> None: """Defer a node for processing during next type-checking pass. Args: node: function/method being deferred enclosing_class: for methods, the class where the method is defined NOTE: this can't handle nested functions/methods. """ # We don't freeze the entire scope since only top-level functions and methods # can be deferred. Only module/class level scope information is needed. # Module-level scope information is preserved in the TypeChecker instance. self.deferred_nodes.append(DeferredNode(node, enclosing_class)) def handle_cannot_determine_type(self, name: str, context: Context) -> None: node = self.scope.top_level_function() if self.pass_num < self.last_pass and isinstance(node, FuncDef): # Don't report an error yet. Just defer. Note that we don't defer # lambdas because they are coupled to the surrounding function # through the binder and the inferred type of the lambda, so it # would get messy. enclosing_class = self.scope.enclosing_class(node) self.defer_node(node, enclosing_class) # Set a marker so that we won't infer additional types in this # function. Any inferred types could be bogus, because there's at # least one type that we don't know. self.current_node_deferred = True else: self.msg.cannot_determine_type(name, context) def accept(self, stmt: Statement) -> None: """Type check a node in the given type context.""" try: stmt.accept(self) except Exception as err: report_internal_error(err, self.errors.file, stmt.line, self.errors, self.options) def accept_loop( self, body: Statement, else_body: Statement | None = None, *, exit_condition: Expression | None = None, on_enter_body: Callable[[], None] | None = None, ) -> None: """Repeatedly type check a loop body until the frame doesn't change.""" # The outer frame accumulates the results of all iterations: with self.binder.frame_context(can_skip=False, conditional_frame=True): # Check for potential decreases in the number of partial types so as not to stop the # iteration too early: partials_old = sum(len(pts.map) for pts in self.partial_types) # Check if assignment widened the inferred type of a variable; in this case we # need to iterate again (we only do one extra iteration, since this could go # on without bound otherwise) widened_old = len(self.widened_vars) # Disable error types that we cannot safely identify in intermediate iteration steps: warn_unreachable = self.options.warn_unreachable warn_redundant = codes.REDUNDANT_EXPR in self.options.enabled_error_codes self.options.warn_unreachable = False self.options.enabled_error_codes.discard(codes.REDUNDANT_EXPR) iter = 1 while True: with self.binder.frame_context(can_skip=True, break_frame=2, continue_frame=1): if on_enter_body is not None: on_enter_body() self.accept(body) partials_new = sum(len(pts.map) for pts in self.partial_types) widened_new = len(self.widened_vars) # Perform multiple iterations if something changed that might affect # inferred types. Also limit the number of iterations. The limits are # somewhat arbitrary, but they were chosen to 1) avoid slowdown from # multiple iterations in common cases and 2) support common, valid use # cases. Limits are needed since otherwise we could infer infinitely # complex types. if ( (partials_new == partials_old) and (not self.binder.last_pop_changed or iter > 3) and (widened_new == widened_old or iter > 1) ): break partials_old = partials_new widened_old = widened_new iter += 1 if iter == 20: raise RuntimeError("Too many iterations when checking a loop") # If necessary, reset the modified options and make up for the postponed error checks: self.options.warn_unreachable = warn_unreachable if warn_redundant: self.options.enabled_error_codes.add(codes.REDUNDANT_EXPR) if warn_unreachable or warn_redundant: with self.binder.frame_context(can_skip=True, break_frame=2, continue_frame=1): if on_enter_body is not None: on_enter_body() self.accept(body) # If exit_condition is set, assume it must be False on exit from the loop: if exit_condition: _, else_map = self.find_isinstance_check(exit_condition) self.push_type_map(else_map) # Check the else body: if else_body: self.accept(else_body) # # Definitions # def visit_overloaded_func_def(self, defn: OverloadedFuncDef) -> None: if not self.recurse_into_functions: return with self.tscope.function_scope(defn): self._visit_overloaded_func_def(defn) def _visit_overloaded_func_def(self, defn: OverloadedFuncDef) -> None: num_abstract = 0 if not defn.items: # In this case we have already complained about none of these being # valid overloads. return if len(defn.items) == 1: self.fail(message_registry.MULTIPLE_OVERLOADS_REQUIRED, defn) if defn.is_property: # HACK: Infer the type of the property. assert isinstance(defn.items[0], Decorator) self.visit_decorator(defn.items[0]) if defn.items[0].var.is_settable_property: # TODO: here and elsewhere we assume setter immediately follows getter. assert isinstance(defn.items[1], Decorator) # Perform a reduced visit just to infer the actual setter type. self.visit_decorator_inner(defn.items[1], skip_first_item=True) setter_type = defn.items[1].var.type # Check if the setter can accept two positional arguments. any_type = AnyType(TypeOfAny.special_form) fallback_setter_type = CallableType( arg_types=[any_type, any_type], arg_kinds=[ARG_POS, ARG_POS], arg_names=[None, None], ret_type=any_type, fallback=self.named_type("builtins.function"), ) if setter_type and not is_subtype(setter_type, fallback_setter_type): self.fail("Invalid property setter signature", defn.items[1].func) setter_type = self.extract_callable_type(setter_type, defn) if not isinstance(setter_type, CallableType) or len(setter_type.arg_types) != 2: # TODO: keep precise type for callables with tricky but valid signatures. setter_type = fallback_setter_type defn.items[0].var.setter_type = setter_type for i, fdef in enumerate(defn.items): assert isinstance(fdef, Decorator) if defn.is_property: assert isinstance(defn.items[0], Decorator) settable = defn.items[0].var.is_settable_property # Do not visit the second time the items we checked above. if (settable and i > 1) or (not settable and i > 0): self.check_func_item(fdef.func, name=fdef.func.name, allow_empty=True) else: # Perform full check for real overloads to infer type of all decorated # overload variants. self.visit_decorator_inner(fdef, allow_empty=True) if fdef.func.abstract_status in (IS_ABSTRACT, IMPLICITLY_ABSTRACT): num_abstract += 1 if num_abstract not in (0, len(defn.items)): self.fail(message_registry.INCONSISTENT_ABSTRACT_OVERLOAD, defn) if defn.impl: defn.impl.accept(self) if not defn.is_property: self.check_overlapping_overloads(defn) if defn.type is None: item_types = [] for item in defn.items: assert isinstance(item, Decorator) item_type = self.extract_callable_type(item.var.type, item) if item_type is not None: item_types.append(item_type) if item_types: defn.type = Overloaded(item_types) elif defn.type is None: # We store the getter type as an overall overload type, as some # code paths are getting property type this way. assert isinstance(defn.items[0], Decorator) var_type = self.extract_callable_type(defn.items[0].var.type, defn) if not isinstance(var_type, CallableType): # Construct a fallback type, invalid types should be already reported. any_type = AnyType(TypeOfAny.special_form) var_type = CallableType( arg_types=[any_type], arg_kinds=[ARG_POS], arg_names=[None], ret_type=any_type, fallback=self.named_type("builtins.function"), ) defn.type = Overloaded([var_type]) # Check override validity after we analyzed current definition. if defn.info: found_method_base_classes = self.check_method_override(defn) if ( defn.is_explicit_override and not found_method_base_classes and found_method_base_classes is not None # If the class has Any fallback, we can't be certain that a method # is really missing - it might come from unfollowed import. and not defn.info.fallback_to_any ): self.msg.no_overridable_method(defn.name, defn) self.check_explicit_override_decorator(defn, found_method_base_classes, defn.impl) self.check_inplace_operator_method(defn) def extract_callable_type(self, inner_type: Type | None, ctx: Context) -> CallableType | None: """Get type as seen by an overload item caller.""" inner_type = get_proper_type(inner_type) outer_type: FunctionLike | None = None if inner_type is None or isinstance(inner_type, AnyType): return None if isinstance(inner_type, TypeVarLikeType): inner_type = get_proper_type(inner_type.upper_bound) if isinstance(inner_type, TypeType): inner_type = get_proper_type( self.expr_checker.analyze_type_type_callee(inner_type.item, ctx) ) if isinstance(inner_type, FunctionLike): outer_type = inner_type elif isinstance(inner_type, Instance): inner_call = get_proper_type( analyze_member_access( name="__call__", typ=inner_type, context=ctx, is_lvalue=False, is_super=False, is_operator=True, original_type=inner_type, chk=self, ) ) if isinstance(inner_call, FunctionLike): outer_type = inner_call elif isinstance(inner_type, UnionType): union_type = make_simplified_union(inner_type.items) if isinstance(union_type, UnionType): items = [] for item in union_type.items: callable_item = self.extract_callable_type(item, ctx) if callable_item is None: break items.append(callable_item) else: joined_type = get_proper_type(join.join_type_list(items)) if isinstance(joined_type, FunctionLike): outer_type = joined_type else: return self.extract_callable_type(union_type, ctx) if outer_type is None: self.msg.not_callable(inner_type, ctx) return None if isinstance(outer_type, Overloaded): return None assert isinstance(outer_type, CallableType) return outer_type def check_overlapping_overloads(self, defn: OverloadedFuncDef) -> None: # At this point we should have set the impl already, and all remaining # items are decorators if self.msg.errors.file in self.msg.errors.ignored_files or ( self.is_typeshed_stub and self.options.test_env ): # This is a little hacky, however, the quadratic check here is really expensive, this # method has no side effects, so we should skip it if we aren't going to report # anything. In some other places we swallow errors in stubs, but this error is very # useful for stubs! return # Compute some info about the implementation (if it exists) for use below impl_type: CallableType | None = None if defn.impl: if isinstance(defn.impl, FuncDef): inner_type: Type | None = defn.impl.type elif isinstance(defn.impl, Decorator): inner_type = defn.impl.var.type else: assert False, "Impl isn't the right type" # This can happen if we've got an overload with a different # decorator or if the implementation is untyped -- we gave up on the types. impl_type = self.extract_callable_type(inner_type, defn.impl) is_descriptor_get = defn.info and defn.name == "__get__" for i, item in enumerate(defn.items): assert isinstance(item, Decorator) sig1 = self.extract_callable_type(item.var.type, item) if sig1 is None: continue for j, item2 in enumerate(defn.items[i + 1 :]): assert isinstance(item2, Decorator) sig2 = self.extract_callable_type(item2.var.type, item2) if sig2 is None: continue if not are_argument_counts_overlapping(sig1, sig2): continue if overload_can_never_match(sig1, sig2): self.msg.overloaded_signature_will_never_match(i + 1, i + j + 2, item2.func) elif not is_descriptor_get: # Note: we force mypy to check overload signatures in strict-optional mode # so we don't incorrectly report errors when a user tries typing an overload # that happens to have a 'if the argument is None' fallback. # # For example, the following is fine in strict-optional mode but would throw # the unsafe overlap error when strict-optional is disabled: # # @overload # def foo(x: None) -> int: ... # @overload # def foo(x: str) -> str: ... # # See Python 2's map function for a concrete example of this kind of overload. current_class = self.scope.active_class() type_vars = current_class.defn.type_vars if current_class else [] with state.strict_optional_set(True): if is_unsafe_overlapping_overload_signatures(sig1, sig2, type_vars): flip_note = ( j == 0 and not is_unsafe_overlapping_overload_signatures( sig2, sig1, type_vars ) and not overload_can_never_match(sig2, sig1) ) self.msg.overloaded_signatures_overlap( i + 1, i + j + 2, flip_note, item.func ) if impl_type is not None: assert defn.impl is not None # This is what we want from implementation, it should accept all arguments # of an overload, but the return types should go the opposite way. if is_callable_compatible( impl_type, sig1, is_compat=is_subtype, is_proper_subtype=False, is_compat_return=lambda l, r: is_subtype(r, l), ): continue # If the above check didn't work, we repeat some key steps in # is_callable_compatible() to give a better error message. # We perform a unification step that's very similar to what # 'is_callable_compatible' does -- the only difference is that # we check and see if the impl_type's return value is a # *supertype* of the overload alternative, not a *subtype*. # # This is to match the direction the implementation's return # needs to be compatible in. if impl_type.variables: impl: CallableType | None = unify_generic_callable( # Normalize both before unifying impl_type.with_unpacked_kwargs(), sig1.with_unpacked_kwargs(), ignore_return=False, return_constraint_direction=SUPERTYPE_OF, ) if impl is None: self.msg.overloaded_signatures_typevar_specific(i + 1, defn.impl) continue else: impl = impl_type # Prevent extra noise from inconsistent use of @classmethod by copying # the first arg from the method being checked against. if sig1.arg_types and defn.info: impl = impl.copy_modified(arg_types=[sig1.arg_types[0]] + impl.arg_types[1:]) # Is the overload alternative's arguments subtypes of the implementation's? if not is_callable_compatible( impl, sig1, is_compat=is_subtype, is_proper_subtype=False, ignore_return=True ): self.msg.overloaded_signatures_arg_specific(i + 1, defn.impl) # Is the overload alternative's return type a subtype of the implementation's? if not ( is_subtype(sig1.ret_type, impl.ret_type) or is_subtype(impl.ret_type, sig1.ret_type) ): self.msg.overloaded_signatures_ret_specific(i + 1, defn.impl) # Here's the scoop about generators and coroutines. # # There are two kinds of generators: classic generators (functions # with `yield` or `yield from` in the body) and coroutines # (functions declared with `async def`). The latter are specified # in PEP 492 and only available in Python >= 3.5. # # Classic generators can be parameterized with three types: # - ty is the Yield type (the type of y in `yield y`) # - tc is the type reCeived by yield (the type of c in `c = yield`). # - tr is the Return type (the type of r in `return r`) # # A classic generator must define a return type that's either # `Generator[ty, tc, tr]`, Iterator[ty], or Iterable[ty] (or # object or Any). If tc/tr are not given, both are None. # # A coroutine must define a return type corresponding to tr; the # other two are unconstrained. The "external" return type (seen # by the caller) is Awaitable[tr]. # # In addition, there's the synthetic type AwaitableGenerator: it # inherits from both Awaitable and Generator and can be used both # in `yield from` and in `await`. This type is set automatically # for functions decorated with `@types.coroutine` or # `@asyncio.coroutine`. Its single parameter corresponds to tr. # # PEP 525 adds a new type, the asynchronous generator, which was # first released in Python 3.6. Async generators are `async def` # functions that can also `yield` values. They can be parameterized # with two types, ty and tc, because they cannot return a value. # # There are several useful methods, each taking a type t and a # flag c indicating whether it's for a generator or coroutine: # # - is_generator_return_type(t, c) returns whether t is a Generator, # Iterator, Iterable (if not c), or Awaitable (if c), or # AwaitableGenerator (regardless of c). # - is_async_generator_return_type(t) returns whether t is an # AsyncGenerator. # - get_generator_yield_type(t, c) returns ty. # - get_generator_receive_type(t, c) returns tc. # - get_generator_return_type(t, c) returns tr. def is_generator_return_type(self, typ: Type, is_coroutine: bool) -> bool: """Is `typ` a valid type for a generator/coroutine? True if `typ` is a *supertype* of Generator or Awaitable. Also true it it's *exactly* AwaitableGenerator (modulo type parameters). """ typ = get_proper_type(typ) if is_coroutine: # This means we're in Python 3.5 or later. at = self.named_generic_type("typing.Awaitable", [AnyType(TypeOfAny.special_form)]) if is_subtype(at, typ): return True else: any_type = AnyType(TypeOfAny.special_form) gt = self.named_generic_type("typing.Generator", [any_type, any_type, any_type]) if is_subtype(gt, typ): return True return isinstance(typ, Instance) and typ.type.fullname == "typing.AwaitableGenerator" def is_async_generator_return_type(self, typ: Type) -> bool: """Is `typ` a valid type for an async generator? True if `typ` is a supertype of AsyncGenerator. """ try: any_type = AnyType(TypeOfAny.special_form) agt = self.named_generic_type("typing.AsyncGenerator", [any_type, any_type]) except KeyError: # we're running on a version of typing that doesn't have AsyncGenerator yet return False return is_subtype(agt, typ) def get_generator_yield_type(self, return_type: Type, is_coroutine: bool) -> Type: """Given the declared return type of a generator (t), return the type it yields (ty).""" return_type = get_proper_type(return_type) if isinstance(return_type, AnyType): return AnyType(TypeOfAny.from_another_any, source_any=return_type) elif isinstance(return_type, UnionType): return make_simplified_union( [self.get_generator_yield_type(item, is_coroutine) for item in return_type.items] ) elif not self.is_generator_return_type( return_type, is_coroutine ) and not self.is_async_generator_return_type(return_type): # If the function doesn't have a proper Generator (or # Awaitable) return type, anything is permissible. return AnyType(TypeOfAny.from_error) elif not isinstance(return_type, Instance): # Same as above, but written as a separate branch so the typechecker can understand. return AnyType(TypeOfAny.from_error) elif return_type.type.fullname == "typing.Awaitable": # Awaitable: ty is Any. return AnyType(TypeOfAny.special_form) elif return_type.args: # AwaitableGenerator, Generator, AsyncGenerator, Iterator, or Iterable; ty is args[0]. ret_type = return_type.args[0] # TODO not best fix, better have dedicated yield token return ret_type else: # If the function's declared supertype of Generator has no type # parameters (i.e. is `object`), then the yielded values can't # be accessed so any type is acceptable. IOW, ty is Any. # (However, see https://github.com/python/mypy/issues/1933) return AnyType(TypeOfAny.special_form) def get_generator_receive_type(self, return_type: Type, is_coroutine: bool) -> Type: """Given a declared generator return type (t), return the type its yield receives (tc).""" return_type = get_proper_type(return_type) if isinstance(return_type, AnyType): return AnyType(TypeOfAny.from_another_any, source_any=return_type) elif isinstance(return_type, UnionType): return make_simplified_union( [self.get_generator_receive_type(item, is_coroutine) for item in return_type.items] ) elif not self.is_generator_return_type( return_type, is_coroutine ) and not self.is_async_generator_return_type(return_type): # If the function doesn't have a proper Generator (or # Awaitable) return type, anything is permissible. return AnyType(TypeOfAny.from_error) elif not isinstance(return_type, Instance): # Same as above, but written as a separate branch so the typechecker can understand. return AnyType(TypeOfAny.from_error) elif return_type.type.fullname == "typing.Awaitable": # Awaitable, AwaitableGenerator: tc is Any. return AnyType(TypeOfAny.special_form) elif ( return_type.type.fullname in ("typing.Generator", "typing.AwaitableGenerator") and len(return_type.args) >= 3 ): # Generator: tc is args[1]. return return_type.args[1] elif return_type.type.fullname == "typing.AsyncGenerator" and len(return_type.args) >= 2: return return_type.args[1] else: # `return_type` is a supertype of Generator, so callers won't be able to send it # values. IOW, tc is None. return NoneType() def get_coroutine_return_type(self, return_type: Type) -> Type: return_type = get_proper_type(return_type) if isinstance(return_type, AnyType): return AnyType(TypeOfAny.from_another_any, source_any=return_type) assert isinstance(return_type, Instance), "Should only be called on coroutine functions." # Note: return type is the 3rd type parameter of Coroutine. return return_type.args[2] def get_generator_return_type(self, return_type: Type, is_coroutine: bool) -> Type: """Given the declared return type of a generator (t), return the type it returns (tr).""" return_type = get_proper_type(return_type) if isinstance(return_type, AnyType): return AnyType(TypeOfAny.from_another_any, source_any=return_type) elif isinstance(return_type, UnionType): return make_simplified_union( [self.get_generator_return_type(item, is_coroutine) for item in return_type.items] ) elif not self.is_generator_return_type(return_type, is_coroutine): # If the function doesn't have a proper Generator (or # Awaitable) return type, anything is permissible. return AnyType(TypeOfAny.from_error) elif not isinstance(return_type, Instance): # Same as above, but written as a separate branch so the typechecker can understand. return AnyType(TypeOfAny.from_error) elif return_type.type.fullname == "typing.Awaitable" and len(return_type.args) == 1: # Awaitable: tr is args[0]. return return_type.args[0] elif ( return_type.type.fullname in ("typing.Generator", "typing.AwaitableGenerator") and len(return_type.args) >= 3 ): # AwaitableGenerator, Generator: tr is args[2]. return return_type.args[2] else: # We have a supertype of Generator (Iterator, Iterable, object) # Treat `Iterator[X]` as a shorthand for `Generator[X, Any, None]`. return NoneType() def visit_func_def(self, defn: FuncDef) -> None: if not self.recurse_into_functions: return with self.tscope.function_scope(defn): self._visit_func_def(defn) def _visit_func_def(self, defn: FuncDef) -> None: """Type check a function definition.""" self.check_func_item(defn, name=defn.name) if defn.info: if not defn.is_overload and not defn.is_decorated: # If the definition is the implementation for an # overload, the legality of the override has already # been typechecked, and decorated methods will be # checked when the decorator is. found_method_base_classes = self.check_method_override(defn) self.check_explicit_override_decorator(defn, found_method_base_classes) self.check_inplace_operator_method(defn) if defn.original_def: # Override previous definition. new_type = self.function_type(defn) self.check_func_def_override(defn, new_type) def check_func_item( self, defn: FuncItem, type_override: CallableType | None = None, name: str | None = None, allow_empty: bool = False, ) -> None: """Type check a function. If type_override is provided, use it as the function type. """ self.dynamic_funcs.append(defn.is_dynamic() and not type_override) enclosing_node_deferred = self.current_node_deferred with self.enter_partial_types(is_function=True): typ = self.function_type(defn) if type_override: typ = type_override.copy_modified(line=typ.line, column=typ.column) if isinstance(typ, CallableType): with self.enter_attribute_inference_context(): self.check_func_def(defn, typ, name, allow_empty) else: raise RuntimeError("Not supported") self.dynamic_funcs.pop() self.current_node_deferred = enclosing_node_deferred if name == "__exit__": self.check__exit__return_type(defn) # TODO: the following logic should move to the dataclasses plugin # https://github.com/python/mypy/issues/15515 if name == "__post_init__": if dataclasses_plugin.is_processed_dataclass(defn.info): dataclasses_plugin.check_post_init(self, defn, defn.info) def check_func_def_override(self, defn: FuncDef, new_type: FunctionLike) -> None: assert defn.original_def is not None if isinstance(defn.original_def, FuncDef): # Function definition overrides function definition. old_type = self.function_type(defn.original_def) if not is_same_type(new_type, old_type): self.msg.incompatible_conditional_function_def(defn, old_type, new_type) else: # Function definition overrides a variable initialized via assignment or a # decorated function. orig_type = defn.original_def.type if orig_type is None: # If other branch is unreachable, we don't type check it and so we might # not have a type for the original definition return if isinstance(orig_type, PartialType): if orig_type.type is None: # Ah this is a partial type. Give it the type of the function. orig_def = defn.original_def if isinstance(orig_def, Decorator): var = orig_def.var else: var = orig_def partial_types = self.find_partial_types(var) if partial_types is not None: var.type = new_type del partial_types[var] else: # Trying to redefine something like partial empty list as function. self.fail(message_registry.INCOMPATIBLE_REDEFINITION, defn) else: name_expr = NameExpr(defn.name) name_expr.node = defn.original_def self.binder.assign_type(name_expr, new_type, orig_type) self.check_subtype( new_type, orig_type, defn, message_registry.INCOMPATIBLE_REDEFINITION, "redefinition with type", "original type", ) @contextmanager def enter_attribute_inference_context(self) -> Iterator[None]: old_types = self.inferred_attribute_types self.inferred_attribute_types = {} yield None self.inferred_attribute_types = old_types def check_func_def( self, defn: FuncItem, typ: CallableType, name: str | None, allow_empty: bool = False ) -> None: """Type check a function definition.""" # Expand type variables with value restrictions to ordinary types. self.check_typevar_defaults(typ.variables) expanded = self.expand_typevars(defn, typ) original_typ = typ for item, typ in expanded: old_binder = self.binder self.binder = ConditionalTypeBinder(self.options) with self.binder.top_frame_context(): defn.expanded.append(item) # We may be checking a function definition or an anonymous # function. In the first case, set up another reference with the # precise type. if isinstance(item, FuncDef): fdef = item # Check if __init__ has an invalid return type. if ( fdef.info and fdef.name in ("__init__", "__init_subclass__") and not isinstance( get_proper_type(typ.ret_type), (NoneType, UninhabitedType) ) and not self.dynamic_funcs[-1] ): self.fail( message_registry.MUST_HAVE_NONE_RETURN_TYPE.format(fdef.name), item ) # Check validity of __new__ signature if fdef.info and fdef.name == "__new__": self.check___new___signature(fdef, typ) self.check_for_missing_annotations(fdef) if self.options.disallow_any_unimported: if fdef.type and isinstance(fdef.type, CallableType): ret_type = fdef.type.ret_type if has_any_from_unimported_type(ret_type): self.msg.unimported_type_becomes_any("Return type", ret_type, fdef) for idx, arg_type in enumerate(fdef.type.arg_types): if has_any_from_unimported_type(arg_type): prefix = f'Argument {idx + 1} to "{fdef.name}"' self.msg.unimported_type_becomes_any(prefix, arg_type, fdef) check_for_explicit_any( fdef.type, self.options, self.is_typeshed_stub, self.msg, context=fdef ) if name: # Special method names if defn.info and self.is_reverse_op_method(name): self.check_reverse_op_method(item, typ, name, defn) elif name in ("__getattr__", "__getattribute__"): self.check_getattr_method(typ, defn, name) elif name == "__setattr__": self.check_setattr_method(typ, defn) # Refuse contravariant return type variable if isinstance(typ.ret_type, TypeVarType): if typ.ret_type.variance == CONTRAVARIANT: self.fail( message_registry.RETURN_TYPE_CANNOT_BE_CONTRAVARIANT, typ.ret_type ) self.check_unbound_return_typevar(typ) elif ( isinstance(original_typ.ret_type, TypeVarType) and original_typ.ret_type.values ): # Since type vars with values are expanded, the return type is changed # to a raw value. This is a hack to get it back. self.check_unbound_return_typevar(original_typ) # Check that Generator functions have the appropriate return type. if defn.is_generator: if defn.is_async_generator: if not self.is_async_generator_return_type(typ.ret_type): self.fail( message_registry.INVALID_RETURN_TYPE_FOR_ASYNC_GENERATOR, typ ) else: if not self.is_generator_return_type(typ.ret_type, defn.is_coroutine): self.fail(message_registry.INVALID_RETURN_TYPE_FOR_GENERATOR, typ) # Fix the type if decorated with `@types.coroutine` or `@asyncio.coroutine`. if defn.is_awaitable_coroutine: # Update the return type to AwaitableGenerator. # (This doesn't exist in typing.py, only in typing.pyi.) t = typ.ret_type c = defn.is_coroutine ty = self.get_generator_yield_type(t, c) tc = self.get_generator_receive_type(t, c) if c: tr = self.get_coroutine_return_type(t) else: tr = self.get_generator_return_type(t, c) ret_type = self.named_generic_type( "typing.AwaitableGenerator", [ty, tc, tr, t] ) typ = typ.copy_modified(ret_type=ret_type) defn.type = typ # Push return type. self.return_types.append(typ.ret_type) with self.scope.push_function(defn): # We temporary push the definition to get the self type as # visible from *inside* of this function/method. ref_type: Type | None = self.scope.active_self_type() if typ.type_is: arg_index = 0 # For methods and classmethods, we want the second parameter if ref_type is not None and (not defn.is_static or defn.name == "__new__"): arg_index = 1 if arg_index < len(typ.arg_types) and not is_subtype( typ.type_is, typ.arg_types[arg_index] ): self.fail( message_registry.NARROWED_TYPE_NOT_SUBTYPE.format( format_type(typ.type_is, self.options), format_type(typ.arg_types[arg_index], self.options), ), item, ) # Store argument types. for i in range(len(typ.arg_types)): arg_type = typ.arg_types[i] if ( isinstance(defn, FuncDef) and ref_type is not None and i == 0 and (not defn.is_static or defn.name == "__new__") and typ.arg_kinds[0] not in [nodes.ARG_STAR, nodes.ARG_STAR2] ): if defn.is_class or defn.name == "__new__": ref_type = mypy.types.TypeType.make_normalized(ref_type) if not is_same_type(arg_type, ref_type): # This level of erasure matches the one in checkmember.check_self_arg(), # better keep these two checks consistent. erased = get_proper_type(erase_typevars(erase_to_bound(arg_type))) if not is_subtype(ref_type, erased, ignore_type_params=True): if ( isinstance(erased, Instance) and erased.type.is_protocol or isinstance(erased, TypeType) and isinstance(erased.item, Instance) and erased.item.type.is_protocol ): # We allow the explicit self-type to be not a supertype of # the current class if it is a protocol. For such cases # the consistency check will be performed at call sites. msg = None elif typ.arg_names[i] in {"self", "cls"}: msg = message_registry.ERASED_SELF_TYPE_NOT_SUPERTYPE.format( erased.str_with_options(self.options), ref_type.str_with_options(self.options), ) else: msg = message_registry.MISSING_OR_INVALID_SELF_TYPE if msg: self.fail(msg, defn) elif isinstance(arg_type, TypeVarType): # Refuse covariant parameter type variables # TODO: check recursively for inner type variables if ( arg_type.variance == COVARIANT and defn.name not in ("__init__", "__new__", "__post_init__") and not is_private(defn.name) # private methods are not inherited ): ctx: Context = arg_type if ctx.line < 0: ctx = typ self.fail(message_registry.FUNCTION_PARAMETER_CANNOT_BE_COVARIANT, ctx) # Need to store arguments again for the expanded item. store_argument_type(item, i, typ, self.named_generic_type) # Type check initialization expressions. body_is_trivial = is_trivial_body(defn.body) self.check_default_args(item, body_is_trivial) # Type check body in a new scope. with self.binder.top_frame_context(): # Copy some type narrowings from an outer function when it seems safe enough # (i.e. we can't find an assignment that might change the type of the # variable afterwards). new_frame: Frame | None = None for frame in old_binder.frames: for key, narrowed_type in frame.types.items(): key_var = extract_var_from_literal_hash(key) if key_var is not None and not self.is_var_redefined_in_outer_context( key_var, defn.line ): # It seems safe to propagate the type narrowing to a nested scope. if new_frame is None: new_frame = self.binder.push_frame() new_frame.types[key] = narrowed_type self.binder.declarations[key] = old_binder.declarations[key] if self.options.allow_redefinition_new and not self.is_stub: # Add formal argument types to the binder. for arg in defn.arguments: # TODO: Add these directly using a fast path (possibly "put") v = arg.variable if v.type is not None: n = NameExpr(v.name) n.node = v self.binder.assign_type(n, v.type, v.type) with self.scope.push_function(defn): # We suppress reachability warnings for empty generator functions # (return; yield) which have a "yield" that's unreachable by definition # since it's only there to promote the function into a generator function. # # We also suppress reachability warnings when we use TypeVars with value # restrictions: we only want to report a warning if a certain statement is # marked as being suppressed in *all* of the expansions, but we currently # have no good way of doing this. # # TODO: Find a way of working around this limitation if _is_empty_generator_function(item) or len(expanded) >= 2: self.binder.suppress_unreachable_warnings() self.accept(item.body) unreachable = self.binder.is_unreachable() if new_frame is not None: self.binder.pop_frame(True, 0) if not unreachable: if defn.is_generator or is_named_instance( self.return_types[-1], "typing.AwaitableGenerator" ): return_type = self.get_generator_return_type( self.return_types[-1], defn.is_coroutine ) elif defn.is_coroutine: return_type = self.get_coroutine_return_type(self.return_types[-1]) else: return_type = self.return_types[-1] return_type = get_proper_type(return_type) allow_empty = allow_empty or self.options.allow_empty_bodies show_error = ( not body_is_trivial or # Allow empty bodies for abstract methods, overloads, in tests and stubs. ( not allow_empty and not ( isinstance(defn, FuncDef) and defn.abstract_status != NOT_ABSTRACT ) and not self.is_stub ) ) # Ignore plugin generated methods, these usually don't need any bodies. if defn.info is not FUNC_NO_INFO and ( defn.name not in defn.info.names or defn.info.names[defn.name].plugin_generated ): show_error = False # Ignore also definitions that appear in `if TYPE_CHECKING: ...` blocks. # These can't be called at runtime anyway (similar to plugin-generated). if isinstance(defn, FuncDef) and defn.is_mypy_only: show_error = False # We want to minimize the fallout from checking empty bodies # that was absent in many mypy versions. if body_is_trivial and is_subtype(NoneType(), return_type): show_error = False may_be_abstract = ( body_is_trivial and defn.info is not FUNC_NO_INFO and defn.info.metaclass_type is not None and defn.info.metaclass_type.type.has_base("abc.ABCMeta") ) if self.options.warn_no_return: if ( not self.current_node_deferred and not isinstance(return_type, (NoneType, AnyType)) and show_error ): # Control flow fell off the end of a function that was # declared to return a non-None type. if isinstance(return_type, UninhabitedType): # This is a NoReturn function msg = message_registry.INVALID_IMPLICIT_RETURN else: msg = message_registry.MISSING_RETURN_STATEMENT if body_is_trivial: msg = msg._replace(code=codes.EMPTY_BODY) self.fail(msg, defn) if may_be_abstract: self.note(message_registry.EMPTY_BODY_ABSTRACT, defn) elif show_error: msg = message_registry.INCOMPATIBLE_RETURN_VALUE_TYPE if body_is_trivial: msg = msg._replace(code=codes.EMPTY_BODY) # similar to code in check_return_stmt if ( not self.check_subtype( subtype_label="implicitly returns", subtype=NoneType(), supertype_label="expected", supertype=return_type, context=defn, msg=msg, ) and may_be_abstract ): self.note(message_registry.EMPTY_BODY_ABSTRACT, defn) self.return_types.pop() self.binder = old_binder def is_var_redefined_in_outer_context(self, v: Var, after_line: int) -> bool: """Can the variable be assigned to at module top level or outer function? Note that this doesn't do a full CFG analysis but uses a line number based heuristic that isn't correct in some (rare) cases. """ if v.is_final: # Final vars are definitely never reassigned. return False outers = self.tscope.outer_functions() if not outers: # Top-level function -- outer context is top level, and we can't reason about # globals return True for outer in outers: if isinstance(outer, FuncDef): if find_last_var_assignment_line(outer.body, v) >= after_line: return True return False def check_unbound_return_typevar(self, typ: CallableType) -> None: """Fails when the return typevar is not defined in arguments.""" if isinstance(typ.ret_type, TypeVarType) and typ.ret_type in typ.variables: arg_type_visitor = CollectArgTypeVarTypes() for argtype in typ.arg_types: argtype.accept(arg_type_visitor) if typ.ret_type not in arg_type_visitor.arg_types: self.fail(message_registry.UNBOUND_TYPEVAR, typ.ret_type, code=TYPE_VAR) upper_bound = get_proper_type(typ.ret_type.upper_bound) if not ( isinstance(upper_bound, Instance) and upper_bound.type.fullname == "builtins.object" ): self.note( "Consider using the upper bound " f"{format_type(typ.ret_type.upper_bound, self.options)} instead", context=typ.ret_type, ) def check_default_args(self, item: FuncItem, body_is_trivial: bool) -> None: for arg in item.arguments: if arg.initializer is None: continue if body_is_trivial and isinstance(arg.initializer, EllipsisExpr): continue name = arg.variable.name msg = "Incompatible default for " if name.startswith("__tuple_arg_"): msg += f"tuple argument {name[12:]}" else: msg += f'argument "{name}"' if ( not self.options.implicit_optional and isinstance(arg.initializer, NameExpr) and arg.initializer.fullname == "builtins.None" ): notes = [ "PEP 484 prohibits implicit Optional. " "Accordingly, mypy has changed its default to no_implicit_optional=True", "Use https://github.com/hauntsaninja/no_implicit_optional to automatically " "upgrade your codebase", ] else: notes = None self.check_simple_assignment( arg.variable.type, arg.initializer, context=arg.initializer, msg=ErrorMessage(msg, code=codes.ASSIGNMENT), lvalue_name="argument", rvalue_name="default", notes=notes, ) def is_forward_op_method(self, method_name: str) -> bool: return method_name in operators.reverse_op_methods def is_reverse_op_method(self, method_name: str) -> bool: return method_name in operators.reverse_op_method_set def check_for_missing_annotations(self, fdef: FuncItem) -> None: # Check for functions with unspecified/not fully specified types. def is_unannotated_any(t: Type) -> bool: if not isinstance(t, ProperType): return False return isinstance(t, AnyType) and t.type_of_any == TypeOfAny.unannotated has_explicit_annotation = isinstance(fdef.type, CallableType) and any( not is_unannotated_any(t) for t in fdef.type.arg_types + [fdef.type.ret_type] ) show_untyped = not self.is_typeshed_stub or self.options.warn_incomplete_stub check_incomplete_defs = self.options.disallow_incomplete_defs and has_explicit_annotation if show_untyped and (self.options.disallow_untyped_defs or check_incomplete_defs): if fdef.type is None and self.options.disallow_untyped_defs: if not fdef.arguments or ( len(fdef.arguments) == 1 and (fdef.arg_names[0] == "self" or fdef.arg_names[0] == "cls") ): self.fail(message_registry.RETURN_TYPE_EXPECTED, fdef) if not has_return_statement(fdef) and not fdef.is_generator: self.note( 'Use "-> None" if function does not return a value', fdef, code=codes.NO_UNTYPED_DEF, ) else: self.fail(message_registry.FUNCTION_TYPE_EXPECTED, fdef) elif isinstance(fdef.type, CallableType): ret_type = get_proper_type(fdef.type.ret_type) if is_unannotated_any(ret_type): self.fail(message_registry.RETURN_TYPE_EXPECTED, fdef) elif fdef.is_generator: if is_unannotated_any( self.get_generator_return_type(ret_type, fdef.is_coroutine) ): self.fail(message_registry.RETURN_TYPE_EXPECTED, fdef) elif fdef.is_coroutine and isinstance(ret_type, Instance): if is_unannotated_any(self.get_coroutine_return_type(ret_type)): self.fail(message_registry.RETURN_TYPE_EXPECTED, fdef) if any(is_unannotated_any(t) for t in fdef.type.arg_types): self.fail(message_registry.ARGUMENT_TYPE_EXPECTED, fdef) def check___new___signature(self, fdef: FuncDef, typ: CallableType) -> None: self_type = fill_typevars_with_any(fdef.info) bound_type = bind_self(typ, self_type, is_classmethod=True) # Check that __new__ (after binding cls) returns an instance # type (or any). if fdef.info.is_metaclass(): # This is a metaclass, so it must return a new unrelated type. self.check_subtype( bound_type.ret_type, self.type_type(), fdef, message_registry.INVALID_NEW_TYPE, "returns", "but must return a subtype of", ) elif not isinstance( get_proper_type(bound_type.ret_type), (AnyType, Instance, TupleType, UninhabitedType) ): self.fail( message_registry.NON_INSTANCE_NEW_TYPE.format( format_type(bound_type.ret_type, self.options) ), fdef, ) else: # And that it returns a subtype of the class self.check_subtype( bound_type.ret_type, self_type, fdef, message_registry.INVALID_NEW_TYPE, "returns", "but must return a subtype of", ) def check_reverse_op_method( self, defn: FuncItem, reverse_type: CallableType, reverse_name: str, context: Context ) -> None: """Check a reverse operator method such as __radd__.""" # Decides whether it's worth calling check_overlapping_op_methods(). # This used to check for some very obscure scenario. It now # just decides whether it's worth calling # check_overlapping_op_methods(). assert defn.info # First check for a valid signature method_type = CallableType( [AnyType(TypeOfAny.special_form), AnyType(TypeOfAny.special_form)], [nodes.ARG_POS, nodes.ARG_POS], [None, None], AnyType(TypeOfAny.special_form), self.named_type("builtins.function"), ) if not is_subtype(reverse_type, method_type): self.msg.invalid_signature(reverse_type, context) return if reverse_name in ("__eq__", "__ne__"): # These are defined for all objects => can't cause trouble. return # With 'Any' or 'object' return type we are happy, since any possible # return value is valid. ret_type = get_proper_type(reverse_type.ret_type) if isinstance(ret_type, AnyType): return if isinstance(ret_type, Instance): if ret_type.type.fullname == "builtins.object": return if reverse_type.arg_kinds[0] == ARG_STAR: reverse_type = reverse_type.copy_modified( arg_types=[reverse_type.arg_types[0]] * 2, arg_kinds=[ARG_POS] * 2, arg_names=[reverse_type.arg_names[0], "_"], ) assert len(reverse_type.arg_types) >= 2 forward_name = operators.normal_from_reverse_op[reverse_name] forward_inst = get_proper_type(reverse_type.arg_types[1]) if isinstance(forward_inst, TypeVarType): forward_inst = get_proper_type(forward_inst.upper_bound) elif isinstance(forward_inst, TupleType): forward_inst = tuple_fallback(forward_inst) elif isinstance(forward_inst, (FunctionLike, TypedDictType, LiteralType)): forward_inst = forward_inst.fallback if isinstance(forward_inst, TypeType): item = forward_inst.item if isinstance(item, Instance): opt_meta = item.type.metaclass_type if opt_meta is not None: forward_inst = opt_meta def has_readable_member(typ: UnionType | Instance, name: str) -> bool: # TODO: Deal with attributes of TupleType etc. if isinstance(typ, Instance): return typ.type.has_readable_member(name) return all( (isinstance(x, UnionType) and has_readable_member(x, name)) or (isinstance(x, Instance) and x.type.has_readable_member(name)) for x in get_proper_types(typ.relevant_items()) ) if not ( isinstance(forward_inst, (Instance, UnionType)) and has_readable_member(forward_inst, forward_name) ): return forward_base = reverse_type.arg_types[1] forward_type = self.expr_checker.analyze_external_member_access( forward_name, forward_base, context=defn ) self.check_overlapping_op_methods( reverse_type, reverse_name, defn.info, forward_type, forward_name, forward_base, context=defn, ) def check_overlapping_op_methods( self, reverse_type: CallableType, reverse_name: str, reverse_class: TypeInfo, forward_type: Type, forward_name: str, forward_base: Type, context: Context, ) -> None: """Check for overlapping method and reverse method signatures. This function assumes that: - The reverse method has valid argument count and kinds. - If the reverse operator method accepts some argument of type X, the forward operator method also belong to class X. For example, if we have the reverse operator `A.__radd__(B)`, then the corresponding forward operator must have the type `B.__add__(...)`. """ # Note: Suppose we have two operator methods "A.__rOP__(B) -> R1" and # "B.__OP__(C) -> R2". We check if these two methods are unsafely overlapping # by using the following algorithm: # # 1. Rewrite "B.__OP__(C) -> R1" to "temp1(B, C) -> R1" # # 2. Rewrite "A.__rOP__(B) -> R2" to "temp2(B, A) -> R2" # # 3. Treat temp1 and temp2 as if they were both variants in the same # overloaded function. (This mirrors how the Python runtime calls # operator methods: we first try __OP__, then __rOP__.) # # If the first signature is unsafely overlapping with the second, # report an error. # # 4. However, if temp1 shadows temp2 (e.g. the __rOP__ method can never # be called), do NOT report an error. # # This behavior deviates from how we handle overloads -- many of the # modules in typeshed seem to define __OP__ methods that shadow the # corresponding __rOP__ method. # # Note: we do not attempt to handle unsafe overlaps related to multiple # inheritance. (This is consistent with how we handle overloads: we also # do not try checking unsafe overlaps due to multiple inheritance there.) for forward_item in flatten_nested_unions([forward_type]): forward_item = get_proper_type(forward_item) if isinstance(forward_item, CallableType): if self.is_unsafe_overlapping_op(forward_item, forward_base, reverse_type): self.msg.operator_method_signatures_overlap( reverse_class, reverse_name, forward_base, forward_name, context ) elif isinstance(forward_item, Overloaded): for item in forward_item.items: if self.is_unsafe_overlapping_op(item, forward_base, reverse_type): self.msg.operator_method_signatures_overlap( reverse_class, reverse_name, forward_base, forward_name, context ) elif not isinstance(forward_item, AnyType): self.msg.forward_operator_not_callable(forward_name, context) def is_unsafe_overlapping_op( self, forward_item: CallableType, forward_base: Type, reverse_type: CallableType ) -> bool: # TODO: check argument kinds? if len(forward_item.arg_types) < 1: # Not a valid operator method -- can't succeed anyway. return False # Erase the type if necessary to make sure we don't have a single # TypeVar in forward_tweaked. (Having a function signature containing # just a single TypeVar can lead to unpredictable behavior.) forward_base_erased = forward_base if isinstance(forward_base, TypeVarType): forward_base_erased = erase_to_bound(forward_base) # Construct normalized function signatures corresponding to the # operator methods. The first argument is the left operand and the # second operand is the right argument -- we switch the order of # the arguments of the reverse method. # TODO: this manipulation is dangerous if callables are generic. # Shuffling arguments between callables can create meaningless types. forward_tweaked = forward_item.copy_modified( arg_types=[forward_base_erased, forward_item.arg_types[0]], arg_kinds=[nodes.ARG_POS] * 2, arg_names=[None] * 2, ) reverse_tweaked = reverse_type.copy_modified( arg_types=[reverse_type.arg_types[1], reverse_type.arg_types[0]], arg_kinds=[nodes.ARG_POS] * 2, arg_names=[None] * 2, ) reverse_base_erased = reverse_type.arg_types[0] if isinstance(reverse_base_erased, TypeVarType): reverse_base_erased = erase_to_bound(reverse_base_erased) if is_same_type(reverse_base_erased, forward_base_erased): return False elif is_subtype(reverse_base_erased, forward_base_erased): first = reverse_tweaked second = forward_tweaked else: first = forward_tweaked second = reverse_tweaked current_class = self.scope.active_class() type_vars = current_class.defn.type_vars if current_class else [] return is_unsafe_overlapping_overload_signatures( first, second, type_vars, partial_only=False ) def check_inplace_operator_method(self, defn: FuncBase) -> None: """Check an inplace operator method such as __iadd__. They cannot arbitrarily overlap with __add__. """ method = defn.name if method not in operators.inplace_operator_methods: return typ = bind_self(self.function_type(defn)) cls = defn.info other_method = "__" + method[3:] if cls.has_readable_member(other_method): instance = fill_typevars(cls) typ2 = get_proper_type( self.expr_checker.analyze_external_member_access(other_method, instance, defn) ) fail = False if isinstance(typ2, FunctionLike): if not is_more_general_arg_prefix(typ, typ2): fail = True else: # TODO overloads fail = True if fail: self.msg.signatures_incompatible(method, other_method, defn) def check_getattr_method(self, typ: Type, context: Context, name: str) -> None: if len(self.scope.stack) == 1: # module scope if name == "__getattribute__": self.fail(message_registry.MODULE_LEVEL_GETATTRIBUTE, context) return # __getattr__ is fine at the module level as of Python 3.7 (PEP 562). We could # show an error for Python < 3.7, but that would be annoying in code that supports # both 3.7 and older versions. method_type = CallableType( [self.named_type("builtins.str")], [nodes.ARG_POS], [None], AnyType(TypeOfAny.special_form), self.named_type("builtins.function"), ) elif self.scope.active_class(): method_type = CallableType( [AnyType(TypeOfAny.special_form), self.named_type("builtins.str")], [nodes.ARG_POS, nodes.ARG_POS], [None, None], AnyType(TypeOfAny.special_form), self.named_type("builtins.function"), ) else: return if not is_subtype(typ, method_type): self.msg.invalid_signature_for_special_method(typ, context, name) def check_setattr_method(self, typ: Type, context: Context) -> None: if not self.scope.active_class(): return method_type = CallableType( [ AnyType(TypeOfAny.special_form), self.named_type("builtins.str"), AnyType(TypeOfAny.special_form), ], [nodes.ARG_POS, nodes.ARG_POS, nodes.ARG_POS], [None, None, None], NoneType(), self.named_type("builtins.function"), ) if not is_subtype(typ, method_type): self.msg.invalid_signature_for_special_method(typ, context, "__setattr__") def check_slots_definition(self, typ: Type, context: Context) -> None: """Check the type of __slots__.""" str_type = self.named_type("builtins.str") expected_type = UnionType( [str_type, self.named_generic_type("typing.Iterable", [str_type])] ) self.check_subtype( typ, expected_type, context, message_registry.INVALID_TYPE_FOR_SLOTS, "actual type", "expected type", code=codes.ASSIGNMENT, ) def check_match_args(self, var: Var, typ: Type, context: Context) -> None: """Check that __match_args__ contains literal strings""" if not self.scope.active_class(): return typ = get_proper_type(typ) if not isinstance(typ, TupleType) or not all( is_string_literal(item) for item in typ.items ): self.msg.note( "__match_args__ must be a tuple containing string literals for checking " "of match statements to work", context, code=codes.LITERAL_REQ, ) def expand_typevars( self, defn: FuncItem, typ: CallableType ) -> list[tuple[FuncItem, CallableType]]: # TODO use generator subst: list[list[tuple[TypeVarId, Type]]] = [] tvars = list(typ.variables) or [] if defn.info: # Class type variables tvars += defn.info.defn.type_vars or [] for tvar in tvars: if isinstance(tvar, TypeVarType) and tvar.values: subst.append([(tvar.id, value) for value in tvar.values]) # Make a copy of the function to check for each combination of # value restricted type variables. (Except when running mypyc, # where we need one canonical version of the function.) if subst and not (self.options.mypyc or self.options.inspections): result: list[tuple[FuncItem, CallableType]] = [] for substitutions in itertools.product(*subst): mapping = dict(substitutions) result.append((expand_func(defn, mapping), expand_type(typ, mapping))) return result else: return [(defn, typ)] def check_explicit_override_decorator( self, defn: FuncDef | OverloadedFuncDef, found_method_base_classes: list[TypeInfo] | None, context: Context | None = None, ) -> None: plugin_generated = False if defn.info and (node := defn.info.get(defn.name)) and node.plugin_generated: # Do not report issues for plugin generated nodes, # they can't realistically use `@override` for their methods. plugin_generated = True if ( not plugin_generated and found_method_base_classes and not defn.is_explicit_override and defn.name not in ("__init__", "__new__") and not is_private(defn.name) ): self.msg.explicit_override_decorator_missing( defn.name, found_method_base_classes[0].fullname, context or defn ) def check_method_override( self, defn: FuncDef | OverloadedFuncDef | Decorator ) -> list[TypeInfo] | None: """Check if function definition is compatible with base classes. This may defer the method if a signature is not available in at least one base class. Return ``None`` if that happens. Return a list of base classes which contain an attribute with the method name. """ # Check against definitions in base classes. check_override_compatibility = ( defn.name not in ("__init__", "__new__", "__init_subclass__", "__post_init__") and (self.options.check_untyped_defs or not defn.is_dynamic()) and ( # don't check override for synthesized __replace__ methods from dataclasses defn.name != "__replace__" or defn.info.metadata.get("dataclass_tag") is None ) ) found_method_base_classes: list[TypeInfo] = [] for base in defn.info.mro[1:]: result = self.check_method_or_accessor_override_for_base( defn, base, check_override_compatibility ) if result is None: # Node was deferred, we will have another attempt later. return None if result: found_method_base_classes.append(base) return found_method_base_classes def check_method_or_accessor_override_for_base( self, defn: FuncDef | OverloadedFuncDef | Decorator, base: TypeInfo, check_override_compatibility: bool, ) -> bool | None: """Check if method definition is compatible with a base class. Return ``None`` if the node was deferred because one of the corresponding superclass nodes is not ready. Return ``True`` if an attribute with the method name was found in the base class. """ found_base_method = False if base: name = defn.name base_attr = base.names.get(name) if base_attr: # First, check if we override a final (always an error, even with Any types). if is_final_node(base_attr.node) and not is_private(name): self.msg.cant_override_final(name, base.name, defn) # Second, final can't override anything writeable independently of types. if defn.is_final: self.check_if_final_var_override_writable(name, base_attr.node, defn) found_base_method = True if check_override_compatibility: # Check compatibility of the override signature # (__init__, __new__, __init_subclass__ are special). if self.check_method_override_for_base_with_name(defn, name, base): return None if name in operators.inplace_operator_methods: # Figure out the name of the corresponding operator method. method = "__" + name[3:] # An inplace operator method such as __iadd__ might not be # always introduced safely if a base class defined __add__. # TODO can't come up with an example where this is # necessary; now it's "just in case" if self.check_method_override_for_base_with_name(defn, method, base): return None return found_base_method def check_setter_type_override(self, defn: OverloadedFuncDef, base: TypeInfo) -> None: """Check override of a setter type of a mutable attribute. Currently, this should be only called when either base node or the current node is a custom settable property (i.e. where setter type is different from getter type). Note that this check is contravariant. """ typ, _ = self.node_type_from_base(defn.name, defn.info, defn, setter_type=True) original_type, _ = self.node_type_from_base(defn.name, base, defn, setter_type=True) # The caller should handle deferrals. assert typ is not None and original_type is not None if not is_subtype(original_type, typ): self.msg.incompatible_setter_override(defn.items[1], typ, original_type, base) def check_method_override_for_base_with_name( self, defn: FuncDef | OverloadedFuncDef | Decorator, name: str, base: TypeInfo ) -> bool: """Check if overriding an attribute `name` of `base` with `defn` is valid. Return True if the supertype node was not analysed yet, and `defn` was deferred. """ base_attr = base.names.get(name) if not base_attr: return False # The name of the method is defined in the base class. # Point errors at the 'def' line (important for backward compatibility # of type ignores). if not isinstance(defn, Decorator): context = defn else: context = defn.func # Construct the type of the overriding method. if isinstance(defn, (FuncDef, OverloadedFuncDef)): override_class_or_static = defn.is_class or defn.is_static else: override_class_or_static = defn.func.is_class or defn.func.is_static typ, _ = self.node_type_from_base(defn.name, defn.info, defn) assert typ is not None original_node = base_attr.node # `original_type` can be partial if (e.g.) it is originally an # instance variable from an `__init__` block that becomes deferred. supertype_ready = True original_type, _ = self.node_type_from_base(name, base, defn) if original_type is None: supertype_ready = False if self.pass_num < self.last_pass: # If there are passes left, defer this node until next pass, # otherwise try reconstructing the method type from available information. # For consistency, defer an enclosing top-level function (if any). top_level = self.scope.top_level_function() if isinstance(top_level, FuncDef): self.defer_node(top_level, self.scope.enclosing_class(top_level)) else: # Specify enclosing class explicitly, as we check type override before # entering e.g. decorators or overloads. self.defer_node(defn, defn.info) return True elif isinstance(original_node, (FuncDef, OverloadedFuncDef)): original_type = self.function_type(original_node) elif isinstance(original_node, Decorator): original_type = self.function_type(original_node.func) elif isinstance(original_node, Var): # Super type can define method as an attribute. # See https://github.com/python/mypy/issues/10134 # We also check that sometimes `original_node.type` is None. # This is the case when we use something like `__hash__ = None`. if original_node.type is not None: original_type = get_proper_type(original_node.type) else: original_type = NoneType() else: # Will always fail to typecheck below, since we know the node is a method original_type = NoneType() always_allow_covariant = False if is_settable_property(defn) and ( is_settable_property(original_node) or isinstance(original_node, Var) ): if is_custom_settable_property(defn) or (is_custom_settable_property(original_node)): # Unlike with getter, where we try to construct some fallback type in case of # deferral during last_pass, we can't make meaningful setter checks if the # supertype is not known precisely. if supertype_ready: always_allow_covariant = True self.check_setter_type_override(defn, base) if isinstance(original_node, (FuncDef, OverloadedFuncDef)): original_class_or_static = original_node.is_class or original_node.is_static elif isinstance(original_node, Decorator): fdef = original_node.func original_class_or_static = fdef.is_class or fdef.is_static else: original_class_or_static = False # a variable can't be class or static typ = get_proper_type(typ) original_type = get_proper_type(original_type) if ( is_property(defn) and isinstance(original_node, Var) and not original_node.is_final and (not original_node.is_property or original_node.is_settable_property) and isinstance(defn, Decorator) ): # We only give an error where no other similar errors will be given. if not isinstance(original_type, AnyType): self.msg.fail( "Cannot override writeable attribute with read-only property", # Give an error on function line to match old behaviour. defn.func, code=codes.OVERRIDE, ) if isinstance(original_type, AnyType) or isinstance(typ, AnyType): pass elif isinstance(original_type, FunctionLike) and isinstance(typ, FunctionLike): # Check that the types are compatible. ok = self.check_override( typ, original_type, defn.name, name, base.name, original_class_or_static, override_class_or_static, context, ) # Check if this override is covariant. if ( ok and original_node and codes.MUTABLE_OVERRIDE in self.options.enabled_error_codes and self.is_writable_attribute(original_node) and not always_allow_covariant and not is_subtype(original_type, typ, ignore_pos_arg_names=True) ): base_str, override_str = format_type_distinctly( original_type, typ, options=self.options ) msg = message_registry.COVARIANT_OVERRIDE_OF_MUTABLE_ATTRIBUTE.with_additional_msg( f' (base class "{base.name}" defined the type as {base_str},' f" override has type {override_str})" ) self.fail(msg, context) elif isinstance(original_type, UnionType) and any( is_subtype(typ, orig_typ, ignore_pos_arg_names=True) for orig_typ in original_type.items ): # This method is a subtype of at least one union variant. if ( original_node and codes.MUTABLE_OVERRIDE in self.options.enabled_error_codes and self.is_writable_attribute(original_node) and not always_allow_covariant ): # Covariant override of mutable attribute. base_str, override_str = format_type_distinctly( original_type, typ, options=self.options ) msg = message_registry.COVARIANT_OVERRIDE_OF_MUTABLE_ATTRIBUTE.with_additional_msg( f' (base class "{base.name}" defined the type as {base_str},' f" override has type {override_str})" ) self.fail(msg, context) elif is_equivalent(original_type, typ): # Assume invariance for a non-callable attribute here. Note # that this doesn't affect read-only properties which can have # covariant overrides. pass elif ( original_node and (not self.is_writable_attribute(original_node) or always_allow_covariant) and is_subtype(typ, original_type) ): # If the attribute is read-only, allow covariance pass else: self.msg.signature_incompatible_with_supertype( defn.name, name, base.name, context, original=original_type, override=typ ) return False def get_op_other_domain(self, tp: FunctionLike) -> Type | None: if isinstance(tp, CallableType): if tp.arg_kinds and tp.arg_kinds[0] == ARG_POS: # For generic methods, domain comparison is tricky, as a first # approximation erase all remaining type variables. return erase_typevars(tp.arg_types[0], {v.id for v in tp.variables}) return None elif isinstance(tp, Overloaded): raw_items = [self.get_op_other_domain(it) for it in tp.items] items = [it for it in raw_items if it] if items: return make_simplified_union(items) return None else: assert False, "Need to check all FunctionLike subtypes here" def check_override( self, override: FunctionLike, original: FunctionLike, name: str, name_in_super: str, supertype: str, original_class_or_static: bool, override_class_or_static: bool, node: Context, ) -> bool: """Check a method override with given signatures. Arguments: override: The signature of the overriding method. original: The signature of the original supertype method. name: The name of the overriding method. Used primarily for generating error messages. name_in_super: The name of the overridden in the superclass. Used for generating error messages only. supertype: The name of the supertype. original_class_or_static: Indicates whether the original method (from the superclass) is either a class method or a static method. override_class_or_static: Indicates whether the overriding method (from the subclass) is either a class method or a static method. node: Context node. """ # Use boolean variable to clarify code. fail = False op_method_wider_note = False if not is_subtype(override, original, ignore_pos_arg_names=True): fail = True elif isinstance(override, Overloaded) and self.is_forward_op_method(name): # Operator method overrides cannot extend the domain, as # this could be unsafe with reverse operator methods. original_domain = self.get_op_other_domain(original) override_domain = self.get_op_other_domain(override) if ( original_domain and override_domain and not is_subtype(override_domain, original_domain) ): fail = True op_method_wider_note = True if isinstance(override, FunctionLike): if original_class_or_static and not override_class_or_static: fail = True elif isinstance(original, CallableType) and isinstance(override, CallableType): if original.type_guard is not None and override.type_guard is None: fail = True if original.type_is is not None and override.type_is is None: fail = True if is_private(name): fail = False if fail: emitted_msg = False offset_arguments = isinstance(override, CallableType) and override.unpack_kwargs # Normalize signatures, so we get better diagnostics. if isinstance(override, (CallableType, Overloaded)): override = override.with_unpacked_kwargs() if isinstance(original, (CallableType, Overloaded)): original = original.with_unpacked_kwargs() if ( isinstance(override, CallableType) and isinstance(original, CallableType) and len(override.arg_types) == len(original.arg_types) and override.min_args == original.min_args ): # Give more detailed messages for the common case of both # signatures having the same number of arguments and no # overloads. # override might have its own generic function type # variables. If an argument or return type of override # does not have the correct subtyping relationship # with the original type even after these variables # are erased, then it is definitely an incompatibility. override_ids = override.type_var_ids() type_name = None if isinstance(override.definition, FuncDef): type_name = override.definition.info.name def erase_override(t: Type) -> Type: return erase_typevars(t, ids_to_erase=override_ids) for i, (sub_kind, super_kind) in enumerate( zip(override.arg_kinds, original.arg_kinds) ): if sub_kind.is_positional() and super_kind.is_positional(): override_arg_type = override.arg_types[i] original_arg_type = original.arg_types[i] elif sub_kind.is_named() and super_kind.is_named() and not offset_arguments: arg_name = override.arg_names[i] if arg_name in original.arg_names: override_arg_type = override.arg_types[i] original_i = original.arg_names.index(arg_name) original_arg_type = original.arg_types[original_i] else: continue else: continue if not is_subtype(original_arg_type, erase_override(override_arg_type)): context: Context = node if isinstance(node, FuncDef) and not node.is_property: arg_node = node.arguments[i + len(override.bound_args)] if arg_node.line != -1: context = arg_node self.msg.argument_incompatible_with_supertype( i + 1, name, type_name, name_in_super, original_arg_type, supertype, context, secondary_context=node, ) emitted_msg = True if not is_subtype(erase_override(override.ret_type), original.ret_type): self.msg.return_type_incompatible_with_supertype( name, name_in_super, supertype, original.ret_type, override.ret_type, node ) emitted_msg = True elif isinstance(override, Overloaded) and isinstance(original, Overloaded): # Give a more detailed message in the case where the user is trying to # override an overload, and the subclass's overload is plausible, except # that the order of the variants are wrong. # # For example, if the parent defines the overload f(int) -> int and f(str) -> str # (in that order), and if the child swaps the two and does f(str) -> str and # f(int) -> int order = [] for child_variant in override.items: for i, parent_variant in enumerate(original.items): if is_subtype(child_variant, parent_variant): order.append(i) break if len(order) == len(original.items) and order != sorted(order): self.msg.overload_signature_incompatible_with_supertype( name, name_in_super, supertype, node ) emitted_msg = True if not emitted_msg: # Fall back to generic incompatibility message. self.msg.signature_incompatible_with_supertype( name, name_in_super, supertype, node, original=original, override=override ) if op_method_wider_note: self.note( "Overloaded operator methods can't have wider argument types in overrides", node, code=codes.OVERRIDE, ) return not fail def check__exit__return_type(self, defn: FuncItem) -> None: """Generate error if the return type of __exit__ is problematic. If __exit__ always returns False but the return type is declared as bool, mypy thinks that a with statement may "swallow" exceptions even though this is not the case, resulting in invalid reachability inference. """ if not defn.type or not isinstance(defn.type, CallableType): return ret_type = get_proper_type(defn.type.ret_type) if not has_bool_item(ret_type): return returns = all_return_statements(defn) if not returns: return if all( isinstance(ret.expr, NameExpr) and ret.expr.fullname == "builtins.False" for ret in returns ): self.msg.incorrect__exit__return(defn) def visit_class_def(self, defn: ClassDef) -> None: """Type check a class definition.""" typ = defn.info for base in typ.mro[1:]: if base.is_final: self.fail(message_registry.CANNOT_INHERIT_FROM_FINAL.format(base.name), defn) with self.tscope.class_scope(defn.info), self.enter_partial_types(is_class=True): old_binder = self.binder self.binder = ConditionalTypeBinder(self.options) with self.binder.top_frame_context(): with self.scope.push_class(defn.info): self.accept(defn.defs) self.binder = old_binder if not (defn.info.typeddict_type or defn.info.tuple_type or defn.info.is_enum): # If it is not a normal class (not a special form) check class keywords. self.check_init_subclass(defn) if not defn.has_incompatible_baseclass: # Otherwise we've already found errors; more errors are not useful self.check_multiple_inheritance(typ) self.check_metaclass_compatibility(typ) self.check_final_deletable(typ) if defn.decorators: sig: Type = type_object_type(defn.info, self.named_type) # Decorators are applied in reverse order. for decorator in reversed(defn.decorators): if isinstance(decorator, CallExpr) and isinstance( decorator.analyzed, PromoteExpr ): # _promote is a special type checking related construct. continue dec = self.expr_checker.accept(decorator) temp = self.temp_node(sig, context=decorator) fullname = None if isinstance(decorator, RefExpr): fullname = decorator.fullname or None # TODO: Figure out how to have clearer error messages. # (e.g. "class decorator must be a function that accepts a type." old_allow_abstract_call = self.allow_abstract_call self.allow_abstract_call = True sig, _ = self.expr_checker.check_call( dec, [temp], [nodes.ARG_POS], defn, callable_name=fullname ) self.allow_abstract_call = old_allow_abstract_call # TODO: Apply the sig to the actual TypeInfo so we can handle decorators # that completely swap out the type. (e.g. Callable[[Type[A]], Type[B]]) if typ.defn.type_vars and typ.defn.type_args is None: for base_inst in typ.bases: for base_tvar, base_decl_tvar in zip( base_inst.args, base_inst.type.defn.type_vars ): if ( isinstance(base_tvar, TypeVarType) and base_tvar.variance != INVARIANT and isinstance(base_decl_tvar, TypeVarType) and base_decl_tvar.variance != base_tvar.variance ): self.fail( f'Variance of TypeVar "{base_tvar.name}" incompatible ' "with variance in parent type", context=defn, code=codes.TYPE_VAR, ) if typ.defn.type_vars: self.check_typevar_defaults(typ.defn.type_vars) if typ.is_protocol and typ.defn.type_vars: self.check_protocol_variance(defn) if not defn.has_incompatible_baseclass and defn.info.is_enum: self.check_enum(defn) infer_class_variances(defn.info) def check_final_deletable(self, typ: TypeInfo) -> None: # These checks are only for mypyc. Only perform some checks that are easier # to implement here than in mypyc. for attr in typ.deletable_attributes: node = typ.names.get(attr) if node and isinstance(node.node, Var) and node.node.is_final: self.fail(message_registry.CANNOT_MAKE_DELETABLE_FINAL, node.node) def check_init_subclass(self, defn: ClassDef) -> None: """Check that keywords in a class definition are valid arguments for __init_subclass__(). In this example: 1 class Base: 2 def __init_subclass__(cls, thing: int): 3 pass 4 class Child(Base, thing=5): 5 def __init_subclass__(cls): 6 pass 7 Child() Base.__init_subclass__(thing=5) is called at line 4. This is what we simulate here. Child.__init_subclass__ is never called. """ if defn.info.metaclass_type and defn.info.metaclass_type.type.fullname not in ( "builtins.type", "abc.ABCMeta", ): # We can't safely check situations when both __init_subclass__ and a custom # metaclass are present. return # At runtime, only Base.__init_subclass__ will be called, so # we skip the current class itself. for base in defn.info.mro[1:]: if "__init_subclass__" not in base.names: continue name_expr = NameExpr(defn.name) name_expr.node = base callee = MemberExpr(name_expr, "__init_subclass__") args = list(defn.keywords.values()) arg_names: list[str | None] = list(defn.keywords.keys()) # 'metaclass' keyword is consumed by the rest of the type machinery, # and is never passed to __init_subclass__ implementations if "metaclass" in arg_names: idx = arg_names.index("metaclass") arg_names.pop(idx) args.pop(idx) arg_kinds = [ARG_NAMED] * len(args) call_expr = CallExpr(callee, args, arg_kinds, arg_names) call_expr.line = defn.line call_expr.column = defn.column call_expr.end_line = defn.end_line self.expr_checker.accept(call_expr, allow_none_return=True, always_allow_any=True) # We are only interested in the first Base having __init_subclass__, # all other bases have already been checked. break def check_typevar_defaults(self, tvars: Sequence[TypeVarLikeType]) -> None: for tv in tvars: if not (isinstance(tv, TypeVarType) and tv.has_default()): continue if not is_subtype(tv.default, tv.upper_bound): self.fail("TypeVar default must be a subtype of the bound type", tv) if tv.values and not any(tv.default == value for value in tv.values): self.fail("TypeVar default must be one of the constraint types", tv) def check_enum(self, defn: ClassDef) -> None: assert defn.info.is_enum if defn.info.fullname not in ENUM_BASES and "__members__" in defn.info.names: sym = defn.info.names["__members__"] if isinstance(sym.node, Var) and sym.node.has_explicit_value: # `__members__` will always be overwritten by `Enum` and is considered # read-only so we disallow assigning a value to it self.fail(message_registry.ENUM_MEMBERS_ATTR_WILL_BE_OVERRIDDEN, sym.node) for base in defn.info.mro[1:-1]: # we don't need self and `object` if base.is_enum and base.fullname not in ENUM_BASES: self.check_final_enum(defn, base) if self.is_stub and self.tree.fullname not in {"enum", "_typeshed"}: if not defn.info.enum_members: self.fail( f'Detected enum "{defn.info.fullname}" in a type stub with zero members. ' "There is a chance this is due to a recent change in the semantics of " "enum membership. If so, use `member = value` to mark an enum member, " "instead of `member: type`", defn, ) self.note( "See https://typing.readthedocs.io/en/latest/spec/enums.html#defining-members", defn, ) self.check_enum_bases(defn) self.check_enum_new(defn) def check_final_enum(self, defn: ClassDef, base: TypeInfo) -> None: if base.enum_members: self.fail(f'Cannot extend enum with existing members: "{base.name}"', defn) def is_final_enum_value(self, sym: SymbolTableNode) -> bool: if isinstance(sym.node, (FuncBase, Decorator)): return False # A method is fine if not isinstance(sym.node, Var): return True # Can be a class or anything else # Now, only `Var` is left, we need to check: # 1. Private name like in `__prop = 1` # 2. Dunder name like `__hash__ = some_hasher` # 3. Sunder name like `_order_ = 'a, b, c'` # 4. If it is a method / descriptor like in `method = classmethod(func)` if ( is_private(sym.node.name) or is_dunder(sym.node.name) or is_sunder(sym.node.name) # TODO: make sure that `x = @class/staticmethod(func)` # and `x = property(prop)` both work correctly. # Now they are incorrectly counted as enum members. or isinstance(get_proper_type(sym.node.type), FunctionLike) ): return False return self.is_stub or sym.node.has_explicit_value def check_enum_bases(self, defn: ClassDef) -> None: """ Non-enum mixins cannot appear after enum bases; this is disallowed at runtime: class Foo: ... class Bar(enum.Enum, Foo): ... But any number of enum mixins can appear in a class definition (even if multiple enum bases define __new__). So this is fine: class Foo(enum.Enum): def __new__(cls, val): ... class Bar(enum.Enum): def __new__(cls, val): ... class Baz(int, Foo, Bar, enum.Flag): ... """ enum_base: Instance | None = None for base in defn.info.bases: if enum_base is None and base.type.is_enum: enum_base = base continue elif enum_base is not None and not base.type.is_enum: self.fail( f'No non-enum mixin classes are allowed after "{enum_base.str_with_options(self.options)}"', defn, ) break def check_enum_new(self, defn: ClassDef) -> None: def has_new_method(info: TypeInfo) -> bool: new_method = info.get("__new__") return bool( new_method and new_method.node and new_method.node.fullname != "builtins.object.__new__" ) has_new = False for base in defn.info.bases: candidate = False if base.type.is_enum: # If we have an `Enum`, then we need to check all its bases. candidate = any(not b.is_enum and has_new_method(b) for b in base.type.mro[1:-1]) else: candidate = has_new_method(base.type) if candidate and has_new: self.fail( "Only a single data type mixin is allowed for Enum subtypes, " 'found extra "{}"'.format(base.str_with_options(self.options)), defn, ) elif candidate: has_new = True def check_protocol_variance(self, defn: ClassDef) -> None: """Check that protocol definition is compatible with declared variances of type variables. Note that we also prohibit declaring protocol classes as invariant if they are actually covariant/contravariant, since this may break transitivity of subtyping, see PEP 544. """ if defn.type_args is not None: # Using new-style syntax (PEP 695), so variance will be inferred return info = defn.info object_type = Instance(info.mro[-1], []) tvars = info.defn.type_vars for i, tvar in enumerate(tvars): if not isinstance(tvar, TypeVarType): # Variance of TypeVarTuple and ParamSpec is underspecified by PEPs. continue up_args: list[Type] = [ object_type if i == j else AnyType(TypeOfAny.special_form) for j, _ in enumerate(tvars) ] down_args: list[Type] = [ UninhabitedType() if i == j else AnyType(TypeOfAny.special_form) for j, _ in enumerate(tvars) ] up, down = Instance(info, up_args), Instance(info, down_args) # TODO: add advanced variance checks for recursive protocols if is_subtype(down, up, ignore_declared_variance=True): expected = COVARIANT elif is_subtype(up, down, ignore_declared_variance=True): expected = CONTRAVARIANT else: expected = INVARIANT if expected != tvar.variance: self.msg.bad_proto_variance(tvar.variance, tvar.name, expected, defn) def check_multiple_inheritance(self, typ: TypeInfo) -> None: """Check for multiple inheritance related errors.""" if len(typ.bases) <= 1: # No multiple inheritance. return # Verify that inherited attributes are compatible. mro = typ.mro[1:] all_names = {name for base in mro for name in base.names} for name in sorted(all_names - typ.names.keys()): # Sort for reproducible message order. # Attributes defined in both the type and base are skipped. # Normal checks for attribute compatibility should catch any problems elsewhere. if is_private(name): continue # Compare the first base defining a name with the rest. # Remaining bases may not be pairwise compatible as the first base provides # the used definition. i, base = next((i, base) for i, base in enumerate(mro) if name in base.names) for base2 in mro[i + 1 :]: if name in base2.names and base2 not in base.mro: self.check_compatibility(name, base, base2, typ) def determine_type_of_member(self, sym: SymbolTableNode) -> Type | None: # TODO: this duplicates both checkmember.py and analyze_ref_expr(), delete. if sym.type is not None: return sym.type if isinstance(sym.node, SYMBOL_FUNCBASE_TYPES): return self.function_type(sym.node) if isinstance(sym.node, TypeInfo): if sym.node.typeddict_type: # We special-case TypedDict, because they don't define any constructor. return self.expr_checker.typeddict_callable(sym.node) else: return type_object_type(sym.node, self.named_type) if isinstance(sym.node, TypeVarExpr): # Use of TypeVars is rejected in an expression/runtime context, so # we don't need to check supertype compatibility for them. return AnyType(TypeOfAny.special_form) if isinstance(sym.node, TypeAlias): with self.msg.filter_errors(): # Suppress any errors, they will be given when analyzing the corresponding node. # Here we may have incorrect options and location context. return self.expr_checker.alias_type_in_runtime_context(sym.node, ctx=sym.node) return None def check_compatibility( self, name: str, base1: TypeInfo, base2: TypeInfo, ctx: TypeInfo ) -> None: """Check if attribute name in base1 is compatible with base2 in multiple inheritance. Assume base1 comes before base2 in the MRO, and that base1 and base2 don't have a direct subclass relationship (i.e., the compatibility requirement only derives from multiple inheritance). This check verifies that a definition taken from base1 (and mapped to the current class ctx), is type compatible with the definition taken from base2 (also mapped), so that unsafe subclassing like this can be detected: class A(Generic[T]): def foo(self, x: T) -> None: ... class B: def foo(self, x: str) -> None: ... class C(B, A[int]): ... # this is unsafe because... x: A[int] = C() x.foo # ...runtime type is (str) -> None, while static type is (int) -> None """ if name in ("__init__", "__new__", "__init_subclass__"): # __init__ and friends can be incompatible -- it's a special case. return first = base1.names[name] second = base2.names[name] # Specify current_class explicitly as this function is called after leaving the class. first_type, _ = self.node_type_from_base(name, base1, ctx, current_class=ctx) second_type, _ = self.node_type_from_base(name, base2, ctx, current_class=ctx) # TODO: use more principled logic to decide is_subtype() vs is_equivalent(). # We should rely on mutability of superclass node, not on types being Callable. # (in particular handle settable properties with setter type different from getter). p_first_type = get_proper_type(first_type) p_second_type = get_proper_type(second_type) if isinstance(p_first_type, FunctionLike) and isinstance(p_second_type, FunctionLike): if p_first_type.is_type_obj() and p_second_type.is_type_obj(): # For class objects only check the subtype relationship of the classes, # since we allow incompatible overrides of '__init__'/'__new__' ok = is_subtype( left=fill_typevars_with_any(p_first_type.type_object()), right=fill_typevars_with_any(p_second_type.type_object()), ) else: assert first_type and second_type ok = is_subtype(first_type, second_type, ignore_pos_arg_names=True) elif first_type and second_type: if second.node is not None and not self.is_writable_attribute(second.node): ok = is_subtype(first_type, second_type) else: ok = is_equivalent(first_type, second_type) if ok: if ( first.node and second.node and self.is_writable_attribute(second.node) and is_property(first.node) and isinstance(first.node, Decorator) and not isinstance(p_second_type, AnyType) ): self.msg.fail( f'Cannot override writeable attribute "{name}" in base "{base2.name}"' f' with read-only property in base "{base1.name}"', ctx, code=codes.OVERRIDE, ) else: if first_type is None: self.msg.cannot_determine_type_in_base(name, base1.name, ctx) if second_type is None: self.msg.cannot_determine_type_in_base(name, base2.name, ctx) ok = True # Final attributes can never be overridden, but can override # non-final read-only attributes. if is_final_node(second.node) and not is_private(name): self.msg.cant_override_final(name, base2.name, ctx) if is_final_node(first.node): self.check_if_final_var_override_writable(name, second.node, ctx) # Some attributes like __slots__ and __deletable__ are special, and the type can # vary across class hierarchy. if isinstance(second.node, Var) and second.node.allow_incompatible_override: ok = True if not ok: self.msg.base_class_definitions_incompatible(name, base1, base2, ctx) def check_metaclass_compatibility(self, typ: TypeInfo) -> None: """Ensures that metaclasses of all parent types are compatible.""" if ( typ.is_metaclass() or typ.is_protocol or typ.is_named_tuple or typ.is_enum or typ.typeddict_type is not None ): return # Reasonable exceptions from this check metaclasses = [ entry.metaclass_type for entry in typ.mro[1:-1] if entry.metaclass_type and not is_named_instance(entry.metaclass_type, "builtins.type") ] if not metaclasses: return if typ.metaclass_type is not None and all( is_subtype(typ.metaclass_type, meta) for meta in metaclasses ): return self.fail( "Metaclass conflict: the metaclass of a derived class must be " "a (non-strict) subclass of the metaclasses of all its bases", typ, ) def visit_import_from(self, node: ImportFrom) -> None: for name, _ in node.names: if (sym := self.globals.get(name)) is not None: self.warn_deprecated(sym.node, node) self.check_import(node) def visit_import_all(self, node: ImportAll) -> None: self.check_import(node) def visit_import(self, node: Import) -> None: self.check_import(node) def check_import(self, node: ImportBase) -> None: for assign in node.assignments: lvalue = assign.lvalues[0] lvalue_type, _, __ = self.check_lvalue(lvalue) if lvalue_type is None: # TODO: This is broken. lvalue_type = AnyType(TypeOfAny.special_form) assert isinstance(assign.rvalue, NameExpr) message = message_registry.INCOMPATIBLE_IMPORT_OF.format(assign.rvalue.name) self.check_simple_assignment( lvalue_type, assign.rvalue, node, msg=message, lvalue_name="local name", rvalue_name="imported name", ) # # Statements # def visit_block(self, b: Block) -> None: if b.is_unreachable: # This block was marked as being unreachable during semantic analysis. # It turns out any blocks marked in this way are *intentionally* marked # as unreachable -- so we don't display an error. self.binder.unreachable() return for s in b.body: if self.binder.is_unreachable(): if not self.should_report_unreachable_issues(): break if not self.is_noop_for_reachability(s): self.msg.unreachable_statement(s) break else: self.accept(s) def should_report_unreachable_issues(self) -> bool: return ( self.in_checked_function() and self.options.warn_unreachable and not self.current_node_deferred and not self.binder.is_unreachable_warning_suppressed() ) def is_noop_for_reachability(self, s: Statement) -> bool: """Returns 'true' if the given statement either throws an error of some kind or is a no-op. We use this function while handling the '--warn-unreachable' flag. When that flag is present, we normally report an error on any unreachable statement. But if that statement is just something like a 'pass' or a just-in-case 'assert False', reporting an error would be annoying. """ if isinstance(s, AssertStmt) and is_false_literal(s.expr): return True elif isinstance(s, (RaiseStmt, PassStmt)): return True elif isinstance(s, ExpressionStmt): if isinstance(s.expr, EllipsisExpr): return True elif isinstance(s.expr, CallExpr): with self.expr_checker.msg.filter_errors(): typ = get_proper_type( self.expr_checker.accept( s.expr, allow_none_return=True, always_allow_any=True ) ) if isinstance(typ, UninhabitedType): return True return False def visit_assignment_stmt(self, s: AssignmentStmt) -> None: """Type check an assignment statement. Handle all kinds of assignment statements (simple, indexed, multiple). """ # Avoid type checking type aliases in stubs to avoid false # positives about modern type syntax available in stubs such # as X | Y. if not (s.is_alias_def and self.is_stub): with self.enter_final_context(s.is_final_def): self.check_assignment(s.lvalues[-1], s.rvalue, s.type is None, s.new_syntax) if s.is_alias_def: self.check_type_alias_rvalue(s) if ( s.type is not None and self.options.disallow_any_unimported and has_any_from_unimported_type(s.type) ): if isinstance(s.lvalues[-1], TupleExpr): # This is a multiple assignment. Instead of figuring out which type is problematic, # give a generic error message. self.msg.unimported_type_becomes_any( "A type on this line", AnyType(TypeOfAny.special_form), s ) else: self.msg.unimported_type_becomes_any("Type of variable", s.type, s) check_for_explicit_any(s.type, self.options, self.is_typeshed_stub, self.msg, context=s) if len(s.lvalues) > 1: # Chained assignment (e.g. x = y = ...). # Make sure that rvalue type will not be reinferred. if not self.has_type(s.rvalue): self.expr_checker.accept(s.rvalue) rvalue = self.temp_node(self.lookup_type(s.rvalue), s) for lv in s.lvalues[:-1]: with self.enter_final_context(s.is_final_def): self.check_assignment(lv, rvalue, s.type is None) self.check_final(s) if ( s.is_final_def and s.type and not has_no_typevars(s.type) and self.scope.active_class() is not None ): self.fail(message_registry.DEPENDENT_FINAL_IN_CLASS_BODY, s) if s.unanalyzed_type and not self.in_checked_function(): self.msg.annotation_in_unchecked_function(context=s) def check_type_alias_rvalue(self, s: AssignmentStmt) -> None: with self.msg.filter_errors(): alias_type = self.expr_checker.accept(s.rvalue) self.store_type(s.lvalues[-1], alias_type) def check_assignment( self, lvalue: Lvalue, rvalue: Expression, infer_lvalue_type: bool = True, new_syntax: bool = False, ) -> None: """Type check a single assignment: lvalue = rvalue.""" if isinstance(lvalue, (TupleExpr, ListExpr)): self.check_assignment_to_multiple_lvalues( lvalue.items, rvalue, rvalue, infer_lvalue_type ) else: self.try_infer_partial_generic_type_from_assignment(lvalue, rvalue, "=") lvalue_type, index_lvalue, inferred = self.check_lvalue(lvalue, rvalue) # If we're assigning to __getattr__ or similar methods, check that the signature is # valid. if isinstance(lvalue, NameExpr) and lvalue.node: name = lvalue.node.name if name in ("__setattr__", "__getattribute__", "__getattr__"): # If an explicit type is given, use that. if lvalue_type: signature = lvalue_type else: signature = self.expr_checker.accept(rvalue) if signature: if name == "__setattr__": self.check_setattr_method(signature, lvalue) else: self.check_getattr_method(signature, lvalue, name) if name == "__slots__": typ = lvalue_type or self.expr_checker.accept(rvalue) self.check_slots_definition(typ, lvalue) if name == "__match_args__" and inferred is not None: typ = self.expr_checker.accept(rvalue) self.check_match_args(inferred, typ, lvalue) if name == "__post_init__": active_class = self.scope.active_class() if active_class and dataclasses_plugin.is_processed_dataclass(active_class): self.fail(message_registry.DATACLASS_POST_INIT_MUST_BE_A_FUNCTION, rvalue) if isinstance(lvalue, MemberExpr) and lvalue.name == "__match_args__": self.fail(message_registry.CANNOT_MODIFY_MATCH_ARGS, lvalue) if lvalue_type: if isinstance(lvalue_type, PartialType) and lvalue_type.type is None: # Try to infer a proper type for a variable with a partial None type. rvalue_type = self.expr_checker.accept(rvalue) if isinstance(get_proper_type(rvalue_type), NoneType): # This doesn't actually provide any additional information -- multiple # None initializers preserve the partial None type. return var = lvalue_type.var if is_valid_inferred_type( rvalue_type, self.options, is_lvalue_final=var.is_final ): partial_types = self.find_partial_types(var) if partial_types is not None: if not self.current_node_deferred: # Partial type can't be final, so strip any literal values. rvalue_type = remove_instance_last_known_values(rvalue_type) inferred_type = make_simplified_union([rvalue_type, NoneType()]) self.set_inferred_type(var, lvalue, inferred_type) else: var.type = None del partial_types[var] lvalue_type = var.type else: # Try to infer a partial type. No need to check the return value, as # an error will be reported elsewhere. self.infer_partial_type(lvalue_type.var, lvalue, rvalue_type) elif ( is_literal_none(rvalue) and isinstance(lvalue, NameExpr) and isinstance(lvalue.node, Var) and lvalue.node.is_initialized_in_class and not new_syntax ): # Allow None's to be assigned to class variables with non-Optional types. rvalue_type = lvalue_type elif ( isinstance(lvalue, MemberExpr) and lvalue.kind is None ): # Ignore member access to modules instance_type = self.expr_checker.accept(lvalue.expr) rvalue_type, lvalue_type, infer_lvalue_type = self.check_member_assignment( lvalue, instance_type, lvalue_type, rvalue, context=rvalue ) else: # Hacky special case for assigning a literal None # to a variable defined in a previous if # branch. When we detect this, we'll go back and # make the type optional. This is somewhat # unpleasant, and a generalization of this would # be an improvement! if ( not self.options.allow_redefinition_new and is_literal_none(rvalue) and isinstance(lvalue, NameExpr) and lvalue.kind == LDEF and isinstance(lvalue.node, Var) and lvalue.node.type and lvalue.node in self.var_decl_frames and not isinstance(get_proper_type(lvalue_type), AnyType) ): decl_frame_map = self.var_decl_frames[lvalue.node] # Check if the nearest common ancestor frame for the definition site # and the current site is the enclosing frame of an if/elif/else block. has_if_ancestor = False for frame in reversed(self.binder.frames): if frame.id in decl_frame_map: has_if_ancestor = frame.conditional_frame break if has_if_ancestor: lvalue_type = make_optional_type(lvalue_type) self.set_inferred_type(lvalue.node, lvalue, lvalue_type) rvalue_type, lvalue_type = self.check_simple_assignment( lvalue_type, rvalue, context=rvalue, inferred=inferred, lvalue=lvalue ) # The above call may update inferred variable type. Prevent further # inference. inferred = None # Special case: only non-abstract non-protocol classes can be assigned to # variables with explicit type Type[A], where A is protocol or abstract. p_rvalue_type = get_proper_type(rvalue_type) p_lvalue_type = get_proper_type(lvalue_type) if ( isinstance(p_rvalue_type, FunctionLike) and p_rvalue_type.is_type_obj() and ( p_rvalue_type.type_object().is_abstract or p_rvalue_type.type_object().is_protocol ) and isinstance(p_lvalue_type, TypeType) and isinstance(p_lvalue_type.item, Instance) and ( p_lvalue_type.item.type.is_abstract or p_lvalue_type.item.type.is_protocol ) ): self.msg.concrete_only_assign(p_lvalue_type, rvalue) return if rvalue_type and infer_lvalue_type and not isinstance(lvalue_type, PartialType): # Don't use type binder for definitions of special forms, like named tuples. if not (isinstance(lvalue, NameExpr) and lvalue.is_special_form): self.binder.assign_type(lvalue, rvalue_type, lvalue_type) if ( isinstance(lvalue, NameExpr) and isinstance(lvalue.node, Var) and lvalue.node.is_inferred and lvalue.node.is_index_var and lvalue_type is not None ): lvalue.node.type = remove_instance_last_known_values(lvalue_type) elif self.options.allow_redefinition_new and lvalue_type is not None: # TODO: Can we use put() here? self.binder.assign_type(lvalue, lvalue_type, lvalue_type) elif index_lvalue: self.check_indexed_assignment(index_lvalue, rvalue, lvalue) if inferred: type_context = self.get_variable_type_context(inferred, rvalue) rvalue_type = self.expr_checker.accept(rvalue, type_context=type_context) if not ( inferred.is_final or inferred.is_index_var or (isinstance(lvalue, NameExpr) and lvalue.name == "__match_args__") ): rvalue_type = remove_instance_last_known_values(rvalue_type) self.infer_variable_type(inferred, lvalue, rvalue_type, rvalue) self.check_assignment_to_slots(lvalue) if isinstance(lvalue, RefExpr) and not ( isinstance(lvalue, NameExpr) and lvalue.name == "__match_args__" ): # We check override here at the end after storing the inferred type, since # override check will try to access the current attribute via symbol tables # (like a regular attribute access). self.check_compatibility_all_supers(lvalue, rvalue) # (type, operator) tuples for augmented assignments supported with partial types partial_type_augmented_ops: Final = {("builtins.list", "+"), ("builtins.set", "|")} def get_variable_type_context(self, inferred: Var, rvalue: Expression) -> Type | None: type_contexts = [] if inferred.info: for base in inferred.info.mro[1:]: if inferred.name not in base.names: continue # For inference within class body, get supertype attribute as it would look on # a class object for lambdas overriding methods, etc. base_node = base.names[inferred.name].node base_type, _ = self.node_type_from_base( inferred.name, base, inferred, is_class=is_method(base_node) or isinstance(base_node, Var) and not is_instance_var(base_node), ) if ( base_type and not (isinstance(base_node, Var) and base_node.invalid_partial_type) and not isinstance(base_type, PartialType) ): type_contexts.append(base_type) # Use most derived supertype as type context if available. if not type_contexts: return None candidate = type_contexts[0] for other in type_contexts: if is_proper_subtype(other, candidate): candidate = other elif not is_subtype(candidate, other): # Multiple incompatible candidates, cannot use any of them as context. return None return candidate def try_infer_partial_generic_type_from_assignment( self, lvalue: Lvalue, rvalue: Expression, op: str ) -> None: """Try to infer a precise type for partial generic type from assignment. 'op' is '=' for normal assignment and a binary operator ('+', ...) for augmented assignment. Example where this happens: x = [] if foo(): x = [1] # Infer List[int] as type of 'x' """ var = None if ( isinstance(lvalue, NameExpr) and isinstance(lvalue.node, Var) and isinstance(lvalue.node.type, PartialType) ): var = lvalue.node elif isinstance(lvalue, MemberExpr): var = self.expr_checker.get_partial_self_var(lvalue) if var is not None: typ = var.type assert isinstance(typ, PartialType) if typ.type is None: return # Return if this is an unsupported augmented assignment. if op != "=" and (typ.type.fullname, op) not in self.partial_type_augmented_ops: return # TODO: some logic here duplicates the None partial type counterpart # inlined in check_assignment(), see #8043. partial_types = self.find_partial_types(var) if partial_types is None: return rvalue_type = self.expr_checker.accept(rvalue) rvalue_type = get_proper_type(rvalue_type) if isinstance(rvalue_type, Instance): if rvalue_type.type == typ.type and is_valid_inferred_type( rvalue_type, self.options ): var.type = rvalue_type del partial_types[var] elif isinstance(rvalue_type, AnyType): var.type = fill_typevars_with_any(typ.type) del partial_types[var] def check_compatibility_all_supers(self, lvalue: RefExpr, rvalue: Expression) -> None: lvalue_node = lvalue.node # Check if we are a class variable with at least one base class if ( isinstance(lvalue_node, Var) # If we have explicit annotation, there is no point in checking the override # for each assignment, so we check only for the first one. # TODO: for some reason annotated attributes on self are stored as inferred vars. and ( lvalue_node.line == lvalue.line or lvalue_node.is_inferred and not lvalue_node.explicit_self_type ) and lvalue.kind in (MDEF, None) # None for Vars defined via self and len(lvalue_node.info.bases) > 0 ): for base in lvalue_node.info.mro[1:]: tnode = base.names.get(lvalue_node.name) if tnode is not None: if not self.check_compatibility_classvar_super(lvalue_node, base, tnode.node): # Show only one error per variable break if not self.check_compatibility_final_super(lvalue_node, base, tnode.node): # Show only one error per variable break direct_bases = lvalue_node.info.direct_base_classes() last_immediate_base = direct_bases[-1] if direct_bases else None # The historical behavior for inferred vars was to compare rvalue type against # the type declared in a superclass. To preserve this behavior, we temporarily # store the rvalue type on the variable. actual_lvalue_type = None if lvalue_node.is_inferred and not lvalue_node.explicit_self_type: rvalue_type = self.expr_checker.accept(rvalue, lvalue_node.type) actual_lvalue_type = lvalue_node.type lvalue_node.type = rvalue_type lvalue_type, _ = self.node_type_from_base(lvalue_node.name, lvalue_node.info, lvalue) if lvalue_node.is_inferred and not lvalue_node.explicit_self_type: lvalue_node.type = actual_lvalue_type if not lvalue_type: return for base in lvalue_node.info.mro[1:]: # The type of "__slots__" and some other attributes usually doesn't need to # be compatible with a base class. We'll still check the type of "__slots__" # against "object" as an exception. if lvalue_node.allow_incompatible_override and not ( lvalue_node.name == "__slots__" and base.fullname == "builtins.object" ): continue if is_private(lvalue_node.name): continue base_type, base_node = self.node_type_from_base(lvalue_node.name, base, lvalue) custom_setter = is_custom_settable_property(base_node) if isinstance(base_type, PartialType): base_type = None if base_type: assert base_node is not None if not self.check_compatibility_super( lvalue_type, rvalue, base, base_type, base_node, always_allow_covariant=custom_setter, ): # Only show one error per variable; even if other # base classes are also incompatible return if lvalue_type and custom_setter: base_type, _ = self.node_type_from_base( lvalue_node.name, base, lvalue, setter_type=True ) # Setter type for a custom property must be ready if # the getter type is ready. assert base_type is not None if not is_subtype(base_type, lvalue_type): self.msg.incompatible_setter_override( lvalue, lvalue_type, base_type, base ) return if base is last_immediate_base: # At this point, the attribute was found to be compatible with all # immediate parents. break def check_compatibility_super( self, compare_type: Type, rvalue: Expression, base: TypeInfo, base_type: Type, base_node: Node, always_allow_covariant: bool, ) -> bool: # TODO: check __set__() type override for custom descriptors. # TODO: for descriptors check also class object access override. ok = self.check_subtype( compare_type, base_type, rvalue, message_registry.INCOMPATIBLE_TYPES_IN_ASSIGNMENT, "expression has type", f'base class "{base.name}" defined the type as', ) if ( ok and codes.MUTABLE_OVERRIDE in self.options.enabled_error_codes and self.is_writable_attribute(base_node) and not always_allow_covariant ): ok = self.check_subtype( base_type, compare_type, rvalue, message_registry.COVARIANT_OVERRIDE_OF_MUTABLE_ATTRIBUTE, f'base class "{base.name}" defined the type as', "expression has type", ) return ok def node_type_from_base( self, name: str, base: TypeInfo, context: Context, *, setter_type: bool = False, is_class: bool = False, current_class: TypeInfo | None = None, ) -> tuple[Type | None, SymbolNode | None]: """Find a type for a name in base class. Return the type found and the corresponding node defining the name or None for both if the name is not defined in base or the node type is not known (yet). The type returned is already properly mapped/bound to the subclass. If setter_type is True, return setter types for settable properties (otherwise the getter type is returned). """ base_node = base.names.get(name) # TODO: defer current node if the superclass node is not ready. if ( not base_node or isinstance(base_node.node, (Var, Decorator)) and not base_node.type or isinstance(base_node.type, PartialType) and base_node.type.type is not None ): return None, None if current_class is None: self_type = self.scope.current_self_type() else: self_type = fill_typevars(current_class) assert self_type is not None, "Internal error: base lookup outside class" if isinstance(self_type, TupleType): instance = tuple_fallback(self_type) else: instance = self_type mx = MemberContext( is_lvalue=setter_type, is_super=False, is_operator=mypy.checkexpr.is_operator_method(name), original_type=self_type, context=context, chk=self, suppress_errors=True, ) # TODO: we should not filter "cannot determine type" errors here. with self.msg.filter_errors(filter_deprecated=True): if is_class: fallback = instance.type.metaclass_type or mx.named_type("builtins.type") base_type = analyze_class_attribute_access( instance, name, mx, mcs_fallback=fallback, override_info=base ) else: base_type = analyze_instance_member_access(name, instance, mx, base) return base_type, base_node.node def check_compatibility_classvar_super( self, node: Var, base: TypeInfo, base_node: Node | None ) -> bool: if not isinstance(base_node, Var): return True if node.is_classvar and not base_node.is_classvar: self.fail(message_registry.CANNOT_OVERRIDE_INSTANCE_VAR.format(base.name), node) return False elif not node.is_classvar and base_node.is_classvar: self.fail(message_registry.CANNOT_OVERRIDE_CLASS_VAR.format(base.name), node) return False return True def check_compatibility_final_super( self, node: Var, base: TypeInfo, base_node: Node | None ) -> bool: """Check if an assignment overrides a final attribute in a base class. This only checks situations where either a node in base class is not a variable but a final method, or where override is explicitly declared as final. In these cases we give a more detailed error message. In addition, we check that a final variable doesn't override writeable attribute, which is not safe. Other situations are checked in `check_final()`. """ if not isinstance(base_node, (Var, FuncBase, Decorator)): return True if is_private(node.name): return True if base_node.is_final and (node.is_final or not isinstance(base_node, Var)): # Give this error only for explicit override attempt with `Final`, or # if we are overriding a final method with variable. # Other override attempts will be flagged as assignment to constant # in `check_final()`. self.msg.cant_override_final(node.name, base.name, node) return False if node.is_final: if base.fullname in ENUM_BASES or node.name in ENUM_SPECIAL_PROPS: return True self.check_if_final_var_override_writable(node.name, base_node, node) return True def check_if_final_var_override_writable( self, name: str, base_node: Node | None, ctx: Context ) -> None: """Check that a final variable doesn't override writeable attribute. This is done to prevent situations like this: class C: attr = 1 class D(C): attr: Final = 2 x: C = D() x.attr = 3 # Oops! """ writable = True if base_node: writable = self.is_writable_attribute(base_node) if writable: self.msg.final_cant_override_writable(name, ctx) def get_final_context(self) -> bool: """Check whether we a currently checking a final declaration.""" return self._is_final_def @contextmanager def enter_final_context(self, is_final_def: bool) -> Iterator[None]: """Store whether the current checked assignment is a final declaration.""" old_ctx = self._is_final_def self._is_final_def = is_final_def try: yield finally: self._is_final_def = old_ctx def check_final(self, s: AssignmentStmt | OperatorAssignmentStmt | AssignmentExpr) -> None: """Check if this assignment does not assign to a final attribute. This function performs the check only for name assignments at module and class scope. The assignments to `obj.attr` and `Cls.attr` are checked in checkmember.py. """ if isinstance(s, AssignmentStmt): lvs = self.flatten_lvalues(s.lvalues) elif isinstance(s, AssignmentExpr): lvs = [s.target] else: lvs = [s.lvalue] is_final_decl = s.is_final_def if isinstance(s, AssignmentStmt) else False if is_final_decl and (active_class := self.scope.active_class()): lv = lvs[0] assert isinstance(lv, RefExpr) if lv.node is not None: assert isinstance(lv.node, Var) if ( lv.node.final_unset_in_class and not lv.node.final_set_in_init and not self.is_stub # It is OK to skip initializer in stub files. and # Avoid extra error messages, if there is no type in Final[...], # then we already reported the error about missing r.h.s. isinstance(s, AssignmentStmt) and s.type is not None # Avoid extra error message for NamedTuples, # they were reported during semanal and not active_class.is_named_tuple ): self.msg.final_without_value(s) for lv in lvs: if isinstance(lv, RefExpr) and isinstance(lv.node, Var): name = lv.node.name cls = self.scope.active_class() if cls is not None: # These additional checks exist to give more error messages # even if the final attribute was overridden with a new symbol # (which is itself an error)... for base in cls.mro[1:]: sym = base.names.get(name) # We only give this error if base node is variable, # overriding final method will be caught in # `check_compatibility_final_super()`. if sym and isinstance(sym.node, Var): if sym.node.is_final and not is_final_decl: self.msg.cant_assign_to_final(name, sym.node.info is None, s) # ...but only once break if lv.node.is_final and not is_final_decl: self.msg.cant_assign_to_final(name, lv.node.info is None, s) def check_assignment_to_slots(self, lvalue: Lvalue) -> None: if not isinstance(lvalue, MemberExpr): return inst = get_proper_type(self.expr_checker.accept(lvalue.expr)) if not isinstance(inst, Instance): return if inst.type.slots is None: return # Slots do not exist, we can allow any assignment if lvalue.name in inst.type.slots: return # We are assigning to an existing slot for base_info in inst.type.mro[:-1]: if base_info.names.get("__setattr__") is not None: # When type has `__setattr__` defined, # we can assign any dynamic value. # We exclude object, because it always has `__setattr__`. return definition = inst.type.get(lvalue.name) if definition is None: # We don't want to duplicate # `"SomeType" has no attribute "some_attr"` # error twice. return if self.is_assignable_slot(lvalue, definition.type): return self.fail( message_registry.NAME_NOT_IN_SLOTS.format(lvalue.name, inst.type.fullname), lvalue ) def is_assignable_slot(self, lvalue: Lvalue, typ: Type | None) -> bool: if getattr(lvalue, "node", None): return False # This is a definition typ = get_proper_type(typ) if typ is None or isinstance(typ, AnyType): return True # Any can be literally anything, like `@property` if isinstance(typ, Instance): # When working with instances, we need to know if they contain # `__set__` special method. Like `@property` does. # This makes assigning to properties possible, # even without extra slot spec. return typ.type.get("__set__") is not None if isinstance(typ, FunctionLike): return True # Can be a property, or some other magic if isinstance(typ, UnionType): return all(self.is_assignable_slot(lvalue, u) for u in typ.items) return False def flatten_rvalues(self, rvalues: list[Expression]) -> list[Expression]: """Flatten expression list by expanding those * items that have tuple type. For each regular type item in the tuple type use a TempNode(), for an Unpack item use a corresponding StarExpr(TempNode()). """ new_rvalues = [] for rv in rvalues: if not isinstance(rv, StarExpr): new_rvalues.append(rv) continue typ = get_proper_type(self.expr_checker.accept(rv.expr)) if not isinstance(typ, TupleType): new_rvalues.append(rv) continue for t in typ.items: if not isinstance(t, UnpackType): new_rvalues.append(TempNode(t)) else: unpacked = get_proper_type(t.type) if isinstance(unpacked, TypeVarTupleType): fallback = unpacked.upper_bound else: assert ( isinstance(unpacked, Instance) and unpacked.type.fullname == "builtins.tuple" ) fallback = unpacked new_rvalues.append(StarExpr(TempNode(fallback))) return new_rvalues def check_assignment_to_multiple_lvalues( self, lvalues: list[Lvalue], rvalue: Expression, context: Context, infer_lvalue_type: bool = True, ) -> None: if isinstance(rvalue, (TupleExpr, ListExpr)): # Recursively go into Tuple or List expression rhs instead of # using the type of rhs, because this allows more fine-grained # control in cases like: a, b = [int, str] where rhs would get # type List[object] rvalues: list[Expression] = [] iterable_type: Type | None = None last_idx: int | None = None for idx_rval, rval in enumerate(self.flatten_rvalues(rvalue.items)): if isinstance(rval, StarExpr): typs = get_proper_type(self.expr_checker.accept(rval.expr)) if self.type_is_iterable(typs) and isinstance(typs, Instance): if iterable_type is not None and iterable_type != self.iterable_item_type( typs, rvalue ): self.fail(message_registry.CONTIGUOUS_ITERABLE_EXPECTED, context) else: if last_idx is None or last_idx + 1 == idx_rval: rvalues.append(rval) last_idx = idx_rval iterable_type = self.iterable_item_type(typs, rvalue) else: self.fail(message_registry.CONTIGUOUS_ITERABLE_EXPECTED, context) else: self.fail(message_registry.ITERABLE_TYPE_EXPECTED.format(typs), context) else: rvalues.append(rval) iterable_start: int | None = None iterable_end: int | None = None for i, rval in enumerate(rvalues): if isinstance(rval, StarExpr): typs = get_proper_type(self.expr_checker.accept(rval.expr)) if self.type_is_iterable(typs) and isinstance(typs, Instance): if iterable_start is None: iterable_start = i iterable_end = i if ( iterable_start is not None and iterable_end is not None and iterable_type is not None ): iterable_num = iterable_end - iterable_start + 1 rvalue_needed = len(lvalues) - (len(rvalues) - iterable_num) if rvalue_needed > 0: rvalues = ( rvalues[0:iterable_start] + [TempNode(iterable_type) for i in range(rvalue_needed)] + rvalues[iterable_end + 1 :] ) if self.check_rvalue_count_in_assignment(lvalues, len(rvalues), context): star_index = next( (i for i, lv in enumerate(lvalues) if isinstance(lv, StarExpr)), len(lvalues) ) left_lvs = lvalues[:star_index] star_lv = ( cast(StarExpr, lvalues[star_index]) if star_index != len(lvalues) else None ) right_lvs = lvalues[star_index + 1 :] left_rvs, star_rvs, right_rvs = self.split_around_star( rvalues, star_index, len(lvalues) ) lr_pairs = list(zip(left_lvs, left_rvs)) if star_lv: rv_list = ListExpr(star_rvs) rv_list.set_line(rvalue) lr_pairs.append((star_lv.expr, rv_list)) lr_pairs.extend(zip(right_lvs, right_rvs)) for lv, rv in lr_pairs: self.check_assignment(lv, rv, infer_lvalue_type) else: self.check_multi_assignment(lvalues, rvalue, context, infer_lvalue_type) def check_rvalue_count_in_assignment( self, lvalues: list[Lvalue], rvalue_count: int, context: Context, rvalue_unpack: int | None = None, ) -> bool: if rvalue_unpack is not None: if not any(isinstance(e, StarExpr) for e in lvalues): self.fail("Variadic tuple unpacking requires a star target", context) return False if len(lvalues) > rvalue_count: self.fail(message_registry.TOO_MANY_TARGETS_FOR_VARIADIC_UNPACK, context) return False left_star_index = next(i for i, lv in enumerate(lvalues) if isinstance(lv, StarExpr)) left_prefix = left_star_index left_suffix = len(lvalues) - left_star_index - 1 right_prefix = rvalue_unpack right_suffix = rvalue_count - rvalue_unpack - 1 if left_suffix > right_suffix or left_prefix > right_prefix: # Case of asymmetric unpack like: # rv: tuple[int, *Ts, int, int] # x, y, *xs, z = rv # it is technically valid, but is tricky to reason about. # TODO: support this (at least if the r.h.s. unpack is a homogeneous tuple). self.fail(message_registry.TOO_MANY_TARGETS_FOR_VARIADIC_UNPACK, context) return True if any(isinstance(lvalue, StarExpr) for lvalue in lvalues): if len(lvalues) - 1 > rvalue_count: self.msg.wrong_number_values_to_unpack(rvalue_count, len(lvalues) - 1, context) return False elif rvalue_count != len(lvalues): self.msg.wrong_number_values_to_unpack(rvalue_count, len(lvalues), context) return False return True def check_multi_assignment( self, lvalues: list[Lvalue], rvalue: Expression, context: Context, infer_lvalue_type: bool = True, rv_type: Type | None = None, undefined_rvalue: bool = False, ) -> None: """Check the assignment of one rvalue to a number of lvalues.""" # Infer the type of an ordinary rvalue expression. # TODO: maybe elsewhere; redundant. rvalue_type = get_proper_type(rv_type or self.expr_checker.accept(rvalue)) if isinstance(rvalue_type, TypeVarLikeType): rvalue_type = get_proper_type(rvalue_type.upper_bound) if isinstance(rvalue_type, UnionType): # If this is an Optional type in non-strict Optional code, unwrap it. relevant_items = rvalue_type.relevant_items() if len(relevant_items) == 1: rvalue_type = get_proper_type(relevant_items[0]) if ( isinstance(rvalue_type, TupleType) and find_unpack_in_list(rvalue_type.items) is not None ): # Normalize for consistent handling with "old-style" homogeneous tuples. rvalue_type = expand_type(rvalue_type, {}) if isinstance(rvalue_type, AnyType): for lv in lvalues: if isinstance(lv, StarExpr): lv = lv.expr temp_node = self.temp_node( AnyType(TypeOfAny.from_another_any, source_any=rvalue_type), context ) self.check_assignment(lv, temp_node, infer_lvalue_type) elif isinstance(rvalue_type, TupleType): self.check_multi_assignment_from_tuple( lvalues, rvalue, rvalue_type, context, undefined_rvalue, infer_lvalue_type ) elif isinstance(rvalue_type, UnionType): self.check_multi_assignment_from_union( lvalues, rvalue, rvalue_type, context, infer_lvalue_type ) elif isinstance(rvalue_type, Instance) and rvalue_type.type.fullname == "builtins.str": self.msg.unpacking_strings_disallowed(context) else: self.check_multi_assignment_from_iterable( lvalues, rvalue_type, context, infer_lvalue_type ) def check_multi_assignment_from_union( self, lvalues: list[Expression], rvalue: Expression, rvalue_type: UnionType, context: Context, infer_lvalue_type: bool, ) -> None: """Check assignment to multiple lvalue targets when rvalue type is a Union[...]. For example: t: Union[Tuple[int, int], Tuple[str, str]] x, y = t reveal_type(x) # Union[int, str] The idea in this case is to process the assignment for every item of the union. Important note: the types are collected in two places, 'union_types' contains inferred types for first assignments, 'assignments' contains the narrowed types for binder. """ self.no_partial_types = True transposed: tuple[list[Type], ...] = tuple([] for _ in self.flatten_lvalues(lvalues)) # Notify binder that we want to defer bindings and instead collect types. with self.binder.accumulate_type_assignments() as assignments: for item in rvalue_type.items: # Type check the assignment separately for each union item and collect # the inferred lvalue types for each union item. self.check_multi_assignment( lvalues, rvalue, context, infer_lvalue_type=infer_lvalue_type, rv_type=item, undefined_rvalue=True, ) for t, lv in zip(transposed, self.flatten_lvalues(lvalues)): # We can access _type_maps directly since temporary type maps are # only created within expressions. t.append(self._type_maps[0].pop(lv, AnyType(TypeOfAny.special_form))) union_types = tuple(make_simplified_union(col) for col in transposed) for expr, items in assignments.items(): # Bind a union of types collected in 'assignments' to every expression. if isinstance(expr, StarExpr): expr = expr.expr # TODO: See comment in binder.py, ConditionalTypeBinder.assign_type # It's unclear why the 'declared_type' param is sometimes 'None' clean_items: list[tuple[Type, Type]] = [] for type, declared_type in items: assert declared_type is not None clean_items.append((type, declared_type)) types, declared_types = zip(*clean_items) self.binder.assign_type( expr, make_simplified_union(list(types)), make_simplified_union(list(declared_types)), ) for union, lv in zip(union_types, self.flatten_lvalues(lvalues)): # Properly store the inferred types. _1, _2, inferred = self.check_lvalue(lv) if inferred: self.set_inferred_type(inferred, lv, union) else: self.store_type(lv, union) self.no_partial_types = False def flatten_lvalues(self, lvalues: list[Expression]) -> list[Expression]: res: list[Expression] = [] for lv in lvalues: if isinstance(lv, (TupleExpr, ListExpr)): res.extend(self.flatten_lvalues(lv.items)) if isinstance(lv, StarExpr): # Unwrap StarExpr, since it is unwrapped by other helpers. lv = lv.expr res.append(lv) return res def check_multi_assignment_from_tuple( self, lvalues: list[Lvalue], rvalue: Expression, rvalue_type: TupleType, context: Context, undefined_rvalue: bool, infer_lvalue_type: bool = True, ) -> None: rvalue_unpack = find_unpack_in_list(rvalue_type.items) if self.check_rvalue_count_in_assignment( lvalues, len(rvalue_type.items), context, rvalue_unpack=rvalue_unpack ): star_index = next( (i for i, lv in enumerate(lvalues) if isinstance(lv, StarExpr)), len(lvalues) ) left_lvs = lvalues[:star_index] star_lv = cast(StarExpr, lvalues[star_index]) if star_index != len(lvalues) else None right_lvs = lvalues[star_index + 1 :] if not undefined_rvalue: # Infer rvalue again, now in the correct type context. lvalue_type = self.lvalue_type_for_inference(lvalues, rvalue_type) reinferred_rvalue_type = get_proper_type( self.expr_checker.accept(rvalue, lvalue_type) ) if isinstance(reinferred_rvalue_type, TypeVarLikeType): reinferred_rvalue_type = get_proper_type(reinferred_rvalue_type.upper_bound) if isinstance(reinferred_rvalue_type, UnionType): # If this is an Optional type in non-strict Optional code, unwrap it. relevant_items = reinferred_rvalue_type.relevant_items() if len(relevant_items) == 1: reinferred_rvalue_type = get_proper_type(relevant_items[0]) if isinstance(reinferred_rvalue_type, UnionType): self.check_multi_assignment_from_union( lvalues, rvalue, reinferred_rvalue_type, context, infer_lvalue_type ) return if isinstance(reinferred_rvalue_type, AnyType): # We can get Any if the current node is # deferred. Doing more inference in deferred nodes # is hard, so give up for now. We can also get # here if reinferring types above changes the # inferred return type for an overloaded function # to be ambiguous. return assert isinstance(reinferred_rvalue_type, TupleType) rvalue_type = reinferred_rvalue_type left_rv_types, star_rv_types, right_rv_types = self.split_around_star( rvalue_type.items, star_index, len(lvalues) ) for lv, rv_type in zip(left_lvs, left_rv_types): self.check_assignment(lv, self.temp_node(rv_type, context), infer_lvalue_type) if star_lv: list_expr = ListExpr( [ ( self.temp_node(rv_type, context) if not isinstance(rv_type, UnpackType) else StarExpr(self.temp_node(rv_type.type, context)) ) for rv_type in star_rv_types ] ) list_expr.set_line(context) self.check_assignment(star_lv.expr, list_expr, infer_lvalue_type) for lv, rv_type in zip(right_lvs, right_rv_types): self.check_assignment(lv, self.temp_node(rv_type, context), infer_lvalue_type) else: # Store meaningful Any types for lvalues, errors are already given # by check_rvalue_count_in_assignment() if infer_lvalue_type: for lv in lvalues: if ( isinstance(lv, NameExpr) and isinstance(lv.node, Var) and lv.node.type is None ): lv.node.type = AnyType(TypeOfAny.from_error) elif isinstance(lv, StarExpr): if ( isinstance(lv.expr, NameExpr) and isinstance(lv.expr.node, Var) and lv.expr.node.type is None ): lv.expr.node.type = self.named_generic_type( "builtins.list", [AnyType(TypeOfAny.from_error)] ) def lvalue_type_for_inference(self, lvalues: list[Lvalue], rvalue_type: TupleType) -> Type: star_index = next( (i for i, lv in enumerate(lvalues) if isinstance(lv, StarExpr)), len(lvalues) ) left_lvs = lvalues[:star_index] star_lv = cast(StarExpr, lvalues[star_index]) if star_index != len(lvalues) else None right_lvs = lvalues[star_index + 1 :] left_rv_types, star_rv_types, right_rv_types = self.split_around_star( rvalue_type.items, star_index, len(lvalues) ) type_parameters: list[Type] = [] def append_types_for_inference(lvs: list[Expression], rv_types: list[Type]) -> None: for lv, rv_type in zip(lvs, rv_types): sub_lvalue_type, index_expr, inferred = self.check_lvalue(lv) if sub_lvalue_type and not isinstance(sub_lvalue_type, PartialType): type_parameters.append(sub_lvalue_type) else: # index lvalue # TODO Figure out more precise type context, probably # based on the type signature of the _set method. type_parameters.append(rv_type) append_types_for_inference(left_lvs, left_rv_types) if star_lv: sub_lvalue_type, index_expr, inferred = self.check_lvalue(star_lv.expr) if sub_lvalue_type and not isinstance(sub_lvalue_type, PartialType): type_parameters.extend([sub_lvalue_type] * len(star_rv_types)) else: # index lvalue # TODO Figure out more precise type context, probably # based on the type signature of the _set method. type_parameters.extend(star_rv_types) append_types_for_inference(right_lvs, right_rv_types) return TupleType(type_parameters, self.named_type("builtins.tuple")) def split_around_star( self, items: list[T], star_index: int, length: int ) -> tuple[list[T], list[T], list[T]]: """Splits a list of items in three to match another list of length 'length' that contains a starred expression at 'star_index' in the following way: star_index = 2, length = 5 (i.e., [a,b,*,c,d]), items = [1,2,3,4,5,6,7] returns in: ([1,2], [3,4,5], [6,7]) """ nr_right_of_star = length - star_index - 1 right_index = -nr_right_of_star if nr_right_of_star != 0 else len(items) left = items[:star_index] star = items[star_index:right_index] right = items[right_index:] return left, star, right def type_is_iterable(self, type: Type) -> bool: type = get_proper_type(type) if isinstance(type, FunctionLike) and type.is_type_obj(): type = type.fallback return is_subtype( type, self.named_generic_type("typing.Iterable", [AnyType(TypeOfAny.special_form)]) ) def check_multi_assignment_from_iterable( self, lvalues: list[Lvalue], rvalue_type: Type, context: Context, infer_lvalue_type: bool = True, ) -> None: rvalue_type = get_proper_type(rvalue_type) if self.type_is_iterable(rvalue_type) and isinstance( rvalue_type, (Instance, CallableType, TypeType, Overloaded) ): item_type = self.iterable_item_type(rvalue_type, context) for lv in lvalues: if isinstance(lv, StarExpr): items_type = self.named_generic_type("builtins.list", [item_type]) self.check_assignment( lv.expr, self.temp_node(items_type, context), infer_lvalue_type ) else: self.check_assignment( lv, self.temp_node(item_type, context), infer_lvalue_type ) else: self.msg.type_not_iterable(rvalue_type, context) def check_lvalue( self, lvalue: Lvalue, rvalue: Expression | None = None ) -> tuple[Type | None, IndexExpr | None, Var | None]: lvalue_type = None index_lvalue = None inferred = None if self.is_definition(lvalue) and ( not isinstance(lvalue, NameExpr) or isinstance(lvalue.node, Var) ): if isinstance(lvalue, NameExpr): assert isinstance(lvalue.node, Var) inferred = lvalue.node else: assert isinstance(lvalue, MemberExpr) self.expr_checker.accept(lvalue.expr) inferred = lvalue.def_var elif isinstance(lvalue, IndexExpr): index_lvalue = lvalue elif isinstance(lvalue, MemberExpr): lvalue_type = self.expr_checker.analyze_ordinary_member_access(lvalue, True, rvalue) self.store_type(lvalue, lvalue_type) elif isinstance(lvalue, NameExpr): lvalue_type = self.expr_checker.analyze_ref_expr(lvalue, lvalue=True) if ( self.options.allow_redefinition_new and isinstance(lvalue.node, Var) and lvalue.node.is_inferred ): inferred = lvalue.node self.store_type(lvalue, lvalue_type) elif isinstance(lvalue, (TupleExpr, ListExpr)): types = [ self.check_lvalue(sub_expr)[0] or # This type will be used as a context for further inference of rvalue, # we put Uninhabited if there is no information available from lvalue. UninhabitedType() for sub_expr in lvalue.items ] lvalue_type = TupleType(types, self.named_type("builtins.tuple")) elif isinstance(lvalue, StarExpr): lvalue_type, _, _ = self.check_lvalue(lvalue.expr) else: lvalue_type = self.expr_checker.accept(lvalue) return lvalue_type, index_lvalue, inferred def is_definition(self, s: Lvalue) -> bool: if isinstance(s, NameExpr): if s.is_inferred_def: return True # If the node type is not defined, this must the first assignment # that we process => this is a definition, even though the semantic # analyzer did not recognize this as such. This can arise in code # that uses isinstance checks, if type checking of the primary # definition is skipped due to an always False type check. node = s.node if isinstance(node, Var): return node.type is None elif isinstance(s, MemberExpr): return s.is_inferred_def return False def infer_variable_type( self, name: Var, lvalue: Lvalue, init_type: Type, context: Context ) -> None: """Infer the type of initialized variables from initializer type.""" if isinstance(init_type, DeletedType): self.msg.deleted_as_rvalue(init_type, context) elif ( not is_valid_inferred_type( init_type, self.options, is_lvalue_final=name.is_final, is_lvalue_member=isinstance(lvalue, MemberExpr), ) and not self.no_partial_types ): # We cannot use the type of the initialization expression for full type # inference (it's not specific enough), but we might be able to give # partial type which will be made more specific later. A partial type # gets generated in assignment like 'x = []' where item type is not known. if name.name != "_" and not self.infer_partial_type(name, lvalue, init_type): self.msg.need_annotation_for_var(name, context, self.options.python_version) self.set_inference_error_fallback_type(name, lvalue, init_type) elif ( isinstance(lvalue, MemberExpr) and self.inferred_attribute_types is not None and lvalue.def_var and lvalue.def_var in self.inferred_attribute_types and not is_same_type(self.inferred_attribute_types[lvalue.def_var], init_type) ): # Multiple, inconsistent types inferred for an attribute. self.msg.need_annotation_for_var(name, context, self.options.python_version) name.type = AnyType(TypeOfAny.from_error) else: # Infer type of the target. # Make the type more general (strip away function names etc.). init_type = strip_type(init_type) self.set_inferred_type(name, lvalue, init_type) if self.options.allow_redefinition_new: self.binder.assign_type(lvalue, init_type, init_type) def infer_partial_type(self, name: Var, lvalue: Lvalue, init_type: Type) -> bool: init_type = get_proper_type(init_type) if isinstance(init_type, NoneType) and ( isinstance(lvalue, MemberExpr) or not self.options.allow_redefinition_new ): # When using --allow-redefinition-new, None types aren't special # when inferring simple variable types. partial_type = PartialType(None, name) elif isinstance(init_type, Instance): fullname = init_type.type.fullname is_ref = isinstance(lvalue, RefExpr) if ( is_ref and ( fullname == "builtins.list" or fullname == "builtins.set" or fullname == "builtins.dict" or fullname == "collections.OrderedDict" ) and all( isinstance(t, (NoneType, UninhabitedType)) for t in get_proper_types(init_type.args) ) ): partial_type = PartialType(init_type.type, name) elif is_ref and fullname == "collections.defaultdict": arg0 = get_proper_type(init_type.args[0]) arg1 = get_proper_type(init_type.args[1]) if isinstance( arg0, (NoneType, UninhabitedType) ) and self.is_valid_defaultdict_partial_value_type(arg1): arg1 = erase_type(arg1) assert isinstance(arg1, Instance) partial_type = PartialType(init_type.type, name, arg1) else: return False else: return False else: return False self.set_inferred_type(name, lvalue, partial_type) self.partial_types[-1].map[name] = lvalue return True def is_valid_defaultdict_partial_value_type(self, t: ProperType) -> bool: """Check if t can be used as the basis for a partial defaultdict value type. Examples: * t is 'int' --> True * t is 'list[Never]' --> True * t is 'dict[...]' --> False (only generic types with a single type argument supported) """ if not isinstance(t, Instance): return False if len(t.args) == 0: return True if len(t.args) == 1: arg = get_proper_type(t.args[0]) if self.options.old_type_inference: # Allow leaked TypeVars for legacy inference logic. allowed = isinstance(arg, (UninhabitedType, NoneType, TypeVarType)) else: allowed = isinstance(arg, (UninhabitedType, NoneType)) if allowed: return True return False def set_inferred_type(self, var: Var, lvalue: Lvalue, type: Type) -> None: """Store inferred variable type. Store the type to both the variable node and the expression node that refers to the variable (lvalue). If var is None, do nothing. """ if var and not self.current_node_deferred: # TODO: should we also set 'is_ready = True' here? var.type = type var.is_inferred = True if var not in self.var_decl_frames: # Used for the hack to improve optional type inference in conditionals self.var_decl_frames[var] = {frame.id for frame in self.binder.frames} if isinstance(lvalue, MemberExpr) and self.inferred_attribute_types is not None: # Store inferred attribute type so that we can check consistency afterwards. if lvalue.def_var is not None: self.inferred_attribute_types[lvalue.def_var] = type self.store_type(lvalue, type) p_type = get_proper_type(type) if isinstance(p_type, CallableType) and is_node_static(p_type.definition): # TODO: handle aliases to class methods (similarly). var.is_staticmethod = True def set_inference_error_fallback_type(self, var: Var, lvalue: Lvalue, type: Type) -> None: """Store best known type for variable if type inference failed. If a program ignores error on type inference error, the variable should get some inferred type so that it can used later on in the program. Example: x = [] # type: ignore x.append(1) # Should be ok! We implement this here by giving x a valid type (replacing inferred Never with Any). """ fallback = self.inference_error_fallback_type(type) self.set_inferred_type(var, lvalue, fallback) def inference_error_fallback_type(self, type: Type) -> Type: fallback = type.accept(SetNothingToAny()) # Type variables may leak from inference, see https://github.com/python/mypy/issues/5738, # we therefore need to erase them. return erase_typevars(fallback) def simple_rvalue(self, rvalue: Expression) -> bool: """Returns True for expressions for which inferred type should not depend on context. Note that this function can still return False for some expressions where inferred type does not depend on context. It only exists for performance optimizations. """ if isinstance(rvalue, (IntExpr, StrExpr, BytesExpr, FloatExpr, RefExpr)): return True if isinstance(rvalue, CallExpr): if isinstance(rvalue.callee, RefExpr) and isinstance( rvalue.callee.node, SYMBOL_FUNCBASE_TYPES ): typ = rvalue.callee.node.type if isinstance(typ, CallableType): return not typ.variables elif isinstance(typ, Overloaded): return not any(item.variables for item in typ.items) return False def check_simple_assignment( self, lvalue_type: Type | None, rvalue: Expression, context: Context, msg: ErrorMessage = message_registry.INCOMPATIBLE_TYPES_IN_ASSIGNMENT, lvalue_name: str = "variable", rvalue_name: str = "expression", *, notes: list[str] | None = None, lvalue: Expression | None = None, inferred: Var | None = None, ) -> tuple[Type, Type | None]: if self.is_stub and isinstance(rvalue, EllipsisExpr): # '...' is always a valid initializer in a stub. return AnyType(TypeOfAny.special_form), lvalue_type else: always_allow_any = lvalue_type is not None and not isinstance( get_proper_type(lvalue_type), AnyType ) if inferred is None or is_typeddict_type_context(lvalue_type): type_context = lvalue_type else: type_context = None rvalue_type = self.expr_checker.accept( rvalue, type_context=type_context, always_allow_any=always_allow_any ) if ( lvalue_type is not None and type_context is None and not is_valid_inferred_type(rvalue_type, self.options) ): # Inference in an empty type context didn't produce a valid type, so # try using lvalue type as context instead. rvalue_type = self.expr_checker.accept( rvalue, type_context=lvalue_type, always_allow_any=always_allow_any ) if not is_valid_inferred_type(rvalue_type, self.options) and inferred is not None: self.msg.need_annotation_for_var( inferred, context, self.options.python_version ) rvalue_type = rvalue_type.accept(SetNothingToAny()) if ( isinstance(lvalue, NameExpr) and inferred is not None and inferred.type is not None and not inferred.is_final ): new_inferred = remove_instance_last_known_values(rvalue_type) if not is_same_type(inferred.type, new_inferred): # Should we widen the inferred type or the lvalue? Variables defined # at module level or class bodies can't be widened in functions, or # in another module. if not self.refers_to_different_scope(lvalue): lvalue_type = make_simplified_union([inferred.type, new_inferred]) if not is_same_type(lvalue_type, inferred.type) and not isinstance( inferred.type, PartialType ): # Widen the type to the union of original and new type. self.widened_vars.append(inferred.name) self.set_inferred_type(inferred, lvalue, lvalue_type) self.binder.put(lvalue, rvalue_type) # TODO: A bit hacky, maybe add a binder method that does put and # updates declaration? lit = literal_hash(lvalue) if lit is not None: self.binder.declarations[lit] = lvalue_type if ( isinstance(get_proper_type(lvalue_type), UnionType) # Skip literal types, as they have special logic (for better errors). and not is_literal_type_like(rvalue_type) and not self.simple_rvalue(rvalue) ): # Try re-inferring r.h.s. in empty context, and use that if it # results in a narrower type. We don't do this always because this # may cause some perf impact, plus we want to partially preserve # the old behavior. This helps with various practical examples, see # e.g. testOptionalTypeNarrowedByGenericCall. with self.msg.filter_errors() as local_errors, self.local_type_map() as type_map: alt_rvalue_type = self.expr_checker.accept( rvalue, None, always_allow_any=always_allow_any ) if ( not local_errors.has_new_errors() # Skip Any type, since it is special cased in binder. and not isinstance(get_proper_type(alt_rvalue_type), AnyType) and is_valid_inferred_type(alt_rvalue_type, self.options) and is_proper_subtype(alt_rvalue_type, rvalue_type) ): rvalue_type = alt_rvalue_type self.store_types(type_map) if isinstance(rvalue_type, DeletedType): self.msg.deleted_as_rvalue(rvalue_type, context) if isinstance(lvalue_type, DeletedType): self.msg.deleted_as_lvalue(lvalue_type, context) elif lvalue_type: self.check_subtype( # Preserve original aliases for error messages when possible. rvalue_type, lvalue_type, context, msg, f"{rvalue_name} has type", f"{lvalue_name} has type", notes=notes, ) return rvalue_type, lvalue_type def refers_to_different_scope(self, name: NameExpr) -> bool: if name.kind == LDEF: # TODO: Consider reference to outer function as a different scope? return False elif self.scope.top_level_function() is not None: # A non-local reference from within a function must refer to a different scope return True elif name.kind == GDEF and name.fullname.rpartition(".")[0] != self.tree.fullname: # Reference to global definition from another module return True return False def check_member_assignment( self, lvalue: MemberExpr, instance_type: Type, attribute_type: Type, rvalue: Expression, context: Context, ) -> tuple[Type, Type, bool]: """Type member assignment. This defers to check_simple_assignment, unless the member expression is a descriptor, in which case this checks descriptor semantics as well. Return the inferred rvalue_type, inferred lvalue_type, and whether to use the binder for this assignment. """ instance_type = get_proper_type(instance_type) # Descriptors don't participate in class-attribute access if (isinstance(instance_type, FunctionLike) and instance_type.is_type_obj()) or isinstance( instance_type, TypeType ): rvalue_type, _ = self.check_simple_assignment(attribute_type, rvalue, context) return rvalue_type, attribute_type, True with self.msg.filter_errors(filter_deprecated=True): get_lvalue_type = self.expr_checker.analyze_ordinary_member_access( lvalue, is_lvalue=False ) # Special case: if the rvalue_type is a subtype of both '__get__' and '__set__' types, # and '__get__' type is narrower than '__set__', then we invoke the binder to narrow type # by this assignment. Technically, this is not safe, but in practice this is # what a user expects. rvalue_type, _ = self.check_simple_assignment(attribute_type, rvalue, context) infer = is_subtype(rvalue_type, get_lvalue_type) and is_subtype( get_lvalue_type, attribute_type ) return rvalue_type if infer else attribute_type, attribute_type, infer def check_indexed_assignment( self, lvalue: IndexExpr, rvalue: Expression, context: Context ) -> None: """Type check indexed assignment base[index] = rvalue. The lvalue argument is the base[index] expression. """ self.try_infer_partial_type_from_indexed_assignment(lvalue, rvalue) basetype = get_proper_type(self.expr_checker.accept(lvalue.base)) method_type = self.expr_checker.analyze_external_member_access( "__setitem__", basetype, lvalue ) lvalue.method_type = method_type res_type, _ = self.expr_checker.check_method_call( "__setitem__", basetype, method_type, [lvalue.index, rvalue], [nodes.ARG_POS, nodes.ARG_POS], context, ) res_type = get_proper_type(res_type) if isinstance(res_type, UninhabitedType) and not res_type.ambiguous: self.binder.unreachable() def replace_partial_type( self, var: Var, new_type: Type, partial_types: dict[Var, Context] ) -> None: """Replace the partial type of var with a non-partial type.""" var.type = new_type del partial_types[var] if self.options.allow_redefinition_new: # When using --allow-redefinition-new, binder tracks all types of # simple variables. n = NameExpr(var.name) n.node = var self.binder.assign_type(n, new_type, new_type) def try_infer_partial_type_from_indexed_assignment( self, lvalue: IndexExpr, rvalue: Expression ) -> None: # TODO: Should we share some of this with try_infer_partial_type? var = None if isinstance(lvalue.base, RefExpr) and isinstance(lvalue.base.node, Var): var = lvalue.base.node elif isinstance(lvalue.base, MemberExpr): var = self.expr_checker.get_partial_self_var(lvalue.base) if isinstance(var, Var): if isinstance(var.type, PartialType): type_type = var.type.type if type_type is None: return # The partial type is None. partial_types = self.find_partial_types(var) if partial_types is None: return typename = type_type.fullname if ( typename == "builtins.dict" or typename == "collections.OrderedDict" or typename == "collections.defaultdict" ): # TODO: Don't infer things twice. key_type = self.expr_checker.accept(lvalue.index) value_type = self.expr_checker.accept(rvalue) if ( is_valid_inferred_type(key_type, self.options) and is_valid_inferred_type(value_type, self.options) and not self.current_node_deferred and not ( typename == "collections.defaultdict" and var.type.value_type is not None and not is_equivalent(value_type, var.type.value_type) ) ): new_type = self.named_generic_type(typename, [key_type, value_type]) self.replace_partial_type(var, new_type, partial_types) def type_requires_usage(self, typ: Type) -> tuple[str, ErrorCode] | None: """Some types require usage in all cases. The classic example is an unused coroutine. In the case that it does require usage, returns a note to attach to the error message. """ proper_type = get_proper_type(typ) if isinstance(proper_type, Instance): # We use different error codes for generic awaitable vs coroutine. # Coroutines are on by default, whereas generic awaitables are not. if proper_type.type.fullname == "typing.Coroutine": return ("Are you missing an await?", UNUSED_COROUTINE) if proper_type.type.get("__await__") is not None: return ("Are you missing an await?", UNUSED_AWAITABLE) return None def visit_expression_stmt(self, s: ExpressionStmt) -> None: expr_type = self.expr_checker.accept(s.expr, allow_none_return=True, always_allow_any=True) error_note_and_code = self.type_requires_usage(expr_type) if error_note_and_code: error_note, code = error_note_and_code self.fail( message_registry.TYPE_MUST_BE_USED.format(format_type(expr_type, self.options)), s, code=code, ) self.note(error_note, s, code=code) def visit_return_stmt(self, s: ReturnStmt) -> None: """Type check a return statement.""" self.check_return_stmt(s) self.binder.unreachable() def check_return_stmt(self, s: ReturnStmt) -> None: defn = self.scope.current_function() if defn is not None: if defn.is_generator: return_type = self.get_generator_return_type( self.return_types[-1], defn.is_coroutine ) elif defn.is_coroutine: return_type = self.get_coroutine_return_type(self.return_types[-1]) else: return_type = self.return_types[-1] return_type = get_proper_type(return_type) is_lambda = isinstance(defn, LambdaExpr) if isinstance(return_type, UninhabitedType): # Avoid extra error messages for failed inference in lambdas if not is_lambda and not return_type.ambiguous: self.fail(message_registry.NO_RETURN_EXPECTED, s) return if s.expr: declared_none_return = isinstance(return_type, NoneType) declared_any_return = isinstance(return_type, AnyType) # This controls whether or not we allow a function call that # returns None as the expression of this return statement. # E.g. `return f()` for some `f` that returns None. We allow # this only if we're in a lambda or in a function that returns # `None` or `Any`. allow_none_func_call = is_lambda or declared_none_return or declared_any_return # Return with a value. typ = get_proper_type( self.expr_checker.accept( s.expr, return_type, allow_none_return=allow_none_func_call ) ) # Treat NotImplemented as having type Any, consistent with its # definition in typeshed prior to python/typeshed#4222. if ( isinstance(typ, Instance) and typ.type.fullname == "builtins._NotImplementedType" ): typ = AnyType(TypeOfAny.special_form) if defn.is_async_generator: self.fail(message_registry.RETURN_IN_ASYNC_GENERATOR, s) return # Returning a value of type Any is always fine. if isinstance(typ, AnyType): # (Unless you asked to be warned in that case, and the # function is not declared to return Any) if ( self.options.warn_return_any and not self.current_node_deferred and not is_proper_subtype(AnyType(TypeOfAny.special_form), return_type) and not ( defn.name in BINARY_MAGIC_METHODS and is_literal_not_implemented(s.expr) ) and not ( isinstance(return_type, Instance) and return_type.type.fullname == "builtins.object" ) and not is_lambda ): self.msg.incorrectly_returning_any(return_type, s) return # Disallow return expressions in functions declared to return # None, subject to two exceptions below. if declared_none_return: # Lambdas are allowed to have None returns. # Functions returning a value of type None are allowed to have a None return. if is_lambda or isinstance(typ, NoneType): return self.fail(message_registry.NO_RETURN_VALUE_EXPECTED, s) else: self.check_subtype( subtype_label="got", subtype=typ, supertype_label="expected", supertype=return_type, context=s.expr, outer_context=s, msg=message_registry.INCOMPATIBLE_RETURN_VALUE_TYPE, ) else: # Empty returns are valid in Generators with Any typed returns, but not in # coroutines. if ( defn.is_generator and not defn.is_coroutine and isinstance(return_type, AnyType) ): return if isinstance(return_type, (NoneType, AnyType)): return if self.in_checked_function(): self.fail(message_registry.RETURN_VALUE_EXPECTED, s) def visit_if_stmt(self, s: IfStmt) -> None: """Type check an if statement.""" # This frame records the knowledge from previous if/elif clauses not being taken. # Fall-through to the original frame is handled explicitly in each block. with self.binder.frame_context(can_skip=False, conditional_frame=True, fall_through=0): for e, b in zip(s.expr, s.body): t = get_proper_type(self.expr_checker.accept(e)) if isinstance(t, DeletedType): self.msg.deleted_as_rvalue(t, s) if_map, else_map = self.find_isinstance_check(e) # XXX Issue a warning if condition is always False? with self.binder.frame_context(can_skip=True, fall_through=2): self.push_type_map(if_map, from_assignment=False) self.accept(b) # XXX Issue a warning if condition is always True? self.push_type_map(else_map, from_assignment=False) with self.binder.frame_context(can_skip=False, fall_through=2): if s.else_body: self.accept(s.else_body) def visit_while_stmt(self, s: WhileStmt) -> None: """Type check a while statement.""" if_stmt = IfStmt([s.expr], [s.body], None) if_stmt.set_line(s) self.accept_loop(if_stmt, s.else_body, exit_condition=s.expr) def visit_operator_assignment_stmt(self, s: OperatorAssignmentStmt) -> None: """Type check an operator assignment statement, e.g. x += 1.""" self.try_infer_partial_generic_type_from_assignment(s.lvalue, s.rvalue, s.op) if isinstance(s.lvalue, MemberExpr): # Special case, some additional errors may be given for # assignments to read-only or final attributes. lvalue_type = self.expr_checker.visit_member_expr(s.lvalue, True) else: lvalue_type = self.expr_checker.accept(s.lvalue) inplace, method = infer_operator_assignment_method(lvalue_type, s.op) if inplace: # There is __ifoo__, treat as x = x.__ifoo__(y) rvalue_type, method_type = self.expr_checker.check_op(method, lvalue_type, s.rvalue, s) if isinstance(inst := get_proper_type(lvalue_type), Instance) and isinstance( defn := inst.type.get_method(method), OverloadedFuncDef ): for item in defn.items: if ( isinstance(item, Decorator) and isinstance(typ := item.func.type, CallableType) and (bind_self(typ) == method_type) ): self.warn_deprecated(item.func, s) if not is_subtype(rvalue_type, lvalue_type): self.msg.incompatible_operator_assignment(s.op, s) else: # There is no __ifoo__, treat as x = x y expr = OpExpr(s.op, s.lvalue, s.rvalue) expr.set_line(s) self.check_assignment( lvalue=s.lvalue, rvalue=expr, infer_lvalue_type=True, new_syntax=False ) self.check_final(s) def visit_assert_stmt(self, s: AssertStmt) -> None: self.expr_checker.accept(s.expr) if isinstance(s.expr, TupleExpr) and len(s.expr.items) > 0: self.fail(message_registry.MALFORMED_ASSERT, s) # If this is asserting some isinstance check, bind that type in the following code true_map, else_map = self.find_isinstance_check(s.expr) if s.msg is not None: self.expr_checker.analyze_cond_branch( else_map, s.msg, None, suppress_unreachable_errors=False ) self.push_type_map(true_map) def visit_raise_stmt(self, s: RaiseStmt) -> None: """Type check a raise statement.""" if s.expr: self.type_check_raise(s.expr, s) if s.from_expr: self.type_check_raise(s.from_expr, s, optional=True) self.binder.unreachable() def type_check_raise(self, e: Expression, s: RaiseStmt, optional: bool = False) -> None: typ = get_proper_type(self.expr_checker.accept(e)) if isinstance(typ, DeletedType): self.msg.deleted_as_rvalue(typ, e) return exc_type = self.named_type("builtins.BaseException") expected_type_items = [exc_type, TypeType(exc_type)] if optional: # This is used for `x` part in a case like `raise e from x`, # where we allow `raise e from None`. expected_type_items.append(NoneType()) self.check_subtype( typ, UnionType.make_union(expected_type_items), s, message_registry.INVALID_EXCEPTION ) if isinstance(typ, FunctionLike): # https://github.com/python/mypy/issues/11089 self.expr_checker.check_call(typ, [], [], e) if isinstance(typ, Instance) and typ.type.fullname == "builtins._NotImplementedType": self.fail( message_registry.INVALID_EXCEPTION.with_additional_msg( '; did you mean "NotImplementedError"?' ), s, ) def visit_try_stmt(self, s: TryStmt) -> None: """Type check a try statement.""" # Our enclosing frame will get the result if the try/except falls through. # This one gets all possible states after the try block exited abnormally # (by exception, return, break, etc.) with self.binder.frame_context(can_skip=False, fall_through=0): # Not only might the body of the try statement exit # abnormally, but so might an exception handler or else # clause. The finally clause runs in *all* cases, so we # need an outer try frame to catch all intermediate states # in case an exception is raised during an except or else # clause. As an optimization, only create the outer try # frame when there actually is a finally clause. self.visit_try_without_finally(s, try_frame=bool(s.finally_body)) if s.finally_body: # First we check finally_body is type safe on all abnormal exit paths self.accept(s.finally_body) if s.finally_body: # Then we try again for the more restricted set of options # that can fall through. (Why do we need to check the # finally clause twice? Depending on whether the finally # clause was reached by the try clause falling off the end # or exiting abnormally, after completing the finally clause # either flow will continue to after the entire try statement # or the exception/return/etc. will be processed and control # flow will escape. We need to check that the finally clause # type checks in both contexts, but only the resulting types # from the latter context affect the type state in the code # that follows the try statement.) if not self.binder.is_unreachable(): self.accept(s.finally_body) def visit_try_without_finally(self, s: TryStmt, try_frame: bool) -> None: """Type check a try statement, ignoring the finally block. On entry, the top frame should receive all flow that exits the try block abnormally (i.e., such that the else block does not execute), and its parent should receive all flow that exits the try block normally. """ # This frame will run the else block if the try fell through. # In that case, control flow continues to the parent of what # was the top frame on entry. with self.binder.frame_context(can_skip=False, fall_through=2, try_frame=try_frame): # This frame receives exit via exception, and runs exception handlers with self.binder.frame_context(can_skip=False, conditional_frame=True, fall_through=2): # Finally, the body of the try statement with self.binder.frame_context(can_skip=False, fall_through=2, try_frame=True): self.accept(s.body) for i in range(len(s.handlers)): with self.binder.frame_context(can_skip=True, fall_through=4): typ = s.types[i] if typ: t = self.check_except_handler_test(typ, s.is_star) var = s.vars[i] if var: # To support local variables, we make this a definition line, # causing assignment to set the variable's type. var.is_inferred_def = True self.check_assignment(var, self.temp_node(t, var)) self.accept(s.handlers[i]) var = s.vars[i] if var: # Exception variables are deleted. # Unfortunately, this doesn't let us detect usage before the # try/except block. source = var.name if isinstance(var.node, Var): new_type = DeletedType(source=source) var.node.type = new_type if self.options.allow_redefinition_new: # TODO: Should we use put() here? self.binder.assign_type(var, new_type, new_type) if not self.options.allow_redefinition_new: self.binder.cleanse(var) if s.else_body: self.accept(s.else_body) def check_except_handler_test(self, n: Expression, is_star: bool) -> Type: """Type check an exception handler test clause.""" typ = self.expr_checker.accept(n) all_types: list[Type] = [] test_types = self.get_types_from_except_handler(typ, n) for ttype in get_proper_types(test_types): if isinstance(ttype, AnyType): all_types.append(ttype) continue if isinstance(ttype, FunctionLike): item = ttype.items[0] if not item.is_type_obj(): self.fail(message_registry.INVALID_EXCEPTION_TYPE, n) return self.default_exception_type(is_star) exc_type = erase_typevars(item.ret_type) elif isinstance(ttype, TypeType): exc_type = ttype.item else: self.fail(message_registry.INVALID_EXCEPTION_TYPE, n) return self.default_exception_type(is_star) if not is_subtype(exc_type, self.named_type("builtins.BaseException")): self.fail(message_registry.INVALID_EXCEPTION_TYPE, n) return self.default_exception_type(is_star) all_types.append(exc_type) if is_star: new_all_types: list[Type] = [] for typ in all_types: if is_proper_subtype(typ, self.named_type("builtins.BaseExceptionGroup")): self.fail(message_registry.INVALID_EXCEPTION_GROUP, n) new_all_types.append(AnyType(TypeOfAny.from_error)) else: new_all_types.append(typ) return self.wrap_exception_group(new_all_types) return make_simplified_union(all_types) def default_exception_type(self, is_star: bool) -> Type: """Exception type to return in case of a previous type error.""" any_type = AnyType(TypeOfAny.from_error) if is_star: return self.named_generic_type("builtins.ExceptionGroup", [any_type]) return any_type def wrap_exception_group(self, types: Sequence[Type]) -> Type: """Transform except* variable type into an appropriate exception group.""" arg = make_simplified_union(types) if is_subtype(arg, self.named_type("builtins.Exception")): base = "builtins.ExceptionGroup" else: base = "builtins.BaseExceptionGroup" return self.named_generic_type(base, [arg]) def get_types_from_except_handler(self, typ: Type, n: Expression) -> list[Type]: """Helper for check_except_handler_test to retrieve handler types.""" typ = get_proper_type(typ) if isinstance(typ, TupleType): return typ.items elif isinstance(typ, UnionType): return [ union_typ for item in typ.relevant_items() for union_typ in self.get_types_from_except_handler(item, n) ] elif is_named_instance(typ, "builtins.tuple"): # variadic tuple return [typ.args[0]] else: return [typ] def visit_for_stmt(self, s: ForStmt) -> None: """Type check a for statement.""" if s.is_async: iterator_type, item_type = self.analyze_async_iterable_item_type(s.expr) else: iterator_type, item_type = self.analyze_iterable_item_type(s.expr) s.inferred_item_type = item_type s.inferred_iterator_type = iterator_type self.accept_loop( s.body, s.else_body, on_enter_body=lambda: self.analyze_index_variables( s.index, item_type, s.index_type is None, s ), ) def analyze_async_iterable_item_type(self, expr: Expression) -> tuple[Type, Type]: """Analyse async iterable expression and return iterator and iterator item types.""" echk = self.expr_checker iterable = echk.accept(expr) iterator = echk.check_method_call_by_name("__aiter__", iterable, [], [], expr)[0] awaitable = echk.check_method_call_by_name("__anext__", iterator, [], [], expr)[0] item_type = echk.check_awaitable_expr( awaitable, expr, message_registry.INCOMPATIBLE_TYPES_IN_ASYNC_FOR ) return iterator, item_type def analyze_iterable_item_type(self, expr: Expression) -> tuple[Type, Type]: """Analyse iterable expression and return iterator and iterator item types.""" iterator, iterable = self.analyze_iterable_item_type_without_expression( self.expr_checker.accept(expr), context=expr ) int_type = self.analyze_range_native_int_type(expr) if int_type: return iterator, int_type return iterator, iterable def analyze_iterable_item_type_without_expression( self, type: Type, context: Context ) -> tuple[Type, Type]: """Analyse iterable type and return iterator and iterator item types.""" echk = self.expr_checker iterable: Type iterable = get_proper_type(type) iterator = echk.check_method_call_by_name("__iter__", iterable, [], [], context)[0] if ( isinstance(iterable, TupleType) and iterable.partial_fallback.type.fullname == "builtins.tuple" ): return iterator, tuple_fallback(iterable).args[0] else: # Non-tuple iterable. iterable = echk.check_method_call_by_name("__next__", iterator, [], [], context)[0] return iterator, iterable def analyze_range_native_int_type(self, expr: Expression) -> Type | None: """Try to infer native int item type from arguments to range(...). For example, return i64 if the expression is "range(0, i64(n))". Return None if unsuccessful. """ if ( isinstance(expr, CallExpr) and isinstance(expr.callee, RefExpr) and expr.callee.fullname == "builtins.range" and 1 <= len(expr.args) <= 3 and all(kind == ARG_POS for kind in expr.arg_kinds) ): native_int: Type | None = None ok = True for arg in expr.args: argt = get_proper_type(self.lookup_type(arg)) if isinstance(argt, Instance) and argt.type.fullname in MYPYC_NATIVE_INT_NAMES: if native_int is None: native_int = argt elif argt != native_int: ok = False if ok and native_int: return native_int return None def analyze_container_item_type(self, typ: Type) -> Type | None: """Check if a type is a nominal container of a union of such. Return the corresponding container item type. """ typ = get_proper_type(typ) if isinstance(typ, UnionType): types: list[Type] = [] for item in typ.items: c_type = self.analyze_container_item_type(item) if c_type: types.append(c_type) return UnionType.make_union(types) if isinstance(typ, Instance) and typ.type.has_base("typing.Container"): supertype = self.named_type("typing.Container").type super_instance = map_instance_to_supertype(typ, supertype) assert len(super_instance.args) == 1 return super_instance.args[0] if isinstance(typ, TupleType): return self.analyze_container_item_type(tuple_fallback(typ)) return None def analyze_index_variables( self, index: Expression, item_type: Type, infer_lvalue_type: bool, context: Context ) -> None: """Type check or infer for loop or list comprehension index vars.""" self.check_assignment(index, self.temp_node(item_type, context), infer_lvalue_type) def visit_del_stmt(self, s: DelStmt) -> None: if isinstance(s.expr, IndexExpr): e = s.expr m = MemberExpr(e.base, "__delitem__") m.line = s.line m.column = s.column c = CallExpr(m, [e.index], [nodes.ARG_POS], [None]) c.line = s.line c.column = s.column self.expr_checker.accept(c, allow_none_return=True) else: s.expr.accept(self.expr_checker) for elt in flatten(s.expr): if isinstance(elt, NameExpr): self.binder.assign_type( elt, DeletedType(source=elt.name), get_declaration(elt) ) def visit_decorator(self, e: Decorator) -> None: for d in e.decorators: if isinstance(d, RefExpr): if d.fullname == "typing.no_type_check": e.var.type = AnyType(TypeOfAny.special_form) e.var.is_ready = True return self.visit_decorator_inner(e) def visit_decorator_inner( self, e: Decorator, allow_empty: bool = False, skip_first_item: bool = False ) -> None: if self.recurse_into_functions: with self.tscope.function_scope(e.func): self.check_func_item(e.func, name=e.func.name, allow_empty=allow_empty) # Process decorators from the inside out to determine decorated signature, which # may be different from the declared signature. sig: Type = self.function_type(e.func) non_trivial_decorator = False # For settable properties skip the first decorator (that is @foo.setter). for d in reversed(e.decorators[1:] if skip_first_item else e.decorators): if refers_to_fullname(d, "abc.abstractmethod"): # This is a hack to avoid spurious errors because of incomplete type # of @abstractmethod in the test fixtures. continue if refers_to_fullname(d, OVERLOAD_NAMES): if not allow_empty: self.fail(message_registry.MULTIPLE_OVERLOADS_REQUIRED, e) continue non_trivial_decorator = True dec = self.expr_checker.accept(d) temp = self.temp_node(sig, context=d) fullname = None if isinstance(d, RefExpr): fullname = d.fullname or None # if this is an expression like @b.a where b is an object, get the type of b, # so we can pass it the method hook in the plugins object_type: Type | None = None if fullname is None and isinstance(d, MemberExpr) and self.has_type(d.expr): object_type = self.lookup_type(d.expr) fullname = self.expr_checker.method_fullname(object_type, d.name) self.check_for_untyped_decorator(e.func, dec, d) sig, t2 = self.expr_checker.check_call( dec, [temp], [nodes.ARG_POS], e, callable_name=fullname, object_type=object_type ) if non_trivial_decorator: self.check_untyped_after_decorator(sig, e.func) sig = set_callable_name(sig, e.func) e.var.type = sig e.var.is_ready = True if e.func.is_property: if isinstance(sig, CallableType): if len([k for k in sig.arg_kinds if k.is_required()]) > 1: self.msg.fail("Too many arguments for property", e) self.check_incompatible_property_override(e) # For overloaded functions/properties we already checked override for overload as a whole. if allow_empty or skip_first_item: return if e.func.info and not e.is_overload: found_method_base_classes = self.check_method_override(e) if ( e.func.is_explicit_override and not found_method_base_classes and found_method_base_classes is not None # If the class has Any fallback, we can't be certain that a method # is really missing - it might come from unfollowed import. and not e.func.info.fallback_to_any ): self.msg.no_overridable_method(e.func.name, e.func) self.check_explicit_override_decorator(e.func, found_method_base_classes) if e.func.info and e.func.name in ("__init__", "__new__"): if e.type and not isinstance(get_proper_type(e.type), (FunctionLike, AnyType)): self.fail(message_registry.BAD_CONSTRUCTOR_TYPE, e) if e.func.original_def and isinstance(sig, FunctionLike): # Function definition overrides function definition. self.check_func_def_override(e.func, sig) def check_for_untyped_decorator( self, func: FuncDef, dec_type: Type, dec_expr: Expression ) -> None: if ( self.options.disallow_untyped_decorators and is_typed_callable(func.type) and is_untyped_decorator(dec_type) and not self.current_node_deferred ): self.msg.typed_function_untyped_decorator(func.name, dec_expr) def check_incompatible_property_override(self, e: Decorator) -> None: if not e.var.is_settable_property and e.func.info: name = e.func.name for base in e.func.info.mro[1:]: base_attr = base.names.get(name) if not base_attr: continue if ( isinstance(base_attr.node, OverloadedFuncDef) and base_attr.node.is_property and cast(Decorator, base_attr.node.items[0]).var.is_settable_property ): self.fail(message_registry.READ_ONLY_PROPERTY_OVERRIDES_READ_WRITE, e) def visit_with_stmt(self, s: WithStmt) -> None: exceptions_maybe_suppressed = False for expr, target in zip(s.expr, s.target): if s.is_async: exit_ret_type = self.check_async_with_item(expr, target, s.unanalyzed_type is None) else: exit_ret_type = self.check_with_item(expr, target, s.unanalyzed_type is None) # Based on the return type, determine if this context manager 'swallows' # exceptions or not. We determine this using a heuristic based on the # return type of the __exit__ method -- see the discussion in # https://github.com/python/mypy/issues/7214 and the section about context managers # in https://github.com/python/typeshed/blob/main/CONTRIBUTING.md#conventions # for more details. exit_ret_type = get_proper_type(exit_ret_type) if is_literal_type(exit_ret_type, "builtins.bool", False): continue if is_literal_type(exit_ret_type, "builtins.bool", True) or ( isinstance(exit_ret_type, Instance) and exit_ret_type.type.fullname == "builtins.bool" and state.strict_optional ): # Note: if strict-optional is disabled, this bool instance # could actually be an Optional[bool]. exceptions_maybe_suppressed = True if exceptions_maybe_suppressed: # Treat this 'with' block in the same way we'd treat a 'try: BODY; except: pass' # block. This means control flow can continue after the 'with' even if the 'with' # block immediately returns. with self.binder.frame_context(can_skip=True, try_frame=True): self.accept(s.body) else: self.accept(s.body) def check_untyped_after_decorator(self, typ: Type, func: FuncDef) -> None: if not self.options.disallow_any_decorated or self.is_stub: return if mypy.checkexpr.has_any_type(typ): self.msg.untyped_decorated_function(typ, func) def check_async_with_item( self, expr: Expression, target: Expression | None, infer_lvalue_type: bool ) -> Type: echk = self.expr_checker ctx = echk.accept(expr) obj = echk.check_method_call_by_name("__aenter__", ctx, [], [], expr)[0] obj = echk.check_awaitable_expr( obj, expr, message_registry.INCOMPATIBLE_TYPES_IN_ASYNC_WITH_AENTER ) if target: self.check_assignment(target, self.temp_node(obj, expr), infer_lvalue_type) arg = self.temp_node(AnyType(TypeOfAny.special_form), expr) res, _ = echk.check_method_call_by_name( "__aexit__", ctx, [arg] * 3, [nodes.ARG_POS] * 3, expr ) return echk.check_awaitable_expr( res, expr, message_registry.INCOMPATIBLE_TYPES_IN_ASYNC_WITH_AEXIT ) def check_with_item( self, expr: Expression, target: Expression | None, infer_lvalue_type: bool ) -> Type: echk = self.expr_checker ctx = echk.accept(expr) obj = echk.check_method_call_by_name("__enter__", ctx, [], [], expr)[0] if target: self.check_assignment(target, self.temp_node(obj, expr), infer_lvalue_type) arg = self.temp_node(AnyType(TypeOfAny.special_form), expr) res, _ = echk.check_method_call_by_name( "__exit__", ctx, [arg] * 3, [nodes.ARG_POS] * 3, expr ) return res def visit_break_stmt(self, s: BreakStmt) -> None: self.binder.handle_break() def visit_continue_stmt(self, s: ContinueStmt) -> None: self.binder.handle_continue() return def visit_match_stmt(self, s: MatchStmt) -> None: named_subject: Expression if isinstance(s.subject, CallExpr): # Create a dummy subject expression to handle cases where a match statement's subject # is not a literal value. This lets us correctly narrow types and check exhaustivity # This is hack! if s.subject_dummy is None: id = s.subject.callee.fullname if isinstance(s.subject.callee, RefExpr) else "" name = "dummy-match-" + id v = Var(name) s.subject_dummy = NameExpr(name) s.subject_dummy.node = v named_subject = s.subject_dummy else: named_subject = s.subject with self.binder.frame_context(can_skip=False, fall_through=0): subject_type = get_proper_type(self.expr_checker.accept(s.subject)) if isinstance(subject_type, DeletedType): self.msg.deleted_as_rvalue(subject_type, s) # We infer types of patterns twice. The first pass is used # to infer the types of capture variables. The type of a # capture variable may depend on multiple patterns (it # will be a union of all capture types). This pass ignores # guard expressions. pattern_types = [self.pattern_checker.accept(p, subject_type) for p in s.patterns] type_maps: list[TypeMap] = [t.captures for t in pattern_types] inferred_types = self.infer_variable_types_from_type_maps(type_maps) # The second pass narrows down the types and type checks bodies. for p, g, b in zip(s.patterns, s.guards, s.bodies): current_subject_type = self.expr_checker.narrow_type_from_binder( named_subject, subject_type ) pattern_type = self.pattern_checker.accept(p, current_subject_type) with self.binder.frame_context(can_skip=True, fall_through=2): if b.is_unreachable or isinstance( get_proper_type(pattern_type.type), UninhabitedType ): self.push_type_map(None, from_assignment=False) else_map: TypeMap = {} else: pattern_map, else_map = conditional_types_to_typemaps( named_subject, pattern_type.type, pattern_type.rest_type ) pattern_map = self.propagate_up_typemap_info(pattern_map) else_map = self.propagate_up_typemap_info(else_map) self.remove_capture_conflicts(pattern_type.captures, inferred_types) self.push_type_map(pattern_map, from_assignment=False) if pattern_map: for expr, typ in pattern_map.items(): self.push_type_map( self._get_recursive_sub_patterns_map(expr, typ), from_assignment=False, ) self.push_type_map(pattern_type.captures, from_assignment=False) if g is not None: with self.binder.frame_context(can_skip=False, fall_through=3): gt = get_proper_type(self.expr_checker.accept(g)) if isinstance(gt, DeletedType): self.msg.deleted_as_rvalue(gt, s) guard_map, guard_else_map = self.find_isinstance_check(g) else_map = or_conditional_maps(else_map, guard_else_map) # If the guard narrowed the subject, copy the narrowed types over if isinstance(p, AsPattern): case_target = p.pattern or p.name if isinstance(case_target, NameExpr): for type_map in (guard_map, else_map): if not type_map: continue for expr in list(type_map): if not ( isinstance(expr, NameExpr) and expr.fullname == case_target.fullname ): continue type_map[named_subject] = type_map[expr] self.push_type_map(guard_map, from_assignment=False) self.accept(b) else: self.accept(b) self.push_type_map(else_map, from_assignment=False) # This is needed due to a quirk in frame_context. Without it types will stay narrowed # after the match. with self.binder.frame_context(can_skip=False, fall_through=2): pass def _get_recursive_sub_patterns_map( self, expr: Expression, typ: Type ) -> dict[Expression, Type]: sub_patterns_map: dict[Expression, Type] = {} typ_ = get_proper_type(typ) if isinstance(expr, TupleExpr) and isinstance(typ_, TupleType): # When matching a tuple expression with a sequence pattern, narrow individual tuple items assert len(expr.items) == len(typ_.items) for item_expr, item_typ in zip(expr.items, typ_.items): sub_patterns_map[item_expr] = item_typ sub_patterns_map.update(self._get_recursive_sub_patterns_map(item_expr, item_typ)) return sub_patterns_map def infer_variable_types_from_type_maps( self, type_maps: list[TypeMap] ) -> dict[SymbolNode, Type]: # Type maps may contain variables inherited from previous code which are not # necessary `Var`s (e.g. a function defined earlier with the same name). all_captures: dict[SymbolNode, list[tuple[NameExpr, Type]]] = defaultdict(list) for tm in type_maps: if tm is not None: for expr, typ in tm.items(): if isinstance(expr, NameExpr): node = expr.node assert node is not None all_captures[node].append((expr, typ)) inferred_types: dict[SymbolNode, Type] = {} for var, captures in all_captures.items(): already_exists = False types: list[Type] = [] for expr, typ in captures: types.append(typ) previous_type, _, _ = self.check_lvalue(expr) if previous_type is not None: already_exists = True if self.check_subtype( typ, previous_type, expr, msg=message_registry.INCOMPATIBLE_TYPES_IN_CAPTURE, subtype_label="pattern captures type", supertype_label="variable has type", ): inferred_types[var] = previous_type if not already_exists: new_type = UnionType.make_union(types) # Infer the union type at the first occurrence first_occurrence, _ = captures[0] # If it didn't exist before ``match``, it's a Var. assert isinstance(var, Var) inferred_types[var] = new_type self.infer_variable_type(var, first_occurrence, new_type, first_occurrence) return inferred_types def remove_capture_conflicts( self, type_map: TypeMap, inferred_types: dict[SymbolNode, Type] ) -> None: if type_map: for expr, typ in list(type_map.items()): if isinstance(expr, NameExpr): node = expr.node if node not in inferred_types or not is_subtype(typ, inferred_types[node]): del type_map[expr] def visit_type_alias_stmt(self, o: TypeAliasStmt) -> None: if o.alias_node: self.check_typevar_defaults(o.alias_node.alias_tvars) with self.msg.filter_errors(): self.expr_checker.accept(o.value) def make_fake_typeinfo( self, curr_module_fullname: str, class_gen_name: str, class_short_name: str, bases: list[Instance], ) -> tuple[ClassDef, TypeInfo]: # Build the fake ClassDef and TypeInfo together. # The ClassDef is full of lies and doesn't actually contain a body. # Use format_bare to generate a nice name for error messages. # We skip fully filling out a handful of TypeInfo fields because they # should be irrelevant for a generated type like this: # is_protocol, protocol_members, is_abstract cdef = ClassDef(class_short_name, Block([])) cdef.fullname = curr_module_fullname + "." + class_gen_name info = TypeInfo(SymbolTable(), cdef, curr_module_fullname) cdef.info = info info.bases = bases calculate_mro(info) info.metaclass_type = info.calculate_metaclass_type() return cdef, info def intersect_instances( self, instances: tuple[Instance, Instance], errors: list[tuple[str, str]] ) -> Instance | None: """Try creating an ad-hoc intersection of the given instances. Note that this function does *not* try and create a full-fledged intersection type. Instead, it returns an instance of a new ad-hoc subclass of the given instances. This is mainly useful when you need a way of representing some theoretical subclass of the instances the user may be trying to use the generated intersection can serve as a placeholder. This function will create a fresh subclass the first time you call it. So this means calling `self.intersect_intersection([inst_1, inst_2], ctx)` twice will return the same subclass of inst_1 and inst_2. Returns None if creating the subclass is impossible (e.g. due to MRO errors or incompatible signatures). If we do successfully create a subclass, its TypeInfo will automatically be added to the global scope. """ curr_module = self.scope.stack[0] assert isinstance(curr_module, MypyFile) # First, retry narrowing while allowing promotions (they are disabled by default # for isinstance() checks, etc). This way we will still type-check branches like # x: complex = 1 # if isinstance(x, int): # ... left, right = instances if is_proper_subtype(left, right, ignore_promotions=False): return left if is_proper_subtype(right, left, ignore_promotions=False): return right def _get_base_classes(instances_: tuple[Instance, Instance]) -> list[Instance]: base_classes_ = [] for inst in instances_: if inst.type.is_intersection: expanded = inst.type.bases else: expanded = [inst] for expanded_inst in expanded: base_classes_.append(expanded_inst) return base_classes_ def _make_fake_typeinfo_and_full_name( base_classes_: list[Instance], curr_module_: MypyFile, options: Options ) -> tuple[TypeInfo, str]: names = [format_type_bare(x, options=options, verbosity=2) for x in base_classes_] name = f"" if (symbol := curr_module_.names.get(name)) is not None: assert isinstance(symbol.node, TypeInfo) return symbol.node, name cdef, info_ = self.make_fake_typeinfo(curr_module_.fullname, name, name, base_classes_) return info_, name base_classes = _get_base_classes(instances) # We use the pretty_names_list for error messages but for the real name that goes # into the symbol table because it is not specific enough. pretty_names_list = pretty_seq( format_type_distinctly(*base_classes, options=self.options, bare=True), "and" ) new_errors = [] for base in base_classes: if base.type.is_final: new_errors.append((pretty_names_list, f'"{base.type.name}" is final')) if new_errors: errors.extend(new_errors) return None try: info, full_name = _make_fake_typeinfo_and_full_name( base_classes, curr_module, self.options ) with self.msg.filter_errors() as local_errors: self.check_multiple_inheritance(info) if local_errors.has_new_errors(): # "class A(B, C)" unsafe, now check "class A(C, B)": base_classes = _get_base_classes(instances[::-1]) info, full_name = _make_fake_typeinfo_and_full_name( base_classes, curr_module, self.options ) with self.msg.filter_errors() as local_errors: self.check_multiple_inheritance(info) info.is_intersection = True except MroError: errors.append((pretty_names_list, "would have inconsistent method resolution order")) return None if local_errors.has_new_errors(): errors.append((pretty_names_list, "would have incompatible method signatures")) return None curr_module.names[full_name] = SymbolTableNode(GDEF, info) return Instance(info, [], extra_attrs=instances[0].extra_attrs or instances[1].extra_attrs) def intersect_instance_callable(self, typ: Instance, callable_type: CallableType) -> Instance: """Creates a fake type that represents the intersection of an Instance and a CallableType. It operates by creating a bare-minimum dummy TypeInfo that subclasses type and adds a __call__ method matching callable_type. """ # In order for this to work in incremental mode, the type we generate needs to # have a valid fullname and a corresponding entry in a symbol table. We generate # a unique name inside the symbol table of the current module. cur_module = self.scope.stack[0] assert isinstance(cur_module, MypyFile) gen_name = gen_unique_name(f"", cur_module.names) # Synthesize a fake TypeInfo short_name = format_type_bare(typ, self.options) cdef, info = self.make_fake_typeinfo(cur_module.fullname, gen_name, short_name, [typ]) # Build up a fake FuncDef so we can populate the symbol table. func_def = FuncDef("__call__", [], Block([]), callable_type) func_def._fullname = cdef.fullname + ".__call__" func_def.info = info info.names["__call__"] = SymbolTableNode(MDEF, func_def) cur_module.names[gen_name] = SymbolTableNode(GDEF, info) return Instance(info, [], extra_attrs=typ.extra_attrs) def make_fake_callable(self, typ: Instance) -> Instance: """Produce a new type that makes type Callable with a generic callable type.""" fallback = self.named_type("builtins.function") callable_type = CallableType( [AnyType(TypeOfAny.explicit), AnyType(TypeOfAny.explicit)], [nodes.ARG_STAR, nodes.ARG_STAR2], [None, None], ret_type=AnyType(TypeOfAny.explicit), fallback=fallback, is_ellipsis_args=True, ) return self.intersect_instance_callable(typ, callable_type) def partition_by_callable( self, typ: Type, unsound_partition: bool ) -> tuple[list[Type], list[Type]]: """Partitions a type into callable subtypes and uncallable subtypes. Thus, given: `callables, uncallables = partition_by_callable(type)` If we assert `callable(type)` then `type` has type Union[*callables], and If we assert `not callable(type)` then `type` has type Union[*uncallables] If unsound_partition is set, assume that anything that is not clearly callable is in fact not callable. Otherwise we generate a new subtype that *is* callable. Guaranteed to not return [], []. """ typ = get_proper_type(typ) if isinstance(typ, (FunctionLike, TypeType)): return [typ], [] if isinstance(typ, AnyType): return [typ], [typ] if isinstance(typ, NoneType): return [], [typ] if isinstance(typ, UnionType): callables = [] uncallables = [] for subtype in typ.items: # Use unsound_partition when handling unions in order to # allow the expected type discrimination. subcallables, subuncallables = self.partition_by_callable( subtype, unsound_partition=True ) callables.extend(subcallables) uncallables.extend(subuncallables) return callables, uncallables if isinstance(typ, TypeVarType): # We could do better probably? # Refine the type variable's bound as our type in the case that # callable() is true. This unfortunately loses the information that # the type is a type variable in that branch. # This matches what is done for isinstance, but it may be possible to # do better. # If it is possible for the false branch to execute, return the original # type to avoid losing type information. callables, uncallables = self.partition_by_callable( erase_to_union_or_bound(typ), unsound_partition ) uncallables = [typ] if uncallables else [] return callables, uncallables # A TupleType is callable if its fallback is, but needs special handling # when we dummy up a new type. ityp = typ if isinstance(typ, TupleType): ityp = tuple_fallback(typ) if isinstance(ityp, Instance): method = ityp.type.get_method("__call__") if method and method.type: callables, uncallables = self.partition_by_callable( method.type, unsound_partition=False ) if callables and not uncallables: # Only consider the type callable if its __call__ method is # definitely callable. return [typ], [] if not unsound_partition: fake = self.make_fake_callable(ityp) if isinstance(typ, TupleType): fake.type.tuple_type = TupleType(typ.items, fake) return [fake.type.tuple_type], [typ] return [fake], [typ] if unsound_partition: return [], [typ] else: # We don't know how properly make the type callable. return [typ], [typ] def conditional_callable_type_map( self, expr: Expression, current_type: Type | None ) -> tuple[TypeMap, TypeMap]: """Takes in an expression and the current type of the expression. Returns a 2-tuple: The first element is a map from the expression to the restricted type if it were callable. The second element is a map from the expression to the type it would hold if it weren't callable. """ if not current_type: return {}, {} if isinstance(get_proper_type(current_type), AnyType): return {}, {} callables, uncallables = self.partition_by_callable(current_type, unsound_partition=False) if callables and uncallables: callable_map = {expr: UnionType.make_union(callables)} if callables else None uncallable_map = {expr: UnionType.make_union(uncallables)} if uncallables else None return callable_map, uncallable_map elif callables: return {}, None return None, {} def conditional_types_for_iterable( self, item_type: Type, iterable_type: Type ) -> tuple[Type | None, Type | None]: """ Narrows the type of `iterable_type` based on the type of `item_type`. For now, we only support narrowing unions of TypedDicts based on left operand being literal string(s). """ if_types: list[Type] = [] else_types: list[Type] = [] iterable_type = get_proper_type(iterable_type) if isinstance(iterable_type, UnionType): possible_iterable_types = get_proper_types(iterable_type.relevant_items()) else: possible_iterable_types = [iterable_type] item_str_literals = try_getting_str_literals_from_type(item_type) for possible_iterable_type in possible_iterable_types: if item_str_literals and isinstance(possible_iterable_type, TypedDictType): for key in item_str_literals: if key in possible_iterable_type.required_keys: if_types.append(possible_iterable_type) elif ( key in possible_iterable_type.items or not possible_iterable_type.is_final ): if_types.append(possible_iterable_type) else_types.append(possible_iterable_type) else: else_types.append(possible_iterable_type) else: if_types.append(possible_iterable_type) else_types.append(possible_iterable_type) return ( UnionType.make_union(if_types) if if_types else None, UnionType.make_union(else_types) if else_types else None, ) def _is_truthy_type(self, t: ProperType) -> bool: return ( ( isinstance(t, Instance) and bool(t.type) and not t.type.has_readable_member("__bool__") and not t.type.has_readable_member("__len__") and t.type.fullname != "builtins.object" ) or isinstance(t, FunctionLike) or ( isinstance(t, UnionType) and all(self._is_truthy_type(t) for t in get_proper_types(t.items)) ) ) def check_for_truthy_type(self, t: Type, expr: Expression) -> None: """ Check if a type can have a truthy value. Used in checks like:: if x: # <--- not x # <--- """ if not state.strict_optional: return # if everything can be None, all bets are off t = get_proper_type(t) if not self._is_truthy_type(t): return def format_expr_type() -> str: typ = format_type(t, self.options) if isinstance(expr, MemberExpr): return f'Member "{expr.name}" has type {typ}' elif isinstance(expr, RefExpr) and expr.fullname: return f'"{expr.fullname}" has type {typ}' elif isinstance(expr, CallExpr): if isinstance(expr.callee, MemberExpr): return f'"{expr.callee.name}" returns {typ}' elif isinstance(expr.callee, RefExpr) and expr.callee.fullname: return f'"{expr.callee.fullname}" returns {typ}' return f"Call returns {typ}" else: return f"Expression has type {typ}" def get_expr_name() -> str: if isinstance(expr, (NameExpr, MemberExpr)): return f'"{expr.name}"' else: # return type if expr has no name return format_type(t, self.options) if isinstance(t, FunctionLike): self.fail(message_registry.FUNCTION_ALWAYS_TRUE.format(get_expr_name()), expr) elif isinstance(t, UnionType): self.fail(message_registry.TYPE_ALWAYS_TRUE_UNIONTYPE.format(format_expr_type()), expr) elif isinstance(t, Instance) and t.type.fullname == "typing.Iterable": _, info = self.make_fake_typeinfo("typing", "Collection", "Collection", []) self.fail( message_registry.ITERABLE_ALWAYS_TRUE.format( format_expr_type(), format_type(Instance(info, t.args), self.options) ), expr, ) else: self.fail(message_registry.TYPE_ALWAYS_TRUE.format(format_expr_type()), expr) def find_type_equals_check( self, node: ComparisonExpr, expr_indices: list[int] ) -> tuple[TypeMap, TypeMap]: """Narrow types based on any checks of the type ``type(x) == T`` Args: node: The node that might contain the comparison expr_indices: The list of indices of expressions in ``node`` that are being compared """ def is_type_call(expr: CallExpr) -> bool: """Is expr a call to type with one argument?""" return refers_to_fullname(expr.callee, "builtins.type") and len(expr.args) == 1 # exprs that are being passed into type exprs_in_type_calls: list[Expression] = [] # type that is being compared to type(expr) type_being_compared: list[TypeRange] | None = None # whether the type being compared to is final is_final = False for index in expr_indices: expr = node.operands[index] if isinstance(expr, CallExpr) and is_type_call(expr): exprs_in_type_calls.append(expr.args[0]) else: current_type = self.get_isinstance_type(expr) if current_type is None: continue if type_being_compared is not None: # It doesn't really make sense to have several types being # compared to the output of type (like type(x) == int == str) # because whether that's true is solely dependent on what the # types being compared are, so we don't try to narrow types any # further because we can't really get any information about the # type of x from that check return {}, {} else: if isinstance(expr, RefExpr) and isinstance(expr.node, TypeInfo): is_final = expr.node.is_final type_being_compared = current_type if not exprs_in_type_calls: return {}, {} if_maps: list[TypeMap] = [] else_maps: list[TypeMap] = [] for expr in exprs_in_type_calls: current_if_type, current_else_type = self.conditional_types_with_intersection( self.lookup_type(expr), type_being_compared, expr ) current_if_map, current_else_map = conditional_types_to_typemaps( expr, current_if_type, current_else_type ) if_maps.append(current_if_map) else_maps.append(current_else_map) def combine_maps(list_maps: list[TypeMap]) -> TypeMap: """Combine all typemaps in list_maps into one typemap""" if all(m is None for m in list_maps): return None result_map = {} for d in list_maps: if d is not None: result_map.update(d) return result_map if_map = combine_maps(if_maps) # type(x) == T is only true when x has the same type as T, meaning # that it can be false if x is an instance of a subclass of T. That means # we can't do any narrowing in the else case unless T is final, in which # case T can't be subclassed if is_final: else_map = combine_maps(else_maps) else: else_map = {} return if_map, else_map def find_isinstance_check( self, node: Expression, *, in_boolean_context: bool = True ) -> tuple[TypeMap, TypeMap]: """Find any isinstance checks (within a chain of ands). Includes implicit and explicit checks for None and calls to callable. Also includes TypeGuard and TypeIs functions. Return value is a map of variables to their types if the condition is true and a map of variables to their types if the condition is false. If either of the values in the tuple is None, then that particular branch can never occur. If `in_boolean_context=True` is passed, it means that we handle a walrus expression. We treat rhs values in expressions like `(a := A())` specially: for example, some errors are suppressed. May return {}, {}. Can return None, None in situations involving NoReturn. """ if_map, else_map = self.find_isinstance_check_helper( node, in_boolean_context=in_boolean_context ) new_if_map = self.propagate_up_typemap_info(if_map) new_else_map = self.propagate_up_typemap_info(else_map) return new_if_map, new_else_map def find_isinstance_check_helper( self, node: Expression, *, in_boolean_context: bool = True ) -> tuple[TypeMap, TypeMap]: if is_true_literal(node): return {}, None if is_false_literal(node): return None, {} if isinstance(node, CallExpr) and len(node.args) != 0: expr = collapse_walrus(node.args[0]) if refers_to_fullname(node.callee, "builtins.isinstance"): if len(node.args) != 2: # the error will be reported elsewhere return {}, {} if literal(expr) == LITERAL_TYPE: return conditional_types_to_typemaps( expr, *self.conditional_types_with_intersection( self.lookup_type(expr), self.get_isinstance_type(node.args[1]), expr ), ) elif refers_to_fullname(node.callee, "builtins.issubclass"): if len(node.args) != 2: # the error will be reported elsewhere return {}, {} if literal(expr) == LITERAL_TYPE: return self.infer_issubclass_maps(node, expr) elif refers_to_fullname(node.callee, "builtins.callable"): if len(node.args) != 1: # the error will be reported elsewhere return {}, {} if literal(expr) == LITERAL_TYPE: vartype = self.lookup_type(expr) return self.conditional_callable_type_map(expr, vartype) elif refers_to_fullname(node.callee, "builtins.hasattr"): if len(node.args) != 2: # the error will be reported elsewhere return {}, {} attr = try_getting_str_literals(node.args[1], self.lookup_type(node.args[1])) if literal(expr) == LITERAL_TYPE and attr and len(attr) == 1: return self.hasattr_type_maps(expr, self.lookup_type(expr), attr[0]) elif isinstance(node.callee, RefExpr): if node.callee.type_guard is not None or node.callee.type_is is not None: # TODO: Follow *args, **kwargs if node.arg_kinds[0] != nodes.ARG_POS: # the first argument might be used as a kwarg called_type = get_proper_type(self.lookup_type(node.callee)) # TODO: there are some more cases in check_call() to handle. if isinstance(called_type, Instance): call = find_member( "__call__", called_type, called_type, is_operator=True ) if call is not None: called_type = get_proper_type(call) # *assuming* the overloaded function is correct, there's a couple cases: # 1) The first argument has different names, but is pos-only. We don't # care about this case, the argument must be passed positionally. # 2) The first argument allows keyword reference, therefore must be the # same between overloads. if isinstance(called_type, (CallableType, Overloaded)): name = called_type.items[0].arg_names[0] if name in node.arg_names: idx = node.arg_names.index(name) # we want the idx-th variable to be narrowed expr = collapse_walrus(node.args[idx]) else: kind = ( "guard" if node.callee.type_guard is not None else "narrower" ) self.fail( message_registry.TYPE_GUARD_POS_ARG_REQUIRED.format(kind), node ) return {}, {} if literal(expr) == LITERAL_TYPE: # Note: we wrap the target type, so that we can special case later. # Namely, for isinstance() we use a normal meet, while TypeGuard is # considered "always right" (i.e. even if the types are not overlapping). # Also note that a care must be taken to unwrap this back at read places # where we use this to narrow down declared type. if node.callee.type_guard is not None: return {expr: TypeGuardedType(node.callee.type_guard)}, {} else: assert node.callee.type_is is not None return conditional_types_to_typemaps( expr, *self.conditional_types_with_intersection( self.lookup_type(expr), [TypeRange(node.callee.type_is, is_upper_bound=False)], expr, ), ) elif isinstance(node, ComparisonExpr): return self.comparison_type_narrowing_helper(node) elif isinstance(node, AssignmentExpr): if_map: dict[Expression, Type] | None else_map: dict[Expression, Type] | None if_map = {} else_map = {} if_assignment_map, else_assignment_map = self.find_isinstance_check(node.target) if if_assignment_map is not None: if_map.update(if_assignment_map) if else_assignment_map is not None: else_map.update(else_assignment_map) if_condition_map, else_condition_map = self.find_isinstance_check( node.value, in_boolean_context=False ) if if_condition_map is not None: if_map.update(if_condition_map) if else_condition_map is not None: else_map.update(else_condition_map) return ( (None if if_assignment_map is None or if_condition_map is None else if_map), (None if else_assignment_map is None or else_condition_map is None else else_map), ) elif isinstance(node, OpExpr) and node.op == "and": left_if_vars, left_else_vars = self.find_isinstance_check(node.left) right_if_vars, right_else_vars = self.find_isinstance_check(node.right) # (e1 and e2) is true if both e1 and e2 are true, # and false if at least one of e1 and e2 is false. return ( and_conditional_maps(left_if_vars, right_if_vars), # Note that if left else type is Any, we can't add any additional # types to it, since the right maps were computed assuming # the left is True, which may be not the case in the else branch. or_conditional_maps(left_else_vars, right_else_vars, coalesce_any=True), ) elif isinstance(node, OpExpr) and node.op == "or": left_if_vars, left_else_vars = self.find_isinstance_check(node.left) right_if_vars, right_else_vars = self.find_isinstance_check(node.right) # (e1 or e2) is true if at least one of e1 or e2 is true, # and false if both e1 and e2 are false. return ( or_conditional_maps(left_if_vars, right_if_vars), and_conditional_maps(left_else_vars, right_else_vars), ) elif isinstance(node, UnaryExpr) and node.op == "not": left, right = self.find_isinstance_check(node.expr) return right, left elif ( literal(node) == LITERAL_TYPE and self.has_type(node) and self.can_be_narrowed_with_len(self.lookup_type(node)) # Only translate `if x` to `if len(x) > 0` when possible. and not custom_special_method(self.lookup_type(node), "__bool__") and self.options.strict_optional ): # Combine a `len(x) > 0` check with the default logic below. yes_type, no_type = self.narrow_with_len(self.lookup_type(node), ">", 0) if yes_type is not None: yes_type = true_only(yes_type) else: yes_type = UninhabitedType() if no_type is not None: no_type = false_only(no_type) else: no_type = UninhabitedType() if_map = {node: yes_type} if not isinstance(yes_type, UninhabitedType) else None else_map = {node: no_type} if not isinstance(no_type, UninhabitedType) else None return if_map, else_map # Restrict the type of the variable to True-ish/False-ish in the if and else branches # respectively original_vartype = self.lookup_type(node) if in_boolean_context: # We don't check `:=` values in expressions like `(a := A())`, # because they produce two error messages. self.check_for_truthy_type(original_vartype, node) vartype = try_expanding_sum_type_to_union(original_vartype, "builtins.bool") if_type = true_only(vartype) else_type = false_only(vartype) if_map = {node: if_type} if not isinstance(if_type, UninhabitedType) else None else_map = {node: else_type} if not isinstance(else_type, UninhabitedType) else None return if_map, else_map def comparison_type_narrowing_helper(self, node: ComparisonExpr) -> tuple[TypeMap, TypeMap]: """Infer type narrowing from a comparison expression.""" # Step 1: Obtain the types of each operand and whether or not we can # narrow their types. (For example, we shouldn't try narrowing the # types of literal string or enum expressions). operands = [collapse_walrus(x) for x in node.operands] operand_types = [] narrowable_operand_index_to_hash = {} for i, expr in enumerate(operands): if not self.has_type(expr): return {}, {} expr_type = self.lookup_type(expr) operand_types.append(expr_type) if ( literal(expr) == LITERAL_TYPE and not is_literal_none(expr) and not self.is_literal_enum(expr) ): h = literal_hash(expr) if h is not None: narrowable_operand_index_to_hash[i] = h # Step 2: Group operands chained by either the 'is' or '==' operands # together. For all other operands, we keep them in groups of size 2. # So the expression: # # x0 == x1 == x2 < x3 < x4 is x5 is x6 is not x7 is not x8 # # ...is converted into the simplified operator list: # # [("==", [0, 1, 2]), ("<", [2, 3]), ("<", [3, 4]), # ("is", [4, 5, 6]), ("is not", [6, 7]), ("is not", [7, 8])] # # We group identity/equality expressions so we can propagate information # we discover about one operand across the entire chain. We don't bother # handling 'is not' and '!=' chains in a special way: those are very rare # in practice. simplified_operator_list = group_comparison_operands( node.pairwise(), narrowable_operand_index_to_hash, {"==", "is"} ) # Step 3: Analyze each group and infer more precise type maps for each # assignable operand, if possible. We combine these type maps together # in the final step. partial_type_maps = [] for operator, expr_indices in simplified_operator_list: if operator in {"is", "is not", "==", "!="}: if_map, else_map = self.equality_type_narrowing_helper( node, operator, operands, operand_types, expr_indices, narrowable_operand_index_to_hash, ) elif operator in {"in", "not in"}: assert len(expr_indices) == 2 left_index, right_index = expr_indices item_type = operand_types[left_index] iterable_type = operand_types[right_index] if_map, else_map = {}, {} if left_index in narrowable_operand_index_to_hash: # We only try and narrow away 'None' for now if is_overlapping_none(item_type): collection_item_type = get_proper_type(builtin_item_type(iterable_type)) if ( collection_item_type is not None and not is_overlapping_none(collection_item_type) and not ( isinstance(collection_item_type, Instance) and collection_item_type.type.fullname == "builtins.object" ) and is_overlapping_erased_types(item_type, collection_item_type) ): if_map[operands[left_index]] = remove_optional(item_type) if right_index in narrowable_operand_index_to_hash: if_type, else_type = self.conditional_types_for_iterable( item_type, iterable_type ) expr = operands[right_index] if if_type is None: if_map = None else: if_map[expr] = if_type if else_type is None: else_map = None else: else_map[expr] = else_type else: if_map = {} else_map = {} if operator in {"is not", "!=", "not in"}: if_map, else_map = else_map, if_map partial_type_maps.append((if_map, else_map)) # If we have found non-trivial restrictions from the regular comparisons, # then return soon. Otherwise try to infer restrictions involving `len(x)`. # TODO: support regular and len() narrowing in the same chain. if any(m != ({}, {}) for m in partial_type_maps): return reduce_conditional_maps(partial_type_maps) else: # Use meet for `and` maps to get correct results for chained checks # like `if 1 < len(x) < 4: ...` return reduce_conditional_maps(self.find_tuple_len_narrowing(node), use_meet=True) def equality_type_narrowing_helper( self, node: ComparisonExpr, operator: str, operands: list[Expression], operand_types: list[Type], expr_indices: list[int], narrowable_operand_index_to_hash: dict[int, tuple[Key, ...]], ) -> tuple[TypeMap, TypeMap]: """Calculate type maps for '==', '!=', 'is' or 'is not' expression.""" # is_valid_target: # Controls which types we're allowed to narrow exprs to. Note that # we cannot use 'is_literal_type_like' in both cases since doing # 'x = 10000 + 1; x is 10001' is not always True in all Python # implementations. # # coerce_only_in_literal_context: # If true, coerce types into literal types only if one or more of # the provided exprs contains an explicit Literal type. This could # technically be set to any arbitrary value, but it seems being liberal # with narrowing when using 'is' and conservative when using '==' seems # to break the least amount of real-world code. # # should_narrow_by_identity: # Set to 'false' only if the user defines custom __eq__ or __ne__ methods # that could cause identity-based narrowing to produce invalid results. if operator in {"is", "is not"}: is_valid_target: Callable[[Type], bool] = is_singleton_type coerce_only_in_literal_context = False should_narrow_by_identity = True else: def is_exactly_literal_type(t: Type) -> bool: return isinstance(get_proper_type(t), LiteralType) def has_no_custom_eq_checks(t: Type) -> bool: return not custom_special_method( t, "__eq__", check_all=False ) and not custom_special_method(t, "__ne__", check_all=False) is_valid_target = is_exactly_literal_type coerce_only_in_literal_context = True expr_types = [operand_types[i] for i in expr_indices] should_narrow_by_identity = all( map(has_no_custom_eq_checks, expr_types) ) and not is_ambiguous_mix_of_enums(expr_types) if_map: TypeMap = {} else_map: TypeMap = {} if should_narrow_by_identity: if_map, else_map = self.refine_identity_comparison_expression( operands, operand_types, expr_indices, narrowable_operand_index_to_hash.keys(), is_valid_target, coerce_only_in_literal_context, ) if if_map == {} and else_map == {}: if_map, else_map = self.refine_away_none_in_comparison( operands, operand_types, expr_indices, narrowable_operand_index_to_hash.keys() ) # If we haven't been able to narrow types yet, we might be dealing with a # explicit type(x) == some_type check if if_map == {} and else_map == {}: if_map, else_map = self.find_type_equals_check(node, expr_indices) return if_map, else_map def propagate_up_typemap_info(self, new_types: TypeMap) -> TypeMap: """Attempts refining parent expressions of any MemberExpr or IndexExprs in new_types. Specifically, this function accepts two mappings of expression to original types: the original mapping (existing_types), and a new mapping (new_types) intended to update the original. This function iterates through new_types and attempts to use the information to try refining any parent types that happen to be unions. For example, suppose there are two types "A = Tuple[int, int]" and "B = Tuple[str, str]". Next, suppose that 'new_types' specifies the expression 'foo[0]' has a refined type of 'int' and that 'foo' was previously deduced to be of type Union[A, B]. Then, this function will observe that since A[0] is an int and B[0] is not, the type of 'foo' can be further refined from Union[A, B] into just B. We perform this kind of "parent narrowing" for member lookup expressions and indexing expressions into tuples, namedtuples, and typeddicts. We repeat this narrowing recursively if the parent is also a "lookup expression". So for example, if we have the expression "foo['bar'].baz[0]", we'd potentially end up refining types for the expressions "foo", "foo['bar']", and "foo['bar'].baz". We return the newly refined map. This map is guaranteed to be a superset of 'new_types'. """ if new_types is None: return None output_map = {} for expr, expr_type in new_types.items(): # The original inferred type should always be present in the output map, of course output_map[expr] = expr_type # Next, try using this information to refine the parent types, if applicable. new_mapping = self.refine_parent_types(expr, expr_type) for parent_expr, proposed_parent_type in new_mapping.items(): # We don't try inferring anything if we've already inferred something for # the parent expression. # TODO: Consider picking the narrower type instead of always discarding this? if parent_expr in new_types: continue output_map[parent_expr] = proposed_parent_type return output_map def refine_parent_types(self, expr: Expression, expr_type: Type) -> Mapping[Expression, Type]: """Checks if the given expr is a 'lookup operation' into a union and iteratively refines the parent types based on the 'expr_type'. For example, if 'expr' is an expression like 'a.b.c.d', we'll potentially return refined types for expressions 'a', 'a.b', and 'a.b.c'. For more details about what a 'lookup operation' is and how we use the expr_type to refine the parent types of lookup_expr, see the docstring in 'propagate_up_typemap_info'. """ output: dict[Expression, Type] = {} # Note: parent_expr and parent_type are progressively refined as we crawl up the # parent lookup chain. while True: # First, check if this expression is one that's attempting to # "lookup" some key in the parent type. If so, save the parent type # and create function that will try replaying the same lookup # operation against arbitrary types. if isinstance(expr, MemberExpr): parent_expr = collapse_walrus(expr.expr) parent_type = self.lookup_type_or_none(parent_expr) member_name = expr.name def replay_lookup(new_parent_type: ProperType) -> Type | None: with self.msg.filter_errors() as w: member_type = analyze_member_access( name=member_name, typ=new_parent_type, context=parent_expr, is_lvalue=False, is_super=False, is_operator=False, original_type=new_parent_type, chk=self, in_literal_context=False, ) if w.has_new_errors(): return None else: return member_type elif isinstance(expr, IndexExpr): parent_expr = collapse_walrus(expr.base) parent_type = self.lookup_type_or_none(parent_expr) index_type = self.lookup_type_or_none(expr.index) if index_type is None: return output str_literals = try_getting_str_literals_from_type(index_type) if str_literals is not None: # Refactoring these two indexing replay functions is surprisingly # tricky -- see https://github.com/python/mypy/pull/7917, which # was blocked by https://github.com/mypyc/mypyc/issues/586 def replay_lookup(new_parent_type: ProperType) -> Type | None: if not isinstance(new_parent_type, TypedDictType): return None try: assert str_literals is not None member_types = [new_parent_type.items[key] for key in str_literals] except KeyError: return None return make_simplified_union(member_types) else: int_literals = try_getting_int_literals_from_type(index_type) if int_literals is not None: def replay_lookup(new_parent_type: ProperType) -> Type | None: if not isinstance(new_parent_type, TupleType): return None try: assert int_literals is not None member_types = [new_parent_type.items[key] for key in int_literals] except IndexError: return None return make_simplified_union(member_types) else: return output else: return output # If we somehow didn't previously derive the parent type, abort completely # with what we have so far: something went wrong at an earlier stage. if parent_type is None: return output # We currently only try refining the parent type if it's a Union. # If not, there's no point in trying to refine any further parents # since we have no further information we can use to refine the lookup # chain, so we end early as an optimization. parent_type = get_proper_type(parent_type) if not isinstance(parent_type, UnionType): return output # Take each element in the parent union and replay the original lookup procedure # to figure out which parents are compatible. new_parent_types = [] for item in flatten_nested_unions(parent_type.items): member_type = replay_lookup(get_proper_type(item)) if member_type is None: # We were unable to obtain the member type. So, we give up on refining this # parent type entirely and abort. return output if is_overlapping_types(member_type, expr_type): new_parent_types.append(item) # If none of the parent types overlap (if we derived an empty union), something # went wrong. We should never hit this case, but deriving the uninhabited type or # reporting an error both seem unhelpful. So we abort. if not new_parent_types: return output expr = parent_expr expr_type = output[parent_expr] = make_simplified_union(new_parent_types) def refine_identity_comparison_expression( self, operands: list[Expression], operand_types: list[Type], chain_indices: list[int], narrowable_operand_indices: AbstractSet[int], is_valid_target: Callable[[ProperType], bool], coerce_only_in_literal_context: bool, ) -> tuple[TypeMap, TypeMap]: """Produce conditional type maps refining expressions by an identity/equality comparison. The 'operands' and 'operand_types' lists should be the full list of operands used in the overall comparison expression. The 'chain_indices' list is the list of indices actually used within this identity comparison chain. So if we have the expression: a <= b is c is d <= e ...then 'operands' and 'operand_types' would be lists of length 5 and 'chain_indices' would be the list [1, 2, 3]. The 'narrowable_operand_indices' parameter is the set of all indices we are allowed to refine the types of: that is, all operands that will potentially be a part of the output TypeMaps. Although this function could theoretically try setting the types of the operands in the chains to the meet, doing that causes too many issues in real-world code. Instead, we use 'is_valid_target' to identify which of the given chain types we could plausibly use as the refined type for the expressions in the chain. Similarly, 'coerce_only_in_literal_context' controls whether we should try coercing expressions in the chain to a Literal type. Performing this coercion is sometimes too aggressive of a narrowing, depending on context. """ should_coerce = True if coerce_only_in_literal_context: def should_coerce_inner(typ: Type) -> bool: typ = get_proper_type(typ) return is_literal_type_like(typ) or ( isinstance(typ, Instance) and typ.type.is_enum ) should_coerce = any(should_coerce_inner(operand_types[i]) for i in chain_indices) target: Type | None = None possible_target_indices = [] for i in chain_indices: expr_type = operand_types[i] if should_coerce: expr_type = coerce_to_literal(expr_type) if not is_valid_target(get_proper_type(expr_type)): continue if target and not is_same_type(target, expr_type): # We have multiple disjoint target types. So the 'if' branch # must be unreachable. return None, {} target = expr_type possible_target_indices.append(i) # There's nothing we can currently infer if none of the operands are valid targets, # so we end early and infer nothing. if target is None: return {}, {} # If possible, use an unassignable expression as the target. # We skip refining the type of the target below, so ideally we'd # want to pick an expression we were going to skip anyways. singleton_index = -1 for i in possible_target_indices: if i not in narrowable_operand_indices: singleton_index = i # But if none of the possible singletons are unassignable ones, we give up # and arbitrarily pick the last item, mostly because other parts of the # type narrowing logic bias towards picking the rightmost item and it'd be # nice to stay consistent. # # That said, it shouldn't matter which index we pick. For example, suppose we # have this if statement, where 'x' and 'y' both have singleton types: # # if x is y: # reveal_type(x) # reveal_type(y) # else: # reveal_type(x) # reveal_type(y) # # At this point, 'x' and 'y' *must* have the same singleton type: we would have # ended early in the first for-loop in this function if they weren't. # # So, we should always get the same result in the 'if' case no matter which # index we pick. And while we do end up getting different results in the 'else' # case depending on the index (e.g. if we pick 'y', then its type stays the same # while 'x' is narrowed to ''), this distinction is also moot: mypy # currently will just mark the whole branch as unreachable if either operand is # narrowed to . if singleton_index == -1: singleton_index = possible_target_indices[-1] sum_type_name = None target = get_proper_type(target) if isinstance(target, LiteralType) and ( target.is_enum_literal() or isinstance(target.value, bool) ): sum_type_name = target.fallback.type.fullname target_type = [TypeRange(target, is_upper_bound=False)] partial_type_maps = [] for i in chain_indices: # If we try refining a type against itself, conditional_type_map # will end up assuming that the 'else' branch is unreachable. This is # typically not what we want: generally the user will intend for the # target type to be some fixed 'sentinel' value and will want to refine # the other exprs against this one instead. if i == singleton_index: continue # Naturally, we can't refine operands which are not permitted to be refined. if i not in narrowable_operand_indices: continue expr = operands[i] expr_type = coerce_to_literal(operand_types[i]) if sum_type_name is not None: expr_type = try_expanding_sum_type_to_union(expr_type, sum_type_name) # We intentionally use 'conditional_types' directly here instead of # 'self.conditional_types_with_intersection': we only compute ad-hoc # intersections when working with pure instances. types = conditional_types(expr_type, target_type) partial_type_maps.append(conditional_types_to_typemaps(expr, *types)) return reduce_conditional_maps(partial_type_maps) def refine_away_none_in_comparison( self, operands: list[Expression], operand_types: list[Type], chain_indices: list[int], narrowable_operand_indices: AbstractSet[int], ) -> tuple[TypeMap, TypeMap]: """Produces conditional type maps refining away None in an identity/equality chain. For more details about what the different arguments mean, see the docstring of 'refine_identity_comparison_expression' up above. """ non_optional_types = [] for i in chain_indices: typ = operand_types[i] if not is_overlapping_none(typ): non_optional_types.append(typ) if_map, else_map = {}, {} if not non_optional_types or (len(non_optional_types) != len(chain_indices)): # Narrow e.g. `Optional[A] == "x"` or `Optional[A] is "x"` to `A` (which may be # convenient but is strictly not type-safe): for i in narrowable_operand_indices: expr_type = operand_types[i] if not is_overlapping_none(expr_type): continue if any(is_overlapping_erased_types(expr_type, t) for t in non_optional_types): if_map[operands[i]] = remove_optional(expr_type) # Narrow e.g. `Optional[A] != None` to `A` (which is stricter than the above step and # so type-safe but less convenient, because e.g. `Optional[A] == None` still results # in `Optional[A]`): if any(isinstance(get_proper_type(ot), NoneType) for ot in operand_types): for i in narrowable_operand_indices: expr_type = operand_types[i] if is_overlapping_none(expr_type): else_map[operands[i]] = remove_optional(expr_type) return if_map, else_map def is_len_of_tuple(self, expr: Expression) -> bool: """Is this expression a `len(x)` call where x is a tuple or union of tuples?""" if not isinstance(expr, CallExpr): return False if not refers_to_fullname(expr.callee, "builtins.len"): return False if len(expr.args) != 1: return False expr = expr.args[0] if literal(expr) != LITERAL_TYPE: return False if not self.has_type(expr): return False return self.can_be_narrowed_with_len(self.lookup_type(expr)) def can_be_narrowed_with_len(self, typ: Type) -> bool: """Is this a type that can benefit from length check type restrictions? Currently supported types are TupleTypes, Instances of builtins.tuple, and unions involving such types. """ if custom_special_method(typ, "__len__"): # If user overrides builtin behavior, we can't do anything. return False p_typ = get_proper_type(typ) # Note: we are conservative about tuple subclasses, because some code may rely on # the fact that tuple_type of fallback TypeInfo matches the original TupleType. if isinstance(p_typ, TupleType): if any(isinstance(t, UnpackType) for t in p_typ.items): return p_typ.partial_fallback.type.fullname == "builtins.tuple" return True if isinstance(p_typ, Instance): return p_typ.type.has_base("builtins.tuple") if isinstance(p_typ, UnionType): return any(self.can_be_narrowed_with_len(t) for t in p_typ.items) return False def literal_int_expr(self, expr: Expression) -> int | None: """Is this expression an int literal, or a reference to an int constant? If yes, return the corresponding int value, otherwise return None. """ if not self.has_type(expr): return None expr_type = self.lookup_type(expr) expr_type = coerce_to_literal(expr_type) proper_type = get_proper_type(expr_type) if not isinstance(proper_type, LiteralType): return None if not isinstance(proper_type.value, int): return None return proper_type.value def find_tuple_len_narrowing(self, node: ComparisonExpr) -> list[tuple[TypeMap, TypeMap]]: """Top-level logic to find type restrictions from a length check on tuples. We try to detect `if` checks like the following: x: tuple[int, int] | tuple[int, int, int] y: tuple[int, int] | tuple[int, int, int] if len(x) == len(y) == 2: a, b = x # OK c, d = y # OK z: tuple[int, ...] if 1 < len(z) < 4: x = z # OK and report corresponding type restrictions to the binder. """ # First step: group consecutive `is` and `==` comparisons together. # This is essentially a simplified version of group_comparison_operands(), # tuned to the len()-like checks. Note that we don't propagate indirect # restrictions like e.g. `len(x) > foo() > 1` yet, since it is tricky. # TODO: propagate indirect len() comparison restrictions. chained = [] last_group = set() for op, left, right in node.pairwise(): if isinstance(left, AssignmentExpr): left = left.value if isinstance(right, AssignmentExpr): right = right.value if op in ("is", "=="): last_group.add(left) last_group.add(right) else: if last_group: chained.append(("==", list(last_group))) last_group = set() if op in {"is not", "!=", "<", "<=", ">", ">="}: chained.append((op, [left, right])) if last_group: chained.append(("==", list(last_group))) # Second step: infer type restrictions from each group found above. type_maps = [] for op, items in chained: # TODO: support unions of literal types as len() comparison targets. if not any(self.literal_int_expr(it) is not None for it in items): continue if not any(self.is_len_of_tuple(it) for it in items): continue # At this step we know there is at least one len(x) and one literal in the group. if op in ("is", "=="): literal_values = set() tuples = [] for it in items: lit = self.literal_int_expr(it) if lit is not None: literal_values.add(lit) continue if self.is_len_of_tuple(it): assert isinstance(it, CallExpr) tuples.append(it.args[0]) if len(literal_values) > 1: # More than one different literal value found, like 1 == len(x) == 2, # so the corresponding branch is unreachable. return [(None, {})] size = literal_values.pop() if size > MAX_PRECISE_TUPLE_SIZE: # Avoid creating huge tuples from checks like if len(x) == 300. continue for tpl in tuples: yes_type, no_type = self.narrow_with_len(self.lookup_type(tpl), op, size) yes_map = None if yes_type is None else {tpl: yes_type} no_map = None if no_type is None else {tpl: no_type} type_maps.append((yes_map, no_map)) else: left, right = items if self.is_len_of_tuple(right): # Normalize `1 < len(x)` and similar as `len(x) > 1`. left, right = right, left op = flip_ops.get(op, op) r_size = self.literal_int_expr(right) assert r_size is not None if r_size > MAX_PRECISE_TUPLE_SIZE: # Avoid creating huge unions from checks like if len(x) > 300. continue assert isinstance(left, CallExpr) yes_type, no_type = self.narrow_with_len( self.lookup_type(left.args[0]), op, r_size ) yes_map = None if yes_type is None else {left.args[0]: yes_type} no_map = None if no_type is None else {left.args[0]: no_type} type_maps.append((yes_map, no_map)) return type_maps def narrow_with_len(self, typ: Type, op: str, size: int) -> tuple[Type | None, Type | None]: """Dispatch tuple type narrowing logic depending on the kind of type we got.""" typ = get_proper_type(typ) if isinstance(typ, TupleType): return self.refine_tuple_type_with_len(typ, op, size) elif isinstance(typ, Instance): return self.refine_instance_type_with_len(typ, op, size) elif isinstance(typ, UnionType): yes_types = [] no_types = [] other_types = [] for t in typ.items: if not self.can_be_narrowed_with_len(t): other_types.append(t) continue yt, nt = self.narrow_with_len(t, op, size) if yt is not None: yes_types.append(yt) if nt is not None: no_types.append(nt) yes_types += other_types no_types += other_types if yes_types: yes_type = make_simplified_union(yes_types) else: yes_type = None if no_types: no_type = make_simplified_union(no_types) else: no_type = None return yes_type, no_type else: assert False, "Unsupported type for len narrowing" def refine_tuple_type_with_len( self, typ: TupleType, op: str, size: int ) -> tuple[Type | None, Type | None]: """Narrow a TupleType using length restrictions.""" unpack_index = find_unpack_in_list(typ.items) if unpack_index is None: # For fixed length tuple situation is trivial, it is either reachable or not, # depending on the current length, expected length, and the comparison op. method = int_op_to_method[op] if method(typ.length(), size): return typ, None return None, typ unpack = typ.items[unpack_index] assert isinstance(unpack, UnpackType) unpacked = get_proper_type(unpack.type) if isinstance(unpacked, TypeVarTupleType): # For tuples involving TypeVarTuple unpack we can't do much except # inferring reachability, and recording the restrictions on TypeVarTuple # for further "manual" use elsewhere. min_len = typ.length() - 1 + unpacked.min_len if op in ("==", "is"): if min_len <= size: return typ, typ return None, typ elif op in ("<", "<="): if op == "<=": size += 1 if min_len < size: prefix = typ.items[:unpack_index] suffix = typ.items[unpack_index + 1 :] # TODO: also record max_len to avoid false negatives? unpack = UnpackType(unpacked.copy_modified(min_len=size - typ.length() + 1)) return typ, typ.copy_modified(items=prefix + [unpack] + suffix) return None, typ else: yes_type, no_type = self.refine_tuple_type_with_len(typ, neg_ops[op], size) return no_type, yes_type # Homogeneous variadic item is the case where we are most flexible. Essentially, # we adjust the variadic item by "eating away" from it to satisfy the restriction. assert isinstance(unpacked, Instance) and unpacked.type.fullname == "builtins.tuple" min_len = typ.length() - 1 arg = unpacked.args[0] prefix = typ.items[:unpack_index] suffix = typ.items[unpack_index + 1 :] if op in ("==", "is"): if min_len <= size: # TODO: return fixed union + prefixed variadic tuple for no_type? return typ.copy_modified(items=prefix + [arg] * (size - min_len) + suffix), typ return None, typ elif op in ("<", "<="): if op == "<=": size += 1 if min_len < size: # Note: there is some ambiguity w.r.t. to where to put the additional # items: before or after the unpack. However, such types are equivalent, # so we always put them before for consistency. no_type = typ.copy_modified( items=prefix + [arg] * (size - min_len) + [unpack] + suffix ) yes_items = [] for n in range(size - min_len): yes_items.append(typ.copy_modified(items=prefix + [arg] * n + suffix)) return UnionType.make_union(yes_items, typ.line, typ.column), no_type return None, typ else: yes_type, no_type = self.refine_tuple_type_with_len(typ, neg_ops[op], size) return no_type, yes_type def refine_instance_type_with_len( self, typ: Instance, op: str, size: int ) -> tuple[Type | None, Type | None]: """Narrow a homogeneous tuple using length restrictions.""" base = map_instance_to_supertype(typ, self.lookup_typeinfo("builtins.tuple")) arg = base.args[0] # Again, we are conservative about subclasses until we gain more confidence. allow_precise = ( PRECISE_TUPLE_TYPES in self.options.enable_incomplete_feature ) and typ.type.fullname == "builtins.tuple" if op in ("==", "is"): # TODO: return fixed union + prefixed variadic tuple for no_type? return TupleType(items=[arg] * size, fallback=typ), typ elif op in ("<", "<="): if op == "<=": size += 1 if allow_precise: unpack = UnpackType(self.named_generic_type("builtins.tuple", [arg])) no_type: Type | None = TupleType(items=[arg] * size + [unpack], fallback=typ) else: no_type = typ if allow_precise: items = [] for n in range(size): items.append(TupleType([arg] * n, fallback=typ)) yes_type: Type | None = UnionType.make_union(items, typ.line, typ.column) else: yes_type = typ return yes_type, no_type else: yes_type, no_type = self.refine_instance_type_with_len(typ, neg_ops[op], size) return no_type, yes_type # # Helpers # @overload def check_subtype( self, subtype: Type, supertype: Type, context: Context, msg: str, subtype_label: str | None = None, supertype_label: str | None = None, *, notes: list[str] | None = None, code: ErrorCode | None = None, outer_context: Context | None = None, ) -> bool: ... @overload def check_subtype( self, subtype: Type, supertype: Type, context: Context, msg: ErrorMessage, subtype_label: str | None = None, supertype_label: str | None = None, *, notes: list[str] | None = None, outer_context: Context | None = None, ) -> bool: ... def check_subtype( self, subtype: Type, supertype: Type, context: Context, msg: str | ErrorMessage, subtype_label: str | None = None, supertype_label: str | None = None, *, notes: list[str] | None = None, code: ErrorCode | None = None, outer_context: Context | None = None, ) -> bool: """Generate an error if the subtype is not compatible with supertype.""" if is_subtype(subtype, supertype, options=self.options): return True if isinstance(msg, str): msg = ErrorMessage(msg, code=code) if self.msg.prefer_simple_messages(): self.fail(msg, context) # Fast path -- skip all fancy logic return False orig_subtype = subtype subtype = get_proper_type(subtype) orig_supertype = supertype supertype = get_proper_type(supertype) if self.msg.try_report_long_tuple_assignment_error( subtype, supertype, context, msg, subtype_label, supertype_label ): return False extra_info: list[str] = [] note_msg = "" notes = notes or [] if subtype_label is not None or supertype_label is not None: subtype_str, supertype_str = format_type_distinctly( orig_subtype, orig_supertype, options=self.options ) if subtype_label is not None: extra_info.append(subtype_label + " " + subtype_str) if supertype_label is not None: extra_info.append(supertype_label + " " + supertype_str) note_msg = make_inferred_type_note( outer_context or context, subtype, supertype, supertype_str ) if isinstance(subtype, Instance) and isinstance(supertype, Instance): notes = append_invariance_notes(notes, subtype, supertype) if isinstance(subtype, UnionType) and isinstance(supertype, UnionType): notes = append_union_note(notes, subtype, supertype, self.options) if extra_info: msg = msg.with_additional_msg(" (" + ", ".join(extra_info) + ")") self.fail(msg, context) for note in notes: self.msg.note(note, context, code=msg.code) if note_msg: self.note(note_msg, context, code=msg.code) self.msg.maybe_note_concatenate_pos_args(subtype, supertype, context, code=msg.code) if ( isinstance(supertype, Instance) and supertype.type.is_protocol and isinstance(subtype, (CallableType, Instance, TupleType, TypedDictType)) ): self.msg.report_protocol_problems(subtype, supertype, context, code=msg.code) if isinstance(supertype, CallableType) and isinstance(subtype, Instance): call = find_member("__call__", subtype, subtype, is_operator=True) if call: self.msg.note_call(subtype, call, context, code=msg.code) if isinstance(subtype, (CallableType, Overloaded)) and isinstance(supertype, Instance): if supertype.type.is_protocol and "__call__" in supertype.type.protocol_members: call = find_member("__call__", supertype, subtype, is_operator=True) assert call is not None if not is_subtype(subtype, call, options=self.options): self.msg.note_call(supertype, call, context, code=msg.code) self.check_possible_missing_await(subtype, supertype, context, code=msg.code) return False def get_precise_awaitable_type(self, typ: Type, local_errors: ErrorWatcher) -> Type | None: """If type implements Awaitable[X] with non-Any X, return X. In all other cases return None. This method must be called in context of local_errors. """ if isinstance(get_proper_type(typ), PartialType): # Partial types are special, ignore them here. return None try: aw_type = self.expr_checker.check_awaitable_expr( typ, Context(), "", ignore_binder=True ) except KeyError: # This is a hack to speed up tests by not including Awaitable in all typing stubs. return None if local_errors.has_new_errors(): return None if isinstance(get_proper_type(aw_type), (AnyType, UnboundType)): return None return aw_type @contextmanager def checking_await_set(self) -> Iterator[None]: self.checking_missing_await = True try: yield finally: self.checking_missing_await = False def check_possible_missing_await( self, subtype: Type, supertype: Type, context: Context, code: ErrorCode | None ) -> None: """Check if the given type becomes a subtype when awaited.""" if self.checking_missing_await: # Avoid infinite recursion. return with self.checking_await_set(), self.msg.filter_errors() as local_errors: aw_type = self.get_precise_awaitable_type(subtype, local_errors) if aw_type is None: return if not self.check_subtype( aw_type, supertype, context, msg=message_registry.INCOMPATIBLE_TYPES ): return self.msg.possible_missing_await(context, code) def named_type(self, name: str) -> Instance: """Return an instance type with given name and implicit Any type args. For example, named_type('builtins.object') produces the 'object' type. """ # Assume that the name refers to a type. sym = self.lookup_qualified(name) node = sym.node if isinstance(node, TypeAlias): assert isinstance(node.target, Instance) # type: ignore[misc] node = node.target.type assert isinstance(node, TypeInfo) any_type = AnyType(TypeOfAny.from_omitted_generics) return Instance(node, [any_type] * len(node.defn.type_vars)) def named_generic_type(self, name: str, args: list[Type]) -> Instance: """Return an instance with the given name and type arguments. Assume that the number of arguments is correct. Assume that the name refers to a compatible generic type. """ info = self.lookup_typeinfo(name) args = [remove_instance_last_known_values(arg) for arg in args] # TODO: assert len(args) == len(info.defn.type_vars) return Instance(info, args) def lookup_typeinfo(self, fullname: str) -> TypeInfo: # Assume that the name refers to a class. sym = self.lookup_qualified(fullname) node = sym.node assert isinstance(node, TypeInfo) return node def type_type(self) -> Instance: """Return instance type 'type'.""" return self.named_type("builtins.type") def str_type(self) -> Instance: """Return instance type 'str'.""" return self.named_type("builtins.str") def store_type(self, node: Expression, typ: Type) -> None: """Store the type of a node in the type map.""" self._type_maps[-1][node] = typ def has_type(self, node: Expression) -> bool: return any(node in m for m in reversed(self._type_maps)) def lookup_type_or_none(self, node: Expression) -> Type | None: for m in reversed(self._type_maps): if node in m: return m[node] return None def lookup_type(self, node: Expression) -> Type: for m in reversed(self._type_maps): t = m.get(node) if t is not None: return t raise KeyError(node) def store_types(self, d: dict[Expression, Type]) -> None: self._type_maps[-1].update(d) @contextmanager def local_type_map(self) -> Iterator[dict[Expression, Type]]: """Store inferred types into a temporary type map (returned). This can be used to perform type checking "experiments" without affecting exported types (which are used by mypyc). """ temp_type_map: dict[Expression, Type] = {} self._type_maps.append(temp_type_map) yield temp_type_map self._type_maps.pop() def in_checked_function(self) -> bool: """Should we type-check the current function? - Yes if --check-untyped-defs is set. - Yes outside functions. - Yes in annotated functions. - No otherwise. """ return ( self.options.check_untyped_defs or not self.dynamic_funcs or not self.dynamic_funcs[-1] ) def lookup(self, name: str) -> SymbolTableNode: """Look up a definition from the symbol table with the given name.""" if name in self.globals: return self.globals[name] else: b = self.globals.get("__builtins__", None) if b: assert isinstance(b.node, MypyFile) table = b.node.names if name in table: return table[name] raise KeyError(f"Failed lookup: {name}") def lookup_qualified(self, name: str) -> SymbolTableNode: if "." not in name: return self.lookup(name) else: parts = name.split(".") n = self.modules[parts[0]] for i in range(1, len(parts) - 1): sym = n.names.get(parts[i]) assert sym is not None, "Internal error: attempted lookup of unknown name" assert isinstance(sym.node, MypyFile) n = sym.node last = parts[-1] if last in n.names: return n.names[last] elif len(parts) == 2 and parts[0] in ("builtins", "typing"): fullname = ".".join(parts) if fullname in SUGGESTED_TEST_FIXTURES: suggestion = ", e.g. add '[{} fixtures/{}]' to your test".format( parts[0], SUGGESTED_TEST_FIXTURES[fullname] ) else: suggestion = "" raise KeyError( "Could not find builtin symbol '{}' (If you are running a " "test case, use a fixture that " "defines this symbol{})".format(last, suggestion) ) else: msg = "Failed qualified lookup: '{}' (fullname = '{}')." raise KeyError(msg.format(last, name)) @contextmanager def enter_partial_types( self, *, is_function: bool = False, is_class: bool = False ) -> Iterator[None]: """Enter a new scope for collecting partial types. Also report errors for (some) variables which still have partial types, i.e. we couldn't infer a complete type. """ is_local = (self.partial_types and self.partial_types[-1].is_local) or is_function self.partial_types.append(PartialTypeScope({}, is_function, is_local)) yield # Don't complain about not being able to infer partials if it is # at the toplevel (with allow_untyped_globals) or if it is in an # untyped function being checked with check_untyped_defs. permissive = (self.options.allow_untyped_globals and not is_local) or ( self.options.check_untyped_defs and self.dynamic_funcs and self.dynamic_funcs[-1] ) partial_types, _, _ = self.partial_types.pop() if not self.current_node_deferred: for var, context in partial_types.items(): # If we require local partial types, there are a few exceptions where # we fall back to inferring just "None" as the type from a None initializer: # # 1. If all happens within a single function this is acceptable, since only # the topmost function is a separate target in fine-grained incremental mode. # We primarily want to avoid "splitting" partial types across targets. # # 2. A None initializer in the class body if the attribute is defined in a base # class is fine, since the attribute is already defined and it's currently okay # to vary the type of an attribute covariantly. The None type will still be # checked for compatibility with base classes elsewhere. Without this exception # mypy could require an annotation for an attribute that already has been # declared in a base class, which would be bad. allow_none = ( not self.options.local_partial_types or is_function or (is_class and self.is_defined_in_base_class(var)) ) if ( allow_none and isinstance(var.type, PartialType) and var.type.type is None and not permissive ): var.type = NoneType() else: if var not in self.partial_reported and not permissive: self.msg.need_annotation_for_var(var, context, self.options.python_version) self.partial_reported.add(var) if var.type: fixed = fixup_partial_type(var.type) var.invalid_partial_type = fixed != var.type var.type = fixed def handle_partial_var_type( self, typ: PartialType, is_lvalue: bool, node: Var, context: Context ) -> Type: """Handle a reference to a partial type through a var. (Used by checkexpr and checkmember.) """ in_scope, is_local, partial_types = self.find_partial_types_in_all_scopes(node) if typ.type is None and in_scope: # 'None' partial type. It has a well-defined type. In an lvalue context # we want to preserve the knowledge of it being a partial type. if not is_lvalue: return NoneType() else: return typ else: if partial_types is not None and not self.current_node_deferred: if in_scope: context = partial_types[node] if is_local or not self.options.allow_untyped_globals: self.msg.need_annotation_for_var( node, context, self.options.python_version ) self.partial_reported.add(node) else: # Defer the node -- we might get a better type in the outer scope self.handle_cannot_determine_type(node.name, context) return fixup_partial_type(typ) def is_defined_in_base_class(self, var: Var) -> bool: if not var.info: return False return var.info.fallback_to_any or any( base.get(var.name) is not None for base in var.info.mro[1:] ) def find_partial_types(self, var: Var) -> dict[Var, Context] | None: """Look for an active partial type scope containing variable. A scope is active if assignments in the current context can refine a partial type originally defined in the scope. This is affected by the local_partial_types configuration option. """ in_scope, _, partial_types = self.find_partial_types_in_all_scopes(var) if in_scope: return partial_types return None def find_partial_types_in_all_scopes( self, var: Var ) -> tuple[bool, bool, dict[Var, Context] | None]: """Look for partial type scope containing variable. Return tuple (is the scope active, is the scope a local scope, scope). """ for scope in reversed(self.partial_types): if var in scope.map: # All scopes within the outermost function are active. Scopes out of # the outermost function are inactive to allow local reasoning (important # for fine-grained incremental mode). disallow_other_scopes = self.options.local_partial_types if isinstance(var.type, PartialType) and var.type.type is not None and var.info: # This is an ugly hack to make partial generic self attributes behave # as if --local-partial-types is always on (because it used to be like this). disallow_other_scopes = True scope_active = ( not disallow_other_scopes or scope.is_local == self.partial_types[-1].is_local ) return scope_active, scope.is_local, scope.map return False, False, None def temp_node(self, t: Type, context: Context | None = None) -> TempNode: """Create a temporary node with the given, fixed type.""" return TempNode(t, context=context) def fail( self, msg: str | ErrorMessage, context: Context, *, code: ErrorCode | None = None ) -> None: """Produce an error message.""" if isinstance(msg, ErrorMessage): self.msg.fail(msg.value, context, code=msg.code) return self.msg.fail(msg, context, code=code) def note( self, msg: str | ErrorMessage, context: Context, offset: int = 0, *, code: ErrorCode | None = None, ) -> None: """Produce a note.""" if isinstance(msg, ErrorMessage): self.msg.note(msg.value, context, code=msg.code) return self.msg.note(msg, context, offset=offset, code=code) def iterable_item_type( self, it: Instance | CallableType | TypeType | Overloaded, context: Context ) -> Type: if isinstance(it, Instance): iterable = map_instance_to_supertype(it, self.lookup_typeinfo("typing.Iterable")) item_type = iterable.args[0] if not isinstance(get_proper_type(item_type), AnyType): # This relies on 'map_instance_to_supertype' returning 'Iterable[Any]' # in case there is no explicit base class. return item_type # Try also structural typing. return self.analyze_iterable_item_type_without_expression(it, context)[1] def function_type(self, func: FuncBase) -> FunctionLike: return function_type(func, self.named_type("builtins.function")) def push_type_map(self, type_map: TypeMap, *, from_assignment: bool = True) -> None: if type_map is None: self.binder.unreachable() else: for expr, type in type_map.items(): self.binder.put(expr, type, from_assignment=from_assignment) def infer_issubclass_maps(self, node: CallExpr, expr: Expression) -> tuple[TypeMap, TypeMap]: """Infer type restrictions for an expression in issubclass call.""" vartype = self.lookup_type(expr) type = self.get_isinstance_type(node.args[1]) if isinstance(vartype, TypeVarType): vartype = vartype.upper_bound vartype = get_proper_type(vartype) if isinstance(vartype, UnionType): union_list = [] for t in get_proper_types(vartype.items): if isinstance(t, TypeType): union_list.append(t.item) else: # This is an error that should be reported earlier # if we reach here, we refuse to do any type inference. return {}, {} vartype = UnionType(union_list) elif isinstance(vartype, TypeType): vartype = vartype.item elif isinstance(vartype, Instance) and vartype.type.is_metaclass(): vartype = self.named_type("builtins.object") else: # Any other object whose type we don't know precisely # for example, Any or a custom metaclass. return {}, {} # unknown type yes_type, no_type = self.conditional_types_with_intersection(vartype, type, expr) yes_map, no_map = conditional_types_to_typemaps(expr, yes_type, no_type) yes_map, no_map = map(convert_to_typetype, (yes_map, no_map)) return yes_map, no_map @overload def conditional_types_with_intersection( self, expr_type: Type, type_ranges: list[TypeRange] | None, ctx: Context, default: None = None, ) -> tuple[Type | None, Type | None]: ... @overload def conditional_types_with_intersection( self, expr_type: Type, type_ranges: list[TypeRange] | None, ctx: Context, default: Type ) -> tuple[Type, Type]: ... def conditional_types_with_intersection( self, expr_type: Type, type_ranges: list[TypeRange] | None, ctx: Context, default: Type | None = None, ) -> tuple[Type | None, Type | None]: initial_types = conditional_types(expr_type, type_ranges, default) # For some reason, doing "yes_map, no_map = conditional_types_to_typemaps(...)" # doesn't work: mypyc will decide that 'yes_map' is of type None if we try. yes_type: Type | None = initial_types[0] no_type: Type | None = initial_types[1] if not isinstance(get_proper_type(yes_type), UninhabitedType) or type_ranges is None: return yes_type, no_type # If conditional_types was unable to successfully narrow the expr_type # using the type_ranges and concluded if-branch is unreachable, we try # computing it again using a different algorithm that tries to generate # an ad-hoc intersection between the expr_type and the type_ranges. proper_type = get_proper_type(expr_type) if isinstance(proper_type, UnionType): possible_expr_types = get_proper_types(proper_type.relevant_items()) else: possible_expr_types = [proper_type] possible_target_types = [] for tr in type_ranges: item = get_proper_type(tr.item) if isinstance(item, (Instance, NoneType)): possible_target_types.append(item) if not possible_target_types: return yes_type, no_type out = [] errors: list[tuple[str, str]] = [] for v in possible_expr_types: if not isinstance(v, Instance): return yes_type, no_type for t in possible_target_types: if isinstance(t, NoneType): errors.append((f'"{v.type.name}" and "NoneType"', '"NoneType" is final')) continue intersection = self.intersect_instances((v, t), errors) if intersection is None: continue out.append(intersection) if not out: # Only report errors if no element in the union worked. if self.should_report_unreachable_issues(): for types, reason in errors: self.msg.impossible_intersection(types, reason, ctx) return UninhabitedType(), expr_type new_yes_type = make_simplified_union(out) return new_yes_type, expr_type def is_writable_attribute(self, node: Node) -> bool: """Check if an attribute is writable""" if isinstance(node, Var): if node.is_property and not node.is_settable_property: return False return True elif isinstance(node, OverloadedFuncDef) and node.is_property: first_item = node.items[0] assert isinstance(first_item, Decorator) return first_item.var.is_settable_property return False def get_isinstance_type(self, expr: Expression) -> list[TypeRange] | None: if isinstance(expr, OpExpr) and expr.op == "|": left = self.get_isinstance_type(expr.left) if left is None and is_literal_none(expr.left): left = [TypeRange(NoneType(), is_upper_bound=False)] right = self.get_isinstance_type(expr.right) if right is None and is_literal_none(expr.right): right = [TypeRange(NoneType(), is_upper_bound=False)] if left is None or right is None: return None return left + right all_types = get_proper_types(flatten_types(self.lookup_type(expr))) types: list[TypeRange] = [] for typ in all_types: if isinstance(typ, FunctionLike) and typ.is_type_obj(): # Type variables may be present -- erase them, which is the best # we can do (outside disallowing them here). erased_type = erase_typevars(typ.items[0].ret_type) types.append(TypeRange(erased_type, is_upper_bound=False)) elif isinstance(typ, TypeType): # Type[A] means "any type that is a subtype of A" rather than "precisely type A" # we indicate this by setting is_upper_bound flag is_upper_bound = True if isinstance(typ.item, NoneType): # except for Type[None], because "'NoneType' is not an acceptable base type" is_upper_bound = False types.append(TypeRange(typ.item, is_upper_bound=is_upper_bound)) elif isinstance(typ, Instance) and typ.type.fullname == "builtins.type": object_type = Instance(typ.type.mro[-1], []) types.append(TypeRange(object_type, is_upper_bound=True)) elif isinstance(typ, Instance) and typ.type.fullname == "types.UnionType" and typ.args: types.append(TypeRange(UnionType(typ.args), is_upper_bound=False)) elif isinstance(typ, AnyType): types.append(TypeRange(typ, is_upper_bound=False)) else: # we didn't see an actual type, but rather a variable with unknown value return None if not types: # this can happen if someone has empty tuple as 2nd argument to isinstance # strictly speaking, we should return UninhabitedType but for simplicity we will simply # refuse to do any type inference for now return None return types def is_literal_enum(self, n: Expression) -> bool: """Returns true if this expression (with the given type context) is an Enum literal. For example, if we had an enum: class Foo(Enum): A = 1 B = 2 ...and if the expression 'Foo' referred to that enum within the current type context, then the expression 'Foo.A' would be a literal enum. However, if we did 'a = Foo.A', then the variable 'a' would *not* be a literal enum. We occasionally special-case expressions like 'Foo.A' and treat them as a single primitive unit for the same reasons we sometimes treat 'True', 'False', or 'None' as a single primitive unit. """ if not isinstance(n, MemberExpr) or not isinstance(n.expr, NameExpr): return False parent_type = self.lookup_type_or_none(n.expr) member_type = self.lookup_type_or_none(n) if member_type is None or parent_type is None: return False parent_type = get_proper_type(parent_type) member_type = get_proper_type(coerce_to_literal(member_type)) if not isinstance(parent_type, FunctionLike) or not isinstance(member_type, LiteralType): return False if not parent_type.is_type_obj(): return False return ( member_type.is_enum_literal() and member_type.fallback.type == parent_type.type_object() ) def add_any_attribute_to_type(self, typ: Type, name: str) -> Type: """Inject an extra attribute with Any type using fallbacks.""" orig_typ = typ typ = get_proper_type(typ) any_type = AnyType(TypeOfAny.unannotated) if isinstance(typ, Instance): result = typ.copy_with_extra_attr(name, any_type) # For instances, we erase the possible module name, so that restrictions # become anonymous types.ModuleType instances, allowing hasattr() to # have effect on modules. assert result.extra_attrs is not None result.extra_attrs.mod_name = None return result if isinstance(typ, TupleType): fallback = typ.partial_fallback.copy_with_extra_attr(name, any_type) return typ.copy_modified(fallback=fallback) if isinstance(typ, CallableType): fallback = typ.fallback.copy_with_extra_attr(name, any_type) return typ.copy_modified(fallback=fallback) if isinstance(typ, TypeType) and isinstance(typ.item, Instance): return TypeType.make_normalized(self.add_any_attribute_to_type(typ.item, name)) if isinstance(typ, TypeVarType): return typ.copy_modified( upper_bound=self.add_any_attribute_to_type(typ.upper_bound, name), values=[self.add_any_attribute_to_type(v, name) for v in typ.values], ) if isinstance(typ, UnionType): with_attr, without_attr = self.partition_union_by_attr(typ, name) return make_simplified_union( with_attr + [self.add_any_attribute_to_type(typ, name) for typ in without_attr] ) return orig_typ def hasattr_type_maps( self, expr: Expression, source_type: Type, name: str ) -> tuple[TypeMap, TypeMap]: """Simple support for hasattr() checks. Essentially the logic is following: * In the if branch, keep types that already has a valid attribute as is, for other inject an attribute with `Any` type. * In the else branch, remove types that already have a valid attribute, while keeping the rest. """ if self.has_valid_attribute(source_type, name): return {expr: source_type}, {} source_type = get_proper_type(source_type) if isinstance(source_type, UnionType): _, without_attr = self.partition_union_by_attr(source_type, name) yes_map = {expr: self.add_any_attribute_to_type(source_type, name)} return yes_map, {expr: make_simplified_union(without_attr)} type_with_attr = self.add_any_attribute_to_type(source_type, name) if type_with_attr != source_type: return {expr: type_with_attr}, {} return {}, {} def partition_union_by_attr( self, source_type: UnionType, name: str ) -> tuple[list[Type], list[Type]]: with_attr = [] without_attr = [] for item in source_type.items: if self.has_valid_attribute(item, name): with_attr.append(item) else: without_attr.append(item) return with_attr, without_attr def has_valid_attribute(self, typ: Type, name: str) -> bool: p_typ = get_proper_type(typ) if isinstance(p_typ, AnyType): return False if isinstance(p_typ, Instance) and p_typ.extra_attrs and p_typ.extra_attrs.mod_name: # Presence of module_symbol_table means this check will skip ModuleType.__getattr__ module_symbol_table = p_typ.type.names else: module_symbol_table = None with self.msg.filter_errors() as watcher: analyze_member_access( name, typ, TempNode(AnyType(TypeOfAny.special_form)), is_lvalue=False, is_super=False, is_operator=False, original_type=typ, chk=self, # This is not a real attribute lookup so don't mess with deferring nodes. no_deferral=True, module_symbol_table=module_symbol_table, ) return not watcher.has_new_errors() def get_expression_type(self, node: Expression, type_context: Type | None = None) -> Type: return self.expr_checker.accept(node, type_context=type_context) def check_deprecated(self, node: Node | None, context: Context) -> None: """Warn if deprecated and not directly imported with a `from` statement.""" if isinstance(node, Decorator): node = node.func if isinstance(node, (FuncDef, OverloadedFuncDef, TypeInfo)) and ( node.deprecated is not None ): for imp in self.tree.imports: if isinstance(imp, ImportFrom) and any(node.name == n[0] for n in imp.names): break else: self.warn_deprecated(node, context) def warn_deprecated(self, node: Node | None, context: Context) -> None: """Warn if deprecated.""" if isinstance(node, Decorator): node = node.func if ( isinstance(node, (FuncDef, OverloadedFuncDef, TypeInfo)) and ((deprecated := node.deprecated) is not None) and not self.is_typeshed_stub and not any( node.fullname == p or node.fullname.startswith(f"{p}.") for p in self.options.deprecated_calls_exclude ) ): warn = self.msg.note if self.options.report_deprecated_as_note else self.msg.fail warn(deprecated, context, code=codes.DEPRECATED) def warn_deprecated_overload_item( self, node: Node | None, context: Context, *, target: Type, selftype: Type | None = None ) -> None: """Warn if the overload item corresponding to the given callable is deprecated.""" target = get_proper_type(target) if isinstance(node, OverloadedFuncDef) and isinstance(target, CallableType): for item in node.items: if isinstance(item, Decorator) and isinstance( candidate := item.func.type, CallableType ): if selftype is not None and not node.is_static: candidate = bind_self(candidate, selftype) if candidate == target: self.warn_deprecated(item.func, context) # leafs def visit_pass_stmt(self, o: PassStmt, /) -> None: return None def visit_nonlocal_decl(self, o: NonlocalDecl, /) -> None: return None def visit_global_decl(self, o: GlobalDecl, /) -> None: return None class CollectArgTypeVarTypes(TypeTraverserVisitor): """Collects the non-nested argument types in a set.""" def __init__(self) -> None: self.arg_types: set[TypeVarType] = set() def visit_type_var(self, t: TypeVarType) -> None: self.arg_types.add(t) @overload def conditional_types( current_type: Type, proposed_type_ranges: list[TypeRange] | None, default: None = None ) -> tuple[Type | None, Type | None]: ... @overload def conditional_types( current_type: Type, proposed_type_ranges: list[TypeRange] | None, default: Type ) -> tuple[Type, Type]: ... def conditional_types( current_type: Type, proposed_type_ranges: list[TypeRange] | None, default: Type | None = None ) -> tuple[Type | None, Type | None]: """Takes in the current type and a proposed type of an expression. Returns a 2-tuple: The first element is the proposed type, if the expression can be the proposed type. The second element is the type it would hold if it was not the proposed type, if any. UninhabitedType means unreachable. None means no new information can be inferred. If default is set it is returned instead.""" if proposed_type_ranges: if len(proposed_type_ranges) == 1: target = proposed_type_ranges[0].item target = get_proper_type(target) if isinstance(target, LiteralType) and ( target.is_enum_literal() or isinstance(target.value, bool) ): enum_name = target.fallback.type.fullname current_type = try_expanding_sum_type_to_union(current_type, enum_name) proposed_items = [type_range.item for type_range in proposed_type_ranges] proposed_type = make_simplified_union(proposed_items) if isinstance(proposed_type, AnyType): # We don't really know much about the proposed type, so we shouldn't # attempt to narrow anything. Instead, we broaden the expr to Any to # avoid false positives return proposed_type, default elif not any( type_range.is_upper_bound for type_range in proposed_type_ranges ) and is_proper_subtype(current_type, proposed_type, ignore_promotions=True): # Expression is always of one of the types in proposed_type_ranges return default, UninhabitedType() elif not is_overlapping_types(current_type, proposed_type, ignore_promotions=True): # Expression is never of any type in proposed_type_ranges return UninhabitedType(), default else: # we can only restrict when the type is precise, not bounded proposed_precise_type = UnionType.make_union( [ type_range.item for type_range in proposed_type_ranges if not type_range.is_upper_bound ] ) remaining_type = restrict_subtype_away(current_type, proposed_precise_type) return proposed_type, remaining_type else: # An isinstance check, but we don't understand the type return current_type, default def conditional_types_to_typemaps( expr: Expression, yes_type: Type | None, no_type: Type | None ) -> tuple[TypeMap, TypeMap]: expr = collapse_walrus(expr) maps: list[TypeMap] = [] for typ in (yes_type, no_type): proper_type = get_proper_type(typ) if isinstance(proper_type, UninhabitedType): maps.append(None) elif proper_type is None: maps.append({}) else: assert typ is not None maps.append({expr: typ}) return cast(tuple[TypeMap, TypeMap], tuple(maps)) def gen_unique_name(base: str, table: SymbolTable) -> str: """Generate a name that does not appear in table by appending numbers to base.""" if base not in table: return base i = 1 while base + str(i) in table: i += 1 return base + str(i) def is_true_literal(n: Expression) -> bool: """Returns true if this expression is the 'True' literal/keyword.""" return refers_to_fullname(n, "builtins.True") or isinstance(n, IntExpr) and n.value != 0 def is_false_literal(n: Expression) -> bool: """Returns true if this expression is the 'False' literal/keyword.""" return refers_to_fullname(n, "builtins.False") or isinstance(n, IntExpr) and n.value == 0 def is_literal_none(n: Expression) -> bool: """Returns true if this expression is the 'None' literal/keyword.""" return isinstance(n, NameExpr) and n.fullname == "builtins.None" def is_literal_not_implemented(n: Expression) -> bool: return isinstance(n, NameExpr) and n.fullname == "builtins.NotImplemented" def _is_empty_generator_function(func: FuncItem) -> bool: """ Checks whether a function's body is 'return; yield' (the yield being added only to promote the function into a generator function). """ body = func.body.body return ( len(body) == 2 and isinstance(ret_stmt := body[0], ReturnStmt) and (ret_stmt.expr is None or is_literal_none(ret_stmt.expr)) and isinstance(expr_stmt := body[1], ExpressionStmt) and isinstance(yield_expr := expr_stmt.expr, YieldExpr) and (yield_expr.expr is None or is_literal_none(yield_expr.expr)) ) def builtin_item_type(tp: Type) -> Type | None: """Get the item type of a builtin container. If 'tp' is not one of the built containers (these includes NamedTuple and TypedDict) or if the container is not parameterized (like List or List[Any]) return None. This function is used to narrow optional types in situations like this: x: Optional[int] if x in (1, 2, 3): x + 42 # OK Note: this is only OK for built-in containers, where we know the behavior of __contains__. """ tp = get_proper_type(tp) if isinstance(tp, Instance): if tp.type.fullname in [ "builtins.list", "builtins.tuple", "builtins.dict", "builtins.set", "builtins.frozenset", "_collections_abc.dict_keys", "typing.KeysView", ]: if not tp.args: # TODO: fix tuple in lib-stub/builtins.pyi (it should be generic). return None if not isinstance(get_proper_type(tp.args[0]), AnyType): return tp.args[0] elif isinstance(tp, TupleType): normalized_items = [] for it in tp.items: # This use case is probably rare, but not handling unpacks here can cause crashes. if isinstance(it, UnpackType): unpacked = get_proper_type(it.type) if isinstance(unpacked, TypeVarTupleType): unpacked = get_proper_type(unpacked.upper_bound) assert ( isinstance(unpacked, Instance) and unpacked.type.fullname == "builtins.tuple" ) normalized_items.append(unpacked.args[0]) else: normalized_items.append(it) if all(not isinstance(it, AnyType) for it in get_proper_types(normalized_items)): return make_simplified_union(normalized_items) # this type is not externally visible elif isinstance(tp, TypedDictType): # TypedDict always has non-optional string keys. Find the key type from the Mapping # base class. for base in tp.fallback.type.mro: if base.fullname == "typing.Mapping": return map_instance_to_supertype(tp.fallback, base).args[0] assert False, "No Mapping base class found for TypedDict fallback" return None def and_conditional_maps(m1: TypeMap, m2: TypeMap, use_meet: bool = False) -> TypeMap: """Calculate what information we can learn from the truth of (e1 and e2) in terms of the information that we can learn from the truth of e1 and the truth of e2. """ if m1 is None or m2 is None: # One of the conditions can never be true. return None # Both conditions can be true; combine the information. Anything # we learn from either conditions' truth is valid. If the same # expression's type is refined by both conditions, we somewhat # arbitrarily give precedence to m2 unless m1 value is Any. # In the future, we could use an intersection type or meet_types(). result = m2.copy() m2_keys = {literal_hash(n2) for n2 in m2} for n1 in m1: if literal_hash(n1) not in m2_keys or isinstance(get_proper_type(m1[n1]), AnyType): result[n1] = m1[n1] if use_meet: # For now, meet common keys only if specifically requested. # This is currently used for tuple types narrowing, where having # a precise result is important. for n1 in m1: for n2 in m2: if literal_hash(n1) == literal_hash(n2): result[n1] = meet_types(m1[n1], m2[n2]) return result def or_conditional_maps(m1: TypeMap, m2: TypeMap, coalesce_any: bool = False) -> TypeMap: """Calculate what information we can learn from the truth of (e1 or e2) in terms of the information that we can learn from the truth of e1 and the truth of e2. If coalesce_any is True, consider Any a supertype when joining restrictions. """ if m1 is None: return m2 if m2 is None: return m1 # Both conditions can be true. Combine information about # expressions whose type is refined by both conditions. (We do not # learn anything about expressions whose type is refined by only # one condition.) result: dict[Expression, Type] = {} for n1 in m1: for n2 in m2: if literal_hash(n1) == literal_hash(n2): if coalesce_any and isinstance(get_proper_type(m1[n1]), AnyType): result[n1] = m1[n1] else: result[n1] = make_simplified_union([m1[n1], m2[n2]]) return result def reduce_conditional_maps( type_maps: list[tuple[TypeMap, TypeMap]], use_meet: bool = False ) -> tuple[TypeMap, TypeMap]: """Reduces a list containing pairs of if/else TypeMaps into a single pair. We "and" together all of the if TypeMaps and "or" together the else TypeMaps. So for example, if we had the input: [ ({x: TypeIfX, shared: TypeIfShared1}, {x: TypeElseX, shared: TypeElseShared1}), ({y: TypeIfY, shared: TypeIfShared2}, {y: TypeElseY, shared: TypeElseShared2}), ] ...we'd return the output: ( {x: TypeIfX, y: TypeIfY, shared: PseudoIntersection[TypeIfShared1, TypeIfShared2]}, {shared: Union[TypeElseShared1, TypeElseShared2]}, ) ...where "PseudoIntersection[X, Y] == Y" because mypy actually doesn't understand intersections yet, so we settle for just arbitrarily picking the right expr's type. We only retain the shared expression in the 'else' case because we don't actually know whether x was refined or y was refined -- only just that one of the two was refined. """ if len(type_maps) == 0: return {}, {} elif len(type_maps) == 1: return type_maps[0] else: final_if_map, final_else_map = type_maps[0] for if_map, else_map in type_maps[1:]: final_if_map = and_conditional_maps(final_if_map, if_map, use_meet=use_meet) final_else_map = or_conditional_maps(final_else_map, else_map) return final_if_map, final_else_map def convert_to_typetype(type_map: TypeMap) -> TypeMap: converted_type_map: dict[Expression, Type] = {} if type_map is None: return None for expr, typ in type_map.items(): t = typ if isinstance(t, TypeVarType): t = t.upper_bound # TODO: should we only allow unions of instances as per PEP 484? if not isinstance(get_proper_type(t), (UnionType, Instance, NoneType)): # unknown type; error was likely reported earlier return {} converted_type_map[expr] = TypeType.make_normalized(typ) return converted_type_map def flatten(t: Expression) -> list[Expression]: """Flatten a nested sequence of tuples/lists into one list of nodes.""" if isinstance(t, (TupleExpr, ListExpr)): return [b for a in t.items for b in flatten(a)] elif isinstance(t, StarExpr): return flatten(t.expr) else: return [t] def flatten_types(t: Type) -> list[Type]: """Flatten a nested sequence of tuples into one list of nodes.""" t = get_proper_type(t) if isinstance(t, TupleType): return [b for a in t.items for b in flatten_types(a)] elif is_named_instance(t, "builtins.tuple"): return [t.args[0]] else: return [t] def expand_func(defn: FuncItem, map: dict[TypeVarId, Type]) -> FuncItem: visitor = TypeTransformVisitor(map) ret = visitor.node(defn) assert isinstance(ret, FuncItem) return ret class TypeTransformVisitor(TransformVisitor): def __init__(self, map: dict[TypeVarId, Type]) -> None: super().__init__() self.map = map def type(self, type: Type) -> Type: return expand_type(type, self.map) def are_argument_counts_overlapping(t: CallableType, s: CallableType) -> bool: """Can a single call match both t and s, based just on positional argument counts?""" min_args = max(t.min_args, s.min_args) max_args = min(t.max_possible_positional_args(), s.max_possible_positional_args()) return min_args <= max_args def expand_callable_variants(c: CallableType) -> list[CallableType]: """Expand a generic callable using all combinations of type variables' values/bounds.""" for tv in c.variables: # We need to expand self-type before other variables, because this is the only # type variable that can have other type variables in the upper bound. if tv.id.is_self(): c = expand_type(c, {tv.id: tv.upper_bound}).copy_modified( variables=[v for v in c.variables if not v.id.is_self()] ) break if not c.is_generic(): # Fast path. return [c] tvar_values = [] for tvar in c.variables: if isinstance(tvar, TypeVarType) and tvar.values: tvar_values.append(tvar.values) else: tvar_values.append([tvar.upper_bound]) variants = [] for combination in itertools.product(*tvar_values): tvar_map = {tv.id: subst for (tv, subst) in zip(c.variables, combination)} variants.append(expand_type(c, tvar_map).copy_modified(variables=[])) return variants def is_unsafe_overlapping_overload_signatures( signature: CallableType, other: CallableType, class_type_vars: list[TypeVarLikeType], partial_only: bool = True, ) -> bool: """Check if two overloaded signatures are unsafely overlapping or partially overlapping. We consider two functions 's' and 't' to be unsafely overlapping if three conditions hold: 1. s's parameters are partially overlapping with t's. i.e. there are calls that are valid for both signatures. 2. for these common calls, some of t's parameters types are wider that s's. 3. s's return type is NOT a subset of t's. Note that we use subset rather than subtype relationship in these checks because: * Overload selection happens at runtime, not statically. * This results in more lenient behavior. This can cause false negatives (e.g. if overloaded function returns an externally visible attribute with invariant type), but such situations are rare. In general, overloads in Python are generally unsafe, so we intentionally try to avoid giving non-actionable errors (see more details in comments below). Assumes that 'signature' appears earlier in the list of overload alternatives then 'other' and that their argument counts are overlapping. """ # Try detaching callables from the containing class so that all TypeVars # are treated as being free, i.e. the signature is as seen from inside the class, # where "self" is not yet bound to anything. signature = detach_callable(signature, class_type_vars) other = detach_callable(other, class_type_vars) # Note: We repeat this check twice in both directions compensate for slight # asymmetries in 'is_callable_compatible'. for sig_variant in expand_callable_variants(signature): for other_variant in expand_callable_variants(other): # Using only expanded callables may cause false negatives, we can add # more variants (e.g. using inference between callables) in the future. if is_subset_no_promote(sig_variant.ret_type, other_variant.ret_type): continue if not ( is_callable_compatible( sig_variant, other_variant, is_compat=is_overlapping_types_for_overload, check_args_covariantly=False, is_proper_subtype=False, is_compat_return=lambda l, r: not is_subset_no_promote(l, r), allow_partial_overlap=True, ) or is_callable_compatible( other_variant, sig_variant, is_compat=is_overlapping_types_for_overload, check_args_covariantly=True, is_proper_subtype=False, is_compat_return=lambda l, r: not is_subset_no_promote(r, l), allow_partial_overlap=True, ) ): continue # Using the same `allow_partial_overlap` flag as before, can cause false # negatives in case where star argument is used in a catch-all fallback overload. # But again, practicality beats purity here. if not partial_only or not is_callable_compatible( other_variant, sig_variant, is_compat=is_subset_no_promote, check_args_covariantly=True, is_proper_subtype=False, ignore_return=True, allow_partial_overlap=True, ): return True return False def detach_callable(typ: CallableType, class_type_vars: list[TypeVarLikeType]) -> CallableType: """Ensures that the callable's type variables are 'detached' and independent of the context. A callable normally keeps track of the type variables it uses within its 'variables' field. However, if the callable is from a method and that method is using a class type variable, the callable will not keep track of that type variable since it belongs to the class. """ if not class_type_vars: # Fast path, nothing to update. return typ return typ.copy_modified(variables=list(typ.variables) + class_type_vars) def overload_can_never_match(signature: CallableType, other: CallableType) -> bool: """Check if the 'other' method can never be matched due to 'signature'. This can happen if signature's parameters are all strictly broader then other's parameters. Assumes that both signatures have overlapping argument counts. """ # The extra erasure is needed to prevent spurious errors # in situations where an `Any` overload is used as a fallback # for an overload with type variables. The spurious error appears # because the type variables turn into `Any` during unification in # the below subtype check and (surprisingly?) `is_proper_subtype(Any, Any)` # returns `True`. # TODO: find a cleaner solution instead of this ad-hoc erasure. exp_signature = expand_type( signature, {tvar.id: erase_def_to_union_or_bound(tvar) for tvar in signature.variables} ) return is_callable_compatible( exp_signature, other, is_compat=is_more_precise, is_proper_subtype=True, ignore_return=True ) def is_more_general_arg_prefix(t: FunctionLike, s: FunctionLike) -> bool: """Does t have wider arguments than s?""" # TODO should an overload with additional items be allowed to be more # general than one with fewer items (or just one item)? if isinstance(t, CallableType): if isinstance(s, CallableType): return is_callable_compatible( t, s, is_compat=is_proper_subtype, is_proper_subtype=True, ignore_return=True ) elif isinstance(t, FunctionLike): if isinstance(s, FunctionLike): if len(t.items) == len(s.items): return all( is_same_arg_prefix(items, itemt) for items, itemt in zip(t.items, s.items) ) return False def is_same_arg_prefix(t: CallableType, s: CallableType) -> bool: return is_callable_compatible( t, s, is_compat=is_same_type, is_proper_subtype=True, ignore_return=True, check_args_covariantly=True, ignore_pos_arg_names=True, ) def infer_operator_assignment_method(typ: Type, operator: str) -> tuple[bool, str]: """Determine if operator assignment on given value type is in-place, and the method name. For example, if operator is '+', return (True, '__iadd__') or (False, '__add__') depending on which method is supported by the type. """ typ = get_proper_type(typ) method = operators.op_methods[operator] existing_method = None if isinstance(typ, Instance): existing_method = _find_inplace_method(typ, method, operator) elif isinstance(typ, TypedDictType): existing_method = _find_inplace_method(typ.fallback, method, operator) if existing_method is not None: return True, existing_method return False, method def _find_inplace_method(inst: Instance, method: str, operator: str) -> str | None: if operator in operators.ops_with_inplace_method: inplace_method = "__i" + method[2:] if inst.type.has_readable_member(inplace_method): return inplace_method return None def is_valid_inferred_type( typ: Type, options: Options, is_lvalue_final: bool = False, is_lvalue_member: bool = False ) -> bool: """Is an inferred type valid and needs no further refinement? Examples of invalid types include the None type (when we are not assigning None to a final lvalue) or List[]. When not doing strict Optional checking, all types containing None are invalid. When doing strict Optional checking, only None and types that are incompletely defined (i.e. contain UninhabitedType) are invalid. """ proper_type = get_proper_type(typ) if isinstance(proper_type, NoneType): # If the lvalue is final, we may immediately infer NoneType when the # initializer is None. # # If not, we want to defer making this decision. The final inferred # type could either be NoneType or an Optional type, depending on # the context. This resolution happens in leave_partial_types when # we pop a partial types scope. return is_lvalue_final or (not is_lvalue_member and options.allow_redefinition_new) elif isinstance(proper_type, UninhabitedType): return False return not typ.accept(InvalidInferredTypes()) class InvalidInferredTypes(BoolTypeQuery): """Find type components that are not valid for an inferred type. These include type, and any uninhabited types resulting from failed (ambiguous) type inference. """ def __init__(self) -> None: super().__init__(ANY_STRATEGY) def visit_uninhabited_type(self, t: UninhabitedType) -> bool: return t.ambiguous def visit_erased_type(self, t: ErasedType) -> bool: # This can happen inside a lambda. return True def visit_type_var(self, t: TypeVarType) -> bool: # This is needed to prevent leaking into partial types during # multi-step type inference. return t.id.is_meta_var() def visit_tuple_type(self, t: TupleType, /) -> bool: # Exclude fallback to avoid bogus "need type annotation" errors return self.query_types(t.items) class SetNothingToAny(TypeTranslator): """Replace all ambiguous Uninhabited types with Any (to avoid spurious extra errors).""" def visit_uninhabited_type(self, t: UninhabitedType) -> Type: if t.ambiguous: return AnyType(TypeOfAny.from_error) return t def visit_type_alias_type(self, t: TypeAliasType) -> Type: # Target of the alias cannot be an ambiguous UninhabitedType, so we just # replace the arguments. return t.copy_modified(args=[a.accept(self) for a in t.args]) def is_node_static(node: Node | None) -> bool | None: """Find out if a node describes a static function method.""" if isinstance(node, FuncDef): return node.is_static if isinstance(node, Var): return node.is_staticmethod return None TKey = TypeVar("TKey") TValue = TypeVar("TValue") class DisjointDict(Generic[TKey, TValue]): """An variation of the union-find algorithm/data structure where instead of keeping track of just disjoint sets, we keep track of disjoint dicts -- keep track of multiple Set[Key] -> Set[Value] mappings, where each mapping's keys are guaranteed to be disjoint. This data structure is currently used exclusively by 'group_comparison_operands' below to merge chains of '==' and 'is' comparisons when two or more chains use the same expression in best-case O(n), where n is the number of operands. Specifically, the `add_mapping()` function and `items()` functions will take on average O(k + v) and O(n) respectively, where k and v are the number of keys and values we're adding for a given chain. Note that k <= n and v <= n. We hit these average/best-case scenarios for most user code: e.g. when the user has just a single chain like 'a == b == c == d == ...' or multiple disjoint chains like 'a==b < c==d < e==f < ...'. (Note that a naive iterative merging would be O(n^2) for the latter case). In comparison, this data structure will make 'group_comparison_operands' have a worst-case runtime of O(n*log(n)): 'add_mapping()' and 'items()' are worst-case O(k*log(n) + v) and O(k*log(n)) respectively. This happens only in the rare case where the user keeps repeatedly making disjoint mappings before merging them in a way that persistently dodges the path compression optimization in '_lookup_root_id', which would end up constructing a single tree of height log_2(n). This makes root lookups no longer amoritized constant time when we finally call 'items()'. """ def __init__(self) -> None: # Each key maps to a unique ID self._key_to_id: dict[TKey, int] = {} # Each id points to the parent id, forming a forest of upwards-pointing trees. If the # current id already is the root, it points to itself. We gradually flatten these trees # as we perform root lookups: eventually all nodes point directly to its root. self._id_to_parent_id: dict[int, int] = {} # Each root id in turn maps to the set of values. self._root_id_to_values: dict[int, set[TValue]] = {} def add_mapping(self, keys: set[TKey], values: set[TValue]) -> None: """Adds a 'Set[TKey] -> Set[TValue]' mapping. If there already exists a mapping containing one or more of the given keys, we merge the input mapping with the old one. Note that the given set of keys must be non-empty -- otherwise, nothing happens. """ if not keys: return subtree_roots = [self._lookup_or_make_root_id(key) for key in keys] new_root = subtree_roots[0] root_values = self._root_id_to_values[new_root] root_values.update(values) for subtree_root in subtree_roots[1:]: if subtree_root == new_root or subtree_root not in self._root_id_to_values: continue self._id_to_parent_id[subtree_root] = new_root root_values.update(self._root_id_to_values.pop(subtree_root)) def items(self) -> list[tuple[set[TKey], set[TValue]]]: """Returns all disjoint mappings in key-value pairs.""" root_id_to_keys: dict[int, set[TKey]] = {} for key in self._key_to_id: root_id = self._lookup_root_id(key) if root_id not in root_id_to_keys: root_id_to_keys[root_id] = set() root_id_to_keys[root_id].add(key) output = [] for root_id, keys in root_id_to_keys.items(): output.append((keys, self._root_id_to_values[root_id])) return output def _lookup_or_make_root_id(self, key: TKey) -> int: if key in self._key_to_id: return self._lookup_root_id(key) else: new_id = len(self._key_to_id) self._key_to_id[key] = new_id self._id_to_parent_id[new_id] = new_id self._root_id_to_values[new_id] = set() return new_id def _lookup_root_id(self, key: TKey) -> int: i = self._key_to_id[key] while i != self._id_to_parent_id[i]: # Optimization: make keys directly point to their grandparents to speed up # future traversals. This prevents degenerate trees of height n from forming. new_parent = self._id_to_parent_id[self._id_to_parent_id[i]] self._id_to_parent_id[i] = new_parent i = new_parent return i def group_comparison_operands( pairwise_comparisons: Iterable[tuple[str, Expression, Expression]], operand_to_literal_hash: Mapping[int, Key], operators_to_group: set[str], ) -> list[tuple[str, list[int]]]: """Group a series of comparison operands together chained by any operand in the 'operators_to_group' set. All other pairwise operands are kept in groups of size 2. For example, suppose we have the input comparison expression: x0 == x1 == x2 < x3 < x4 is x5 is x6 is not x7 is not x8 If we get these expressions in a pairwise way (e.g. by calling ComparisonExpr's 'pairwise()' method), we get the following as input: [('==', x0, x1), ('==', x1, x2), ('<', x2, x3), ('<', x3, x4), ('is', x4, x5), ('is', x5, x6), ('is not', x6, x7), ('is not', x7, x8)] If `operators_to_group` is the set {'==', 'is'}, this function will produce the following "simplified operator list": [("==", [0, 1, 2]), ("<", [2, 3]), ("<", [3, 4]), ("is", [4, 5, 6]), ("is not", [6, 7]), ("is not", [7, 8])] Note that (a) we yield *indices* to the operands rather then the operand expressions themselves and that (b) operands used in a consecutive chain of '==' or 'is' are grouped together. If two of these chains happen to contain operands with the same underlying literal hash (e.g. are assignable and correspond to the same expression), we combine those chains together. For example, if we had: same == x < y == same ...and if 'operand_to_literal_hash' contained the same values for the indices 0 and 3, we'd produce the following output: [("==", [0, 1, 2, 3]), ("<", [1, 2])] But if the 'operand_to_literal_hash' did *not* contain an entry, we'd instead default to returning: [("==", [0, 1]), ("<", [1, 2]), ("==", [2, 3])] This function is currently only used to assist with type-narrowing refinements and is extracted out to a helper function so we can unit test it. """ groups: dict[str, DisjointDict[Key, int]] = {op: DisjointDict() for op in operators_to_group} simplified_operator_list: list[tuple[str, list[int]]] = [] last_operator: str | None = None current_indices: set[int] = set() current_hashes: set[Key] = set() for i, (operator, left_expr, right_expr) in enumerate(pairwise_comparisons): if last_operator is None: last_operator = operator if current_indices and (operator != last_operator or operator not in operators_to_group): # If some of the operands in the chain are assignable, defer adding it: we might # end up needing to merge it with other chains that appear later. if not current_hashes: simplified_operator_list.append((last_operator, sorted(current_indices))) else: groups[last_operator].add_mapping(current_hashes, current_indices) last_operator = operator current_indices = set() current_hashes = set() # Note: 'i' corresponds to the left operand index, so 'i + 1' is the # right operand. current_indices.add(i) current_indices.add(i + 1) # We only ever want to combine operands/combine chains for these operators if operator in operators_to_group: left_hash = operand_to_literal_hash.get(i) if left_hash is not None: current_hashes.add(left_hash) right_hash = operand_to_literal_hash.get(i + 1) if right_hash is not None: current_hashes.add(right_hash) if last_operator is not None: if not current_hashes: simplified_operator_list.append((last_operator, sorted(current_indices))) else: groups[last_operator].add_mapping(current_hashes, current_indices) # Now that we know which chains happen to contain the same underlying expressions # and can be merged together, add in this info back to the output. for operator, disjoint_dict in groups.items(): for keys, indices in disjoint_dict.items(): simplified_operator_list.append((operator, sorted(indices))) # For stability, reorder list by the first operand index to appear simplified_operator_list.sort(key=lambda item: item[1][0]) return simplified_operator_list def is_typed_callable(c: Type | None) -> bool: c = get_proper_type(c) if not c or not isinstance(c, CallableType): return False return not all( isinstance(t, AnyType) and t.type_of_any == TypeOfAny.unannotated for t in get_proper_types(c.arg_types + [c.ret_type]) ) def is_untyped_decorator(typ: Type | None) -> bool: typ = get_proper_type(typ) if not typ: return True elif isinstance(typ, CallableType): return not is_typed_callable(typ) elif isinstance(typ, Instance): method = typ.type.get_method("__call__") if method: if isinstance(method, Decorator): return is_untyped_decorator(method.func.type) or is_untyped_decorator( method.var.type ) if isinstance(method.type, Overloaded): return any(is_untyped_decorator(item) for item in method.type.items) else: return not is_typed_callable(method.type) else: return False elif isinstance(typ, Overloaded): return any(is_untyped_decorator(item) for item in typ.items) return True def is_static(func: FuncBase | Decorator) -> bool: if isinstance(func, Decorator): return is_static(func.func) elif isinstance(func, FuncBase): return func.is_static assert False, f"Unexpected func type: {type(func)}" def is_property(defn: SymbolNode) -> bool: if isinstance(defn, Decorator): return defn.func.is_property if isinstance(defn, OverloadedFuncDef): if defn.items and isinstance(defn.items[0], Decorator): return defn.items[0].func.is_property return False def is_settable_property(defn: SymbolNode | None) -> TypeGuard[OverloadedFuncDef]: if isinstance(defn, OverloadedFuncDef): if defn.items and isinstance(defn.items[0], Decorator): return defn.items[0].func.is_property return False def is_custom_settable_property(defn: SymbolNode | None) -> bool: """Check if a node is a settable property with a non-trivial setter type. By non-trivial here we mean that it is known (i.e. definition was already type checked), it is not Any, and it is different from the property getter type. """ if defn is None: return False if not is_settable_property(defn): return False first_item = defn.items[0] assert isinstance(first_item, Decorator) if not first_item.var.is_settable_property: return False var = first_item.var if var.type is None or var.setter_type is None or isinstance(var.type, PartialType): # The caller should defer in case of partial types or not ready variables. return False setter_type = var.setter_type.arg_types[1] if isinstance(get_proper_type(setter_type), AnyType): return False return not is_same_type(get_property_type(get_proper_type(var.type)), setter_type) def get_property_type(t: ProperType) -> ProperType: if isinstance(t, CallableType): return get_proper_type(t.ret_type) if isinstance(t, Overloaded): return get_proper_type(t.items[0].ret_type) return t def is_subset_no_promote(left: Type, right: Type) -> bool: return is_subtype(left, right, ignore_promotions=True, always_covariant=True) def is_overlapping_types_for_overload(left: Type, right: Type) -> bool: # Note that among other effects 'overlap_for_overloads' flag will effectively # ignore possible overlap between type variables and None. This is technically # unsafe, but unsafety is tiny and this prevents some common use cases like: # @overload # def foo(x: None) -> None: .. # @overload # def foo(x: T) -> Foo[T]: ... return is_overlapping_types( left, right, ignore_promotions=True, prohibit_none_typevar_overlap=True, overlap_for_overloads=True, ) def is_private(node_name: str) -> bool: """Check if node is private to class definition.""" return node_name.startswith("__") and not node_name.endswith("__") def is_string_literal(typ: Type) -> bool: strs = try_getting_str_literals_from_type(typ) return strs is not None and len(strs) == 1 def has_bool_item(typ: ProperType) -> bool: """Return True if type is 'bool' or a union with a 'bool' item.""" if is_named_instance(typ, "builtins.bool"): return True if isinstance(typ, UnionType): return any(is_named_instance(item, "builtins.bool") for item in typ.items) return False def collapse_walrus(e: Expression) -> Expression: """If an expression is an AssignmentExpr, pull out the assignment target. We don't make any attempt to pull out all the targets in code like `x := (y := z)`. We could support narrowing those if that sort of code turns out to be common. """ if isinstance(e, AssignmentExpr): return e.target return e def find_last_var_assignment_line(n: Node, v: Var) -> int: """Find the highest line number of a potential assignment to variable within node. This supports local and global variables. Return -1 if no assignment was found. """ visitor = VarAssignVisitor(v) n.accept(visitor) return visitor.last_line class VarAssignVisitor(TraverserVisitor): def __init__(self, v: Var) -> None: self.last_line = -1 self.lvalue = False self.var_node = v def visit_assignment_stmt(self, s: AssignmentStmt) -> None: self.lvalue = True for lv in s.lvalues: lv.accept(self) self.lvalue = False def visit_name_expr(self, e: NameExpr) -> None: if self.lvalue and e.node is self.var_node: self.last_line = max(self.last_line, e.line) def visit_member_expr(self, e: MemberExpr) -> None: old_lvalue = self.lvalue self.lvalue = False super().visit_member_expr(e) self.lvalue = old_lvalue def visit_index_expr(self, e: IndexExpr) -> None: old_lvalue = self.lvalue self.lvalue = False super().visit_index_expr(e) self.lvalue = old_lvalue def visit_with_stmt(self, s: WithStmt) -> None: self.lvalue = True for lv in s.target: if lv is not None: lv.accept(self) self.lvalue = False s.body.accept(self) def visit_for_stmt(self, s: ForStmt) -> None: self.lvalue = True s.index.accept(self) self.lvalue = False s.body.accept(self) if s.else_body: s.else_body.accept(self) def visit_assignment_expr(self, e: AssignmentExpr) -> None: self.lvalue = True e.target.accept(self) self.lvalue = False e.value.accept(self) def visit_as_pattern(self, p: AsPattern) -> None: if p.pattern is not None: p.pattern.accept(self) if p.name is not None: self.lvalue = True p.name.accept(self) self.lvalue = False def visit_starred_pattern(self, p: StarredPattern) -> None: if p.capture is not None: self.lvalue = True p.capture.accept(self) self.lvalue = False def is_ambiguous_mix_of_enums(types: list[Type]) -> bool: """Do types have IntEnum/StrEnum types that are potentially overlapping with other types? If True, we shouldn't attempt type narrowing based on enum values, as it gets too ambiguous. For example, return True if there's an 'int' type together with an IntEnum literal. However, IntEnum together with a literal of the same IntEnum type is not ambiguous. """ # We need these things for this to be ambiguous: # (1) an IntEnum or StrEnum type # (2) either a different IntEnum/StrEnum type or a non-enum type ("") # # It would be slightly more correct to calculate this separately for IntEnum and # StrEnum related types, as an IntEnum can't be confused with a StrEnum. return len(_ambiguous_enum_variants(types)) > 1 def _ambiguous_enum_variants(types: list[Type]) -> set[str]: result = set() for t in types: t = get_proper_type(t) if isinstance(t, UnionType): result.update(_ambiguous_enum_variants(t.items)) elif isinstance(t, Instance): if t.last_known_value: result.update(_ambiguous_enum_variants([t.last_known_value])) elif t.type.is_enum and any( base.fullname in ("enum.IntEnum", "enum.StrEnum") for base in t.type.mro ): result.add(t.type.fullname) elif not t.type.is_enum: # These might compare equal to IntEnum/StrEnum types (e.g. Decimal), so # let's be conservative result.add("") elif isinstance(t, LiteralType): result.update(_ambiguous_enum_variants([t.fallback])) elif isinstance(t, NoneType): pass else: result.add("") return result def is_typeddict_type_context(lvalue_type: Type | None) -> bool: if lvalue_type is None: return False lvalue_proper = get_proper_type(lvalue_type) return isinstance(lvalue_proper, TypedDictType) def is_method(node: SymbolNode | None) -> bool: if isinstance(node, OverloadedFuncDef): return not node.is_property if isinstance(node, Decorator): return not node.var.is_property return isinstance(node, FuncDef)