"""Semantic analysis of TypedDict definitions.""" from __future__ import annotations from collections.abc import Collection from typing import Final from mypy import errorcodes as codes, message_registry from mypy.errorcodes import ErrorCode from mypy.expandtype import expand_type from mypy.exprtotype import TypeTranslationError, expr_to_unanalyzed_type from mypy.message_registry import TYPEDDICT_OVERRIDE_MERGE from mypy.messages import MessageBuilder from mypy.nodes import ( ARG_NAMED, ARG_POS, AssignmentStmt, CallExpr, ClassDef, Context, DictExpr, EllipsisExpr, Expression, ExpressionStmt, IndexExpr, NameExpr, PassStmt, RefExpr, Statement, StrExpr, TempNode, TupleExpr, TypeAlias, TypedDictExpr, TypeInfo, ) from mypy.options import Options from mypy.semanal_shared import ( SemanticAnalyzerInterface, has_placeholder, require_bool_literal_argument, ) from mypy.state import state from mypy.typeanal import check_for_explicit_any, has_any_from_unimported_type from mypy.types import ( TPDICT_NAMES, AnyType, ReadOnlyType, RequiredType, Type, TypedDictType, TypeOfAny, TypeVarLikeType, get_proper_type, ) TPDICT_CLASS_ERROR: Final = ( 'Invalid statement in TypedDict definition; expected "field_name: field_type"' ) class TypedDictAnalyzer: def __init__( self, options: Options, api: SemanticAnalyzerInterface, msg: MessageBuilder ) -> None: self.options = options self.api = api self.msg = msg def analyze_typeddict_classdef(self, defn: ClassDef) -> tuple[bool, TypeInfo | None]: """Analyze a class that may define a TypedDict. Assume that base classes have been analyzed already. Note: Unlike normal classes, we won't create a TypeInfo until the whole definition of the TypeDict (including the body and all key names and types) is complete. This is mostly because we store the corresponding TypedDictType in the TypeInfo. Return (is this a TypedDict, new TypeInfo). Specifics: * If we couldn't finish due to incomplete reference anywhere in the definition, return (True, None). * If this is not a TypedDict, return (False, None). """ possible = False for base_expr in defn.base_type_exprs: if isinstance(base_expr, CallExpr): base_expr = base_expr.callee if isinstance(base_expr, IndexExpr): base_expr = base_expr.base if isinstance(base_expr, RefExpr): self.api.accept(base_expr) if base_expr.fullname in TPDICT_NAMES or self.is_typeddict(base_expr): possible = True if isinstance(base_expr.node, TypeInfo) and base_expr.node.is_final: err = message_registry.CANNOT_INHERIT_FROM_FINAL self.fail(err.format(base_expr.node.name).value, defn, code=err.code) if not possible: return False, None existing_info = None if isinstance(defn.analyzed, TypedDictExpr): existing_info = defn.analyzed.info field_types: dict[str, Type] | None if ( len(defn.base_type_exprs) == 1 and isinstance(defn.base_type_exprs[0], RefExpr) and defn.base_type_exprs[0].fullname in TPDICT_NAMES ): # Building a new TypedDict field_types, statements, required_keys, readonly_keys = ( self.analyze_typeddict_classdef_fields(defn) ) if field_types is None: return True, None # Defer if self.api.is_func_scope() and "@" not in defn.name: defn.name += "@" + str(defn.line) info = self.build_typeddict_typeinfo( defn.name, field_types, required_keys, readonly_keys, defn.line, existing_info ) defn.analyzed = TypedDictExpr(info) defn.analyzed.line = defn.line defn.analyzed.column = defn.column defn.defs.body = statements return True, info # Extending/merging existing TypedDicts typeddict_bases: list[Expression] = [] typeddict_bases_set = set() for expr in defn.base_type_exprs: ok, maybe_type_info, _ = self.check_typeddict(expr, None, False) if ok and maybe_type_info is not None: # expr is a CallExpr info = maybe_type_info typeddict_bases_set.add(info.fullname) typeddict_bases.append(expr) elif isinstance(expr, RefExpr) and expr.fullname in TPDICT_NAMES: if "TypedDict" not in typeddict_bases_set: typeddict_bases_set.add("TypedDict") else: self.fail('Duplicate base class "TypedDict"', defn) elif ( isinstance(expr, RefExpr) and self.is_typeddict(expr) or isinstance(expr, IndexExpr) and self.is_typeddict(expr.base) ): info = self._parse_typeddict_base(expr, defn) if info.fullname not in typeddict_bases_set: typeddict_bases_set.add(info.fullname) typeddict_bases.append(expr) else: self.fail(f'Duplicate base class "{info.name}"', defn) else: self.fail("All bases of a new TypedDict must be TypedDict types", defn) field_types = {} required_keys = set() readonly_keys = set() # Iterate over bases in reverse order so that leftmost base class' keys take precedence for base in reversed(typeddict_bases): self.add_keys_and_types_from_base( base, field_types, required_keys, readonly_keys, defn ) (new_field_types, new_statements, new_required_keys, new_readonly_keys) = ( self.analyze_typeddict_classdef_fields(defn, oldfields=field_types) ) if new_field_types is None: return True, None # Defer field_types.update(new_field_types) required_keys.update(new_required_keys) readonly_keys.update(new_readonly_keys) info = self.build_typeddict_typeinfo( defn.name, field_types, required_keys, readonly_keys, defn.line, existing_info ) defn.analyzed = TypedDictExpr(info) defn.analyzed.line = defn.line defn.analyzed.column = defn.column defn.defs.body = new_statements return True, info def add_keys_and_types_from_base( self, base: Expression, field_types: dict[str, Type], required_keys: set[str], readonly_keys: set[str], ctx: Context, ) -> None: info = self._parse_typeddict_base(base, ctx) base_args: list[Type] = [] if isinstance(base, IndexExpr): args = self.analyze_base_args(base, ctx) if args is None: return base_args = args assert info.typeddict_type is not None base_typed_dict = info.typeddict_type base_items = base_typed_dict.items valid_items = base_items.copy() # Always fix invalid bases to avoid crashes. tvars = info.defn.type_vars if len(base_args) != len(tvars): any_kind = TypeOfAny.from_omitted_generics if base_args: self.fail(f'Invalid number of type arguments for "{info.name}"', ctx) any_kind = TypeOfAny.from_error base_args = [AnyType(any_kind) for _ in tvars] with state.strict_optional_set(self.options.strict_optional): valid_items = self.map_items_to_base(valid_items, tvars, base_args) for key in base_items: if key in field_types: self.fail(TYPEDDICT_OVERRIDE_MERGE.format(key), ctx) field_types.update(valid_items) required_keys.update(base_typed_dict.required_keys) readonly_keys.update(base_typed_dict.readonly_keys) def _parse_typeddict_base(self, base: Expression, ctx: Context) -> TypeInfo: if isinstance(base, RefExpr): if isinstance(base.node, TypeInfo): return base.node elif isinstance(base.node, TypeAlias): # Only old TypeAlias / plain assignment, PEP695 `type` stmt # cannot be used as a base class target = get_proper_type(base.node.target) assert isinstance(target, TypedDictType) return target.fallback.type else: assert False elif isinstance(base, IndexExpr): assert isinstance(base.base, RefExpr) return self._parse_typeddict_base(base.base, ctx) else: assert isinstance(base, CallExpr) assert isinstance(base.analyzed, TypedDictExpr) return base.analyzed.info def analyze_base_args(self, base: IndexExpr, ctx: Context) -> list[Type] | None: """Analyze arguments of base type expressions as types. We need to do this, because normal base class processing happens after the TypedDict special-casing (plus we get a custom error message). """ base_args = [] if isinstance(base.index, TupleExpr): args = base.index.items else: args = [base.index] for arg_expr in args: try: type = expr_to_unanalyzed_type(arg_expr, self.options, self.api.is_stub_file) except TypeTranslationError: self.fail("Invalid TypedDict type argument", ctx) return None analyzed = self.api.anal_type( type, allow_typed_dict_special_forms=True, allow_placeholder=not self.api.is_func_scope(), ) if analyzed is None: return None base_args.append(analyzed) return base_args def map_items_to_base( self, valid_items: dict[str, Type], tvars: list[TypeVarLikeType], base_args: list[Type] ) -> dict[str, Type]: """Map item types to how they would look in their base with type arguments applied. Note it is safe to use expand_type() during semantic analysis, because it should never (indirectly) call is_subtype(). """ mapped_items = {} for key in valid_items: type_in_base = valid_items[key] if not tvars: mapped_items[key] = type_in_base continue # TODO: simple zip can't be used for variadic types. mapped_items[key] = expand_type( type_in_base, {t.id: a for (t, a) in zip(tvars, base_args)} ) return mapped_items def analyze_typeddict_classdef_fields( self, defn: ClassDef, oldfields: Collection[str] | None = None ) -> tuple[dict[str, Type] | None, list[Statement], set[str], set[str]]: """Analyze fields defined in a TypedDict class definition. This doesn't consider inherited fields (if any). Also consider totality, if given. Return tuple with these items: * Dict of key -> type (or None if found an incomplete reference -> deferral) * List of statements from defn.defs.body that are legally allowed to be a part of a TypedDict definition * Set of required keys """ fields: dict[str, Type] = {} readonly_keys = set[str]() required_keys = set[str]() statements: list[Statement] = [] total: bool | None = True for key in defn.keywords: if key == "total": total = require_bool_literal_argument( self.api, defn.keywords["total"], "total", True ) continue for_function = ' for "__init_subclass__" of "TypedDict"' self.msg.unexpected_keyword_argument_for_function(for_function, key, defn) for stmt in defn.defs.body: if not isinstance(stmt, AssignmentStmt): # Still allow pass or ... (for empty TypedDict's) and docstrings if isinstance(stmt, PassStmt) or ( isinstance(stmt, ExpressionStmt) and isinstance(stmt.expr, (EllipsisExpr, StrExpr)) ): statements.append(stmt) else: defn.removed_statements.append(stmt) self.fail(TPDICT_CLASS_ERROR, stmt) elif len(stmt.lvalues) > 1 or not isinstance(stmt.lvalues[0], NameExpr): # An assignment, but an invalid one. defn.removed_statements.append(stmt) self.fail(TPDICT_CLASS_ERROR, stmt) else: name = stmt.lvalues[0].name if name in (oldfields or []): self.fail(f'Overwriting TypedDict field "{name}" while extending', stmt) if name in fields: self.fail(f'Duplicate TypedDict key "{name}"', stmt) continue # Append stmt, name, and type in this case... statements.append(stmt) field_type: Type if stmt.unanalyzed_type is None: field_type = AnyType(TypeOfAny.unannotated) else: analyzed = self.api.anal_type( stmt.unanalyzed_type, allow_typed_dict_special_forms=True, allow_placeholder=not self.api.is_func_scope(), prohibit_self_type="TypedDict item type", prohibit_special_class_field_types="TypedDict", ) if analyzed is None: return None, [], set(), set() # Need to defer field_type = analyzed if not has_placeholder(analyzed): stmt.type = self.extract_meta_info(analyzed, stmt)[0] field_type, required, readonly = self.extract_meta_info(field_type) fields[name] = field_type if (total or required is True) and required is not False: required_keys.add(name) if readonly: readonly_keys.add(name) # ...despite possible minor failures that allow further analysis. if stmt.type is None or hasattr(stmt, "new_syntax") and not stmt.new_syntax: self.fail(TPDICT_CLASS_ERROR, stmt) elif not isinstance(stmt.rvalue, TempNode): # x: int assigns rvalue to TempNode(AnyType()) self.fail("Right hand side values are not supported in TypedDict", stmt) return fields, statements, required_keys, readonly_keys def extract_meta_info( self, typ: Type, context: Context | None = None ) -> tuple[Type, bool | None, bool]: """Unwrap all metadata types.""" is_required = None # default, no modification readonly = False # by default all is mutable seen_required = False seen_readonly = False while isinstance(typ, (RequiredType, ReadOnlyType)): if isinstance(typ, RequiredType): if context is not None and seen_required: self.fail( '"{}" type cannot be nested'.format( "Required[]" if typ.required else "NotRequired[]" ), context, code=codes.VALID_TYPE, ) is_required = typ.required seen_required = True typ = typ.item if isinstance(typ, ReadOnlyType): if context is not None and seen_readonly: self.fail('"ReadOnly[]" type cannot be nested', context, code=codes.VALID_TYPE) readonly = True seen_readonly = True typ = typ.item return typ, is_required, readonly def check_typeddict( self, node: Expression, var_name: str | None, is_func_scope: bool ) -> tuple[bool, TypeInfo | None, list[TypeVarLikeType]]: """Check if a call defines a TypedDict. The optional var_name argument is the name of the variable to which this is assigned, if any. Return a pair (is it a typed dict, corresponding TypeInfo). If the definition is invalid but looks like a TypedDict, report errors but return (some) TypeInfo. If some type is not ready, return (True, None). """ if not isinstance(node, CallExpr): return False, None, [] call = node callee = call.callee if not isinstance(callee, RefExpr): return False, None, [] fullname = callee.fullname if fullname not in TPDICT_NAMES: return False, None, [] res = self.parse_typeddict_args(call) if res is None: # This is a valid typed dict, but some type is not ready. # The caller should defer this until next iteration. return True, None, [] name, items, types, total, tvar_defs, ok = res if not ok: # Error. Construct dummy return value. if var_name: name = var_name if is_func_scope: name += "@" + str(call.line) else: name = var_name = "TypedDict@" + str(call.line) info = self.build_typeddict_typeinfo(name, {}, set(), set(), call.line, None) else: if var_name is not None and name != var_name: self.fail( 'First argument "{}" to TypedDict() does not match variable name "{}"'.format( name, var_name ), node, code=codes.NAME_MATCH, ) if name != var_name or is_func_scope: # Give it a unique name derived from the line number. name += "@" + str(call.line) required_keys = { field for (field, t) in zip(items, types) if (total or (isinstance(t, RequiredType) and t.required)) and not (isinstance(t, RequiredType) and not t.required) } readonly_keys = { field for (field, t) in zip(items, types) if isinstance(t, ReadOnlyType) } types = [ # unwrap Required[T] or ReadOnly[T] to just T t.item if isinstance(t, (RequiredType, ReadOnlyType)) else t for t in types ] # Perform various validations after unwrapping. for t in types: check_for_explicit_any( t, self.options, self.api.is_typeshed_stub_file, self.msg, context=call ) if self.options.disallow_any_unimported: for t in types: if has_any_from_unimported_type(t): self.msg.unimported_type_becomes_any("Type of a TypedDict key", t, call) existing_info = None if isinstance(node.analyzed, TypedDictExpr): existing_info = node.analyzed.info info = self.build_typeddict_typeinfo( name, dict(zip(items, types)), required_keys, readonly_keys, call.line, existing_info, ) info.line = node.line # Store generated TypeInfo under both names, see semanal_namedtuple for more details. if name != var_name or is_func_scope: self.api.add_symbol_skip_local(name, info) if var_name: self.api.add_symbol(var_name, info, node) call.analyzed = TypedDictExpr(info) call.analyzed.set_line(call) return True, info, tvar_defs def parse_typeddict_args( self, call: CallExpr ) -> tuple[str, list[str], list[Type], bool, list[TypeVarLikeType], bool] | None: """Parse typed dict call expression. Return names, types, totality, was there an error during parsing. If some type is not ready, return None. """ # TODO: Share code with check_argument_count in checkexpr.py? args = call.args if len(args) < 2: return self.fail_typeddict_arg("Too few arguments for TypedDict()", call) if len(args) > 3: return self.fail_typeddict_arg("Too many arguments for TypedDict()", call) # TODO: Support keyword arguments if call.arg_kinds not in ([ARG_POS, ARG_POS], [ARG_POS, ARG_POS, ARG_NAMED]): return self.fail_typeddict_arg("Unexpected arguments to TypedDict()", call) if len(args) == 3 and call.arg_names[2] != "total": return self.fail_typeddict_arg( f'Unexpected keyword argument "{call.arg_names[2]}" for "TypedDict"', call ) if not isinstance(args[0], StrExpr): return self.fail_typeddict_arg( "TypedDict() expects a string literal as the first argument", call ) if not isinstance(args[1], DictExpr): return self.fail_typeddict_arg( "TypedDict() expects a dictionary literal as the second argument", call ) total: bool | None = True if len(args) == 3: total = require_bool_literal_argument(self.api, call.args[2], "total") if total is None: return "", [], [], True, [], False dictexpr = args[1] tvar_defs = self.api.get_and_bind_all_tvars([t for k, t in dictexpr.items]) res = self.parse_typeddict_fields_with_types(dictexpr.items) if res is None: # One of the types is not ready, defer. return None items, types, ok = res assert total is not None return args[0].value, items, types, total, tvar_defs, ok def parse_typeddict_fields_with_types( self, dict_items: list[tuple[Expression | None, Expression]] ) -> tuple[list[str], list[Type], bool] | None: """Parse typed dict items passed as pairs (name expression, type expression). Return names, types, was there an error. If some type is not ready, return None. """ seen_keys = set() items: list[str] = [] types: list[Type] = [] for field_name_expr, field_type_expr in dict_items: if isinstance(field_name_expr, StrExpr): key = field_name_expr.value items.append(key) if key in seen_keys: self.fail(f'Duplicate TypedDict key "{key}"', field_name_expr) seen_keys.add(key) else: name_context = field_name_expr or field_type_expr self.fail_typeddict_arg("Invalid TypedDict() field name", name_context) return [], [], False try: type = expr_to_unanalyzed_type( field_type_expr, self.options, self.api.is_stub_file ) except TypeTranslationError: self.fail_typeddict_arg("Use dict literal for nested TypedDict", field_type_expr) return [], [], False analyzed = self.api.anal_type( type, allow_typed_dict_special_forms=True, allow_placeholder=not self.api.is_func_scope(), prohibit_self_type="TypedDict item type", prohibit_special_class_field_types="TypedDict", ) if analyzed is None: return None types.append(analyzed) return items, types, True def fail_typeddict_arg( self, message: str, context: Context ) -> tuple[str, list[str], list[Type], bool, list[TypeVarLikeType], bool]: self.fail(message, context) return "", [], [], True, [], False def build_typeddict_typeinfo( self, name: str, item_types: dict[str, Type], required_keys: set[str], readonly_keys: set[str], line: int, existing_info: TypeInfo | None, ) -> TypeInfo: # Prefer typing then typing_extensions if available. fallback = ( self.api.named_type_or_none("typing._TypedDict", []) or self.api.named_type_or_none("typing_extensions._TypedDict", []) or self.api.named_type_or_none("mypy_extensions._TypedDict", []) ) assert fallback is not None info = existing_info or self.api.basic_new_typeinfo(name, fallback, line) typeddict_type = TypedDictType(item_types, required_keys, readonly_keys, fallback) if info.special_alias and has_placeholder(info.special_alias.target): self.api.process_placeholder( None, "TypedDict item", info, force_progress=typeddict_type != info.typeddict_type ) info.update_typeddict_type(typeddict_type) return info # Helpers def is_typeddict(self, expr: Expression) -> bool: return isinstance(expr, RefExpr) and ( isinstance(expr.node, TypeInfo) and expr.node.typeddict_type is not None or isinstance(expr.node, TypeAlias) and isinstance(get_proper_type(expr.node.target), TypedDictType) ) def fail(self, msg: str, ctx: Context, *, code: ErrorCode | None = None) -> None: self.api.fail(msg, ctx, code=code) def note(self, msg: str, ctx: Context) -> None: self.api.note(msg, ctx)