def solve_constraints(vars, constraints, basic):
"""Solve type constraints.
Return lower bound for each type variable or None if the variable could
not be solved.
"""
# Collect a list of constraints for each type variable.
cmap = {}
for con in constraints:
a = cmap.get(con.type_var, [])
a.append(con)
cmap[con.type_var] = a
res = []
# Solve each type variable separately.
for tvar in vars:
bottom = None
top = None
# Process each contraint separely, and calculate the lower and upper
# bounds based on constraints. Note that we assume that the contraint
# targets do not have contraint references.
for c in cmap.get(tvar, []):
if c.op == SUPERTYPE_OF:
if bottom is None:
bottom = c.target
else:
bottom = join_types(bottom, c.target, basic)
else:
if top is None:
top = c.target
else:
top = meet_types(top, c.target, basic)
if top is None:
if isinstance(bottom, Void):
top = Void()
else:
top = basic.object
if bottom is None:
if isinstance(top, Void):
bottom = Void()
else:
bottom = NoneTyp()
if isinstance(top, Any) or isinstance(bottom, Any):
top = Any()
bottom = Any()
# Pick the most specific type if it satisfies the constraints.
if (not top or not bottom or is_subtype(bottom, top)) and (
not isinstance(top, ErrorType) and
not isinstance(bottom, ErrorType)):
res.append(bottom)
else:
res.append(None)
return res
def solve_constraints(vars: List[TypeVarId], constraints: List[Constraint],
strict: bool =True) -> List[Optional[Type]]:
"""Solve type constraints.
Return the best type(s) for type variables; each type can be None if the value of the variable
could not be solved.
If a variable has no constraints, if strict=True then arbitrarily
pick NoneTyp as the value of the type variable. If strict=False,
pick AnyType.
"""
# Collect a list of constraints for each type variable.
cmap = defaultdict(list) # type: Dict[TypeVarId, List[Constraint]]
for con in constraints:
cmap[con.type_var].append(con)
res = [] # type: List[Optional[Type]]
# Solve each type variable separately.
for tvar in vars:
bottom = None # type: Optional[Type]
top = None # type: Optional[Type]
candidate = None # type: Optional[Type]
# Process each constraint separately, and calculate the lower and upper
# bounds based on constraints. Note that we assume that the constraint
# targets do not have constraint references.
for c in cmap.get(tvar, []):
if c.op == SUPERTYPE_OF:
if bottom is None:
bottom = c.target
else:
bottom = join_types(bottom, c.target)
else:
if top is None:
top = c.target
else:
top = meet_types(top, c.target)
if isinstance(top, AnyType) or isinstance(bottom, AnyType):
res.append(AnyType())
continue
elif bottom is None:
if top:
candidate = top
else:
# No constraints for type variable -- 'UninhabitedType' is the most specific type.
if strict:
candidate = UninhabitedType()
else:
candidate = AnyType()
elif top is None:
candidate = bottom
elif is_subtype(bottom, top):
candidate = bottom
else:
candidate = None
res.append(candidate)
return res
def test_mixed_truth_restricted_type(self) -> None:
# join_types against differently restricted truthiness types drops restrictions.
true_any = true_only(AnyType(TypeOfAny.special_form))
false_o = false_only(self.fx.o)
j = join_types(true_any, false_o)
assert_true(j.can_be_true)
assert_true(j.can_be_false)
def test_mixed_truth_restricted_type(self) -> None:
# join_types against differently restricted truthiness types drops restrictions.
true_any = true_only(AnyType(TypeOfAny.special_form))
false_o = false_only(self.fx.o)
j = join_types(true_any, false_o)
assert_true(j.can_be_true)
assert_true(j.can_be_false)
def assert_simple_join(self, s: Type, t: Type, join: Type) -> None:
result = join_types(s, t)
actual = str(result)
expected = str(join)
assert_equal(actual, expected,
'join({}, {}) == {{}} ({{}} expected)'.format(s, t))
assert is_subtype(s, result), '{} not subtype of {}'.format(s, result)
assert is_subtype(t, result), '{} not subtype of {}'.format(t, result)
def solve_constraints(vars: List[int], constraints: List[Constraint],
basic: BasicTypes) -> List[Type]:
"""Solve type constraints.
Return the best type(s) for type variables; each type can be None if the value of the variable
could not be solved. If a variable has no constraints, arbitrarily pick NoneTyp as the value of
the type variable.
"""
# Collect a list of constraints for each type variable.
cmap = Dict[int, List[Constraint]]()
for con in constraints:
a = cmap.get(con.type_var, [])
a.append(con)
cmap[con.type_var] = a
res = [] # type: List[Type]
# Solve each type variable separately.
for tvar in vars:
bottom = None # type: Type
top = None # type: Type
# Process each contraint separely, and calculate the lower and upper
# bounds based on constraints. Note that we assume that the constraint
# targets do not have constraint references.
for c in cmap.get(tvar, []):
if c.op == SUPERTYPE_OF:
if bottom is None:
bottom = c.target
else:
bottom = join_types(bottom, c.target, basic)
else:
if top is None:
top = c.target
else:
top = meet_types(top, c.target, basic)
if isinstance(top, AnyType) or isinstance(bottom, AnyType):
res.append(AnyType())
continue
elif bottom is None:
if top:
candidate = top
else:
# No constraints for type variable -- type 'None' is the most specific type.
candidate = NoneTyp()
elif top is None:
candidate = bottom
elif is_subtype(bottom, top):
candidate = bottom
else:
candidate = None
if isinstance(candidate, ErrorType):
res.append(None)
else:
res.append(candidate)
return res
def test_simple_type_objects(self):
t1 = self.type_callable(self.fx.a, self.fx.a)
t2 = self.type_callable(self.fx.b, self.fx.b)
self.assert_join(t1, t1, t1)
assert_true(join_types(t1, t1, self.fx.basic).is_type_obj())
self.assert_join(t1, t2, self.fx.std_type)
self.assert_join(t1, self.fx.std_type, self.fx.std_type)
self.assert_join(self.fx.std_type, self.fx.std_type, self.fx.std_type)
def assert_simple_join(self, s: Type, t: Type, join: Type) -> None:
result = join_types(s, t)
actual = str(result)
expected = str(join)
assert_equal(actual, expected,
'join({}, {}) == {{}} ({{}} expected)'.format(s, t))
assert_true(is_subtype(s, result),
'{} not subtype of {}'.format(s, result))
assert_true(is_subtype(t, result),
'{} not subtype of {}'.format(t, result))
def test_simple_type_objects(self):
t1 = self.type_callable(self.fx.a, self.fx.a)
t2 = self.type_callable(self.fx.b, self.fx.b)
self.assert_join(t1, t1, t1)
assert_true(join_types(t1, t1).is_type_obj())
self.assert_join(t1, t2, self.fx.type_type)
self.assert_join(t1, self.fx.type_type, self.fx.type_type)
self.assert_join(self.fx.type_type, self.fx.type_type,
self.fx.type_type)
def assert_simple_join(self, s, t, join):
result = join_types(s, t)
actual = str(result)
expected = str(join)
assert_equal(actual, expected,
'join({}, {}) == {{}} ({{}} expected)'.format(s, t))
if not isinstance(s, ErrorType) and not isinstance(result, ErrorType):
assert_true(is_subtype(s, result),
'{} not subtype of {}'.format(s, result))
if not isinstance(t, ErrorType) and not isinstance(result, ErrorType):
assert_true(is_subtype(t, result),
'{} not subtype of {}'.format(t, result))
def assert_simple_join(self, s, t, join):
result = join_types(s, t)
actual = str(result)
expected = str(join)
assert_equal(actual, expected,
'join({}, {}) == {{}} ({{}} expected)'.format(s, t))
if not isinstance(s, ErrorType) and not isinstance(result, ErrorType):
assert_true(is_subtype(s, result),
'{} not subtype of {}'.format(s, result))
if not isinstance(t, ErrorType) and not isinstance(result, ErrorType):
assert_true(is_subtype(t, result),
'{} not subtype of {}'.format(t, result))
def test_simple_type_objects(self) -> None:
t1 = self.type_callable(self.fx.a, self.fx.a)
t2 = self.type_callable(self.fx.b, self.fx.b)
self.assert_join(t1, t1, t1)
j = join_types(t1, t1)
assert isinstance(j, CallableType)
assert_true(j.is_type_obj())
self.assert_join(t1, t2, self.fx.type_type)
self.assert_join(t1, self.fx.type_type, self.fx.type_type)
self.assert_join(self.fx.type_type, self.fx.type_type,
self.fx.type_type)
def test_simple_type_objects(self) -> None:
t1 = self.type_callable(self.fx.a, self.fx.a)
t2 = self.type_callable(self.fx.b, self.fx.b)
self.assert_join(t1, t1, t1)
j = join_types(t1, t1)
assert isinstance(j, CallableType)
assert_true(j.is_type_obj())
self.assert_join(t1, t2, self.fx.type_type)
self.assert_join(t1, self.fx.type_type, self.fx.type_type)
self.assert_join(self.fx.type_type, self.fx.type_type,
self.fx.type_type)
def visit_or_pattern(self, o: OrPattern) -> PatternType:
current_type = self.type_context[-1]
#
# Check all the subpatterns
#
pattern_types = []
for pattern in o.patterns:
pattern_type = self.accept(pattern, current_type)
pattern_types.append(pattern_type)
current_type = pattern_type.rest_type
#
# Collect the final type
#
types = []
for pattern_type in pattern_types:
if not is_uninhabited(pattern_type.type):
types.append(pattern_type.type)
#
# Check the capture types
#
capture_types: Dict[Var, List[Tuple[Expression,
Type]]] = defaultdict(list)
# Collect captures from the first subpattern
for expr, typ in pattern_types[0].captures.items():
node = get_var(expr)
capture_types[node].append((expr, typ))
# Check if other subpatterns capture the same names
for i, pattern_type in enumerate(pattern_types[1:]):
vars = {get_var(expr) for expr, _ in pattern_type.captures.items()}
if capture_types.keys() != vars:
self.msg.fail(message_registry.OR_PATTERN_ALTERNATIVE_NAMES,
o.patterns[i])
for expr, typ in pattern_type.captures.items():
node = get_var(expr)
capture_types[node].append((expr, typ))
captures: Dict[Expression, Type] = {}
for var, capture_list in capture_types.items():
typ = UninhabitedType()
for _, other in capture_list:
typ = join_types(typ, other)
captures[capture_list[0][0]] = typ
union_type = make_simplified_union(types)
return PatternType(union_type, current_type, captures)
def meet_similar_callables(t: CallableType, s: CallableType) -> CallableType:
from mypy.join import join_types
arg_types = [] # type: List[Type]
for i in range(len(t.arg_types)):
arg_types.append(join_types(t.arg_types[i], s.arg_types[i]))
# TODO in combine_similar_callables also applies here (names and kinds)
# The fallback type can be either 'function' or 'type'. The result should have 'function' as
# fallback only if both operands have it as 'function'.
if t.fallback.type.fullname() != 'builtins.function':
fallback = t.fallback
else:
fallback = s.fallback
return t.copy_modified(arg_types=arg_types,
ret_type=meet_types(t.ret_type, s.ret_type),
fallback=fallback,
name=None)
def meet_similar_callables(t: CallableType, s: CallableType) -> CallableType:
from mypy.join import join_types
arg_types = [] # type: List[Type]
for i in range(len(t.arg_types)):
arg_types.append(join_types(t.arg_types[i], s.arg_types[i]))
# TODO in combine_similar_callables also applies here (names and kinds)
# The fallback type can be either 'function' or 'type'. The result should have 'function' as
# fallback only if both operands have it as 'function'.
if t.fallback.type.fullname() != 'builtins.function':
fallback = t.fallback
else:
fallback = s.fallback
return t.copy_modified(arg_types=arg_types,
ret_type=meet_types(t.ret_type, s.ret_type),
fallback=fallback,
name=None)
def _analyze_iterable_item_type(self, expr: Expression) -> Type:
"""Return the item type given by 'expr' in an iterable context."""
# This logic is copied from mypy's TypeChecker.analyze_iterable_item_type.
iterable = get_proper_type(self.types[expr])
echk = self.graph[self.module_name].type_checker().expr_checker
iterator = echk.check_method_call_by_name('__iter__', iterable, [], [], expr)[0]
from mypy.join import join_types
if isinstance(iterable, TupleType):
joined = UninhabitedType() # type: Type
for item in iterable.items:
joined = join_types(joined, item)
return joined
else:
# Non-tuple iterable.
return echk.check_method_call_by_name('__next__', iterator, [], [], expr)[0]
def solve_constraints(vars: List[TypeVarId], constraints: List[Constraint],
strict: bool =True) -> List[Optional[Type]]:
"""Solve type constraints.
Return the best type(s) for type variables; each type can be None if the value of the variable
could not be solved.
If a variable has no constraints, if strict=True then arbitrarily
pick NoneTyp as the value of the type variable. If strict=False,
pick AnyType.
"""
# Collect a list of constraints for each type variable.
cmap = defaultdict(list) # type: Dict[TypeVarId, List[Constraint]]
for con in constraints:
cmap[con.type_var].append(con)
res = [] # type: List[Optional[Type]]
# Solve each type variable separately.
for tvar in vars:
bottom = None # type: Optional[Type]
top = None # type: Optional[Type]
candidate = None # type: Optional[Type]
# Process each constraint separately, and calculate the lower and upper
# bounds based on constraints. Note that we assume that the constraint
# targets do not have constraint references.
for c in cmap.get(tvar, []):
if c.op == SUPERTYPE_OF:
if bottom is None:
bottom = c.target
else:
bottom = join_types(bottom, c.target)
else:
if top is None:
top = c.target
else:
top = meet_types(top, c.target)
if isinstance(top, AnyType) or isinstance(bottom, AnyType):
source_any = top if isinstance(top, AnyType) else bottom
assert isinstance(source_any, AnyType)
res.append(AnyType(TypeOfAny.from_another_any, source_any=source_any))
continue
elif bottom is None:
if top:
candidate = top
else:
# No constraints for type variable -- 'UninhabitedType' is the most specific type.
if strict:
candidate = UninhabitedType()
candidate.ambiguous = True
else:
candidate = AnyType(TypeOfAny.special_form)
elif top is None:
candidate = bottom
elif is_subtype(bottom, top):
candidate = bottom
else:
candidate = None
res.append(candidate)
return res
def solve_constraints(vars: List[int], constraints: List[Constraint],
basic: BasicTypes) -> List[Type]:
"""Solve type constraints.
Return lower bound for each type variable or None if the variable could
not be solved.
"""
# Collect a list of constraints for each type variable.
cmap = Dict[int, List[Constraint]]()
for con in constraints:
a = cmap.get(con.type_var, [])
a.append(con)
cmap[con.type_var] = a
res = [] # type: List[Type]
# Solve each type variable separately.
for tvar in vars:
bottom = None # type: Type
top = None # type: Type
# Process each contraint separely, and calculate the lower and upper
# bounds based on constraints. Note that we assume that the contraint
# targets do not have contraint references.
for c in cmap.get(tvar, []):
if c.op == SUPERTYPE_OF:
if bottom is None:
bottom = c.target
else:
bottom = join_types(bottom, c.target, basic)
else:
if top is None:
top = c.target
else:
top = meet_types(top, c.target, basic)
if top is None:
if isinstance(bottom, Void):
top = Void()
else:
top = basic.object
if bottom is None:
if isinstance(top, Void):
bottom = Void()
else:
bottom = NoneTyp()
if isinstance(top, AnyType) or isinstance(bottom, AnyType):
top = AnyType()
bottom = AnyType()
# Pick the most specific type if it satisfies the constraints.
if (not top or not bottom or is_subtype(
bottom, top)) and (not isinstance(top, ErrorType)
and not isinstance(bottom, ErrorType)):
res.append(bottom)
else:
res.append(None)
return res
Type[] res = []
# Solve each type variable separately.
for tvar in vars:
Type bottom = None
Type top = None
# Process each contraint separely, and calculate the lower and upper
# bounds based on constraints. Note that we assume that the contraint
# targets do not have contraint references.
for c in cmap.get(tvar, []):
if c.op == SUPERTYPE_OF:
if bottom is None:
bottom = c.target
else:
bottom = join_types(bottom, c.target, basic)
else:
if top is None:
top = c.target
else:
top = meet_types(top, c.target, basic)
if top is None:
if isinstance(bottom, Void):
top = Void()
else:
top = basic.object
if bottom is None:
if isinstance(top, Void):
bottom = Void()
def visit_class_pattern(self, o: ClassPattern) -> PatternType:
current_type = get_proper_type(self.type_context[-1])
#
# Check class type
#
type_info = o.class_ref.node
assert type_info is not None
if isinstance(type_info, TypeAlias) and not type_info.no_args:
self.msg.fail(message_registry.CLASS_PATTERN_GENERIC_TYPE_ALIAS, o)
return self.early_non_match()
if isinstance(type_info, TypeInfo):
any_type = AnyType(TypeOfAny.implementation_artifact)
typ: Type = Instance(type_info,
[any_type] * len(type_info.defn.type_vars))
elif isinstance(type_info, TypeAlias):
typ = type_info.target
else:
if isinstance(type_info, Var):
name = str(type_info.type)
else:
name = type_info.name
self.msg.fail(
message_registry.CLASS_PATTERN_TYPE_REQUIRED.format(name),
o.class_ref)
return self.early_non_match()
new_type, rest_type = self.chk.conditional_types_with_intersection(
current_type, [get_type_range(typ)], o, default=current_type)
if is_uninhabited(new_type):
return self.early_non_match()
# TODO: Do I need this?
narrowed_type = narrow_declared_type(current_type, new_type)
#
# Convert positional to keyword patterns
#
keyword_pairs: List[Tuple[Optional[str], Pattern]] = []
match_arg_set: Set[str] = set()
captures: Dict[Expression, Type] = {}
if len(o.positionals) != 0:
if self.should_self_match(typ):
if len(o.positionals) > 1:
self.msg.fail(
message_registry.
CLASS_PATTERN_TOO_MANY_POSITIONAL_ARGS, o)
pattern_type = self.accept(o.positionals[0], narrowed_type)
if not is_uninhabited(pattern_type.type):
return PatternType(
pattern_type.type,
join_types(rest_type, pattern_type.rest_type),
pattern_type.captures)
captures = pattern_type.captures
else:
local_errors = self.msg.clean_copy()
match_args_type = analyze_member_access("__match_args__",
typ,
o,
False,
False,
False,
local_errors,
original_type=typ,
chk=self.chk)
if local_errors.is_errors():
self.msg.fail(
message_registry.MISSING_MATCH_ARGS.format(typ), o)
return self.early_non_match()
proper_match_args_type = get_proper_type(match_args_type)
if isinstance(proper_match_args_type, TupleType):
match_arg_names = get_match_arg_names(
proper_match_args_type)
if len(o.positionals) > len(match_arg_names):
self.msg.fail(
message_registry.
CLASS_PATTERN_TOO_MANY_POSITIONAL_ARGS, o)
return self.early_non_match()
else:
match_arg_names = [None] * len(o.positionals)
for arg_name, pos in zip(match_arg_names, o.positionals):
keyword_pairs.append((arg_name, pos))
if arg_name is not None:
match_arg_set.add(arg_name)
#
# Check for duplicate patterns
#
keyword_arg_set = set()
has_duplicates = False
for key, value in zip(o.keyword_keys, o.keyword_values):
keyword_pairs.append((key, value))
if key in match_arg_set:
self.msg.fail(
message_registry.CLASS_PATTERN_KEYWORD_MATCHES_POSITIONAL.
format(key), value)
has_duplicates = True
elif key in keyword_arg_set:
self.msg.fail(
message_registry.CLASS_PATTERN_DUPLICATE_KEYWORD_PATTERN.
format(key), value)
has_duplicates = True
keyword_arg_set.add(key)
if has_duplicates:
return self.early_non_match()
#
# Check keyword patterns
#
can_match = True
for keyword, pattern in keyword_pairs:
key_type: Optional[Type] = None
local_errors = self.msg.clean_copy()
if keyword is not None:
key_type = analyze_member_access(keyword,
narrowed_type,
pattern,
False,
False,
False,
local_errors,
original_type=new_type,
chk=self.chk)
else:
key_type = AnyType(TypeOfAny.from_error)
if local_errors.is_errors() or key_type is None:
key_type = AnyType(TypeOfAny.from_error)
self.msg.fail(
message_registry.CLASS_PATTERN_UNKNOWN_KEYWORD.format(
typ, keyword), value)
inner_type, inner_rest_type, inner_captures = self.accept(
pattern, key_type)
if is_uninhabited(inner_type):
can_match = False
else:
self.update_type_map(captures, inner_captures)
if not is_uninhabited(inner_rest_type):
rest_type = current_type
if not can_match:
new_type = UninhabitedType()
return PatternType(new_type, rest_type, captures)
def visit_sequence_pattern(self, o: SequencePattern) -> PatternType:
#
# check for existence of a starred pattern
#
current_type = get_proper_type(self.type_context[-1])
if not self.can_match_sequence(current_type):
return self.early_non_match()
star_positions = [
i for i, p in enumerate(o.patterns)
if isinstance(p, StarredPattern)
]
star_position: Optional[int] = None
if len(star_positions) == 1:
star_position = star_positions[0]
elif len(star_positions) >= 2:
assert False, "Parser should prevent multiple starred patterns"
required_patterns = len(o.patterns)
if star_position is not None:
required_patterns -= 1
#
# get inner types of original type
#
if isinstance(current_type, TupleType):
inner_types = current_type.items
size_diff = len(inner_types) - required_patterns
if size_diff < 0:
return self.early_non_match()
elif size_diff > 0 and star_position is None:
return self.early_non_match()
else:
inner_type = self.get_sequence_type(current_type)
if inner_type is None:
inner_type = self.chk.named_type("builtins.object")
inner_types = [inner_type] * len(o.patterns)
#
# match inner patterns
#
contracted_new_inner_types: List[Type] = []
contracted_rest_inner_types: List[Type] = []
captures: Dict[Expression, Type] = {}
contracted_inner_types = self.contract_starred_pattern_types(
inner_types, star_position, required_patterns)
can_match = True
for p, t in zip(o.patterns, contracted_inner_types):
pattern_type = self.accept(p, t)
typ, rest, type_map = pattern_type
if is_uninhabited(typ):
can_match = False
else:
contracted_new_inner_types.append(typ)
contracted_rest_inner_types.append(rest)
self.update_type_map(captures, type_map)
new_inner_types = self.expand_starred_pattern_types(
contracted_new_inner_types, star_position, len(inner_types))
#
# Calculate new type
#
new_type: Type
rest_type: Type = current_type
if not can_match:
new_type = UninhabitedType()
elif isinstance(current_type, TupleType):
narrowed_inner_types = []
inner_rest_types = []
for inner_type, new_inner_type in zip(inner_types,
new_inner_types):
narrowed_inner_type, inner_rest_type = \
self.chk.conditional_types_with_intersection(
new_inner_type,
[get_type_range(inner_type)],
o,
default=new_inner_type
)
narrowed_inner_types.append(narrowed_inner_type)
inner_rest_types.append(inner_rest_type)
if all(not is_uninhabited(typ) for typ in narrowed_inner_types):
new_type = TupleType(narrowed_inner_types,
current_type.partial_fallback)
else:
new_type = UninhabitedType()
if all(is_uninhabited(typ) for typ in inner_rest_types):
# All subpatterns always match, so we can apply negative narrowing
new_type, rest_type = self.chk.conditional_types_with_intersection(
current_type, [get_type_range(new_type)],
o,
default=current_type)
else:
new_inner_type = UninhabitedType()
for typ in new_inner_types:
new_inner_type = join_types(new_inner_type, typ)
new_type = self.construct_sequence_child(current_type,
new_inner_type)
if not is_subtype(new_type, current_type):
new_type = current_type
return PatternType(new_type, rest_type, captures)