def duplicate_name(self, node: NameExpr) -> NameExpr:
# This method is used when the transform result must be a NameExpr.
# visit_name_expr() is used when there is no such restriction.
new = NameExpr(node.name)
new.info = node.info
self.copy_ref(new, node)
return new
def name_expr(self, name):
nexpr = NameExpr(name)
nexpr.kind = nodes.LDEF
node = self.names[name]
nexpr.node = node
self.type_map[nexpr] = node.type
return nexpr
def convert_arg(index: int, arg: ast27.expr) -> Var:
if isinstance(arg, ast27.Name):
v = arg.id
elif isinstance(arg, ast27.Tuple):
v = '__tuple_arg_{}'.format(index + 1)
rvalue = NameExpr(v)
rvalue.set_line(line)
assignment = AssignmentStmt([self.visit(arg)], rvalue)
assignment.set_line(line)
decompose_stmts.append(assignment)
else:
raise RuntimeError("'{}' is not a valid argument.".format(ast27.dump(arg)))
return Var(v)
def _attribute_from_attrib_maker(ctx: 'mypy.plugin.ClassDefContext',
auto_attribs: bool,
lhs: NameExpr,
rvalue: CallExpr,
stmt: AssignmentStmt) -> Optional[Attribute]:
"""Return an Attribute from the assignment or None if you can't make one."""
if auto_attribs and not stmt.new_syntax:
# auto_attribs requires an annotation on *every* attr.ib.
assert lhs.node is not None
ctx.api.msg.need_annotation_for_var(lhs.node, stmt)
return None
if len(stmt.lvalues) > 1:
ctx.api.fail("Too many names for one attribute", stmt)
return None
# This is the type that belongs in the __init__ method for this attrib.
init_type = stmt.type
# Read all the arguments from the call.
init = _get_bool_argument(ctx, rvalue, 'init', True)
# TODO: Check for attr.NOTHING
attr_has_default = bool(_get_argument(rvalue, 'default'))
# If the type isn't set through annotation but is passed through `type=` use that.
type_arg = _get_argument(rvalue, 'type')
if type_arg and not init_type:
try:
un_type = expr_to_unanalyzed_type(type_arg)
except TypeTranslationError:
ctx.api.fail('Invalid argument to type', type_arg)
else:
init_type = ctx.api.anal_type(un_type)
if init_type and isinstance(lhs.node, Var) and not lhs.node.type:
# If there is no annotation, add one.
lhs.node.type = init_type
lhs.is_inferred_def = False
# Note: convert is deprecated but works the same as converter.
converter = _get_argument(rvalue, 'converter')
convert = _get_argument(rvalue, 'convert')
if convert and converter:
ctx.api.fail("Can't pass both `convert` and `converter`.", rvalue)
elif convert:
ctx.api.fail("convert is deprecated, use converter", rvalue)
converter = convert
converter_name = _get_converter_name(ctx, converter)
return Attribute(lhs.name, ctx.cls.info, attr_has_default, init, converter_name, stmt)
def add_method(
ctx: ClassDefContext,
name: str,
args: List[Argument],
return_type: Type,
self_type: Optional[Type] = None,
tvar_def: Optional[TypeVarDef] = None,
is_classmethod: bool = False,
is_new: bool = False,
# is_staticmethod: bool = False,
) -> None:
"""
Adds a new method to a class.
This can be dropped if/when https://github.com/python/mypy/issues/7301 is merged
"""
info = ctx.cls.info
# First remove any previously generated methods with the same name
# to avoid clashes and problems in the semantic analyzer.
if name in info.names:
sym = info.names[name]
if sym.plugin_generated and isinstance(sym.node, FuncDef):
ctx.cls.defs.body.remove(sym.node)
self_type = self_type or fill_typevars(info)
if is_classmethod or is_new:
first = [Argument(Var('_cls'), TypeType.make_normalized(self_type), None, ARG_POS)]
# elif is_staticmethod:
# first = []
else:
self_type = self_type or fill_typevars(info)
first = [Argument(Var('self'), self_type, None, ARG_POS)]
args = first + args
arg_types, arg_names, arg_kinds = [], [], []
for arg in args:
assert arg.type_annotation, 'All arguments must be fully typed.'
arg_types.append(arg.type_annotation)
arg_names.append(get_name(arg.variable))
arg_kinds.append(arg.kind)
function_type = ctx.api.named_type('__builtins__.function')
signature = CallableType(arg_types, arg_kinds, arg_names, return_type, function_type)
if tvar_def:
signature.variables = [tvar_def]
func = FuncDef(name, args, Block([PassStmt()]))
func.info = info
func.type = set_callable_name(signature, func)
func.is_class = is_classmethod
# func.is_static = is_staticmethod
func._fullname = get_fullname(info) + '.' + name
func.line = info.line
# NOTE: we would like the plugin generated node to dominate, but we still
# need to keep any existing definitions so they get semantically analyzed.
if name in info.names:
# Get a nice unique name instead.
r_name = get_unique_redefinition_name(name, info.names)
info.names[r_name] = info.names[name]
if is_classmethod: # or is_staticmethod:
func.is_decorated = True
v = Var(name, func.type)
v.info = info
v._fullname = func._fullname
# if is_classmethod:
v.is_classmethod = True
dec = Decorator(func, [NameExpr('classmethod')], v)
# else:
# v.is_staticmethod = True
# dec = Decorator(func, [NameExpr('staticmethod')], v)
dec.line = info.line
sym = SymbolTableNode(MDEF, dec)
else:
sym = SymbolTableNode(MDEF, func)
sym.plugin_generated = True
info.names[name] = sym
info.defn.defs.body.append(func)
def visit_Name(self, n: Name) -> NameExpr:
e = NameExpr(n.id)
return self.set_line(e, n)
def visit_Name(self, n: ast3.Name) -> NameExpr:
return NameExpr(n.id)
def parse_key_typeddict_fields(attrs_expr: DictExpr) -> Tuple[List[str], List[Type], Set[str]]:
fields = []
types = []
required_fields = set()
for field_name_expr, field_type_expr in attrs_expr.items:
if isinstance(field_name_expr, StrExpr):
fields.append(field_name_expr.value)
required_fields.add(field_name_expr.value)
elif isinstance(field_name_expr, CallExpr):
fields.append(field_name_expr.args[0].value)
required_expr = field_name_expr.args[1] if len(field_name_expr.args) == 2 else NameExpr('builtins.True')
if required_expr.fullname == 'builtins.True':
required_fields.add(field_name_expr.args[0].value)
else:
raise UnsupportedKeyTypeError(str(type(field_name_expr)))
types.append(expr_to_unanalyzed_type(field_type_expr))
return fields, types, required_fields
fdef.type = wrapper_sig
return fdef
Instance self_type(self):
return self_type(self.tf.type_context())
Scope make_scope(self):
return Scope(self.tf.type_map)
class Scope:
"""Maintain a temporary local scope during transformation."""
void __init__(self, dict<Node, Type> type_map):
self.names = <str, Var> {}
self.type_map = type_map
Var add(self, str name, Type type):
v = Var(name)
v.type = type
self.names[name] = v
return v
NameExpr name_expr(self, str name):
nexpr = NameExpr(name)
nexpr.kind = nodes.LDEF
node = self.names[name]
nexpr.node = node
self.type_map[nexpr] = node.type
return nexpr
def visit_Name(self, n):
return NameExpr(n.id)
def visit_NameConstant(self, n):
return NameExpr(str(n.value))
def visit_Name(self, n: ast35.Name) -> Node:
return NameExpr(n.id)
def test_multiple_groups_coalescing(self) -> None:
x0 = NameExpr('x0')
x1 = NameExpr('x1')
x2 = NameExpr('x2')
x3 = NameExpr('x3')
x4 = NameExpr('x4')
nothing_combined = [('==', [0, 1, 2]), ('<', [2, 3]), ('==', [3, 4,
5])]
everything_combined = [('==', [0, 1, 2, 3, 4, 5]), ('<', [2, 3])]
# Note: We do 'x4 == x0' at the very end!
two_groups = [
('==', x0, x1),
('==', x1, x2),
('<', x2, x3),
('==', x3, x4),
('==', x4, x0),
]
self.assertEqual(
group_comparison_operands(
two_groups,
self.literal_keymap({
0: x0,
1: x1,
2: x2,
3: x3,
4: x4,
5: x0
}),
{'=='},
), everything_combined,
"All vars are assignable, everything is combined")
self.assertEqual(
group_comparison_operands(
two_groups,
self.literal_keymap({
1: x1,
2: x2,
3: x3,
4: x4
}),
{'=='},
), nothing_combined, "x0 is unassignable, so no combining")
self.assertEqual(
group_comparison_operands(
two_groups,
self.literal_keymap({
0: x0,
1: x1,
3: x3,
5: x0
}),
{'=='},
), everything_combined,
"Some vars are unassignable but x0 is, so we combine")
self.assertEqual(
group_comparison_operands(
two_groups,
self.literal_keymap({
0: x0,
5: x0
}),
{'=='},
), everything_combined,
"All vars are unassignable but x0 is, so we combine")
def _attribute_from_attrib_maker(ctx: 'mypy.plugin.ClassDefContext',
auto_attribs: bool,
kw_only: bool,
lhs: NameExpr,
rvalue: CallExpr,
stmt: AssignmentStmt) -> Optional[Attribute]:
"""Return an Attribute from the assignment or None if you can't make one."""
if auto_attribs and not stmt.new_syntax:
# auto_attribs requires an annotation on *every* attr.ib.
assert lhs.node is not None
ctx.api.msg.need_annotation_for_var(lhs.node, stmt)
return None
if len(stmt.lvalues) > 1:
ctx.api.fail("Too many names for one attribute", stmt)
return None
# This is the type that belongs in the __init__ method for this attrib.
init_type = stmt.type
# Read all the arguments from the call.
init = _get_bool_argument(ctx, rvalue, 'init', True)
# Note: If the class decorator says kw_only=True the attribute is ignored.
# See https://github.com/python-attrs/attrs/issues/481 for explanation.
kw_only |= _get_bool_argument(ctx, rvalue, 'kw_only', False)
if kw_only and ctx.api.options.python_version[0] < 3:
ctx.api.fail(KW_ONLY_PYTHON_2_UNSUPPORTED, stmt)
return None
# TODO: Check for attr.NOTHING
attr_has_default = bool(_get_argument(rvalue, 'default'))
attr_has_factory = bool(_get_argument(rvalue, 'factory'))
if attr_has_default and attr_has_factory:
ctx.api.fail("Can't pass both `default` and `factory`.", rvalue)
elif attr_has_factory:
attr_has_default = True
# If the type isn't set through annotation but is passed through `type=` use that.
type_arg = _get_argument(rvalue, 'type')
if type_arg and not init_type:
try:
un_type = expr_to_unanalyzed_type(type_arg)
except TypeTranslationError:
ctx.api.fail('Invalid argument to type', type_arg)
else:
init_type = ctx.api.anal_type(un_type)
if init_type and isinstance(lhs.node, Var) and not lhs.node.type:
# If there is no annotation, add one.
lhs.node.type = init_type
lhs.is_inferred_def = False
# Note: convert is deprecated but works the same as converter.
converter = _get_argument(rvalue, 'converter')
convert = _get_argument(rvalue, 'convert')
if convert and converter:
ctx.api.fail("Can't pass both `convert` and `converter`.", rvalue)
elif convert:
ctx.api.fail("convert is deprecated, use converter", rvalue)
converter = convert
converter_info = _parse_converter(ctx, converter)
name = unmangle(lhs.name)
return Attribute(name, ctx.cls.info, attr_has_default, init, kw_only, converter_info, stmt)
def add_method_to_class(
api: SemanticAnalyzerPluginInterface,
cls: ClassDef,
name: str,
args: List[Argument],
return_type: Type,
self_type: Optional[Type] = None,
tvar_def: Optional[TypeVarDef] = None,
is_classmethod: bool = False,
) -> None:
"""
Adds a new method to a class definition.
NOTE:
Copied from mypy/plugins/common.py and extended with support for adding
classmethods based on https://github.com/python/mypy/pull/7796
"""
info = cls.info
# First remove any previously generated methods with the same name
# to avoid clashes and problems in the semantic analyzer.
if name in info.names:
sym = info.names[name]
if sym.plugin_generated and isinstance(sym.node, FuncDef):
cls.defs.body.remove(sym.node)
self_type = self_type or fill_typevars(info)
# Add either self or cls as the first argument
if is_classmethod:
first = Argument(Var("cls"), TypeType.make_normalized(self_type), None,
ARG_POS)
else:
first = Argument(Var("self"), self_type, None, ARG_POS)
args = [first] + args
arg_types, arg_names, arg_kinds = [], [], []
for arg in args:
assert arg.type_annotation, "All arguments must be fully typed."
arg_types.append(arg.type_annotation)
arg_names.append(arg.variable.name)
arg_kinds.append(arg.kind)
function_type = api.named_type("__builtins__.function")
signature = CallableType(arg_types, arg_kinds, arg_names, return_type,
function_type)
if tvar_def:
signature.variables = [tvar_def]
func = FuncDef(name, args, Block([PassStmt()]))
func.info = info
func.type = set_callable_name(signature, func)
func._fullname = info.fullname + "." + name # pylint: disable=protected-access
func.line = info.line
func.is_class = is_classmethod
# NOTE: we would like the plugin generated node to dominate, but we still
# need to keep any existing definitions so they get semantically analyzed.
if name in info.names:
# Get a nice unique name instead.
r_name = get_unique_redefinition_name(name, info.names)
info.names[r_name] = info.names[name]
if is_classmethod:
func.is_decorated = True
v = Var(name, func.type)
v.info = info
v._fullname = func._fullname # pylint: disable=protected-access
v.is_classmethod = True
dec = Decorator(func, [NameExpr("classmethod")], v)
dec.line = info.line
sym = SymbolTableNode(MDEF, dec)
else:
sym = SymbolTableNode(MDEF, func)
sym.plugin_generated = True
info.names[name] = sym
info.defn.defs.body.append(func)
def visit_type_var(self, t: TypeVar) -> Type:
# FIX function type variables
return RuntimeTypeVar(NameExpr(tvar_arg_name(t.id)))
def duplicate_name(self, node: NameExpr) -> NameExpr:
# This method is used when the transform result must be a NameExpr.
# visit_name_expr() is used when there is no such restriction.
new = NameExpr(node.name)
self.copy_ref(new, node)
return new
def _scan_declarative_decorator_stmt(
cls: ClassDef,
api: SemanticAnalyzerPluginInterface,
stmt: Decorator,
cls_metadata: util.DeclClassApplied,
) -> None:
"""Extract mapping information from a @declared_attr in a declarative
class.
E.g.::
@reg.mapped
class MyClass:
# ...
@declared_attr
def updated_at(cls) -> Column[DateTime]:
return Column(DateTime)
Will resolve in mypy as::
@reg.mapped
class MyClass:
# ...
updated_at: Mapped[Optional[datetime.datetime]]
"""
for dec in stmt.decorators:
if (isinstance(dec, (NameExpr, MemberExpr, SymbolNode))
and names._type_id_for_named_node(dec) is names.DECLARED_ATTR):
break
else:
return
dec_index = cls.defs.body.index(stmt)
left_hand_explicit_type: Optional[ProperType] = None
if isinstance(stmt.func.type, CallableType):
func_type = stmt.func.type.ret_type
if isinstance(func_type, UnboundType):
type_id = names._type_id_for_unbound_type(func_type, cls, api)
else:
# this does not seem to occur unless the type argument is
# incorrect
return
if (type_id in {
names.MAPPED,
names.RELATIONSHIP,
names.COMPOSITE_PROPERTY,
names.MAPPER_PROPERTY,
names.SYNONYM_PROPERTY,
names.COLUMN_PROPERTY,
} and func_type.args):
left_hand_explicit_type = get_proper_type(func_type.args[0])
elif type_id is names.COLUMN and func_type.args:
typeengine_arg = func_type.args[0]
if isinstance(typeengine_arg, UnboundType):
sym = api.lookup_qualified(typeengine_arg.name, typeengine_arg)
if sym is not None and isinstance(sym.node, TypeInfo):
if names._has_base_type_id(sym.node, names.TYPEENGINE):
left_hand_explicit_type = UnionType([
infer._extract_python_type_from_typeengine(
api, sym.node, []),
NoneType(),
])
else:
util.fail(
api,
"Column type should be a TypeEngine "
"subclass not '{}'".format(sym.node.fullname),
func_type,
)
if left_hand_explicit_type is None:
# no type on the decorated function. our option here is to
# dig into the function body and get the return type, but they
# should just have an annotation.
msg = ("Can't infer type from @declared_attr on function '{}'; "
"please specify a return type from this function that is "
"one of: Mapped[<python type>], relationship[<target class>], "
"Column[<TypeEngine>], MapperProperty[<python type>]")
util.fail(api, msg.format(stmt.var.name), stmt)
left_hand_explicit_type = AnyType(TypeOfAny.special_form)
left_node = NameExpr(stmt.var.name)
left_node.node = stmt.var
# totally feeling around in the dark here as I don't totally understand
# the significance of UnboundType. It seems to be something that is
# not going to do what's expected when it is applied as the type of
# an AssignmentStatement. So do a feeling-around-in-the-dark version
# of converting it to the regular Instance/TypeInfo/UnionType structures
# we see everywhere else.
if isinstance(left_hand_explicit_type, UnboundType):
left_hand_explicit_type = get_proper_type(
util._unbound_to_instance(api, left_hand_explicit_type))
left_node.node.type = api.named_type("__sa_Mapped",
[left_hand_explicit_type])
# this will ignore the rvalue entirely
# rvalue = TempNode(AnyType(TypeOfAny.special_form))
# rewrite the node as:
# <attr> : Mapped[<typ>] =
# _sa_Mapped._empty_constructor(lambda: <function body>)
# the function body is maintained so it gets type checked internally
column_descriptor = nodes.NameExpr("__sa_Mapped")
column_descriptor.fullname = "sqlalchemy.orm.attributes.Mapped"
mm = nodes.MemberExpr(column_descriptor, "_empty_constructor")
arg = nodes.LambdaExpr(stmt.func.arguments, stmt.func.body)
rvalue = CallExpr(
mm,
[arg],
[nodes.ARG_POS],
["arg1"],
)
new_stmt = AssignmentStmt([left_node], rvalue)
new_stmt.type = left_node.node.type
cls_metadata.mapped_attr_names.append(
(left_node.name, left_hand_explicit_type))
cls.defs.body[dec_index] = new_stmt
def _attribute_from_attrib_maker(ctx: 'mypy.plugin.ClassDefContext',
auto_attribs: bool, kw_only: bool,
lhs: NameExpr, rvalue: CallExpr,
stmt: AssignmentStmt) -> Optional[Attribute]:
"""Return an Attribute from the assignment or None if you can't make one."""
if auto_attribs and not stmt.new_syntax:
# auto_attribs requires an annotation on *every* attr.ib.
assert lhs.node is not None
ctx.api.msg.need_annotation_for_var(lhs.node, stmt)
return None
if len(stmt.lvalues) > 1:
ctx.api.fail("Too many names for one attribute", stmt)
return None
# This is the type that belongs in the __init__ method for this attrib.
init_type = stmt.type
# Read all the arguments from the call.
init = _get_bool_argument(ctx, rvalue, 'init', True)
# Note: If the class decorator says kw_only=True the attribute is ignored.
# See https://github.com/python-attrs/attrs/issues/481 for explanation.
kw_only |= _get_bool_argument(ctx, rvalue, 'kw_only', False)
if kw_only and ctx.api.options.python_version[0] < 3:
ctx.api.fail(KW_ONLY_PYTHON_2_UNSUPPORTED, stmt)
return None
# TODO: Check for attr.NOTHING
attr_has_default = bool(_get_argument(rvalue, 'default'))
attr_has_factory = bool(_get_argument(rvalue, 'factory'))
if attr_has_default and attr_has_factory:
ctx.api.fail("Can't pass both `default` and `factory`.", rvalue)
elif attr_has_factory:
attr_has_default = True
# If the type isn't set through annotation but is passed through `type=` use that.
type_arg = _get_argument(rvalue, 'type')
if type_arg and not init_type:
try:
un_type = expr_to_unanalyzed_type(type_arg)
except TypeTranslationError:
ctx.api.fail('Invalid argument to type', type_arg)
else:
init_type = ctx.api.anal_type(un_type)
if init_type and isinstance(lhs.node, Var) and not lhs.node.type:
# If there is no annotation, add one.
lhs.node.type = init_type
lhs.is_inferred_def = False
# Note: convert is deprecated but works the same as converter.
converter = _get_argument(rvalue, 'converter')
convert = _get_argument(rvalue, 'convert')
if convert and converter:
ctx.api.fail("Can't pass both `convert` and `converter`.", rvalue)
elif convert:
ctx.api.fail("convert is deprecated, use converter", rvalue)
converter = convert
converter_info = _parse_converter(ctx, converter)
name = unmangle(lhs.name)
return Attribute(name, ctx.cls.info, attr_has_default, init, kw_only,
converter_info, stmt)
def self_expr() -> NameExpr:
n = NameExpr('self')
n.kind = LDEF
return n
def self_expr():
n = NameExpr('self')
n.kind = LDEF
return n
def visit_NameConstant(self, n: ast3.NameConstant) -> NameExpr:
return NameExpr(str(n.value))
if is_alt != BOUND_VAR:
if n > 0:
# Equivalent to slot name.
return tvar_slot_name(n - 1)
elif n == -1:
return '__ftv'
else:
return '__ftv{}'.format(-n)
else:
if n > 0:
# Equivalent to slot name.
return tvar_slot_name(n - 1, BOUND_VAR)
elif n == -1:
return '__bftv' # FIX do we need this?
else:
return '__bftv{}'.format(-n) # FIX do we need this?
str dynamic_suffix(bool is_pretty):
"""Return the suffix of the dynamic wrapper of a method or class."""
if is_pretty:
return '*'
else:
return '___dyn'
NameExpr self_expr():
n = NameExpr('self')
n.kind = LDEF
return n
def self_expr() -> NameExpr:
n = NameExpr("self")
n.kind = LDEF
return n
