def _update_generic_parameters_signature(generic_dict: Dict, method: Callable):
"""
Args:
generic_dict:
method:
Returns:
"""
sig = inspect.signature(method)
params = sig.parameters
new_params = []
for k, v in params.items():
annotation = v.annotation
if typing_inspect.is_typevar(annotation):
new_params.append(
inspect.Parameter(name=k,
kind=v.kind,
annotation=generic_dict[annotation],
default=v.default))
else:
new_params.append(v)
return_val = generic_dict[
sig.return_annotation] if typing_inspect.is_typevar(
sig.return_annotation) else sig.return_annotation
setattr(method, "__signature__",
sig.replace(parameters=new_params, return_annotation=return_val))
def _generate_field_schema(field: Field, context: str,
schemas: Dict[str, Schema]) -> Tuple[bool, Schema]:
is_optional, annotation = extract_optional_annotation(field.annotation)
if is_schema(annotation):
field_schema_name = _generate_schema(context, annotation, schemas)
field_schema = Schema(all_of=[_make_schema_ref(field_schema_name)])
elif is_generic_type(annotation):
origin = get_origin(annotation)
if origin in (list, List):
arguments = get_args(annotation)
if not arguments or arguments == [Any] or is_typevar(arguments[0]):
field_schema = _generate_primitive_schema(list)
else:
item_schema_name = _generate_schema(context, arguments[0],
schemas)
field_schema = Schema("array",
items=_make_schema_ref(item_schema_name))
elif origin in (dict, Dict):
# TODO: Improve support for dicts.
field_schema = _generate_primitive_schema(dict)
else:
field_schema = _generate_primitive_schema(annotation)
if field_schema is not None:
field_schema.description = field.description
for option, value in field.validator_options.items():
if option in Schema._FIELDS:
setattr(field_schema, option, value)
return is_optional, field_schema
def robust_isinstance(inst, typ) -> bool:
"""
Similar to isinstance, but if 'typ' is a parametrized generic Type, it is first transformed into its base generic
class so that the instance check works. It is also robust to Union and Any.
:param inst:
:param typ:
:return:
"""
if typ is Any:
return True
if is_typevar(typ):
if hasattr(typ, '__constraints__') and typ.__constraints__ is not None:
typs = get_args(typ, evaluate=True)
return any(robust_isinstance(inst, t) for t in typs)
elif hasattr(typ, '__bound__') and typ.__bound__ is not None:
return robust_isinstance(inst, typ.__bound__)
else:
# a raw TypeVar means 'anything'
return True
else:
if is_union_type(typ):
typs = get_args(typ, evaluate=True)
return any(robust_isinstance(inst, t) for t in typs)
else:
return isinstance(inst, get_base_generic_type(typ))
def is_valid_pep484_type_hint(typ_hint, allow_forward_refs: bool = False):
"""
Returns True if the provided type is a valid PEP484 type hint, False otherwise.
Note: string type hints (forward references) are not supported by default, since callers of this function in
parsyfiles lib actually require them to be resolved already.
:param typ_hint:
:param allow_forward_refs:
:return:
"""
# most common case first, to be faster
try:
if isinstance(typ_hint, type):
return True
except:
pass
# optionally, check forward reference
try:
if allow_forward_refs and is_forward_ref(typ_hint):
return True
except:
pass
# finally check unions and typevars
try:
return is_union_type(typ_hint) or is_typevar(typ_hint)
except:
return False
def is_collection(object_type, strict: bool = False) -> bool:
"""
Utility method to check if a type is a subclass of typing.{List,Dict,Set,Tuple}
or of list, dict, set, tuple.
If strict is set to True, the method will return True only if the class IS directly one of the base collection
classes
:param object_type:
:param strict: if set to True, this method will look for a strict match.
:return:
"""
if object_type is None or object_type is Any or is_union_type(
object_type) or is_typevar(object_type):
return False
elif strict:
return object_type == dict \
or object_type == list \
or object_type == tuple \
or object_type == set \
or get_base_generic_type(object_type) == Dict \
or get_base_generic_type(object_type) == List \
or get_base_generic_type(object_type) == Set \
or get_base_generic_type(object_type) == Tuple
else:
return issubclass(object_type, Dict) \
or issubclass(object_type, List) \
or issubclass(object_type, Set) \
or issubclass(object_type, Tuple) \
or issubclass(object_type, dict) \
or issubclass(object_type, list) \
or issubclass(object_type, tuple) \
or issubclass(object_type, set)
def get_argument_to_typevar(cls: Type, generic_base_class: Type,
typevar: TypeVar):
"""
Gets the argument given to a type variable parameterising
a generic base class in a particular sub-class of that base.
:param cls: The sub-class specifying the argument.
:param generic_base_class: The generic base-class specifying the type variable.
:param typevar: The type variable to get the argument for.
:return: The argument to the type variable.
"""
# Check the arguments
typevar_index: int = check_args(cls, generic_base_class, typevar)
# Get the decendency path from derived to base class
bases = [cls]
while bases[-1] is not generic_base_class:
# Keep track of if we found a base
base_found = False
# Try and find a generic base
for base in typing_inspect.get_generic_bases(bases[-1]):
if issubclass(base, generic_base_class):
bases.append(base)
base_found = True
break
# If we didn't find a generic base, find a non-generic base
if not base_found:
for base in bases[-1].__bases__:
if issubclass(base, generic_base_class):
bases.append(base)
break
# Search the dependency path for the type variable's final argument
arg = None
while len(bases) > 1:
# Get the arguments to the generic base class
args = typing_inspect.get_args(bases[-2])
# If no arguments are given, the signature stays the same
if len(args) == 0:
bases = bases[:-2] + bases[-1:]
continue
# Get the argument to this typevar
arg = args[typevar_index]
# If it's another type variable, keep looking for the argument to this
# type variable
if typing_inspect.is_typevar(arg):
typevar_index = typing_inspect.get_parameters(bases[-2]).index(arg)
bases = bases[:-1]
continue
# Otherwise return the argument to the type variable
return arg
return arg
def match_types(hint: typing.Type, t: typing.Type) -> TypeVarMapping:
"""
Matches a type hint with a type, return a mapping of any type vars to their values.
"""
if hint == t:
return {}
# If it is an instance of OfType[Type[T]], then we should consider it as T
if isinstance(t, OfType):
of_type, = typing_inspect.get_args(get_type(t))
assert issubclass(of_type, typing.Type)
t, = typing_inspect.get_args(of_type)
return match_types(hint, t)
# If the type is an OfType[T] then we should really just consider it as T
if issubclass(t, OfType) and not issubclass(hint, OfType):
t, = typing_inspect.get_args(t)
return match_types(hint, t)
if issubclass(hint, OfType) and not issubclass(t, OfType):
hint, = typing_inspect.get_args(hint)
return match_types(hint, t)
# Matching an expanded type is like matching just whatever it represents
if issubclass(t, ExpandedType):
t, = typing_inspect.get_args(t)
if typing_inspect.is_typevar(hint):
return {hint: t}
if typing_inspect.is_typevar(t):
return {}
if typing_inspect.is_union_type(hint):
# If this is a union, iterate through and use the first that is a subclass
for inner_type in typing_inspect.get_args(hint):
if issubclass(t, inner_type):
hint = inner_type
break
else:
raise TypeError(f"Cannot match concrete type {t} with hint {hint}")
if not issubclass(t, hint):
raise TypeError(f"Cannot match concrete type {t} with hint {hint}")
return merge_typevars(*(match_types(inner_hint, inner_t)
for inner_hint, inner_t in zip(
get_inner_types(hint), get_inner_types(t))))
def is_dataclass_type(t: Type) -> bool:
"""Returns wether t is a dataclass type or a TypeVar of a dataclass type.
Args:
t (Type): Some type.
Returns:
bool: Wether its a dataclass type.
"""
return dataclasses.is_dataclass(t) or (
tpi.is_typevar(t) and dataclasses.is_dataclass(tpi.get_bound(t)))
def is_type(type_):
return (
isinstance(type_, type) or
type_ is Unknown or
type_ is Any or
is_parameterized(type_) or
is_parametrical(type_) or
is_typevar(type_) or
is_union_type(type_)
)
def merge_typevars(*typevars: TypeVarMapping) -> TypeVarMapping:
"""
Merges typevar mappings. If there is a duplicate key, either the values should be the
same or one should have `typing.Any` type, or one should be a typevar itself. If it is a typevar,
that typevar is also set to the other's value
"""
merged: TypeVarMapping = {}
typevars_: typing.List[TypeVarMapping] = list(typevars)
while typevars_:
tvs: TypeVarMapping = typevars_.pop()
for tv, tp in tvs.items(): # type: ignore
if tv not in merged:
merged[tv] = tp # type: ignore
continue
prev_tp = merged[tv]
if prev_tp == typing.Any:
merged[tv] = tp # type: ignore
elif prev_tp == tp or tp == typing.Any:
pass
elif typing_inspect.is_typevar(prev_tp):
merged[prev_tp] = merged[tv] = tp # type: ignore
elif typing_inspect.is_typevar(tp):
merged[tp] = prev_tp # type: ignore
else:
# Try merging them and choosing replacing the hint with the
# merged values
try:
merged[tv] = replace_typevars( # type: ignore
match_types(prev_tp, tp), prev_tp)
continue
except TypeError:
pass
try:
merged[tv] = replace_typevars( # type: ignore
match_types(tp, prev_tp), tp)
continue
except TypeError:
pass
raise TypeError(
f"Cannot merge {prev_tp} and {tp} for type var {tv}")
return merged
def wrapper(*a: object, **kw: Dict[str, object]) -> object:
#debug('short circuit wrapper ', original)
space = optional_context_statespace()
if (not self.engaged) or (not space) or space.running_framework_code:
return original(*a, **kw)
# We *heavily* bias towards concrete execution, because it's often the case
# that a single short-circuit will render the path useless. TODO: consider
# decaying short-crcuit probability over time.
use_short_circuit = space.fork_with_confirm_or_else(0.95)
if not use_short_circuit:
#debug('short circuit: Choosing not to intercept', original)
return original(*a, **kw)
try:
self.engaged = False
debug('short circuit: Short circuiting over a call to ', original)
self.intercepted = True
return_type = sig.return_annotation
# Deduce type vars if necessary
if len(typing_inspect.get_parameters(sig.return_annotation)) > 0 or typing_inspect.is_typevar(sig.return_annotation):
typevar_bindings: typing.ChainMap[object, type] = collections.ChainMap(
)
bound = sig.bind(*a, **kw)
bound.apply_defaults()
for param in sig.parameters.values():
argval = bound.arguments[param.name]
value_type = python_type(argval)
#debug('unify', value_type, param.annotation)
if not dynamic_typing.unify(value_type, param.annotation, typevar_bindings):
debug(
'aborting intercept due to signature unification failure')
return original(*a, **kw)
#debug('unify bindings', typevar_bindings)
return_type = dynamic_typing.realize(
sig.return_annotation, typevar_bindings)
debug('short circuit: Deduced return type was ', return_type)
# adjust arguments that may have been mutated
assert subconditions is not None
bound = sig.bind(*a, **kw)
mutable_args = subconditions.mutable_args
for argname, arg in bound.arguments.items():
if mutable_args is None or argname in mutable_args:
forget_contents(arg)
if return_type is type(None):
return None
# note that the enforcement wrapper ensures postconditions for us, so we
# can just return a free variable here.
return proxy_for_type(return_type, 'proxyreturn' + space.uniq())
finally:
self.engaged = True
def _repr(val: t.Any) -> str:
assert val is not None
if types.is_none_type(val):
return 'NoneType'
elif ti.is_literal_type(val):
return str(val)
elif ti.is_new_type(val):
nested_type = val.__supertype__
return f'{_qualified_name(val)}[{get_repr(nested_type)}]'
elif ti.is_typevar(val):
tv_constraints = ti.get_constraints(val)
tv_bound = ti.get_bound(val)
if tv_constraints:
constraints_repr = (get_repr(tt) for tt in tv_constraints)
return f'typing.TypeVar(?, {", ".join(constraints_repr)})'
elif tv_bound:
return get_repr(tv_bound)
else:
return 'typing.Any'
elif ti.is_optional_type(val):
optional_args = ti.get_args(val, True)[:-1]
nested_union = len(optional_args) > 1
optional_reprs = (get_repr(tt) for tt in optional_args)
if nested_union:
return f'typing.Optional[typing.Union[{", ".join(optional_reprs)}]]'
else:
return f'typing.Optional[{", ".join(optional_reprs)}]'
elif ti.is_union_type(val):
union_reprs = (get_repr(tt) for tt in ti.get_args(val, True))
return f'typing.Union[{", ".join(union_reprs)}]'
elif ti.is_generic_type(val):
attr_name = val._name
generic_reprs = (get_repr(tt) for tt in ti.get_args(val, evaluate=True))
return f'typing.{attr_name}[{", ".join(generic_reprs)}]'
else:
val_name = _qualified_name(val)
maybe_td_entries = getattr(val, '__annotations__', {}).copy()
if maybe_td_entries:
# we are dealing with typed dict
# that's quite lovely
td_keys = sorted(maybe_td_entries.keys())
internal_members_repr = ', '.join(
'{key}: {type}'.format(key=k, type=get_repr(maybe_td_entries.get(k)))
for k in td_keys
)
return f'{val_name}{{{internal_members_repr}}}'
elif 'TypedDict' == getattr(val, '__name__', ''):
return 'typing_extensions.TypedDict'
else:
return val_name
def evaluate(tp: t.Union[str, t.TypeVar, t.Type, t.ForwardRef], *, frame=None):
if isinstance(tp, str):
tp = t.ForwardRef(tp)
if ti.is_typevar(tp):
tp = ti.get_bound(tp)
# TODO python versions
return t._eval_type(
tp,
frame.f_globals if frame else None,
frame.f_locals if frame else None,
)
def _init_parametric_user(cls) -> None:
"""Initialize an indirect descendant of ParametricType."""
# For ParametricType grandchildren we have to deal with possible
# TypeVar remapping and generally check for type sanity.
ob = getattr(cls, '__orig_bases__', ())
for b in ob:
if (isinstance(b, type) and issubclass(b, ParametricType)
and b is not ParametricType):
raise TypeError(
f'{cls.__name__}: missing one or more type arguments for'
f' base {b.__name__!r}')
if not typing_inspect.is_generic_type(b):
continue
org = typing_inspect.get_origin(b)
if not isinstance(org, type):
continue
if not issubclass(org, ParametricType):
continue
base_params = getattr(org, '__parameters__', ())
args = typing_inspect.get_args(b)
expected = len(base_params)
if len(args) != expected:
raise TypeError(
f'{b.__name__} expects {expected} type arguments'
f' got {len(args)}')
base_map = dict(cls._type_param_map)
subclass_map = {}
for i, arg in enumerate(args):
if not typing_inspect.is_typevar(arg):
raise TypeError(f'{b.__name__} expects all arguments to be'
f' TypeVars')
base_typevar = base_params[i]
attr = base_map.get(base_typevar)
if attr is not None:
subclass_map[arg] = attr
if len(subclass_map) != len(base_map):
raise TypeError(
f'{cls.__name__}: missing one or more type arguments for'
f' base {org.__name__!r}')
cls._type_param_map = subclass_map
def validate(self, value: Optional[Any]) -> _T:
"""Validate and possibly transform the given value.
Raises:
FieldValidationError: When the value is not valid.
"""
is_optional, annotation = extract_optional_annotation(self.annotation)
# Distinguishing between missing values and null values is
# important. Optional types can have None as a value whereas
# types with a default cannot. Additionally, it's possible to
# have an optional type without a default value.
if value is Missing:
if self.default is not Missing:
return self.default
elif self.default_factory:
return self.default_factory()
elif is_optional:
return None
raise FieldValidationError("this field is required")
if value is None:
if not is_optional:
raise FieldValidationError("this field cannot be null")
return value
if annotation not in (Any,) and \
not is_forward_ref(annotation) and \
not is_generic_type(annotation) and \
not is_union_type(annotation) and \
not is_typevar(annotation) and \
not is_schema(annotation) and \
not isinstance(value, annotation):
if not self.allow_coerce:
raise FieldValidationError(
f"unexpected type {type(value).__name__}")
try:
value = annotation(value)
except Exception:
raise FieldValidationError(
f"value could not be coerced to {annotation.__name__}")
if self.validator:
return self.validator.validate(self, value,
**self.validator_options)
return value
def realize(pytype: Type, bindings: Mapping[object, type]) -> object:
if typing_inspect.is_typevar(pytype):
return bindings[pytype]
if not hasattr(pytype, '__args__'):
return pytype
newargs: List = []
for arg in pytype.__args__: # type:ignore
newargs.append(realize(arg, bindings))
#print('realizing pytype', repr(pytype), 'newargs', repr(newargs))
pytype_origin = origin_of(pytype)
if not hasattr(pytype_origin, '_name'):
pytype_origin = getattr(typing, pytype._name) # type:ignore
if pytype_origin is Callable: # Callable args get flattened
newargs = [newargs[:-1], newargs[-1]]
return pytype_origin.__getitem__(tuple(newargs))
def _generate_primitive_schema(annotation: Any) -> Optional[Schema]:
try:
arguments = _PRIMITIVE_ANNOTATION_MAP[annotation]
return Schema(*arguments)
except KeyError:
origin = get_origin(annotation)
if origin in _LIST_TYPES:
arguments = get_args(annotation)
if not arguments or is_typevar(arguments[0]):
return Schema("array", items=_ANY_VALUE)
else:
return Schema("array", items=_generate_primitive_schema(arguments[0]))
# TODO: Add support for additionalFields.
return Schema("string")
def _init_parametric_base(cls) -> None:
"""Initialize a direct subclass of ParametricType"""
# Direct subclasses of ParametricType must declare
# ClassVar attributes corresponding to the Generic type vars.
# For example:
# class P(ParametricType, Generic[T, V]):
# t: ClassVar[Type[T]]
# v: ClassVar[Type[V]]
params = getattr(cls, '__parameters__', None)
if not params:
raise TypeError(f'{cls} must be declared as Generic')
mod = sys.modules[cls.__module__]
annos = get_type_hints(cls, mod.__dict__)
param_map = {}
for attr, t in annos.items():
if not typing_inspect.is_classvar(t):
continue
args = typing_inspect.get_args(t)
# ClassVar constructor should have the check, but be extra safe.
assert len(args) == 1
arg = args[0]
if typing_inspect.get_origin(arg) != type:
continue
arg_args = typing_inspect.get_args(arg)
# Likewise, rely on Type checking its stuff in the constructor
assert len(arg_args) == 1
if not typing_inspect.is_typevar(arg_args[0]):
continue
if arg_args[0] in params:
param_map[arg_args[0]] = attr
for param in params:
if param not in param_map:
raise TypeError(f'{cls.__name__}: missing ClassVar for'
f' generic parameter {param}')
cls._type_param_map = param_map
def is_pep484_nonable(typ):
"""
Checks if a given type is nonable, meaning that it explicitly or implicitly declares a Union with NoneType.
Nested TypeVars and Unions are supported.
:param typ:
:return:
"""
# TODO rely on typing_inspect if there is an answer to https://github.com/ilevkivskyi/typing_inspect/issues/14
if typ is type(None):
return True
elif is_typevar(typ) or is_union_type(typ):
return any(
is_pep484_nonable(tt) for tt in
get_alternate_types_resolving_forwardref_union_and_typevar(typ))
else:
return False
def normalize_pytype(typ: Type) -> Type:
if typing_inspect.is_typevar(typ):
# we treat type vars in the most general way possible (the bound, or as 'object')
bound = typing_inspect.get_bound(typ)
if bound is not None:
return normalize_pytype(bound)
constraints = typing_inspect.get_constraints(typ)
if constraints:
raise CrosshairUnsupported
# TODO: not easy; interpreting as a Union allows the type to be
# instantiated differently in different places. So, this doesn't work:
# return Union.__getitem__(tuple(map(normalize_pytype, constraints)))
return object
if typ is Any:
# The distinction between any and object is for type checking, crosshair treats them the same
return object
if typ is Type:
return type
return typ
def replace_typevars(typevars: TypeVarMapping, hint: T_type) -> T_type:
"""
Replaces type vars in a type hint with other types.
"""
if typing_inspect.is_typevar(hint):
return typing.cast(T_type, typevars.get(hint, hint))
# Special case empty callable, which raisees error on getting args
if hint == typing.Callable: # type: ignore
return hint
if typing_inspect.get_origin(hint) == collections.abc.Callable:
arg_types, return_type = typing_inspect.get_args(hint)
return typing.Callable[
[replace_typevars(typevars, a) for a in arg_types],
replace_typevars(typevars, return_type), ]
args = typing_inspect.get_args(hint)
if not args:
return hint
replaced_args = tuple(replace_typevars(typevars, arg) for arg in args)
return get_origin(hint)[replaced_args]
def get_pretty_type_str(object_type) -> str:
"""
Utility method to check if a type is a subclass of typing.{List,Dict,Set,Tuple}. In that case returns a
user-friendly character string with the inner item types, such as Dict[str, int].
:param object_type:
:return: type.__name__ if type is not a subclass of typing.{List,Dict,Set,Tuple}, otherwise
type__name__[list of inner_types.__name__]
"""
try:
# DO NOT resolve forward references otherwise this can lead to infinite recursion
contents_item_type, contents_key_type = _extract_collection_base_type(
object_type, resolve_fwd_refs=False)
if isinstance(contents_item_type, tuple):
return object_type.__name__ + '[' \
+ ', '.join([get_pretty_type_str(item_type) for item_type in contents_item_type]) + ']'
else:
if contents_key_type is not None:
return object_type.__name__ + '[' + get_pretty_type_str(contents_key_type) + ', ' \
+ get_pretty_type_str(contents_item_type) + ']'
elif contents_item_type is not None:
return object_type.__name__ + '[' + get_pretty_type_str(
contents_item_type) + ']'
except Exception as e:
pass
if is_union_type(object_type):
return 'Union[' + ', '.join([
get_pretty_type_str(item_type)
for item_type in get_args(object_type, evaluate=True)
]) + ']'
elif is_typevar(object_type):
# typevars usually do not display their namespace so str() is compact. And it displays the cov/contrav symbol
return str(object_type)
else:
try:
return object_type.__name__
except:
return str(object_type)
def _get_generic_types(
instance: _tp.Any,
count: _tp.Union[int, _tp.Set[int]],
*,
module_from: _tp.Any,
hint: str = ""
) -> _tp.Tuple[_tp.Type[_tp.Any], ...]:
types = _typing_inspect.get_args(_typing_inspect.get_generic_type(instance))
if not types:
types = _typing_inspect.get_args(_typing_inspect.get_generic_bases(instance)[0])
globalns = _sys.modules[module_from.__module__].__dict__
_eval_type = _tp._eval_type # type: ignore
types = tuple(_eval_type(i, globalns, None) for i in types)
if isinstance(count, int):
count = {count}
if count != {-1} and len(types) not in count or any(_typing_inspect.is_typevar(i) for i in types):
raise TypeError(f"{instance.__class__.__name__} generic was not properly parameterized{hint}: {types}")
return types
def is_vague_type(t: typing.Type) -> bool:
"""
Returns true if the type is a typevar, object or typing.
"""
return typing_inspect.is_typevar(t) or t == object or t == typing.Any
def decode(obj: Any, hint: Type, hint_args: Any = ()) -> Any:
ftype = hint
origin = get_origin(ftype)
bases = get_generic_bases(ftype)
targs = get_args(ftype)
if hint_args and any(is_typevar(t) for t in targs):
targs = hint_args
if ftype in PRIMITIVES:
return obj
if is_optional_type(ftype):
if obj is None:
return None
real_args = [t for t in targs if t is not type(None)]
if len(real_args) > 1:
raise NotImplementedError(f"can't decode union types ({real_args})")
ftype = real_args[0]
origin = get_origin(ftype)
elif is_union_type(ftype):
raise NotImplementedError(f"can't decode union types ({targs})")
if is_primitive(ftype):
return ftype(obj)
if is_datatype(ftype) or (origin and is_dataclass(origin)):
if not isinstance(obj, dict):
raise TypeError(f"invalid data {obj!r} for {ftype}")
kwargs: Dict[str, Any] = {}
namespace = sys.modules[ftype.__module__].__dict__
if origin and is_dataclass(origin):
type_hints = get_type_hints(origin, namespace)
else:
type_hints = get_type_hints(ftype, namespace)
for fname, ft in type_hints.items():
key = camelcase(fname.strip("_"))
if key in obj:
kwargs[fname] = decode(obj[key], ft, targs)
return ftype(**kwargs)
if is_generic_type(ftype):
while origin is None and bases:
if len(bases) > 1: # pragma: nocover
raise NotImplementedError(f"can't decode multiple bases {ftype}")
ftype = bases[0]
origin = get_origin(ftype)
bases = get_generic_bases(ftype)
targs = get_args(ftype)
if origin in (dict, Dict, Mapping):
if not is_primitive(targs[0]):
raise NotImplementedError(f"can't decode object keys {ftype}")
ftype = targs[1]
if ftype in PRIMITIVES:
return dict(obj)
else:
return {k: decode(v, ftype) for k, v in obj.items()}
if origin in (tuple, Tuple):
return tuple(decode(v, ftype) for v, ftype in zip(obj, targs))
if origin in (set, Set):
ftype = targs[0]
if ftype in PRIMITIVES:
return set(obj)
else:
return set(decode(v, ftype) for v in obj)
if origin in (list, List):
ftype = targs[0]
if ftype in PRIMITIVES:
return list(obj)
else:
return [decode(v, ftype) for v in obj]
raise NotImplementedError(f"failed to decode {obj} as type {hint}")
def match_expression(
wildcards: typing.List[Expression], template: object,
expr: object) -> typing.Tuple[TypeVarMapping, WildcardMapping]:
"""
Returns a mapping of wildcards to the objects at that level, or None if it does not match.
A wildcard can match either an expression or a value. If it matches two nodes, they must be equal.
"""
if template in wildcards:
# If we are matching against a placeholder and the expression is not resolved to that placeholder, don't match.
if (isinstance(template, PlaceholderExpression)
and isinstance(expr, Expression)
and not typing_inspect.is_typevar(
typing_inspect.get_args(
typing_inspect.get_generic_type(template))[0])):
raise NoMatch
# Match type of wildcard with type of expression
try:
return (
match_values(template, expr),
UnhashableMapping(Item(typing.cast(Expression, template),
expr)),
)
except TypeError:
raise NoMatch
if isinstance(expr, Expression):
if not isinstance(template, Expression):
raise NoMatch
# Any typevars in the template that are unbound should be matched with their
# versions in the expr
try:
fn_type_mapping: TypeVarMapping = match_functions(
template.function, expr.function)
except TypeError:
raise NoMatch
if set(expr.kwargs.keys()) != set(template.kwargs.keys()):
raise TypeError("Wrong kwargs in match")
template_args: typing.Iterable[object]
expr_args: typing.Iterable[object]
# Process args in the template that can represent any number of args.
# These are the "IteratedPlaceholder"s
# Allow one iterated placeholder in the template args
# For example fn(a, b, [...], *c, d, e, [...])
# Here `c` should take as many args as it can between the ends,
# Each of those should be matched against the inner
iterated_args = [
arg for arg in template.args
if isinstance(arg, IteratedPlaceholder)
]
if iterated_args:
# template args, minus the iterator, is the minimum length of the values
# If they have less values than this, raise an error
if len(expr.args) < len(template.args) - 1:
raise TypeError("Wrong number of args in match")
template_args_ = list(template.args)
# Only support one iterated arg for now
# TODO: Support more than one, would require branching
template_iterated, = iterated_args
template_index_iterated = list(
template.args).index(template_iterated)
# Swap template iterated with inner wildcard
template_args_[template_index_iterated], = template_iterated.args
template_args = template_args_
expr_args = collapse_tuple(
expr.args,
template_index_iterated,
# The number we should preserve on the right, is the number of template
# args after index
len(template.args) - template_index_iterated - 1,
)
else:
if len(template.args) != len(expr.args):
raise TypeError("Wrong number of args in match")
template_args = template.args
expr_args = expr.args
type_mappings, expr_mappings = list(
zip(
*(match_expression(wildcards, arg_template, arg_value)
for arg_template, arg_value in zip(template_args, expr_args)
),
*(match_expression(wildcards, template.kwargs[key],
expr.kwargs[key])
for key in template.kwargs.keys()),
)) or ((), ())
try:
merged_typevars: TypeVarMapping = merge_typevars(
fn_type_mapping, *type_mappings)
except TypeError:
raise NoMatch
try:
return (
merged_typevars,
safe_merge(*expr_mappings, dict_constructor=UnhashableMapping),
)
except ValueError:
raise NoMatch
if template != expr:
raise NoMatch
return match_values(template, expr), UnhashableMapping()
def match_types(hint: typing.Type, t: typing.Type) -> TypeVarMapping:
"""
Matches a type hint with a type, return a mapping of any type vars to their values.
"""
logger.debug("match_types hint=%s type=%s", hint, t)
if hint == object:
hint = typing.Any # type: ignore
if t == object:
t = typing.Any # type: ignore
if hint == t:
return {}
# If it is an instance of OfType[Type[T]], then we should consider it as T
if isinstance(t, OfType):
(of_type, ) = typing_inspect.get_args(get_type(t))
assert issubclass(of_type, typing.Type)
(t, ) = typing_inspect.get_args(of_type)
return match_types(hint, t)
# If the type is an OfType[T] then we should really just consider it as T
if issubclass(t, OfType) and not issubclass(hint, OfType):
(t, ) = typing_inspect.get_args(t)
return match_types(hint, t)
if issubclass(hint, OfType) and not issubclass(t, OfType):
(hint, ) = typing_inspect.get_args(hint)
return match_types(hint, t)
# Matching an expanded type is like matching just whatever it represents
if issubclass(t, ExpandedType):
(t, ) = typing_inspect.get_args(t)
if typing_inspect.is_typevar(hint):
return {hint: t}
# This happens with match rule on conversion, like when the value is TypeVar
if typing_inspect.is_typevar(t):
return {}
# if both are generic sequences, verify they are the same and have the same contents
if (typing_inspect.is_generic_type(hint)
and typing_inspect.is_generic_type(t)
and typing_inspect.get_origin(hint) == collections.abc.Sequence
and typing_inspect.get_origin(t) == collections.abc.Sequence):
t_inner = typing_inspect.get_args(t)[0]
# If t's inner arg is just the default one for seuqnce, it hasn't be initialized so assume
# it was an empty tuple that created it and just return a match
if t_inner == typing_inspect.get_args(typing.Sequence)[0]:
return {}
return match_types(typing_inspect.get_args(hint)[0], t_inner)
if typing_inspect.is_union_type(hint):
# If this is a union, iterate through and use the first that is a subclass
for inner_type in typing_inspect.get_args(hint):
if issubclass(t, inner_type):
hint = inner_type
break
else:
raise TypeError(f"Cannot match concrete type {t} with hint {hint}")
logger.debug("checking if type subclass hint hint=%s type=%s", hint, t)
if not issubclass(t, hint):
logger.debug("not subclass")
raise TypeError(f"Cannot match concrete type {t} with hint {hint}")
return merge_typevars(*(match_types(inner_hint, inner_t)
for inner_hint, inner_t in zip(
get_inner_types(hint), get_inner_types(t))))
def get(cls, type_or_hint, *, is_argument: bool = False) -> "TypeChecker":
# This ensures the validity of the type passed (see typing documentation for info)
type_or_hint = is_valid_type(type_or_hint, "Invalid type.",
is_argument)
if type_or_hint is Any:
return AnyTypeChecker()
if is_type(type_or_hint):
return TypeTypeChecker.make(type_or_hint, is_argument)
if is_literal_type(type_or_hint):
return LiteralTypeChecker.make(type_or_hint, is_argument)
if is_generic_type(type_or_hint):
origin = get_origin(type_or_hint)
if issubclass(origin, MappingCol):
return MappingTypeChecker.make(type_or_hint, is_argument)
if issubclass(origin, Collection):
return CollectionTypeChecker.make(type_or_hint, is_argument)
# CONSIDER: how to cater for exhaustible generators?
if issubclass(origin, Iterable):
raise NotImplementedError(
"No type-checker is setup for iterables that exhaust.")
return GenericTypeChecker.make(type_or_hint, is_argument)
if is_tuple_type(type_or_hint):
return TupleTypeChecker.make(type_or_hint, is_argument)
if is_callable_type(type_or_hint):
return CallableTypeChecker.make(type_or_hint, is_argument)
if isclass(type_or_hint):
if is_typed_dict(type_or_hint):
return TypedDictChecker.make(type_or_hint, is_argument)
return ConcreteTypeChecker.make(type_or_hint, is_argument)
if is_union_type(type_or_hint):
return UnionTypeChecker.make(type_or_hint, is_argument)
if is_typevar(type_or_hint):
bound_type = get_bound(type_or_hint)
if bound_type:
return cls.get(bound_type)
constraints = get_constraints(type_or_hint)
if constraints:
union_type_checkers = tuple(
cls.get(type_) for type_ in constraints)
return UnionTypeChecker(Union.__getitem__(constraints),
union_type_checkers)
else:
return AnyTypeChecker()
if is_new_type(type_or_hint):
super_type = getattr(type_or_hint, "__supertype__", None)
if super_type is None:
raise TypeError(
f"No supertype for NewType: {type_or_hint}. This is not allowed."
)
return cls.get(super_type)
if is_forward_ref(type_or_hint):
return ForwardTypeChecker.make(type_or_hint,
is_argument=is_argument)
if is_classvar(type_or_hint):
var_type = get_args(type_or_hint, evaluate=True)[0]
return cls.get(var_type)
raise NotImplementedError(
f"No {TypeChecker.__qualname__} is available for type or hint: '{type_or_hint}'"
)
def get_parsing_fn(t: Type[T]) -> Callable[[Any], T]:
"""Gets a parsing function for the given type or type annotation.
Args:
t (Type[T]): A type or type annotation.
Returns:
Callable[[Any], T]: A function that will parse a value of the given type
from the command-line when available, or a no-op function that
will return the raw value, when a parsing fn cannot be found or
constructed.
"""
if t in _parsing_fns:
logger.debug(f"The type {t} has a dedicated parsing function.")
return _parsing_fns[t]
elif t is Any:
logger.debug(f"parsing an Any type: {t}")
return no_op
# TODO: Do we want to support parsing a Dict from command-line?
# elif is_dict(t):
# logger.debug(f"parsing a Dict field: {t}")
# args = get_type_arguments(t)
# if len(args) != 2:
# args = (Any, Any)
# return parse_dict(*args)
# TODO: This would require some sort of 'postprocessing' step to convert a
# list to a Set or something like that.
# elif is_set(t):
# logger.debug(f"parsing a Set field: {t}")
# args = get_type_arguments(t)
# if len(args) != 1:
# args = (Any,)
# return parse_set(args[0])
elif is_tuple(t):
logger.debug(f"parsing a Tuple field: {t}")
args = get_type_arguments(t)
if is_homogeneous_tuple_type(t):
if not args:
args = (str, ...)
parsing_fn = get_parsing_fn(args[0])
else:
parsing_fn = parse_tuple(args)
parsing_fn.__name__ = str(t)
return parsing_fn
elif is_list(t):
logger.debug(f"parsing a List field: {t}")
args = get_type_arguments(t)
assert len(args) == 1
return parse_list(args[0])
elif is_union(t):
logger.debug(f"parsing a Union field: {t}")
args = get_type_arguments(t)
return parse_union(*args)
elif is_enum(t):
logger.debug(f"Parsing an Enum field of type {t}")
return parse_enum(t)
# import typing_inspect as tpi
# from .serializable import get_dataclass_type_from_forward_ref, Serializable
if tpi.is_forward_ref(t):
forward_arg = tpi.get_forward_arg(t)
for t, fn in _parsing_fns.items():
if getattr(t, "__name__", str(t)) == forward_arg:
return fn
if tpi.is_typevar(t):
bound = tpi.get_bound(t)
logger.debug(f"parsing a typevar: {t}, bound type is {bound}.")
if bound is not None:
return get_parsing_fn(bound)
logger.debug(f"Couldn't find a parsing function for type {t}, will try "
f"to use the type directly.")
return t
def is_value_of_type( # noqa: C901 "too complex"
# pyre-fixme[2]: Parameter annotation cannot be `Any`.
value: Any,
# pyre-fixme[2]: Parameter annotation cannot be `Any`.
expected_type: Any,
invariant_check: bool = False,
) -> bool:
"""
This method attempts to verify a given value is of a given type. If the type is
not supported, it returns True but throws an exception in tests.
It is similar to typeguard / enforce pypi modules, but neither of those have
permissive options for types they do not support.
Supported types for now:
- List/Set/Iterable
- Dict/Mapping
- base types (str, int, etc)
- Literal
- Unions
- Tuples
- Concrete Classes
- ClassVar
Not supported:
- Callables, which will likely not be used in XHP anyways
- Generics, Type Vars (treated as Any)
- Generators
- Forward Refs -- use `typing.get_type_hints` to resolve these
- Type[...]
"""
if is_classvar(expected_type):
# `ClassVar` (no subscript) is implicitly `ClassVar[Any]`
if hasattr(expected_type, "__type__"): # py36
expected_type = expected_type.__type__ or Any
else: # py37+
classvar_args = get_args(expected_type)
expected_type = (classvar_args[0] or Any) if classvar_args else Any
if is_typevar(expected_type):
# treat this the same as Any
# TODO: evaluate bounds
return True
expected_origin_type = get_origin(expected_type) or expected_type
if expected_origin_type == Any:
return True
elif is_union_type(expected_type):
return any(
is_value_of_type(value, subtype) for subtype in expected_type.__args__
)
elif isinstance(expected_origin_type, type(Literal)):
if hasattr(expected_type, "__values__"): # py36
literal_values = expected_type.__values__
else: # py37+
literal_values = get_args(expected_type, evaluate=True)
return any(value == literal for literal in literal_values)
elif isinstance(expected_origin_type, ForwardRef):
# not much we can do here for now, lets just return :(
return True
# Handle `Tuple[A, B, C]`.
# We don't want to include Tuple subclasses, like NamedTuple, because they're
# unlikely to behave similarly.
elif expected_origin_type in [Tuple, tuple]: # py36 uses Tuple, py37+ uses tuple
if not isinstance(value, tuple):
return False
type_args = get_args(expected_type, evaluate=True)
if len(type_args) == 0:
# `Tuple` (no subscript) is implicitly `Tuple[Any, ...]`
return True
if type_args is None:
return True
if len(value) != len(type_args):
return False
# TODO: Handle `Tuple[T, ...]` like `Iterable[T]`
for subvalue, subtype in zip(value, type_args):
if not is_value_of_type(subvalue, subtype):
return False
return True
elif issubclass(expected_origin_type, Mapping):
# We're expecting *some* kind of Mapping, but we also want to make sure it's
# the correct Mapping subtype. That means we want {a: b, c: d} to match Mapping,
# MutableMapping, and Dict, but we don't want MappingProxyType({a: b, c: d}) to
# match MutableMapping or Dict.
if not issubclass(type(value), expected_origin_type):
return False
type_args = get_args(expected_type, evaluate=True)
if len(type_args) == 0:
# `Mapping` (no subscript) is implicitly `Mapping[Any, Any]`.
return True
invariant_check = issubclass(expected_origin_type, MutableMapping)
for subkey, subvalue in value.items():
if not is_value_of_type(
subkey,
type_args[0],
# key type is always invariant
invariant_check=True,
):
return False
if not is_value_of_type(
subvalue, type_args[1], invariant_check=invariant_check
):
return False
return True
# While this does technically work fine for str and bytes (they are iterables), it's
# better to use the default isinstance behavior for them.
#
# Similarly, tuple subclasses tend to have pretty different behavior, and we should
# fall back to the default check.
elif issubclass(expected_origin_type, Iterable) and not issubclass(
expected_origin_type,
(str, bytes, tuple),
):
# We know this thing is *some* kind of Iterable, but we want to
# allow subclasses. That means we want [1,2,3] to match both
# List[int] and Iterable[int], but we do NOT want that
# to match Set[int].
if not issubclass(type(value), expected_origin_type):
return False
type_args = get_args(expected_type, evaluate=True)
if len(type_args) == 0:
# `Iterable` (no subscript) is implicitly `Iterable[Any]`.
return True
# We invariant check if its a mutable sequence
invariant_check = issubclass(expected_origin_type, MutableSequence)
return all(
is_value_of_type(subvalue, type_args[0], invariant_check=invariant_check)
for subvalue in value
)
try:
if not invariant_check:
if expected_type is float:
return isinstance(value, (int, float))
else:
return isinstance(value, expected_type)
return type(value) is expected_type
except Exception as e:
raise NotImplementedError(
f"the value {value!r} was compared to type {expected_type!r} "
+ f"but support for that has not been implemented yet! Exception: {e!r}"
)