def _decode_generic(type_, value, infer_missing):
if value is None:
res = value
elif _is_collection(type_):
if _is_mapping(type_):
k_type, v_type = type_.__args__
# a mapping type has `.keys()` and `.values()` (see collections.abc)
ks = _decode_dict_keys(k_type, value.keys(), infer_missing)
vs = _decode_items(v_type, value.values(), infer_missing)
xs = zip(ks, vs)
else:
xs = _decode_items(type_.__args__[0], value, infer_missing)
# get the constructor if using corresponding generic type in `typing`
# otherwise fallback on constructing using type_ itself
try:
res = _get_type_cons(type_)(xs)
except TypeError:
res = type_(xs)
elif _issubclass_safe(type_, Enum):
# Convert to an Enum using the type as a constructor. Assumes a direct match is found.
res = type_(value)
else: # Optional
type_arg = type_.__args__[0]
if is_dataclass(type_arg) or is_dataclass(value):
res = _decode_dataclass(type_arg, value, infer_missing)
elif _is_supported_generic(type_arg):
res = _decode_generic(type_arg, value, infer_missing)
else:
res = value
return res
def _decode_generic(type_, value, infer_missing):
if value is None:
res = value
elif _issubclass_safe(type_, Enum):
# Convert to an Enum using the type as a constructor. Assumes a direct match is found.
res = type_(value)
# FIXME this is a hack to fix a deeper underlying issue. A refactor is due.
elif _is_collection(type_):
if _is_mapping(type_):
k_type, v_type = type_.__args__
# a mapping type has `.keys()` and `.values()` (see collections.abc)
ks = _decode_dict_keys(k_type, value.keys(), infer_missing)
vs = _decode_items(v_type, value.values(), infer_missing)
xs = zip(ks, vs)
else:
xs = _decode_items(type_.__args__[0], value, infer_missing)
# get the constructor if using corresponding generic type in `typing`
# otherwise fallback on constructing using type_ itself
try:
res = _get_type_cons(type_)(xs)
except TypeError:
res = type_(xs)
else: # Optional or Union
if _is_optional(type_) and len(type_.__args__) == 2: # Optional
type_arg = type_.__args__[0]
if is_dataclass(type_arg) or is_dataclass(value):
res = _decode_dataclass(type_arg, value, infer_missing)
elif _is_supported_generic(type_arg):
res = _decode_generic(type_arg, value, infer_missing)
else:
res = _support_extended_types(type_arg, value)
else: # Union (already decoded or unsupported 'from_json' used)
res = value
return res
def _make_default_field(type_, default, cls):
cons_type = type_
cons_type = (list if _is_nonstr_collection(cons_type) else cons_type)
cons_type = (dict if _is_mapping(cons_type) else cons_type)
cons_type = (type_.__args__[0] if _is_optional(cons_type) else cons_type)
cons = _type_to_cons[cons_type]
if cons is fields.List:
type_arg = type_.___args__[0]
if type_arg not in _type_to_cons:
raise TypeError(f"Unsupported {type_arg} detected. Is it "
f"a supported JSON type or dataclass_json "
f"instance?")
arg_cons = _type_to_cons[type_arg]
return cons(cls, arg_cons, missing=default)
return cons(cls, missing=default)
