def process_type(type_str):
normalized_type_str = normalize(type_str)
abi_type = parse(normalized_type_str)
type_str_repr = repr(type_str)
if type_str != normalized_type_str:
type_str_repr = '{} (normalized to {})'.format(
type_str_repr,
repr(normalized_type_str),
)
if isinstance(abi_type, TupleType):
raise ValueError(
"Cannot process type {}: tuple types not supported".format(
type_str_repr, ))
abi_type.validate()
sub = abi_type.sub
if isinstance(sub, tuple):
sub = 'x'.join(map(str, sub))
elif isinstance(sub, int):
sub = str(sub)
else:
sub = ''
arrlist = abi_type.arrlist
if isinstance(arrlist, tuple):
arrlist = list(map(list, arrlist))
else:
arrlist = []
return abi_type.base, sub, arrlist
def get_strategy(self, type_str: TypeStr) -> st.SearchStrategy:
"""
Returns a hypothesis strategy for the given ABI type.
:param type_str: The canonical string representation of the ABI type
for which a hypothesis strategy should be returned.
:returns: A hypothesis strategy for generating Python values that are
encodable as values of the given ABI type.
"""
registration = self._get_registration(self._strategies, type_str)
if isinstance(registration, st.SearchStrategy):
# If a hypothesis strategy was registered, just return it
return registration
else:
# Otherwise, assume the factory is a callable. Call it with the abi
# type to get an appropriate hypothesis strategy.
normalized_type_str = normalize(type_str)
abi_type = parse(normalized_type_str)
strategy = registration(abi_type, self)
return strategy
def test_normalizing_and_parsing_works(type_str, expected_type):
assert parse(normalize(type_str)) == expected_type
def test_normalize(type_str, normalized):
assert normalize(type_str) == normalized
def test_normalizing_and_parsing_works(type_str, expected_type):
assert parse(normalize(type_str)) == expected_type
def test_normalize(type_str, normalized):
assert normalize(type_str) == normalized
