def testEncoders(self):
for class_, fake_func in TEST_CASES:
original_object = fake_func()
# We can skip metrics and runners; the encoders will automatically
# handle the addition of new fields to these classes
if isinstance(original_object, Metric) or isinstance(
original_object, Runner
):
continue
json_object = object_to_json(original_object)
object_keys = {
remove_prefix(key, "_") for key in original_object.__dict__.keys()
}
json_keys = {key for key in json_object.keys() if key != "__type"}
# Account for fields that appear in the Python object but not the JSON
# and for fields that appear in both places but with different names
if class_ in ENCODE_DECODE_FIELD_MAPS:
map = ENCODE_DECODE_FIELD_MAPS[class_]
for field in map.python_only:
json_keys.add(field)
for field in map.encoded_only:
object_keys.add(field)
for python, encoded in map.python_to_encoded.items():
json_keys.remove(encoded)
json_keys.add(python)
self.assertEqual(
object_keys,
json_keys,
msg=f"Mismatch between Python and JSON representation in {class_}.",
)
def testEncoders(self):
for class_, fake_func, unbound_encode_func, _ in TEST_CASES:
original_object = fake_func()
# We can skip metrics and runners; the encoders will automatically
# handle the addition of new fields to these classes
if isinstance(original_object, Metric) or isinstance(
original_object, Runner
):
continue
encode_func = unbound_encode_func.__get__(self.encoder)
sqa_object = encode_func(original_object)
if isinstance(
original_object, AbandonedArm
): # handle NamedTuple differently
object_keys = original_object._asdict().keys()
else:
object_keys = original_object.__dict__.keys()
object_keys = {remove_prefix(key, "_") for key in object_keys}
sqa_keys = {
remove_prefix(key, "_")
for key in sqa_object.attributes
if key not in ["id", "_sa_instance_state"]
and not is_foreign_key_field(key)
}
# Account for fields that appear in the Python object but not the SQA
# the SQA but not the Python, and for fields that appear in both places
# but with different names
if class_ in ENCODE_DECODE_FIELD_MAPS:
map = ENCODE_DECODE_FIELD_MAPS[class_]
for field in map.python_only:
sqa_keys.add(field)
for field in map.encoded_only:
object_keys.add(field)
for python, encoded in map.python_to_encoded.items():
sqa_keys.remove(encoded)
sqa_keys.add(python)
self.assertEqual(
object_keys,
sqa_keys,
msg=f"Mismatch between Python and SQA representation in {class_}.",
)
def testEncoders(self):
for class_, fake_func in TEST_CASES:
original_object = fake_func()
# We can skip metrics and runners; the encoders will automatically
# handle the addition of new fields to these classes
if isinstance(original_object, Metric) or isinstance(
original_object, Runner):
continue
json_object = object_to_json(original_object)
object_keys = {
remove_prefix(key, "_")
for key in original_object.__dict__.keys()
}
json_keys = {key for key in json_object.keys() if key != "__type"}
# Account for fields that appear in the Python object but not the JSON
# and for fields that appear in both places but with different names
if class_ in ENCODE_DECODE_FIELD_MAPS:
map = ENCODE_DECODE_FIELD_MAPS[class_]
for field in map.python_only:
json_keys.add(field)
for field in map.encoded_only:
object_keys.add(field)
for python, encoded in map.python_to_encoded.items():
json_keys.remove(encoded)
json_keys.add(python)
# TODO: Remove this check if able. `_slotnames__` is not a class attribute
# when testing locally, but it is a class attribute on Travis
if class_ == "Type[Model]":
object_keys.discard("_slotnames__")
if class_ == "Type[MarginalLogLikelihood]":
object_keys.discard("add_other_terms")
self.assertEqual(
object_keys,
json_keys,
msg=
(f"Mismatch between Python and JSON representation in {class_}."
f"Python: {object_keys} does not match JSON: {json_keys}."),
)
