def testCallback(self):
class Foo(object):
def __init__(self):
self.x = 1
class Bar(object):
def __init__(self):
self.foo = Foo()
def serialize(obj):
return dict(obj.__dict__, **{"_pytype_": type(obj).__name__})
def deserialize(obj):
if obj["_pytype_"] == "Foo":
result = Foo()
elif obj["_pytype_"] == "Bar":
result = Bar()
obj.pop("_pytype_", None)
result.__dict__ = obj
return result
bar = Bar()
bar.foo.x = 42
numbuf.register_callbacks(serialize, deserialize)
metadata, size, serialized = numbuf.serialize_list([bar])
self.assertEqual(numbuf.deserialize_list(serialized)[0].foo.x, 42)
def testCallback(self):
class Foo(object):
def __init__(self):
self.x = 1
class Bar(object):
def __init__(self):
self.foo = Foo()
def serialize(obj):
return dict(obj.__dict__, **{"_pytype_": type(obj).__name__})
def deserialize(obj):
if obj["_pytype_"] == "Foo":
result = Foo()
elif obj["_pytype_"] == "Bar":
result = Bar()
obj.pop("_pytype_", None)
result.__dict__ = obj
return result
bar = Bar()
bar.foo.x = 42
numbuf.register_callbacks(serialize, deserialize)
metadata, size, serialized = numbuf.serialize_list([bar])
self.assertEqual(numbuf.deserialize_list(serialized)[0].foo.x, 42)
def testObjectArray(self):
x = np.array([1, 2, "hello"], dtype=object)
y = np.array([[1, 2], [3, 4]], dtype=object)
def myserialize(obj):
return {"_pytype_": "numpy.array", "data": obj.tolist()}
def mydeserialize(obj):
if obj["_pytype_"] == "numpy.array":
return np.array(obj["data"], dtype=object)
numbuf.register_callbacks(myserialize, mydeserialize)
metadata, size, serialized = numbuf.serialize_list([x, y])
assert_equal(numbuf.deserialize_list(serialized), [x, y])
def testObjectArray(self):
x = np.array([1, 2, "hello"], dtype=object)
y = np.array([[1, 2], [3, 4]], dtype=object)
def myserialize(obj):
return {"_pytype_": "numpy.array", "data": obj.tolist()}
def mydeserialize(obj):
if obj["_pytype_"] == "numpy.array":
return np.array(obj["data"], dtype=object)
numbuf.register_callbacks(myserialize, mydeserialize)
metadata, size, serialized = numbuf.serialize_list([x, y])
assert_equal(numbuf.deserialize_list(serialized), [x, y])
"""This is the callback that will be used by numbuf.
If numbuf encounters a dictionary that contains the key "_pytype_" during
deserialization, it will ask this callback to deserialize the object.
Args:
serialized_obj (object): A dictionary that contains the key "_pytype_".
Returns:
A Python object.
"""
class_id = serialized_obj["_pytype_"]
cls = whitelisted_classes[class_id]
if class_id in classes_to_pickle:
obj = pickling.loads(serialized_obj["data"])
elif class_id in custom_deserializers.keys():
obj = custom_deserializers[class_id](serialized_obj["data"])
else:
# In this case, serialized_obj should just be the __dict__ field.
if "_ray_getnewargs_" in serialized_obj:
obj = cls.__new__(cls, *serialized_obj["_ray_getnewargs_"])
else:
obj = cls.__new__(cls)
serialized_obj.pop("_pytype_")
obj.__dict__.update(serialized_obj)
return obj
# Register the callbacks with numbuf.
numbuf.register_callbacks(serialize, deserialize)