def test_pickling():
@parameterize
def check(node_class, attribute, value, expected):
"""{0.__name__}.{1} pickling works as expected"""
node = node_class()
setattr(node, attribute, value)
unpickled_node = _pickle_unpickle(node)
if isinstance(expected, type) and issubclass(expected, Exception):
assert_raises(expected, getattr, unpickled_node, attribute)
else:
value = getattr(unpickled_node, attribute)
if callable(expected):
assert expected(value)
elif isinstance(expected, np.ndarray):
assert vector.vector_eq(expected, value)
else:
assert expected == value
# arguments: (node class, attribute, value to set,
# expected value/exception/test)
yield check(vector.Input, 'name', 'constant',
'constant')
yield check(vector.Input, '_value', 42.0,
42.0)
yield check(vector.Input, '_value', DIRTY,
DIRTY)
yield check(vector.Input, '_value', np.array([42.0]),
np.array([42.0]))
yield check(vector.Input, 'last_timestamp', 1234,
1234)
yield check(vector.Input, 'extra_attribute', 42.0,
AttributeError)
yield check(vector.Node, 'name', 'constant',
'constant')
yield check(vector.Node, '_value', 42.0,
42.0)
yield check(vector.Node, '_value', np.array([42.0]),
np.array([42.0]))
yield check(vector.Node, '_action', sum,
lambda _action: _action == sum)
yield check(vector.Node, 'triggered', True,
True)
yield check(vector.Node, '_positional_inputs',
(vector.Input(name='foo'),),
(lambda _positional_inputs:
[n.name for n in _positional_inputs] == ['foo']))
yield check(vector.Node, '_keyword_inputs',
{'foo': vector.Input(name='bar')},
(lambda _keyword_inputs:
{k: v.name for k, v in _keyword_inputs.items()}
== {'foo': 'bar'}))
yield check(vector.Node, 'extra_attribute', 42.0,
AttributeError)
def test_array_value(self):
inp = vector.Input(value=np.array([1, 2]))
eq_(None, inp.last_timestamp)
def test_scalar_value(self):
inp = vector.Input(value=100000.0)
eq_(None, inp.last_timestamp)
def test_set_value(self):
inp = vector.Input()
inp.value = pd.Series([1, 2], index=[1001, 1002])
eq_(1002, inp.last_timestamp)
def test_initial_value(self):
inp = vector.Input(value=pd.Series([1, 2], [1001, 1002]))
eq_(1002, inp.last_timestamp)
def test_no_value(self):
inp = vector.Input()
eq_(None, inp.last_timestamp)
def test_dirty_value(self):
inp = vector.Input(value=DIRTY)
eq_(None, inp.last_timestamp)