def test_evaluate_second_variation_no_target_match():
feature = copy(minimal_feature)
hash_value = long(hashlib.sha1('feature.key.abc.xyz').hexdigest()[:15], 16) / float(0xFFFFFFFFFFFFFFF)
feature['variations'] = [
{
u'value': True,
u'weight': floor(hash_value) - 1,
u'targets': [
{
u'attribute': u'bizzle',
u'op': u'in',
u'values': [ u'defg' ]
}
]
},
{
u'value': False,
u'weight': 100 - (floor(hash_value) - 1),
u'targets': [
{
u'attribute': u'bazzle',
u'op': u'in',
u'values': [ u'zyx' ]
},
{
u'attribute': u'bizzle',
u'op': u'in',
u'values': [ u'defg' ]
}
]
}
]
assert ldclient._evaluate(feature, user) == False
def test_evaluate_second_variation_target_match():
feature = copy(minimal_feature)
feature['variations'] = [
{
u'value': True,
u'weight': 0,
u'targets': [
{
u'attribute': u'bizzle',
u'op': u'in',
u'values': [ u'defg' ]
}
]
},
{
u'value': False,
u'weight': 100,
u'targets': [
{
u'attribute': u'bazzle',
u'op': u'in',
u'values': [ u'zyx' ]
},
{
u'attribute': u'bizzle',
u'op': u'in',
u'values': [ u'def' ]
}
]
}
]
assert ldclient._evaluate(feature, user) == False
def test_evaluate_first_variation_both_targets_match_user_key_match_no_user_target():
feature = copy(minimal_feature)
feature['variations'] = [
{
u'value': True,
u'weight': 0,
u'targets': [
{
u'attribute': u'key',
u'op': u'in',
u'values': [ 'xyz' ]
},
]
},
{
u'value': False,
u'weight': 100,
u'targets': [
{
u'attribute': u'bazzle',
u'op': u'in',
u'values': [ u'zyx' ]
},
{
u'attribute': u'bizzle',
u'op': u'in',
u'values': [ u'def' ]
}
]
}
]
assert ldclient._evaluate(feature, user) == True
def mock_toggle(key, user, default):
hash = minimal_feature = {
u'key': u'feature.key',
u'salt': u'abc',
u'on': True,
u'variations': [
{
u'value': True,
u'weight': 100,
u'targets': []
},
{
u'value': False,
u'weight': 0,
u'targets': []
}
]
}
val = ldclient._evaluate(hash, user)
if val is None:
return defer.succeed(default)
return defer.succeed(val)
def _toggle(self, key, user, default):
self._toggle_count += 1
hash = minimal_feature = {
u'key': u'feature.key',
u'salt': u'abc',
u'on': True,
u'variations': [
{
u'value': True,
u'weight': 100,
u'targets': []
},
{
u'value': False,
u'weight': 0,
u'targets': []
}
]
}
val = ldclient._evaluate(hash, user)
if val is None:
return default
return val
def test_evaluate_feature_off(): feature = copy(minimal_feature) feature['on'] = False assert ldclient._evaluate(feature, user) == None