def test_deep_merge_dicts(self):
arg1 = {
('C1', 'CLUSTER'): {
('N1', 'NODE'): {
('NS1', 'NAMESPACE'): {
('CONFIG1', 'KEY'): (1, [])
},
('NS2', 'NAMESPACE'): {
('CONFIG2', 'KEY'): (2, []),
('CONFIG3', 'KEY'): (3, [])
}
}
}
}
arg2 = {
('C1', 'CLUSTER'): {
('N1', 'NODE'): {
('NS3', 'NAMESPACE'): {
('CONFIG1', 'KEY'): (3, [])
},
('NS2', 'NAMESPACE'): {
('CONFIG2', 'KEY'): (4, []),
('CONFIG5', 'KEY'): (7, [])
}
}
}
}
expected = {
('C1', 'CLUSTER'): {
('N1', 'NODE'): {
('NS1', 'NAMESPACE'): {
('CONFIG1', 'KEY'): (1, [])
},
('NS3', 'NAMESPACE'): {
('CONFIG1', 'KEY'): (3, [])
},
('NS2', 'NAMESPACE'): {
('CONFIG2', 'KEY'): (2, []),
('CONFIG3', 'KEY'): (3, []),
('CONFIG5', 'KEY'): (7, [])
}
}
}
}
result = util.deep_merge_dicts(arg1, arg2)
self.assertEqual(
result, expected,
"deep_merge_dicts did not return the expected result")
def do_group_by(data, group_by, keys=[]):
if not group_by:
raise HealthException("No Group ID for group by operation")
if not data:
raise HealthException("Wrong Input Data for group by operation.")
if not isinstance(data, dict):
raise HealthException("Wrong group id %s for group by operation." %
(str(group_by)))
res = {}
for k, t in data.keys():
temp_d = res
if t == group_by:
if (k, t) not in temp_d:
temp_d[(k, t)] = {}
if keys:
temp_d = temp_d[(k, t)]
for _k in keys[:-1]:
if _k not in temp_d:
temp_d[_k] = {}
temp_d = temp_d[_k]
temp_d[keys[-1]] = data[(k, t)]
else:
temp_d[(k, t)] = data[(k, t)]
else:
keys.append((k, t))
try:
res = deep_merge_dicts(
res, do_group_by(data[(k, t)], group_by, keys))
except Exception as e:
raise e
finally:
keys.remove((k, t))
return res
def select_keys_from_dict(data={},
keys=[],
from_keys=[],
ignore_keys=[],
save_param=None,
config_param=False):
"""
Function takes dictionary, list of keys to fetch, list of from_keys to filter scope
Returns dictionary of selected keys and values
"""
if not data or not isinstance(data, dict):
raise HealthException("Wrong Input Data for select operation.")
result_dict = {}
if not keys:
raise HealthException("No key provided for select operation.")
for _key in data:
if from_keys:
f_key = from_keys[0]
if isinstance(_key, tuple):
# from_keys work with static component keys only, if we get
# tuple keys means we have done with checking of all component
# keys and not found any from key match so no need to check
# further in this direction
break
if (f_key == "ALL") or (_key == f_key):
# from_key is ALL or matching with _key
child_res = select_keys_from_dict(
data[_key],
keys=keys,
from_keys=from_keys[1:] if len(from_keys) > 1 else [],
ignore_keys=ignore_keys,
save_param=save_param,
config_param=config_param)
else:
# no key match, need to check further
child_res = select_keys_from_dict(data[_key],
keys=keys,
from_keys=from_keys,
ignore_keys=ignore_keys,
save_param=save_param,
config_param=config_param)
if child_res:
if f_key == "ALL":
# It assumes ALL is only for top snapshot level
result_dict[(_key, "SNAPSHOT")] = copy.deepcopy(child_res)
else:
result_dict = deep_merge_dicts(result_dict,
copy.deepcopy(child_res))
else:
# if (False, "*", None) in keys and isinstance(_key, tuple):
# result_dict[_key] = copy.deepcopy(data[_key])
if isinstance(_key, tuple) and _key[1] == "KEY":
for check_substring, s_key, new_name in keys:
if ((s_key == "*"
and not _is_key_in_ignore_keys(_key[0], ignore_keys))
or (check_substring and re.search(s_key, _key[0]))
or (not check_substring and _key[0] == s_key)):
val_to_save = create_value_list_to_save(
save_param=save_param,
key=_key[0],
value=data[_key],
formatting=not config_param)
if new_name:
result_dict[(
new_name,
"KEY")] = create_health_internal_tuple(
data[_key], val_to_save)
else:
result_dict[_key] = create_health_internal_tuple(
data[_key], val_to_save)
break
elif data[_key] and isinstance(data[_key], dict):
child_res = select_keys_from_dict(data[_key],
keys=keys,
ignore_keys=ignore_keys,
save_param=save_param,
config_param=config_param)
if child_res:
if isinstance(_key, tuple):
result_dict[_key] = copy.deepcopy(child_res)
else:
result_dict = deep_merge_dicts(
result_dict, copy.deepcopy(child_res))
return result_dict