def _operate_each_key(self, arg1, arg2, save_param=None):
if isinstance(arg1, dict) and isinstance(arg2, dict):
return None
if not isinstance(arg1, dict) and not isinstance(arg2, dict):
try:
raw_arg1 = get_value_from_health_internal_tuple(arg1)
raw_arg2 = get_value_from_health_internal_tuple(arg2)
if self.op == operator.div and raw_arg2 == 0:
val_to_save = create_value_list_to_save(save_param,
value=0,
op1=arg1,
op2=arg2)
return (0, val_to_save)
# if any of the arg is type float or operation is division
# cast all argument to float
if self.op == operator.div or isinstance(
raw_arg1, float) or isinstance(raw_arg2, float):
raw_arg1 = float(raw_arg1)
raw_arg2 = float(raw_arg2)
result = self.op(raw_arg1, raw_arg2)
val_to_save = create_value_list_to_save(save_param,
value=result,
op1=arg1,
op2=arg2)
return create_health_internal_tuple(result, val_to_save)
except Exception:
return create_health_internal_tuple(None, [])
dict_first = True
if isinstance(arg1, dict):
d = arg1
v = arg2
elif isinstance(arg2, dict):
d = arg2
v = arg1
dict_first = False
res_dict = {}
for _k in d:
if dict_first:
res_dict[_k] = self._operate_each_key(d[_k],
v,
save_param=save_param)
else:
res_dict[_k] = self._operate_each_key(v,
d[_k],
save_param=save_param)
return res_dict
def test_create_value_list_to_save(self):
op1 = [{
('observed_nodes', 'KEY'): (6.0, [('conf2', 100, True)])
}, {
('c', 'KEY'): (106.0, [('conf1', 6.0, True)])
}]
op2 = [{
('observed_nodes', 'KEY'): ("conf3", [('a', "abcd", True)])
}, {
('a', 'KEY'): ("testval", [('conf4', "testval", True)])
}]
key = "key"
value = "value"
result = util.create_value_list_to_save(save_param=None,
key=key,
value=value,
op1=op1,
op2=op2)
expected = [('conf2', 100, True), ('conf1', 6.0, True),
('a', 'abcd', True), ('conf4', 'testval', True)]
self.assertEqual(
result, expected,
"create_value_list_to_save did not return the expected result")
result = util.create_value_list_to_save(save_param="",
key=key,
value=value,
op1=op1,
op2=op2)
expected = [('conf2', 100, True), ('conf1', 6.0, True),
('a', 'abcd', True), ('conf4', 'testval', True),
(key, value, True)]
self.assertEqual(
result, expected,
"create_value_list_to_save did not return the expected result")
result = util.create_value_list_to_save(save_param="save_key",
key=key,
value=value,
op1=op1,
op2=op2)
expected = [('conf2', 100, True), ('conf1', 6.0, True),
('a', 'abcd', True), ('conf4', 'testval', True),
("save_key", value, True)]
self.assertEqual(
result, expected,
"create_value_list_to_save did not return the expected result")
def op_fn_distributor(self, v, save_param):
result = AggOperation.operator_and_function[self.op](v)
val_to_save = create_value_list_to_save(save_param,
value=result,
op1=v)
return create_health_internal_tuple(result, val_to_save)
def vector_to_vector_no_match_operation(kv, op, a, save_param):
"""
Passed Vector values
[ {(name, tag) : value}, {(name, tag) : value} ...
Return health internal tuple
(True/False , [(key, value, formatting), (key, value, formatting), ...])
"""
res = {}
operand = get_value_from_health_internal_tuple(a)
if not kv:
raise HealthException("Insufficient input for NO_MATCH operation ")
try:
values = [
get_value_from_health_internal_tuple(get_kv(m)[1]) for m in kv
]
match_operand = _find_match_operand_value(operand, values)
result = False
val_to_save = []
for x in kv:
k, v = get_kv(x)
_val = get_value_from_health_internal_tuple(v)
if not op(_val, match_operand):
result |= True
val_to_save += create_value_list_to_save(save_param=None,
value=result,
op1=v)
if operand and operand == MAJORITY:
key = "Majority Value"
else:
key = "Expected Value"
val_to_save += create_value_list_to_save(save_param=save_param,
key=key,
value=match_operand)
res = create_health_internal_tuple(result, val_to_save)
except Exception:
res = create_health_internal_tuple(False, None)
return res
def _operate_each_key(self, arg1, arg2, save_param=None):
if isinstance(arg1, dict):
return None
try:
raw_arg1 = get_value_from_health_internal_tuple(arg1)
raw_arg2 = get_value_from_health_internal_tuple(arg2)
result = self.op(raw_arg1, raw_arg2)
val_to_save = create_value_list_to_save(save_param,
value=result,
op1=arg1,
op2=arg2)
return create_health_internal_tuple(result, val_to_save)
except Exception:
return create_health_internal_tuple(None, [])
def _operate_dicts(self,
arg1,
arg2,
comp_op=None,
check_common=True,
save_param=None):
if isinstance(arg1, dict):
if not isinstance(arg2, dict):
check_common = False
if check_common:
k1_set = set(arg1.keys())
k2_set = set(arg2.keys())
if not list(k1_set.intersection(k2_set)):
check_common = False
result_dict = {}
for _k in arg1:
if check_common:
if _k in arg2:
result_dict[_k] = self._operate_dicts(
arg1[_k],
arg2[_k],
comp_op=comp_op,
check_common=check_common,
save_param=save_param)
else:
result_dict[_k] = self._operate_dicts(
arg1[_k],
arg2,
comp_op=comp_op,
check_common=check_common,
save_param=save_param)
return result_dict
else:
result = self._operate_each_key(arg1, arg2, comp_op=comp_op)
val_to_save = create_value_list_to_save(save_param,
value=result,
op1=arg1)
return create_health_internal_tuple(result, val_to_save)
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
def vector_to_vector_sd_anomaly_operation(kv, op, a, save_param):
"""
Passed Vector values
[ {(name, tag) : value}, {(name, tag) : value} ...
Return health internal tuple
(True/False , [(key, value, formatting), (key, value, formatting), ...])
"""
res = {}
sd_multiplier = get_value_from_health_internal_tuple(a)
if not kv or not sd_multiplier:
raise HealthException("Insufficient input for SD_ANOMALY operation ")
try:
n = len(kv)
if n < 3:
no_anomaly = True
range_start = 0
range_end = 0
else:
values = [
get_value_from_health_internal_tuple(get_kv(m)[1]) for m in kv
]
no_anomaly = False
try:
# We should consider int and floats only
s = sum(values)
except Exception:
no_anomaly = True
if not no_anomaly:
mean = float(s) / float(n)
variance = 0
for v in values:
variance += pow((v - mean), 2)
variance = float(variance) / float(n)
sd = sqrt(variance)
range_start = mean - (sd_multiplier * sd)
range_end = mean + (sd_multiplier * sd)
result = False
val_to_save = []
for x in kv:
k, v = get_kv(x)
_val = get_value_from_health_internal_tuple(v)
if not no_anomaly and (float(_val) < float(range_start)
or float(_val) > float(range_end)):
result |= True
val_to_save += create_value_list_to_save(save_param=None,
value=result,
op1=v)
val_to_save += create_value_list_to_save(save_param=save_param,
value=result)
res = create_health_internal_tuple(result, val_to_save)
except Exception:
res = create_health_internal_tuple(False, None)
return res
def vector_to_vector_diff_operation(kv, op, a, save_param):
"""
Passed Vector values
[ {(name, tag) : value}, {(name, tag) : value} ...
Return boolean dictionary result
{ (name, tag) : True/False , (name, tag) : True/False, ... }
"""
res = {}
temp_res = {}
if not kv or not a:
raise HealthException("Insufficient input for Diff operation ")
exception_found = False
try:
for x, y in itertools.combinations(kv, 2):
k1, v1 = get_kv(x)
k2, v2 = get_kv(y)
_v1 = get_value_from_health_internal_tuple(v1)
_v2 = get_value_from_health_internal_tuple(v2)
if op(abs(_v1 - _v2), a):
try:
temp_res[make_key(k1)] |= True
except Exception:
temp_res[make_key(k1)] = True
try:
temp_res[make_key(k2)] |= True
except Exception:
temp_res[make_key(k2)] = True
else:
try:
temp_res[make_key(k1)] |= False
except Exception:
temp_res[make_key(k1)] = False
try:
temp_res[make_key(k2)] |= False
except Exception:
temp_res[make_key(k2)] = False
for i in kv:
k, v = get_kv(i)
val_to_save = create_value_list_to_save(
save_param, value=temp_res[make_key(k)], op1=v)
res[make_key(k)] = create_health_internal_tuple(
temp_res[make_key(k)], val_to_save)
except Exception:
exception_found = True
if exception_found:
for x in kv:
k, v = get_kv(x)
res[make_key(k)] = create_health_internal_tuple(None, None)
return res