def __getitem__(self, index):
if index == 0:
self._zero_value["key"] = self._key
return self._zero_value
else:
if self._accuracy >= self._batch_duration:
logging.warning(
"Current accuracy {} is more or equal batch duration {}. You can get incorrect "
"results of analysis in this case ".format(
self._accuracy, self._batch_duration))
nano_timestamp, nano_delta, nano_accuracy = nanotime.timestamp(
time()), nanotime.seconds(
index * self._batch_duration), nanotime.seconds(
self._accuracy)
begin_time_interval = nano_timestamp - nano_delta - nano_accuracy
end_time_interval = nano_timestamp - nano_delta + nano_accuracy
influx_key = None
if self._key:
influx_key = dict(
map(lambda x, y: (x, y), self._key_fields_name, self._key))
historical_values = self._historical_data_repository_singleton.read(
self._measurement, begin_time_interval.nanoseconds(),
end_time_interval.nanoseconds(), influx_key)
if historical_values:
historical_values = sorted(historical_values,
key=lambda point: point["time"],
reverse=True)[0]
historical_values["key"] = self._key
return historical_values
else:
return {}
def test_construction(self):
def eq(time1, time2):
self.assertEqual(time1, time2)
self.assertEqual(int(time1), time2._ns)
self.assertEqual(time1._ns, int(time1))
self.assertEqual(time1._ns, int(time2))
self.assertEqual(time1._ns, time2._ns)
self.assertEqual(time1.nanoseconds(), time2.nanoseconds())
self.assertEqual(time1.microseconds(), time2.microseconds())
self.assertEqual(time1.milliseconds(), time2.milliseconds())
self.assertEqual(time1.seconds(), time2.seconds())
self.assertEqual(time1.minutes(), time2.minutes())
self.assertEqual(time1.hours(), time2.hours())
self.assertEqual(time1.days(), time2.days())
self.assertEqual(time1.timestamp(), time2.timestamp())
self.assertEqual(time1.datetime(), time2.datetime())
self.assertEqual(time1.unixtime(), time2.unixtime())
#self.assertEqual(time1, time1.unixtime())
#self.assertEqual(time1, time2.unixtime())
#self.assertEqual(time1, time1.timestamp())
#self.assertEqual(time1, time2.timestamp())
#self.assertEqual(time2, time1.unixtime())
#self.assertEqual(time2, time2.unixtime())
#self.assertEqual(time2, time1.timestamp())
#self.assertEqual(time2, time2.timestamp())
def close(x, y, epsilon=1e-6):
return abs(x - y) < epsilon
for i in range(0, 50):
# basic
eq(nanotime.seconds(1), nanotime.nanoseconds(1e9))
eq(nanotime.seconds(1), nanotime.microseconds(1e6))
eq(nanotime.seconds(1), nanotime.milliseconds(1e3))
eq(nanotime.seconds(1), nanotime.seconds(1))
eq(nanotime.seconds(1), nanotime.minutes(1.0/60))
eq(nanotime.seconds(1), nanotime.hours(1.0/3600))
eq(nanotime.seconds(1), nanotime.days(1.0/(3600 * 24)))
nt1 = nanotime.now()
self.assertTrue(nanotime.now() > nt1)
# timestamp
ts1 = time.time()
ts2 = nanotime.timestamp(ts1).timestamp()
eq(nanotime.timestamp(ts1), nanotime.timestamp(ts1))
self.assertTrue(close(ts2, ts1))
self.assertEqual(nanotime.timestamp(ts1), ts1)
# datetime
dt1 = datetime.datetime.now()
dt2 = nanotime.datetime(dt1).datetime()
eq(nanotime.datetime(dt1), nanotime.datetime(dt1))
self.assertTrue(close(dt1, dt2, datetime.timedelta(microseconds=1)))
def analysis_record(input_tuple_value, data_structure, time_delta, accuracy, rule, alert_sender_singleton,
historical_data_repository_singleton, measurement, key_fields_name=None, key=None):
"""
Checks data for deviations
:param key: This is the key to the data aggregation
:param input_tuple_value: input data to check
:return:
"""
nano_timestamp, nano_delta, nano_accuracy = nanotime.timestamp(time()), nanotime.seconds(
time_delta), nanotime.seconds(accuracy)
begin_time_interval = nano_timestamp - nano_delta - nano_accuracy
end_time_interval = nano_timestamp - nano_delta + nano_accuracy
# create a dictionary with a key equal to the name of field from rule and a value equal to index in the
# input tuple nfti (name field to index)
name_to_index = dict(map(lambda x: (x, data_structure[x]), rule.keys()))
# call for real historical data
influx_key = None
if key:
influx_key = dict(map(lambda x, y: (x, y), key_fields_name, key))
historical_values = historical_data_repository_singleton.read(measurement, begin_time_interval.nanoseconds(),
end_time_interval.nanoseconds(), influx_key)
if historical_values:
historical_values = sorted(historical_values, key=lambda point: point["time"])
# we analyse only first value from data, because next values will analysed in next moments
for field in rule.keys():
lower_bound = historical_values[0][field] * (1 - float(rule[field]) / 100)
upper_bound = historical_values[0][field] * (1 + float(rule[field]) / 100)
current_value = input_tuple_value[name_to_index[field]]
if (current_value < lower_bound) or (current_value > upper_bound):
alert_sender_singleton.send_message(timestamp=time(),
param={"key": key,
"field": field,
"lower_bound": lower_bound,
"upper_bound": upper_bound,
"value": current_value})
def test_other(self):
test = self.subtest_attribute(TimeAttribute)
test(5, nanotime.nanotime(5))
test(5.2, nanotime.nanotime(5.2))
self.assertRaises(TypeError, test, self)
self.assertRaises(TypeError, test, '5')
self.assertRaises(TypeError, test, '5a')
test(nanotime.seconds(1000))
test(None)
test = self.subtest_attribute(DateTimeAttribute)
self.assertRaises(TypeError, test, 5)
self.assertRaises(TypeError, test, 5.2)
self.assertRaises(TypeError, test, self)
self.assertRaises(ValueError, test, '5')
self.assertRaises(ValueError, test, '5a')
test(datetime.datetime.now())
test(None)
d = datetime.datetime(2011, 7, 12, 13, 19, 29, 151455)
test(str(d), d)
d = datetime.datetime(2011, 7, 12, 13, 19, 29, 0)
test(str(d), d)
test = self.subtest_attribute(ListAttribute)
self.assertRaises(TypeError, test, 5, ['5'])
self.assertRaises(TypeError, test, 5.2, ['5.2'])
self.assertRaises(TypeError, test, self, [str(self)])
test('5', ['5'])
test('5a', ['5', 'a'])
test([])
test(['fdgfds', 'gfdsgfds', 'gfdsgfds', 'gfdsgfds'])
test([4214, 321, 43, 21], ['4214', '321', '43', '21'])
test(xrange(0, 10), map(str, range(0, 10)))
test(None)
test = self.subtest_attribute(DictAttribute)
self.assertRaises(TypeError, test, 5)
self.assertRaises(TypeError, test, 5.2)
self.assertRaises(TypeError, test, self)
self.assertRaises(TypeError, test, '5')
self.assertRaises(TypeError, test, '5a')
test({})
test({'a':'b'})
test({'1213':3214}, {'1213':'3214'})
test({1213:3214}, {'1213':'3214'})
test(None)
def test_other(self):
test = self.subtest_attribute(TimeAttribute)
test(5, nanotime.nanotime(5))
test(5.2, nanotime.nanotime(5.2))
self.assertRaises(TypeError, test, self)
self.assertRaises(TypeError, test, "5")
self.assertRaises(TypeError, test, "5a")
test(nanotime.seconds(1000))
test(None)
test = self.subtest_attribute(DateTimeAttribute)
self.assertRaises(TypeError, test, 5)
self.assertRaises(TypeError, test, 5.2)
self.assertRaises(TypeError, test, self)
self.assertRaises(ValueError, test, "5")
self.assertRaises(ValueError, test, "5a")
test(datetime.datetime.now())
test(None)
d = datetime.datetime(2011, 7, 12, 13, 19, 29, 151455)
test(str(d), d)
d = datetime.datetime(2011, 7, 12, 13, 19, 29, 0)
test(str(d), d)
test = self.subtest_attribute(ListAttribute)
self.assertRaises(TypeError, test, 5, ["5"])
self.assertRaises(TypeError, test, 5.2, ["5.2"])
self.assertRaises(TypeError, test, self, [str(self)])
test("5", ["5"])
test("5a", ["5", "a"])
test([])
test(["fdgfds", "gfdsgfds", "gfdsgfds", "gfdsgfds"])
test([4214, 321, 43, 21], ["4214", "321", "43", "21"])
test(xrange(0, 10), map(str, range(0, 10)))
test(None)
test = self.subtest_attribute(DictAttribute)
self.assertRaises(TypeError, test, 5)
self.assertRaises(TypeError, test, 5.2)
self.assertRaises(TypeError, test, self)
self.assertRaises(TypeError, test, "5")
self.assertRaises(TypeError, test, "5a")
test({})
test({"a": "b"})
test({"1213": 3214}, {"1213": "3214"})
test({1213: 3214}, {"1213": "3214"})
test(None)
def __subtest_arithmetic(self, start, extra):
eq = self.assertEqual
start = float(start)
extra = float(extra)
t1 = nanotime.seconds(start)
eq(nanotime.seconds(start + extra), t1 + nanotime.nanotime(extra * 1e9))
eq(nanotime.seconds(start + extra), t1 + nanotime.seconds(extra))
eq(nanotime.seconds(start - extra), t1 - nanotime.nanotime(extra * 1e9))
eq(nanotime.seconds(start - extra), t1 - nanotime.seconds(extra))
eq(nanotime.seconds(start * extra), t1 * nanotime.nanotime(extra))
eq(nanotime.seconds(start * extra), t1 * nanotime.nanoseconds(extra))
eq(nanotime.seconds(start / extra), t1 / nanotime.nanotime(extra))
eq(nanotime.seconds(start / extra), t1 / nanotime.nanoseconds(extra))
self.assertTrue(nanotime.seconds(start + extra) > t1)
self.assertTrue(nanotime.seconds(start - extra) < t1)
t2 = nanotime.seconds(start + extra)
self.assertTrue(t2 > nanotime.nanotime(0))
self.assertTrue(nanotime.nanotime(0) < t2)
def __subtest_arithmetic(self, start, extra):
eq = self.assertEqual
start = float(start)
extra = float(extra)
t1 = nanotime.seconds(start)
eq(nanotime.seconds(start + extra), t1 + nanotime.nanotime(extra * 1e9))
eq(nanotime.seconds(start + extra), t1 + nanotime.seconds(extra))
eq(nanotime.seconds(start - extra), t1 - nanotime.nanotime(extra * 1e9))
eq(nanotime.seconds(start - extra), t1 - nanotime.seconds(extra))
eq(nanotime.seconds(start * extra), t1 * nanotime.nanotime(extra))
eq(nanotime.seconds(start * extra), t1 * nanotime.nanoseconds(extra))
eq(nanotime.seconds(start / extra), t1 / nanotime.nanotime(extra))
eq(nanotime.seconds(start / extra), t1 / nanotime.nanoseconds(extra))
self.assertTrue(nanotime.seconds(start + extra) > t1)
self.assertTrue(nanotime.seconds(start - extra) < t1)
t2 = nanotime.seconds(start + extra)
self.assertTrue(t2 > nanotime.nanotime(0))
self.assertTrue(nanotime.nanotime(0) < t2)
