def setUp(self):
self.api = API()
logging.basicConfig(level=logging.DEBUG)
self.name = 'TEST_' + TestUtils.random_string(6)
self.display_name = 'green'
self.display_name_short = 'blue'
self.description = 'magenta'
self.default_aggregate = aggregates.SUM
self.default_resolution = 60000
self.unit = units.DURATION
self.type = 'FOOBAR'
self.is_disabled = False
self.metric = Metric(name=self.name,
display_name=self.display_name,
display_name_short=self.display_name_short,
description=self.description,
default_aggregate=self.default_aggregate,
default_resolution=self.default_resolution,
unit=self.unit,
_type=self.type,
is_disabled=self.is_disabled)
self.api.metric_create_batch([self.metric])
logging.basicConfig(level=logging.INFO)
def test_metric_list_to_json(self):
l = [Metric(name="ONE"), Metric(name="TWO")]
self.maxDiff = None
s = [
'[{"defaultAggregate": "avg", "defaultResolutionMS": 1000, "description": "", "displayName": "ONE",',
' "displayNameShort": "ONE", "isDisabled": false, "name": "ONE",',
' "unit": "number"},',
' {"defaultAggregate": "avg", "defaultResolutionMS": 1000, "description": "", "displayName": "TWO",',
' "displayNameShort": "TWO", "isDisabled": false, "name": "TWO",',
' "unit": "number"}]'
]
expected = "".join(s)
data = json.dumps(l,
sort_keys=True,
default=tspapi.metric.serialize_instance)
self.assertEqual(expected, data)
def test_minimal_constructor(self):
name = 'FOO'
m = Metric(name=name)
self.assertEqual(name, m.name)
self.assertEqual(name, m.display_name)
self.assertEqual(name, m.display_name_short)
self.assertEqual('', m.description)
self.assertEqual(m.default_aggregate, aggregates.AVG)
self.assertEqual(m.default_resolution, 1000)
self.assertEqual(m.unit, units.NUMBER)
self.assertIsNone(m.type)
def test_metric_instance_empty_name(self):
"""
Ensure that creating a metric with an empty name throws a
ValueError exception
:return:
"""
try:
m = Metric()
print(m)
self.assertTrue(False)
except ValueError:
pass
def test_metric_to_json(self):
m = Metric(name="TEST")
data = json.dumps(m,
sort_keys=True,
default=tspapi.metric.serialize_instance)
s = [
'{"defaultAggregate": "avg", "defaultResolutionMS": 1000, "description": "",',
' "displayName": "TEST", "displayNameShort": "TEST", "isDisabled": false, "name": "TEST",',
' "unit": "number"}'
]
expected = "".join(s)
self.assertEqual(expected, data)
def test_metric_create_one_batch(self):
name = 'TEST_CREATE_BATCH_ONE_FOOBAR' + TestUtils.random_string(6)
display_name = "BATCH" + TestUtils.random_string(6)
display_name_short = "BATCH" + TestUtils.random_string(3)
description = TestUtils.random_string(32)
default_aggregate = aggregates.SUM
default_resolution = random.randrange(1000, 60000)
unit = units.PERCENT
_type = 'FOO'
is_disabled = True
metric1 = Metric(name=name,
display_name=display_name,
display_name_short=display_name_short,
description=description,
default_aggregate=default_aggregate,
default_resolution=default_resolution,
unit=unit,
_type=_type,
is_disabled=is_disabled)
metrics = self.api.metric_create_batch([metric1])
self.assertEqual(len(metrics), 1)
m = metrics[0]
self.assertEqual(name, m.name)
self.assertEqual(display_name, m.display_name)
self.assertEqual(display_name_short, m.display_name_short)
self.assertEqual(description, m.description)
self.assertEqual(default_aggregate.upper(), m.default_aggregate)
self.assertEqual(default_resolution, m.default_resolution)
self.assertEqual(unit, m.unit)
self.assertEqual(_type, m.type)
self.assertEqual(is_disabled, m.is_disabled)
self.api.metric_delete(name)
def test_metric_create_multiple_batch(self):
name1 = 'TEST_CREATE_BATCH_ONE_FOOBAR' + TestUtils.random_string(6)
name2 = 'TEST_CREATE_BATCH_TWO_FOOBAR' + TestUtils.random_string(6)
name3 = 'TEST_CREATE_BATCH_THREE_FOOBAR' + TestUtils.random_string(6)
name4 = 'TEST_CREATE_BATCH_FOUR_FOOBAR' + TestUtils.random_string(6)
display_name1 = 'TEST_DISPLAY_NAME' + TestUtils.random_string(6)
display_name2 = 'TEST_DISPLAY_NAME' + TestUtils.random_string(6)
display_name3 = 'TEST_DISPLAY_NAME' + TestUtils.random_string(6)
display_name4 = 'TEST_DISPLAY_NAME' + TestUtils.random_string(6)
display_name_short1 = 'TEST_SHORT' + TestUtils.random_string(10)
display_name_short2 = 'TEST_SHORT' + TestUtils.random_string(10)
display_name_short3 = 'TEST_SHORT' + TestUtils.random_string(10)
display_name_short4 = 'TEST_SHORT' + TestUtils.random_string(10)
description1 = TestUtils.random_string(32)
description2 = TestUtils.random_string(32)
description3 = TestUtils.random_string(32)
description4 = TestUtils.random_string(32)
default_aggregate1 = aggregates.AVG
default_aggregate2 = aggregates.MIN
default_aggregate3 = aggregates.MAX
default_aggregate4 = aggregates.SUM
default_resolution1 = random.randrange(1000, 60000)
default_resolution2 = random.randrange(1000, 60000)
default_resolution3 = random.randrange(1000, 60000)
default_resolution4 = random.randrange(1000, 60000)
unit1 = units.BYTECOUNT
unit2 = units.DURATION
unit3 = units.NUMBER
unit4 = units.PERCENT
is_disabled1 = True
is_disabled2 = False
is_disabled3 = True
is_disabled4 = False
_type1 = TestUtils.random_string(6)
_type2 = TestUtils.random_string(6)
_type3 = TestUtils.random_string(6)
_type4 = TestUtils.random_string(6)
new_metrics = [
Metric(name=name1,
display_name=display_name1,
display_name_short=display_name_short1,
description=description1,
default_aggregate=default_aggregate1,
default_resolution=default_resolution1,
unit=unit1,
_type=_type1,
is_disabled=is_disabled1),
Metric(name=name2,
display_name=display_name2,
display_name_short=display_name_short2,
description=description2,
default_aggregate=default_aggregate2,
default_resolution=default_resolution2,
unit=unit2,
_type=_type2,
is_disabled=is_disabled2),
Metric(name=name3,
display_name=display_name3,
display_name_short=display_name_short3,
description=description3,
default_aggregate=default_aggregate3,
default_resolution=default_resolution3,
unit=unit3,
_type=_type3,
is_disabled=is_disabled3),
Metric(name=name4,
display_name=display_name4,
display_name_short=display_name_short4,
description=description4,
default_aggregate=default_aggregate4,
default_resolution=default_resolution4,
unit=unit4,
_type=_type4,
is_disabled=is_disabled4)
]
metrics = self.api.metric_create_batch(new_metrics)
self.assertEqual(4, len(metrics))
