def test_tags_limit_indirect(mock_post):
"""
Test for failure when too many tags are used indirectly (when combined with global tags)
"""
gtags_list = [
"gtk-%d:gtv-%d" % (i, i)
for i in range(apptuit_client.MAX_TAGS_LIMIT // 2 + 1)
]
global_tags = ",".join(gtags_list)
tags = {
'tagk-%d' % i: 'tagv-%d' % i
for i in range(apptuit_client.MAX_TAGS_LIMIT // 2 + 1)
}
timestamp = int(time.time())
with patch.dict(os.environ, {APPTUIT_PY_TAGS: global_tags}):
client = Apptuit(sanitize_mode=None, token="test_token")
point1 = DataPoint("metric1", {"tagk1": "tagv1"}, timestamp, 3.14)
point2 = DataPoint("metric1", tags, timestamp, 3.14)
with assert_raises(ValueError):
client.send([point1, point2])
with patch.dict(os.environ, {APPTUIT_PY_TAGS: global_tags}):
client = Apptuit(sanitize_mode=None, token="test_token")
series1 = TimeSeries('metric1', {"tagk1": "tagv1"})
series1.add_point(timestamp, 3.14)
series2 = TimeSeries('metric1', tags)
series2.add_point(timestamp, 3.14)
with assert_raises(ValueError):
client.send_timeseries([series1, series2])
def test_timeseries_payload():
"""
Test payload from timeseries list
"""
token = "asdashdsauh_8aeraerf"
client = __get_apptuit_client()
series_list = []
tags1 = {"tagk1": "tagv1", "tagk2": "tagv2"}
tags2 = {"tagk3": "tagv3"}
metric1_name = 'metric1'
metrics2_name = "metric2"
series1 = TimeSeries(metric1_name, tags1)
series2 = TimeSeries(metrics2_name, tags2)
timestamp = int(time.time())
val1 = 3.14
val2 = 42.0
series1.add_point(timestamp, val1)
series2.add_point(timestamp, val2)
series_list.append(series1)
series_list.append(series2)
payload, points_count = client._create_payload_from_timeseries(series_list)
assert_equals(points_count, 2)
expected_payload = [{
"metric": metric1_name,
"tags": tags1,
"timestamp": timestamp,
"value": val1
}, {
"metric": metrics2_name,
"tags": tags2,
"timestamp": timestamp,
"value": val2
}]
assert_equals(expected_payload, payload)
def test_timeseries_length():
"""
Test __len__ for TimeSeries
"""
series = TimeSeries("metric1", {"tagk1": "tagv1"})
for _ in range(10):
series.add_point(int(time.time()), 3.14)
assert_equals(len(series), 10)
def test_timeseries_payload_with_envtags():
"""
Test payload creation from timeseries list with global tags in env variable
"""
token = "asdashdsauh_8aeraerf"
global_tags = "gtagk1:gtagv1"
mock_environ = patch.dict(os.environ, {APPTUIT_PY_TAGS: global_tags})
mock_environ.start()
client = __get_apptuit_client()
series_list = []
metric1_name = 'metric1'
metric2_name = "metric2"
tags2 = {"tagk3": "tagv3"}
series1 = TimeSeries(metric1_name, tags=None)
series2 = TimeSeries(metric2_name, tags2)
timestamp = int(time.time())
val1 = 3.14
val2 = 42.0
series1.add_point(timestamp, val1)
series2.add_point(timestamp, val2)
series_list.append(series1)
series_list.append(series2)
payload, points_count = client._create_payload_from_timeseries(series_list)
mock_environ.stop()
assert_equals(points_count, 2)
expected_payload = [{
"metric": metric1_name,
"tags": {
"gtagk1": "gtagv1"
},
"timestamp": timestamp,
"value": val1
}, {
"metric": metric2_name,
"tags": {
"tagk3": "tagv3",
"gtagk1": "gtagv1"
},
"timestamp": timestamp,
"value": val2
}]
assert_equals(expected_payload, payload)
def test_tags_limit_direct(mock_post):
"""
Test for failure when too many tags are used for datapoints/series
"""
tags = {
'tagk-%d' % i: 'tagv-%d' % i
for i in range(apptuit_client.MAX_TAGS_LIMIT + 1)
}
timestamp = int(time.time())
client = Apptuit(sanitize_mode=None, token="test_token")
point1 = DataPoint("metric1", {"tagk1": "tagv1"}, timestamp, 3.14)
point2 = DataPoint("metric1", tags, timestamp, 3.14)
with assert_raises(ValueError):
client.send([point1, point2])
series1 = TimeSeries('metric1', {"tagk1": "tagv1"})
series1.add_point(timestamp, 3.14)
series2 = TimeSeries('metric1', tags)
series2.add_point(timestamp, 3.14)
with assert_raises(ValueError):
client.send_timeseries([series1, series2])
def test_send_timeseries_empty(mock_post):
"""
Test the send_timeseries API with an empty series list
"""
mock_post.return_value.status_code = 204
token = "asdashdsauh_8aeraerf"
client = __get_apptuit_client()
series_list = []
client.send_timeseries(series_list)
series1 = TimeSeries("metric", {"tagk1": "tagv1"})
client.send_timeseries([series1])
def test_send_timeseries(mock_post):
"""
Test the send_timeseries API
"""
mock_post.return_value.status_code = 204
token = "asdashdsauh_8aeraerf"
client = __get_apptuit_client()
series_list = []
tags1 = {"tagk1": "tagv1", "tagk2": "tagv2"}
tags2 = {"tagk3": "tagv3"}
metric1_name = 'metric1'
metrics2_name = "metric2"
series1 = TimeSeries(metric1_name, tags1)
series2 = TimeSeries(metrics2_name, tags2)
timestamp = int(time.time())
val1 = 3.14
val2 = 42.0
series1.add_point(timestamp, val1)
series2.add_point(timestamp, val2)
series_list.append(series1)
series_list.append(series2)
client.send_timeseries(series_list)
def test_timeseries_payload_negative():
"""
Negative tests for payload creation from timeseries list
"""
token = "asdashdsauh_8aeraerf"
client = __get_apptuit_client()
series_list = []
metric1_name = 'metric1'
metrics2_name = "metric2"
tags2 = {"tagk3": "tagv3"}
series1 = TimeSeries(metric1_name, tags=None)
series2 = TimeSeries(metrics2_name, tags2)
timestamp = int(time.time())
val1 = 3.14
val2 = 42.0
series1.add_point(timestamp, val1)
series2.add_point(timestamp, val2)
series_list.append(series1)
series_list.append(series2)
with assert_raises(ValueError):
payload, points_count = client._create_payload_from_timeseries(
series_list)
def test_timeseries_payload_with_globaltags():
"""
Test payload creation from timeseries list with global tags
"""
token = "asdashdsauh_8aeraerf"
global_tags = {"gtagk1": "gtagv1"}
client = Apptuit(sanitize_mode=None, token=token, global_tags=global_tags)
series_list = []
metric1_name = 'metric1'
metric2_name = "metric2"
tags2 = {"tagk3": "tagv3"}
series1 = TimeSeries(metric1_name, tags=None)
series2 = TimeSeries(metric2_name, tags2)
timestamp = int(time.time())
val1 = 3.14
val2 = 42.0
series1.add_point(timestamp, val1)
series2.add_point(timestamp, val2)
series_list.append(series1)
series_list.append(series2)
payload, points_count = client._create_payload_from_timeseries(series_list)
assert_equals(points_count, 2)
expected_payload = [{
"metric": metric1_name,
"tags": global_tags,
"timestamp": timestamp,
"value": val1
}, {
"metric": metric2_name,
"tags": {
"tagk3": "tagv3",
"gtagk1": "gtagv1"
},
"timestamp": timestamp,
"value": val2
}]
assert_equals(expected_payload, payload)