def testCreateAllModelsHappyPath(self, requestsMock):
requestsMock.post.return_value = Mock(status_code=201,
text='[{"uid":"foo", "name":"bar"}]')
totalModels = len(
metric_utils.getMetricNamesFromConfig(
metric_utils.getMetricsConfiguration()))
metric_utils.createAllModels("localhost", "taurus")
self.assertEqual(requestsMock.post.call_count, totalModels)
for args, kwargs in requestsMock.post.call_args_list:
self.assertEqual(args[0], "https://localhost/_models")
self.assertIn("data", kwargs)
data = json.loads(kwargs["data"])
self.assertIsInstance(data, dict)
self.assertIn("datasource", data)
self.assertEquals(data["datasource"], "custom")
self.assertIn("metricSpec", data)
self.assertIn("metric", data["metricSpec"])
self.assertIn("resource", data["metricSpec"])
self.assertIn("userInfo", data["metricSpec"])
self.assertIsInstance(data["metricSpec"]["userInfo"], dict)
self.assertIn("metricType", data["metricSpec"]["userInfo"])
self.assertIn("metricTypeName", data["metricSpec"]["userInfo"])
self.assertIn("symbol", data["metricSpec"]["userInfo"])
self.assertIn("modelParams", data)
def testCreateAllModelsHappyPath(self, requestsMock):
requestsMock.post.return_value = Mock(
status_code=201, text='[{"uid":"foo", "name":"bar"}]')
totalModels = len(
metric_utils.getMetricNamesFromConfig(
metric_utils.getMetricsConfiguration()))
metric_utils.createAllModels("localhost", "taurus")
self.assertEqual(requestsMock.post.call_count, totalModels)
for args, kwargs in requestsMock.post.call_args_list:
self.assertEqual(args[0], "https://localhost/_models")
self.assertIn("data", kwargs)
data = json.loads(kwargs["data"])
self.assertIsInstance(data, dict)
self.assertIn("datasource", data)
self.assertEquals(data["datasource"], "custom")
self.assertIn("metricSpec", data)
self.assertIn("metric", data["metricSpec"])
self.assertIn("resource", data["metricSpec"])
self.assertIn("userInfo", data["metricSpec"])
self.assertIsInstance(data["metricSpec"]["userInfo"], dict)
self.assertIn("metricType", data["metricSpec"]["userInfo"])
self.assertIn("metricTypeName", data["metricSpec"]["userInfo"])
self.assertIn("symbol", data["metricSpec"]["userInfo"])
self.assertIn("modelParams", data)
def testCreateAllModels(self):
host = os.environ.get("TAURUS_HTM_SERVER", "127.0.0.1")
apikey = os.environ.get("TAURUS_APIKEY", "taurus")
# Resize metrics down to a much smaller random sample of the original
# so as to not overload the system under test. We need only to test that
# everything returned goes through the right channels.
metricsConfig = {
key: value
for (key, value) in random.sample(
metric_utils.getMetricsConfiguration().items(), 3)
}
expectedMetricNames = []
for resVal in metricsConfig.itervalues():
for metricName in resVal["metrics"]:
expectedMetricNames.append(metricName)
self.addCleanup(requests.delete,
"https://%s/_metrics/custom/%s" %
(host, metricName),
auth=(apikey, ""),
verify=False)
self.assertGreater(len(expectedMetricNames), 0)
with patch(
"taurus_metric_collectors.metric_utils.getMetricsConfiguration",
return_value=metricsConfig,
spec_set=metric_utils.getMetricsConfiguration):
createdModels = metric_utils.createAllModels(host, apikey)
self.assertEqual(len(createdModels), len(expectedMetricNames))
for model in createdModels:
remoteModel = metric_utils.getOneModel(host, apikey, model["uid"])
self.assertIn(remoteModel["name"], expectedMetricNames)
# Verify that the model is either in "ACTIVE" or the transient
# "PENDNG DATA" or "CREATE PENDING" states
self.assertIn(remoteModel["status"], [1, 2, 8])
def testCreateAllModels(self):
host = os.environ.get("TAURUS_HTM_SERVER", "127.0.0.1")
apikey = os.environ.get("TAURUS_APIKEY", "taurus")
# Resize metrics down to a much smaller random sample of the original
# so as to not overload the system under test. We need only to test that
# everything returned goes through the right channels.
metricsConfig = {
key:value
for (key, value)
in random.sample(metric_utils.getMetricsConfiguration().items(), 3)
}
expectedMetricNames = []
for resVal in metricsConfig.itervalues():
for metricName in resVal["metrics"]:
expectedMetricNames.append(metricName)
self.addCleanup(requests.delete,
"https://%s/_metrics/custom/%s" % (host, metricName),
auth=(apikey, ""),
verify=False)
self.assertGreater(len(expectedMetricNames), 0)
with patch("taurus_metric_collectors.metric_utils.getMetricsConfiguration",
return_value=metricsConfig,
spec_set=metric_utils.getMetricsConfiguration):
createdModels = metric_utils.createAllModels(host, apikey)
self.assertEqual(len(createdModels), len(expectedMetricNames))
for model in createdModels:
remoteModel = metric_utils.getOneModel(host, apikey, model["uid"])
self.assertIn(remoteModel["name"], expectedMetricNames)
# Verify that the model is either in "ACTIVE" or the transient
# "PENDNG DATA" or "CREATE PENDING" states
self.assertIn(remoteModel["status"], [1, 2, 8])
def testCreateAllModelsWithMetricNameFilter(self,
createCustomHtmModelMock):
allMetricNames = metric_utils.getMetricNamesFromConfig(
metric_utils.getMetricsConfiguration())
subsetOfMetricNames = allMetricNames[:(len(allMetricNames) + 1) // 2]
self.assertGreater(len(subsetOfMetricNames), 0)
createCustomHtmModelMock.side_effect = (lambda **kwargs: dict(
name=kwargs["metricName"], uid=kwargs["metricName"] * 2))
models = metric_utils.createAllModels(
host="host", apiKey="apikey", onlyMetricNames=subsetOfMetricNames)
self.assertEqual(createCustomHtmModelMock.call_count,
len(subsetOfMetricNames))
self.assertEqual(len(models), len(subsetOfMetricNames))
self.assertItemsEqual(subsetOfMetricNames,
[model["name"] for model in models])
def testCreateAllModelsWithMetricNameFilter(self, createCustomHtmModelMock):
allMetricNames = metric_utils.getMetricNamesFromConfig(
metric_utils.getMetricsConfiguration())
subsetOfMetricNames = allMetricNames[:(len(allMetricNames) + 1) // 2]
self.assertGreater(len(subsetOfMetricNames), 0)
createCustomHtmModelMock.side_effect = (
lambda **kwargs: dict(name=kwargs["metricName"],
uid=kwargs["metricName"] * 2))
models = metric_utils.createAllModels(host="host",
apiKey="apikey",
onlyMetricNames=subsetOfMetricNames)
self.assertEqual(createCustomHtmModelMock.call_count,
len(subsetOfMetricNames))
self.assertEqual(len(models), len(subsetOfMetricNames))
self.assertItemsEqual(subsetOfMetricNames,
[model["name"] for model in models])
def testGetMetricsConfiguration(self):
metrics = metric_utils.getMetricsConfiguration()
self.assertIsInstance(metrics, dict)
self.assertTrue(metrics)
for companyName, details in metrics.iteritems():
self.assertIsInstance(companyName, basestring)
self.assertIsInstance(details, dict)
self.assertTrue(details)
self.assertIn("metrics", details)
self.assertIn("stockExchange", details)
self.assertIn("symbol", details)
for metricName, metric in details["metrics"].iteritems():
self.assertIsInstance(metricName, basestring)
self.assertIsInstance(metric, dict)
self.assertTrue(metric)
self.assertIn("metricType", metric)
self.assertIn("metricTypeName", metric)
self.assertIn("modelParams", metric)
self.assertIn("provider", metric)
if metric["provider"] == "twitter":
self.assertIn("screenNames", metric)
elif metric["provider"] == "xignite":
self.assertIn("sampleKey", metric)
def _promoteReadyMetricsToModels():
"""Promote unmonitored company metrics that reached
_NUM_METRIC_DATA_ROWS_THRESHOLD to models
"""
# Build a map of all configured metric names to metric/model args for
# promoting to models
metricsConfig = metric_utils.getMetricsConfiguration()
readyMetricNames = _filterMetricsReadyForPromotion(
metricsConfig=metricsConfig,
allCustomMetrics=metric_utils.getAllCustomMetrics(
_TAURUS_HTM_SERVER,
_TAURUS_API_KEY))
if not readyMetricNames:
g_log.debug("There are no metrics that are ready for promotion at this time")
return
# Promote them to models
metric_utils.createAllModels(host=_TAURUS_HTM_SERVER,
apiKey=_TAURUS_API_KEY,
onlyMetricNames=readyMetricNames)
def testGetMetricsConfiguration(self):
metrics = metric_utils.getMetricsConfiguration()
self.assertIsInstance(metrics, dict)
self.assertTrue(metrics)
for companyName, details in metrics.iteritems():
self.assertIsInstance(companyName, basestring)
self.assertIsInstance(details, dict)
self.assertTrue(details)
self.assertIn("metrics", details)
self.assertIn("stockExchange", details)
self.assertIn("symbol", details)
for metricName, metric in details["metrics"].iteritems():
self.assertIsInstance(metricName, basestring)
self.assertIsInstance(metric, dict)
self.assertTrue(metric)
self.assertIn("metricType", metric)
self.assertIn("metricTypeName", metric)
self.assertIn("modelParams", metric)
self.assertIn("provider", metric)
if metric["provider"] == "twitter":
self.assertIn("screenNames", metric)
elif metric["provider"] == "xignite":
self.assertIn("sampleKey", metric)
def loadMetricSpecs():
""" Load metric specs for the xignite stock provider
:returns: a sequence of StockMetricSpec objects
Excerpt from metrics.json:
{
"Accenture": {
"stockExchange": "NYSE",
"symbol": "ACN",
"metrics": {
"XIGNITE.ACN.CLOSINGPRICE": {
"metricTypeName": "Stock Price",
"provider": "xignite",
"sampleKey": "Close"
},
"XIGNITE.ACN.VOLUME": {
"metricTypeName": "Stock Volume",
"provider": "xignite",
"sampleKey": "Volume"
},
. . .
}
},
. . .
}
"""
return tuple(
StockMetricSpec(
metricName=metricName,
symbol=resVal["symbol"].upper(),
stockExchange=resVal["stockExchange"],
sampleKey=metricVal["sampleKey"])
for resVal in getMetricsConfiguration().itervalues()
for metricName, metricVal in resVal["metrics"].iteritems()
if metricVal["provider"] == "xignite" and "sampleKey" in metricVal)
