def test_predict_response_date(self):
"""Test that predict() returns expected date range."""
dh = DateHelper()
expected = []
for n in range(0, 10):
expected.append({
"usage_start":
dh.n_days_ago(dh.today, 10 - n).date(),
"total_cost":
5,
"infrastructure_cost":
3,
"supplementary_cost":
2,
})
mock_qset = MockQuerySet(expected)
mocked_table = Mock()
mocked_table.objects.filter.return_value.order_by.return_value.values.return_value.annotate.return_value = ( # noqa: E501
mock_qset)
mocked_table.len = mock_qset.len
params = self.mocked_query_params("?", AWSCostForecastView)
instance = AWSForecast(params)
instance.cost_summary_table = mocked_table
results = instance.predict()
for item in results:
self.assertIsInstance(item.get("date"), date)
self.assertLessEqual(item.get("date"), dh.this_month_end.date())
def test_predict_flat(self):
"""Test that predict() returns expected values for flat costs."""
dh = DateHelper()
expected = []
for n in range(0, 10):
expected.append({
"usage_start":
(dh.this_month_start + timedelta(days=n)).date(),
"total_cost":
5 + (0.01 * n),
"infrastructure_cost":
3 + (0.01 * n),
"supplementary_cost":
2 + (0.01 * n),
})
mock_qset = MockQuerySet(expected)
mocked_table = Mock()
mocked_table.objects.filter.return_value.order_by.return_value.values.return_value.annotate.return_value = ( # noqa: E501
mock_qset)
mocked_table.len = mock_qset.len
params = self.mocked_query_params("?", AWSCostForecastView)
instance = AWSForecast(params)
instance.cost_summary_table = mocked_table
results = instance.predict()
for result in results:
for val in result.get("values", []):
with self.subTest(values=val):
self.assertIsInstance(val.get("date"), date)
for item, cost, delta in [
(val.get("cost"), 5, 1),
(val.get("infrastructure"), 3, 1),
(val.get("supplementary"), 2, 1),
]:
with self.subTest(cost=cost, delta=delta, item=item):
self.assertAlmostEqual(float(
item.get("total").get("value")),
cost,
delta=delta)
self.assertAlmostEqual(float(
item.get("confidence_max").get("value")),
cost,
delta=delta)
self.assertAlmostEqual(float(
item.get("confidence_min").get("value")),
cost,
delta=delta)
self.assertGreater(
float(item.get("rsquared").get("value")), 0)
for pval in item.get("pvalues").get("value"):
self.assertGreaterEqual(float(pval), 0)
def test_predict_flat(self):
"""Test that predict() returns expected values for flat costs."""
dh = DateHelper()
expected = []
for n in range(0, 10):
expected.append({
"usage_start":
dh.n_days_ago(dh.today, 10 - n).date(),
"total_cost":
5,
"infrastructure_cost":
3,
"supplementary_cost":
2,
})
mock_qset = MockQuerySet(expected)
mocked_table = Mock()
mocked_table.objects.filter.return_value.order_by.return_value.values.return_value.annotate.return_value = ( # noqa: E501
mock_qset)
mocked_table.len = mock_qset.len
params = self.mocked_query_params("?", AWSCostForecastView)
instance = AWSForecast(params)
instance.cost_summary_table = mocked_table
results = instance.predict()
for result in results:
for val in result.get("values", []):
self.assertIsInstance(val.get("date"), date)
for item, cost in [
(val.get("cost"), 5),
(val.get("infrastructure"), 3),
(val.get("supplementary"), 2),
]:
self.assertAlmostEqual(float(
item.get("total").get("value")),
cost,
delta=0.0001)
self.assertAlmostEqual(float(
item.get("confidence_max").get("value")),
cost,
delta=0.0001)
self.assertAlmostEqual(float(
item.get("confidence_min").get("value")),
cost,
delta=0.0001)
self.assertAlmostEqual(float(
item.get("rsquared").get("value")),
1,
delta=0.0001)
self.assertGreaterEqual(
float(item.get("pvalues").get("value")), 0)
def test_predict_few_values(self):
"""Test that predict() behaves well with a limited data set."""
dh = DateHelper()
num_elements = [AWSForecast.MINIMUM - 1, AWSForecast.MINIMUM, AWSForecast.MINIMUM + 1]
for number in num_elements:
with self.subTest(num_elements=number):
expected = []
for n in range(0, number):
# the test data needs to include some jitter to avoid
# division-by-zero in the underlying dot-product maths.
expected.append(
{
"usage_start": dh.n_days_ago(dh.today, 10 - n).date(),
"total_cost": 5 + (0.01 * n),
"infrastructure_cost": 3 + (0.01 * n),
"supplementary_cost": 2 + (0.01 * n),
}
)
mock_qset = MockQuerySet(expected)
mocked_table = Mock()
mocked_table.objects.filter.return_value.order_by.return_value.values.return_value.annotate.return_value = ( # noqa: E501
mock_qset
)
mocked_table.len = mock_qset.len
params = self.mocked_query_params("?", AWSCostForecastView)
instance = AWSForecast(params)
instance.cost_summary_table = mocked_table
if number < AWSForecast.MINIMUM:
# forecasting isn't useful with less than the minimum number of data points.
with self.assertLogs(logger="forecast.forecast", level=logging.WARNING):
results = instance.predict()
self.assertEqual(results, [])
else:
results = instance.predict()
self.assertNotEqual(results, [])
for result in results:
for val in result.get("values", []):
self.assertIsInstance(val.get("date"), date)
item = val.get("cost")
self.assertGreaterEqual(float(item.get("total").get("value")), 0)
self.assertGreaterEqual(float(item.get("confidence_max").get("value")), 0)
self.assertGreaterEqual(float(item.get("confidence_min").get("value")), 0)
self.assertGreaterEqual(float(item.get("rsquared").get("value")), 0)
for pval in item.get("pvalues").get("value"):
self.assertGreaterEqual(float(pval), 0)
# test that the results always stop at the end of the month.
self.assertEqual(results[-1].get("date"), dh.this_month_end.date())
def test_predict_increasing(self):
"""Test that predict() returns expected values for increasing costs."""
dh = DateHelper()
expected = []
for n in range(0, 10):
# the test data needs to include some jitter to avoid
# division-by-zero in the underlying dot-product maths.
expected.append({
"usage_start":
dh.n_days_ago(dh.today, 10 - n).date(),
"total_cost":
5 + random.random(),
"infrastructure_cost":
3 + random.random(),
"supplementary_cost":
2 + random.random(),
})
mock_qset = MockQuerySet(expected)
mocked_table = Mock()
mocked_table.objects.filter.return_value.order_by.return_value.values.return_value.annotate.return_value = ( # noqa: E501
mock_qset)
mocked_table.len = mock_qset.len
params = self.mocked_query_params("?", AWSCostForecastView)
instance = AWSForecast(params)
instance.cost_summary_table = mocked_table
results = instance.predict()
for result in results:
for val in result.get("values", []):
self.assertIsInstance(val.get("date"), date)
item = val.get("cost")
self.assertGreaterEqual(float(item.get("total").get("value")),
0)
self.assertGreaterEqual(
float(item.get("confidence_max").get("value")), 0)
self.assertGreaterEqual(
float(item.get("confidence_min").get("value")), 0)
self.assertGreaterEqual(
float(item.get("rsquared").get("value")), 0)
for pval in item.get("pvalues").get("value"):
self.assertGreaterEqual(float(pval), 0)
def test_predict_few_values(self):
"""Test that predict() behaves well with a limited data set."""
dh = DateHelper()
num_elements = [1, 2, 3, 4, 5]
for number in num_elements:
with self.subTest(num_elements=number):
expected = []
for n in range(0, number):
expected.append({
"usage_start":
dh.n_days_ago(dh.today, 10 - n).date(),
"total_cost":
5,
"infrastructure_cost":
3,
"supplementary_cost":
2,
})
mock_qset = MockQuerySet(expected)
mocked_table = Mock()
mocked_table.objects.filter.return_value.order_by.return_value.values.return_value.annotate.return_value = ( # noqa: E501
mock_qset)
mocked_table.len = mock_qset.len
params = self.mocked_query_params("?", AWSCostForecastView)
instance = AWSForecast(params)
instance.cost_summary_table = mocked_table
if number == 1:
# forecasting isn't possible with only 1 data point.
with self.assertLogs(logger="forecast.forecast",
level=logging.WARNING):
results = instance.predict()
self.assertEqual(results, [])
else:
with self.assertLogs(logger="forecast.forecast",
level=logging.WARNING):
results = instance.predict()
for result in results:
for val in result.get("values", []):
self.assertIsInstance(val.get("date"), date)
item = val.get("cost")
self.assertGreaterEqual(
float(item.get("total").get("value")), 0)
self.assertGreaterEqual(
float(
item.get("confidence_max").get(
"value")), 0)
self.assertGreaterEqual(
float(
item.get("confidence_min").get(
"value")), 0)
self.assertGreaterEqual(
float(item.get("rsquared").get("value")),
0)
self.assertGreaterEqual(
float(item.get("pvalues").get("value")), 0)
# test that the results always stop at the end of the month.
self.assertEqual(results[-1].get("date"),
dh.this_month_end.date())