def test_multiple_generators(self):
self.maxDiff = None
q = Query(
x - y
for x, y in Query((x.max for x in "metric1"), (x.min for x in "metric2")).by("tag1")
)
a = AST(q.generators, q.groupings)
actual = a.decompile()
expected = Group(
BinarySubtract(
LoadAttr(Metric("metric1"), Value("max")), LoadAttr(Metric("metric2"), Value("min"))
),
Value([["tag1"], "mean"]),
)
self.assertEqual(actual, expected)
def test_complex_case(self):
q = Query(
moving_average(x, size=5) + y.mean + z
for x, y, z in ("test", "test2", "test3")
if z.label == "something" and z.label == "another_one"
).by("host")
a = AST(q.generators, q.groupings)
actual = a.decompile()
expected = Group(
BinaryAdd(
BinaryAdd(
FuncCall(
Value("moving_average"),
FuncArgs(Value([Metric("test")]), Value({"size": 5})),
),
LoadAttr(Metric("test2"), Value("mean")),
),
Filter(
Filter(Metric("test3"), CompareEqual(Value("label"), Value("something"))),
CompareEqual(Value("label"), Value("another_one")),
),
),
Value([["host"], "mean"]),
)
self.assertEqual(actual, expected)
def test_query_with_string_variable_for_metric(self):
value = "test"
q = Query(x for x in value if x.label1 == "prod")
a = AST(q.generators, q.groupings)
actual = a.decompile()
expected = Filter(Metric("test"), CompareEqual(Value("label1"), Value("prod")))
self.assertEqual(actual, expected)
def test_query_with_varname_in_filter(self):
value = "prod"
q = Query(x for x in "test" if x.label1 == value)
a = AST(q.generators, q.groupings)
actual = a.decompile()
expected = Filter(Metric("test"), CompareEqual(Value("label1"), Value("prod")))
self.assertEqual(actual, expected)
def test_for_loop_filter_variables(self):
filters = ["filter1", "filter2", "filter3"]
for i in range(len(filters)):
q = Query(x for x in "test" if x.label1 == filters[i])
a = AST(q.generators, q.groupings)
actual = a.decompile()
expected = Filter(Metric("test"), CompareEqual(Value("label1"), Value(filters[i])))
self.assertEqual(actual, expected)
def test_aggregation_functions(self):
q = Query(mean(x) for x in "test" if x.label1 == "prod")
a = AST(q.generators, q.groupings)
actual = a.decompile()
expected = FuncCall(
Value("mean"),
FuncArgs(
Value([Filter(Metric("test"), CompareEqual(Value("label1"), Value("prod")))]),
Value({}),
),
)
self.assertEqual(actual, expected)
def test_iteration(self):
i = 0
q = Query(x.mean for x in "test")
for i, _ in enumerate(q):
pass
self.assertEqual(0, i)
def test_gather_period(self):
t1 = Query(x.mean for x in "test")[3600]
t1_timeindex = np.array(
[np.float64(t1.time[0] + x) for x in range(0, 3600, Query().DEFAULT_RESOLUTION)],
dtype=np.float64,
)
t2 = Query(x.mean for x in "test")[3600:1800]
t2_timeindex = np.array(
[np.float64(t2.time[0] + x) for x in range(0, 1800, Query().DEFAULT_RESOLUTION)],
dtype=np.float64,
)
t3 = Query(x.mean for x in "test")[3600:1800:300]
t3_timeindex = np.array(
[np.float64(t3.time[0] + x) for x in range(0, 1800, 300)], dtype=np.float64
)
t4 = Query(x.mean for x in "test").fetch()
t4_timeindex = np.array(
[np.float64(t4.time[0] + x) for x in range(0, 3600, Query().DEFAULT_RESOLUTION)],
dtype=np.float64,
)
t5 = Query(x.mean for x in "test")["1h"]
now = int(time.time())
t6 = Query(x.mean for x in "test").range(start=now - 3600, end=now - 1800, resolution=1)
self.assertTrue(np.array_equal(t1.time, t1_timeindex))
self.assertTrue(np.array_equal(t2.time, t2_timeindex))
self.assertTrue(np.array_equal(t3.time, t3_timeindex))
self.assertTrue(np.array_equal(t4.time, t4_timeindex))
self.assertTrue(np.array_equal(t5.time, t1_timeindex))
self.assertTrue(np.array_equal(t6.time, t2_timeindex))
with self.assertRaises(IndexError):
Query(x.mean for x in "test")["1hkbkgvk"]
with self.assertRaises(IndexError):
Query(x.mean for x in "test")[1.04884]
def test_query_for_iterator(self):
q = Query(x for x in Query(x for x in "test"))
a = AST(q.generators, q.groupings)
actual = a.decompile()
expected = Metric('test')
self.assertEqual(actual, expected)