def test_single_keys(self):
r = Results()
r.add_result(18, threshold=15)
self.assertEqual(
r.get_data(),
[{'data': 18, 'severity': self.severity, 'threshold': 15}]
)
def test_multiple_single(self):
r = Results()
r.add_result(18)
r.add_result(42)
self.assertEqual(r.get_data(),
[{'data': 18, 'severity': self.severity},
{'data': 42, 'severity': self.severity}])
def test_single(self):
r = Results()
r.add_result(18)
self.assertEqual(r.get_data(), [{
'data': 18,
'severity': self.severity
}])
def test_sequence_multiple_keys(self):
r = Results()
r.add_results([18, 42], threshold=[15, 40])
self.assertEqual(
r.get_data(),
[{'data': 18, 'severity': self.severity, 'threshold': 15},
{'data': 42, 'severity': self.severity, 'threshold': 40}]
)
def test_single_keys(self):
r = Results()
r.add_result(18, threshold=15)
self.assertEqual(r.get_data(), [{
'data': 18,
'severity': self.severity,
'threshold': 15
}])
def test_sequence_multiple_invalid_keys(self):
r = Results()
with self.assertRaises(ValueError) as cm:
r.add_results([88, 11], threshold=[15])
self.assertTrue('Length' in cm.exception.args[0])
with self.assertRaises(ValueError) as cm:
r.add_results([88, 11], threshold=[15, 22, 33])
self.assertTrue('Length' in cm.exception.args[0])
def test_multiple_sequence(self):
r = Results()
r.add_results([18, 42])
r.add_results([88, 11])
self.assertEqual(r.get_data(),
[{'data': 18, 'severity': self.severity},
{'data': 42, 'severity': self.severity},
{'data': 88, 'severity': self.severity},
{'data': 11, 'severity': self.severity}])
def test_sequence(self):
r = Results()
r.add_results([18, 42])
self.assertEqual(r.get_data(), [{
'data': 18,
'severity': self.severity
}, {
'data': 42,
'severity': self.severity
}])
def test_multiple_sequence_single_keys(self):
r = Results()
r.add_results([18, 42], threshold=15)
r.add_results([88, 11], threshold=15)
self.assertEqual(
r.get_data(),
[{'data': 18, 'severity': self.severity, 'threshold': 15},
{'data': 42, 'severity': self.severity, 'threshold': 15},
{'data': 88, 'severity': self.severity, 'threshold': 15},
{'data': 11, 'severity': self.severity, 'threshold': 15}]
)
def test_sequence_multiple_keys(self):
r = Results()
r.add_results([18, 42], threshold=[15, 40])
self.assertEqual(r.get_data(), [{
'data': 18,
'severity': self.severity,
'threshold': 15
}, {
'data': 42,
'severity': self.severity,
'threshold': 40
}])
def test_dataframe(self):
# create 8x4 dataframe
dates = pandas.date_range('1/1/2000', periods=8)
df = pandas.DataFrame(numpy.random.randn(8, 4), index=dates,
columns=['A', 'B', 'C', 'D'])
data = df.to_dict('records')
result = [dict(data=x, severity=10, threshold=90) for x in data]
r = Results()
r.add_results(df, severity=10, threshold=90)
self.assertEqual(r.get_data(), result)
def test_dataframe(self):
# create 8x4 dataframe
dates = pandas.date_range('1/1/2000', periods=8)
df = pandas.DataFrame(numpy.random.randn(8, 4),
index=dates,
columns=['A', 'B', 'C', 'D'])
data = df.to_dict('records')
result = [dict(data=x, severity=10, threshold=90) for x in data]
r = Results()
r.add_results(df, severity=10, threshold=90)
self.assertEqual(r.get_data(), result)
def local_spike(df, context, params):
"""Find conditions where local spikes occur.
Can operate against timeseries or other data. Optional params:
`column`: specify column to calculate against, defaults to first non-time
column.
`std`: number of standard deviations to consider as a spike,
defaults to 2
"""
column = params.get('column', None)
if column is None:
if 'time' in df:
column = df.drop('time', axis=1).columns[0]
else:
column = df.columns[0]
std = params.get('std', 2)
# extract the column as a Series
s = df[column]
delta = s.std() * std
# create a boolean index where the values exceed the delta threshold
idx = abs(s - s.mean()) > delta
# then use this to create a new dataframe
results = df[idx]
# as an example, dynamically determine severity based on size of results
severity = len(results) * 10 if len(results) < 10 else 99
return Results().add_results(results, severity=severity)
def test_multiple_sequence_invalid_keys(self):
r = Results()
r.add_results([18, 42], threshold=15)
with self.assertRaises(ValueError) as cm:
r.add_results([88, 11])
self.assertTrue('Missing data keys' in cm.exception.args[0])
with self.assertRaises(ValueError) as cm:
r.add_results([88, 11], foo=12)
self.assertTrue('Invalid keys' in cm.exception.args[0])
def simple_trigger(df, context, params):
"""Find any values in column that exceed a given value.
Required params:
`column`: specify column to evaluate
`value`: threshold value, rows which exceed this value will
be returned from the trigger
"""
return Results().add_result((df[params['column']] > params['value']).any(),
severity=5)
def test_multiple_sequence_single_keys(self):
r = Results()
r.add_results([18, 42], threshold=15)
r.add_results([88, 11], threshold=15)
self.assertEqual(r.get_data(), [{
'data': 18,
'severity': self.severity,
'threshold': 15
}, {
'data': 42,
'severity': self.severity,
'threshold': 15
}, {
'data': 88,
'severity': self.severity,
'threshold': 15
}, {
'data': 11,
'severity': self.severity,
'threshold': 15
}])
def test_multiple_sequence_invalid_keys(self):
r = Results()
r.add_results([18, 42], threshold=15)
with self.assertRaises(ValueError) as cm:
r.add_results([88, 11])
self.assertTrue('Missing data keys' in cm.exception.args[0])
with self.assertRaises(ValueError) as cm:
r.add_results([88, 11], foo=12)
self.assertTrue('Invalid keys' in cm.exception.args[0])
def test_sequence_multiple_invalid_keys(self):
r = Results()
with self.assertRaises(ValueError) as cm:
r.add_results([88, 11], threshold=[15])
self.assertTrue('Length' in cm.exception.args[0])
with self.assertRaises(ValueError) as cm:
r.add_results([88, 11], threshold=[15, 22, 33])
self.assertTrue('Length' in cm.exception.args[0])
def test_simple(self):
r = Results()
self.assertEqual(r.get_data(), [])
def test_single_oneliner(self):
r = Results().add_result(18)
self.assertEqual(r.get_data(),
[{'data': 18, 'severity': self.severity}])
def test_simple(self):
r = Results()
self.assertEqual(r.get_data(), [])
