def setUp(self) -> None:
self.interval = HalfClosedIntervalLeft(2, 9)
self.date_interval = HalfClosedIntervalLeft(datetime.date(2019, 2, 7),
datetime.date(2019, 2, 14))
self.datetime_interval = HalfClosedIntervalLeft(
datetime.datetime(2019, 2, 7, 11, 30),
datetime.datetime(2019, 2, 7, 12, 30))
def test_ge(self):
self.assertTrue(self.interval >= HalfClosedIntervalLeft(2, 9))
self.assertTrue(self.interval >= HalfClosedIntervalLeft(1, 9))
self.assertFalse(self.interval >= HalfClosedIntervalLeft(3, 9))
def test_gt(self):
self.assertTrue(self.interval > HalfClosedIntervalLeft(2, 7))
self.assertTrue(self.interval > HalfClosedIntervalLeft(1, 10))
self.assertFalse(self.interval > HalfClosedIntervalLeft(2, 9))
def test_ne(self):
self.assertTrue(self.interval != HalfClosedIntervalLeft(2, 8))
self.assertFalse(self.interval != HalfClosedIntervalLeft(2, 9))
def test_lt(self):
self.assertTrue(self.interval < HalfClosedIntervalLeft(2, 10))
self.assertTrue(self.interval < HalfClosedIntervalLeft(3, 10))
self.assertFalse(self.interval < HalfClosedIntervalLeft(2, 9))
parser = argparse.ArgumentParser(
prog=__file__,
description=
'Generates csv files for dimension-averages exploration story')
parser.add_argument('-input-datapath', type=str, required=True)
parser.add_argument(
'-story-datapath',
type=str,
required=True,
)
parser.add_argument('-partition-date',
type=str,
required=True,
help="partition-date (%Y%m%d) name of subfolder")
parser.add_argument('-start-date',
type=str,
required=True,
help="%Y-%m-%d")
parser.add_argument('-end-date', type=str, required=True, help="%Y-%m-%d")
args = parser.parse_args()
story_data_path = f"{args.story_datapath}/{args.partition_date}"
source_data_path = f"{args.input_datapath}/{args.partition_date}"
in_story_daterange = daterange_filter(
"date", HalfClosedIntervalLeft(args.start_date, args.end_date))
month_intervals_means_csvs(source_data_path, story_data_path,
in_story_daterange)
month_intervals_pace_csv(f"{source_data_path}/workout-summary-run.csv",
story_data_path, in_story_daterange)
if weight in self._div_list[k]:
return self._weight_classes[self._div_list[k]]
if weight > self._div_list[k].upper_end:
delta = -1
else:
delta = 1
while True:
k += delta
if weight in self._div_list[k]:
return self._weight_classes[self._div_list[k]]
boxing_weight_classes = {
HalfClosedIntervalLeft(200, 750): ('Heavyweight', 200), # technically unlimited upperbound
HalfClosedIntervalLeft(175, 200): ('Cruiserweight', 175),
HalfClosedIntervalLeft(168, 175): ('Light Heavyweight', 168),
HalfClosedIntervalLeft(160, 168): ('Super Middleweight', 160),
HalfClosedIntervalLeft(154, 160): ('Middleweight', 154),
HalfClosedIntervalLeft(147, 154): ('Super Welterweight', 147),
HalfClosedIntervalLeft(140, 147): ('Welterweight', 140),
HalfClosedIntervalLeft(135, 140): ('Super Lightweight', 135),
HalfClosedIntervalLeft(130, 135): ('Lightweight', 130),
HalfClosedIntervalLeft(126, 130): ('Super Featherweight', 130),
HalfClosedIntervalLeft(122, 130): ('Featherweight', 122),
HalfClosedIntervalLeft(118, 122): ('Super Bantamweight', 118),
HalfClosedIntervalLeft(115, 118): ('Bantamweight', 115),
HalfClosedIntervalLeft(112, 115): ('Super Flyweight', 112),
HalfClosedIntervalLeft(108, 112): ('Flyweight', 108)
}
def test_Interval_gt_exception(self):
with self.assertRaises(TypeError):
k = HalfClosedIntervalLeft(2, 9)
j = ClosedInterval(2, 9)
k > j
def test_Interval_values_exception(self):
with self.assertRaises(ValueError):
HalfClosedIntervalLeft(9, 2)
def test_Interval_types_mismatch(self):
with self.assertRaises(TypeError):
HalfClosedIntervalLeft(1, 'a')