def test_get_config(self):
config_obj = ConfigObj({"a": 1, "b": {"c": [1, 2, 3, 4, 5]}})
conf = config_obj.get_config("b")
assert conf.c == [1, 2, 3, 4,
5], "get_config should return a config obj."
conf = config_obj.get_config(("b.c"))
assert conf == [1, 2, 3, 4, 5], "get_config should return a value."
conf = config_obj.get_config("c")
print("conf: {}".format(conf))
def Trends(self,
featureSet_to_trend,
trend_ranges,
_dtm=None,
_config: ConfigObj = None):
"""
Trends is a method that constructs the TrendsCommon generic FeatureFamily. It returns features, slope and y-intercept
such that the user can understand the trend line and ideally future values for various features.
:param featureSet_to_trend: A feature set to be trended
:param trend_ranges: list of ranges to be trended [['1m','12m'], ['1w', '4w']]. Accepted range periods are
d = day
w = week
m = month
y = year
:param _dtm: A specific dtm can be passed in but generally the dtm from self should be used
:param _config: A specific configObj can be passed in but generally the config is taken from self
:return:
"""
if _config is None:
time_helpers = self.config.get_config("time_helpers")
else:
time_helpers = _config.get_config("time_helpers")
dtm = self.dtm if _dtm is None else _dtm
trends = TrendsCommon(featureSet_to_trend, trend_ranges, dtm,
time_helpers)
return trends
def _create_from_daterange(
cls,
dtm: DateTimeManager,
time_helpers: ConfigObj,
period_ranges="date_filters.ranges",
):
"""
:param time_helpers: {
snapshot_date: "20190225",
snapshot_type: "DAILY",
partition_col: "p_yyyymm",
date_ranges: {
"1m": {"start": <val>, "end": <val>, "3m": {"start": <val>, "end": <val>}
}
}
:return:
"""
filters = []
filter_vals = []
date_ranges = time_helpers.get_config(period_ranges).as_dict()
partition_col = time_helpers.get_or_else("partition_col", "")
filter_names = list(date_ranges.keys())
filter_cols = [partition_col]
if time_helpers.get_or_else("snapshot_type", "MONTH") == "DAILY":
date_col = time_helpers.get_or_else(
"date_col", "No date col specified in the time_helpers config."
"Daily snapshots require a date_col to be defined")
filter_cols = [partition_col, date_col]
for date_range in date_ranges.keys():
d_filter = dtm.scoped_time_filter(
range_dict=date_ranges[date_range])
filters.append([d_filter])
filter_vals.append(date_ranges[date_range])
else:
for date_range in date_ranges.keys():
p_filter = dtm.scoped_partition_filter(
range_dict=date_ranges[date_range])
filters.append([p_filter])
filter_vals.append(date_ranges[date_range])
return Multiplier(filter_cols, [filter_vals], [filters],
[filter_names])