def runs(self, as_df=False, price_config=None, last=None, since_days=None):
"""Returns the job's run.
Parameters:
-----------
- as_df : boolean (default: False)
Convert the runs to pandas dataframe
- price_config : dict (default: None)
Price config used to compute cluster cost
- last : int (default: None)
Filters the last N results (no filtering if set to None)
- since_days : int (default: None)
Filters to last N days (no filtering if set to None)
Returns:
--------
runs : list of JobRun objects or pd.DataFrame
The job's runs as list of sqlalchemy objects
or as a pandas DataFrame
"""
runs = self.jobruns
if since_days is not None:
runs = [run for run in runs if run.start_time >= since(since_days)]
if last is not None:
runs = runs[-last:]
if as_df:
runs = pd.DataFrame([run.to_dict(price_config) for run in runs])
return runs
def dbu(self, since_days=7):
states = self.state_df()
return (states
.loc[states.timestamp >= since(since_days)]
.interval_dbu
.sum())
def active(self, since_days=7):
states = self.state_df()
states = states.loc[states.timestamp >= since(since_days)]
return not states.empty