time

Module Contents

Classes

TimeBase	A class to capture a time snapshot of benchmark values. Time is reprented as a continous value i.e a datetime which is converted into a np.datetime64. To represent time as a discrete value use the TimeEvent class. The distinction is because holoview and plotly code makes different assumptions about discrete vs continous variables
TimeSnapshot	A class to capture a time snapshot of benchmark values. Time is reprented as a continous value i.e a datetime which is converted into a np.datetime64. To represent time as a discrete value use the TimeEvent class. The distinction is because holoview and plotly code makes different assumptions about discrete vs continous variables
TimeEvent	A class to represent a discrete event in time where the data was captured i.e a series of pull requests. Here time is discrete and can't be interpolated, to represent time as a continous value use the TimeSnapshot class. The distinction is because holoview and plotly code makes different assumptions about discrete vs continous variables

class time.TimeBase(default=None, *, doc=None, label=None, precedence=None, instantiate=False, constant=False, readonly=False, pickle_default_value=True, allow_None=False, per_instance=True, allow_refs=False, nested_refs=False)

Bases: bencher.variables.sweep_base.SweepBase, param.Selector

A class to capture a time snapshot of benchmark values. Time is reprented as a continous value i.e a datetime which is converted into a np.datetime64. To represent time as a discrete value use the TimeEvent class. The distinction is because holoview and plotly code makes different assumptions about discrete vs continous variables

__slots__

values(debug=False) → List[str]

return all the values for a parameter sweep. If debug is true return a reduced list

class time.TimeSnapshot(datetime_src: datetime.datetime | str, units: str = 'time', samples: int = None, samples_debug: int = 2, **params)

Bases: TimeBase

A class to capture a time snapshot of benchmark values. Time is reprented as a continous value i.e a datetime which is converted into a np.datetime64. To represent time as a discrete value use the TimeEvent class. The distinction is because holoview and plotly code makes different assumptions about discrete vs continous variables

__slots__

class time.TimeEvent(time_event: str, units: str = 'event', samples: int = None, samples_debug: int = 2, **params)

Bases: TimeBase

A class to represent a discrete event in time where the data was captured i.e a series of pull requests. Here time is discrete and can’t be interpolated, to represent time as a continous value use the TimeSnapshot class. The distinction is because holoview and plotly code makes different assumptions about discrete vs continous variables

__slots__