bencher.variables.time

Classes

TimeBase	A class to capture a time snapshot of benchmark values. Time is represent as a continuous 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 continuous variables
TimeSnapshot	A class to capture a time snapshot of benchmark values. Time is represent as a continuous 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 continuous 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 continuous value use the TimeSnapshot class. The distinction is because holoview and plotly code makes different assumptions about discrete vs continuous variables

Module Contents

class bencher.variables.time.TimeBase(objects=None, default=None, instantiate=False, compute_default_fn=None, check_on_set=None, allow_None=None, empty_default=False, **params)

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

A class to capture a time snapshot of benchmark values. Time is represent as a continuous 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 continuous variables

__slots__ = ['units', 'samples', 'optimize']

values() → list[str]

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

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

Bases: TimeBase

A class to capture a time snapshot of benchmark values. Time is represent as a continuous 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 continuous variables

__slots__ = ['units', 'samples', 'optimize']

units = 'time'

optimize = False

class bencher.variables.time.TimeEvent(time_event: str, units: str = 'event', samples: int | None = None, **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 continuous value use the TimeSnapshot class. The distinction is because holoview and plotly code makes different assumptions about discrete vs continuous variables

__slots__ = ['units', 'samples', 'optimize']

units = 'event'

optimize = False