API Reference¶
TimeSeries¶
In traces, a TimeSeries is similar to a dictionary that contains measurements of something at different times. One difference is that you can ask for the value at any time – it doesn’t need to be at a measurement time. Let’s say you’re measuring the contents of a grocery cart by the number of minutes within a shopping trip.
>>> cart = traces.TimeSeries()
>>> cart[1.2] = {'broccoli'}
>>> cart[1.7] = {'broccoli', 'apple'}
>>> cart[2.2] = {'apple'}
>>> cart[3.5] = {'apple', 'beets'}
If you want to know what’s in the cart at 2 minutes, you can simply
get the value using cart[2] and you’ll see {'broccoli',
'apple'}. By default, if you ask for a time before the first
measurement, you’ll get None.
>>> cart = traces.TimeSeries()
>>> cart[-1]
None
If, however, you set the default when creating the TimeSeries, you’ll get that instead:
>>> cart = traces.TimeSeries(default=set())
>>> cart[-1]
set([])
In this case, it might also make sense to add the t=0 point as a
measurement with cart[0] = set().
Performance note¶
Traces is not designed for maximal performance, but it’s no slouch since it uses the excellent sortedcontainers.SortedDict under the hood to store sparse time series.
