Danilo J. S. Bellini writes:
[prev * k for k in [5, 2, 4, 3] from prev = 1]
[1, 5, 10, 40, 120]
Among the examples I wrote on PyScanPrev, there are use cases on:
As a practicing economist, I wonder what use cases you're referring to. I can't think of any use cases where if one previous value is useful, having all previous values available (ie, an arbitrary temporal structure, at the modeler's option) isn't vastly more useful.
This means that in modern econometrics, for example, simple procedures like Cochrane-Orcutt (which handles one previous value of the dependent variable in a single-equation regression) are subsumed in ARIMA and VAR estimation, which generalize the number of equations and/or the number of lags to greater than one. BTW, numerical accuracy considerations often mean you don't want to use the compact "for ... in ... if ..." expression syntax anyway, as accuracy can often be greatly improved with appropriate reordering of values in the series.
Even "online" regression algorithms, where you might think to write
( updated_model(datum, prev) for datum in sensor_data() from prev = something )
'prev' need to refer not to the previous value of 'datum', but to the previous value of 'updated_model()' (since you need a sufficient statistic for all previous data). And 'prev' as currently conceived is just plain useless for any long period moving average, etc.
So in the end, even if there are plausible use cases for quick and dirty code, an experienced implementer wouldn't use them anyway as more powerful tools are likely to be immediately to hand.