# [Python-ideas] Proposal: A Reduce-Map Comprehension and a "last" builtin

Peter O'Connor peter.ed.oconnor at gmail.com
Mon Apr 16 09:49:54 EDT 2018

```Hi Danilo,

The idea of decorating a function to show that the return variables could
be fed back in in a scan form is interesting and could solve my problem in
a nice way without new syntax.

I looked at your code but got a bit confused as to how it works (there
seems to be some magic where the decorator injects the scanned variable
into the namespace).  Are you able to show how you'd implement the moving
average example with your package?

I tried:

@enable_scan("average")
def exponential_moving_average_pyscan(signal, decay, initial=0):
yield from ((1-decay)*(average or initial) + decay*x for x in
signal)

smooth_signal_9 = list(exponential_moving_average_pyscan(signal,
decay=decay))[1:]

Which almost gave the right result, but seemed to get the initial
conditions wrong.

- Peter

On Sat, Apr 14, 2018 at 3:57 PM, Danilo J. S. Bellini <
danilo.bellini at gmail.com> wrote:

> On 5 April 2018 at 13:52, Peter O'Connor <peter.ed.oconnor at gmail.com>
> wrote:
>
>> I was thinking it would be nice to be able to encapsulate this common
>> type of operation into a more compact comprehension.
>>
>> I propose a new "Reduce-Map" comprehension that allows us to write:
>>
>> signal = [math.sin(i*0.01) + random.normalvariate(0, 0.1) for i in range(1000)]
>> smooth_signal = [average = (1-decay)*average + decay*x for x in signal from average=0.]
>>
>>
>> def exponential_moving_average(signal: Iterable[float], decay: float, initial_value: float=0.):
>>     average = initial_value
>>     for xt in signal:
>>         average = (1-decay)*average + decay*xt
>>         yield average
>>
>> signal = [math.sin(i*0.01) + random.normalvariate(0, 0.1) for i in range(1000)]
>> smooth_signal = list(exponential_moving_average(signal, decay=0.05))
>>
>> I wrote in this mail list the very same proposal some time ago. I was
> trying to let the scan higher order function (itertools.accumulate with a
> lambda, or what was done in the example above) fit into a simpler list
> comprehension.
>
> As a result, I wrote this project, that adds the "scan" feature to Python
> comprehensions using a decorator that performs bytecode manipulation (and
> it had to fit in with a valid Python syntax):
> https://github.com/danilobellini/pyscanprev
>
> In that GitHub page I've wrote several examples and a rationale on why
> this would be useful.
>
> --
> Danilo J. S. Bellini
> ---------------
> "*It is not our business to set up prohibitions, but to arrive at
> conventions.*" (R. Carnap)
>
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