Align forecast with actuals
Requirement
A five-day temperature forecast sits next to what the sensor actually measured. Pair the two series position by position and print one line per day: forecast, actual, and the signed difference to one decimal place. The data is in the code; both versions must print the lines shown under Expected output.
Expected output
day 1: 21.0 forecast vs 20.6 actual (-0.4) day 2: 22.5 forecast vs 23.1 actual (+0.6) day 3: 23.0 forecast vs 23.0 actual (+0.0) day 4: 24.5 forecast vs 25.2 actual (+0.7) day 5: 22.0 forecast vs 21.4 actual (-0.6)
Side by side
RxDart
FxDart
Why they differ
Positional pairing is symmetric across the models and both libraries
ship it: zipWith combines the n-th event of one stream
with the n-th of another, zip pairs the n-th pulls of
two iterables. Both stop at the shorter side, both keep order by
construction. The formatting function is shared verbatim, so the
panels differ only in how the two series are lifted into a pipeline.
The models do hide different machinery under the shared name. Stream
zipWith is a small coordination engine: two live
subscriptions, a one-slot buffer for whichever side is ahead, and
pause/resume to keep a fast producer from outrunning a slow one.
Iterable zip is two iterators advanced in lockstep — the
consumer's pull is the synchronisation, so there is nothing
to buffer and no one to pause. For two fixed lists none of that
machinery is ever exercised, which is exactly why this one is a tie:
pick the version that matches where your series actually live.
Benchmark
N = 100
Time Tie
Peak memory Tie
N = 1,000,000
Time FxDart wins
Peak memory Tie
Bars are medians of repeated timed iterations in fresh processes per side (small N is batched for timer resolution). Sides within 5% of each other — or within 0.6 ms, a difference no person can perceive — count as a tie; close relative races are re-measured up to 5 runs. In an app, anything under a few milliseconds is invisible to the user regardless of which bar is shorter. Memory is peak process RSS. The Dart VM and the dataset are identical on both sides, so the difference between the two bars is what the pipeline itself holds onto.