Address small tech debt to use a conditional instead of try/except for Python 3.7 support

[kapoor1992]

No description provided.

[codecov-commenter]

Codecov Report

Merging #934 (cdc6e21) into main (169e0b3) will not change coverage.
The diff coverage is 100.00%.

@@           Coverage Diff           @@
##             main     #934   +/-   ##
=======================================
  Coverage   87.68%   87.68%           
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  Files          17       17           
  Lines        4433     4433           
=======================================
  Hits         3887     3887           
  Misses        546      546           

Impacted Files	Coverage Δ
neuralprophet/forecaster.py	87.97% <100.00%> (ø)

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[noxan]

Hi @kapoor1992 and many thanks for your contribution.

To me the two implementations are exactly the same and I got the impression the try catch with ImportError is a frequently seen pattern, e.g. [stack overflow]. Do you know of any other projects using the version check implementation? I'd prefer to follow the most common implementation unless there are any strong reasons for one over the other?

[kapoor1992]

Hey @noxan! So, I found a lot more back-and-forth on this (even in your link) haha! The try/except pattern definitely follows the EAFP principle which is Pythonic in nature while the if/else pattern is deemed "safer" generally since you're checking first. Ultimately, I don't think either choice makes much of a difference here since we're not doing anything major other than picking an import. If you prefer try/except, then feel free to reject + close this PR :)

[noxan]

Looks good to me, thanks for the second opinion @karl-richter :)

[Kevin-Chen0]

LGTM

[github-actions]

135e8b1

Model Benchmark

Benchmark	Metric	main	current	diff
AirPassengers	MAE_val	15.2698	15.2698	0.0%	✅
AirPassengers	RMSE_val	19.4209	19.4209	0.0%	✅
AirPassengers	Loss_val	0.00195	0.00195	0.0%	✅
AirPassengers	RegLoss_val	0	0	0.0%	✅
AirPassengers	epoch	89	89	0.0%	✅
AirPassengers	MAE	9.82902	9.82902	0.0%	✅
AirPassengers	RMSE	11.7005	11.7005	0.0%	✅
AirPassengers	Loss	0.00056	0.00056	0.0%	✅
AirPassengers	RegLoss	0	0	0.0%	✅
PeytonManning	MAE_val	0.64636	0.64636	0.0%	✅
PeytonManning	RMSE_val	0.79276	0.79276	0.0%	✅
PeytonManning	Loss_val	0.01494	0.01494	0.0%	✅
PeytonManning	RegLoss_val	0	0	0.0%	✅
PeytonManning	epoch	37	37	0.0%	✅
PeytonManning	MAE	0.42701	0.42701	0.0%	✅
PeytonManning	RMSE	0.57032	0.57032	0.0%	✅
PeytonManning	Loss	0.00635	0.00635	0.0%	✅
PeytonManning	RegLoss	0	0	0.0%	✅
YosemiteTemps	MAE_val	1.72948	1.72949	0.0%	✅
YosemiteTemps	RMSE_val	2.27386	2.27386	0.0%	✅
YosemiteTemps	Loss_val	0.00096	0.00096	0.0%	✅
YosemiteTemps	RegLoss_val	0	0	0.0%	✅
YosemiteTemps	epoch	84	84	0.0%	✅
YosemiteTemps	MAE	1.45189	1.45189	0.0%	✅
YosemiteTemps	RMSE	2.16631	2.16631	0.0%	✅
YosemiteTemps	Loss	0.00066	0.00066	0.0%	✅
YosemiteTemps	RegLoss	0	0	0.0%	✅

Model Training

PeytonManning

YosemiteTemps

AirPassengers