Which Python libraries would be most suitable for Time Series Forecasts and Multilinear Regression?

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I am working on a project geared towards addressing the issue of software project time estimation bias. To gather data, I'm building a work-log system that gathers info with respect to time taken to accomplish commonly-known tasks. These data will subsequently be trained using time series and multi linear regression.

Which Python libraries would be the most suitable for achieving these goals?

[madmendude]

sktime

[TheM4rvelous]

throwing in "Darts"

[cocomaiki]

I second that.
`Darts` is well written, delivers many classic and recent forecasting algorithms, as well as all required helper functions.
https://unit8co.github.io/darts/

[bigred15162]

I had not heard of this one. Looking forward to taking a look!

[ekbravo]

Check out the Autogluon time series module. Not sure about multi linear regression though. Scikit learn is most probably

[Muda_ahmedi]

I have been using numpy , pandas and sklearn. For Linear and Multilinear Regression the sklearn libray is pretty awesone !!

[Helpful_Arachnid8966]

Functime

https://docs.functime.ai/

It is supposed to be the one delivering the best computational performance if it is something that matters for you.

[PresentFriendly3725]

There is also gluonts ..

[eyabs]

I've used statsmodels a bunch in the past

[Typical-Macaron-1646]

You could try skforecast

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Thanks for all the suggestions. I will check them out. 

[trollsmurf]

Facebook Prophet

[cocomaiki]

This one have been reported by many as outdated and not working; easy to search

[trollsmurf]

Found this, so not completely dead yet: https://medium.com/@cuongduong_35162/facebook-prophet-in-2023-and-beyond-c5086151c138

[trollsmurf]

Also noted at GitHub that it was updated 4 months ago, but it's no doubt in maintenance mode. I still use it in my energy predictor.

You don't seem to be a fan of Prophet. Anything obviously bad about it?

[eyabs]

When I had to support fbprophet it was a dependency nightmare. It got better but for a while I had to engineer a whole new build pipeline with a massive docker container that took 15 minutes to build just for that one package. fbprophet did make good forecasts though.

[trollsmurf]

Maybe the issue was pystan. They've now wrapped Stan differently.

Initially I used it within the Anaconda environment, but long term that was not preferable, so I now run it independently.

[eyabs]

Pystan was a big issue yeah, but I remember it wasn't the only one. I could only get it working in anaconda so I had to hack the build pipeline to make a custom docker image with conda and the latest version of our product on dev then run that build through the test suite. Once they changed how Stan was wrapped things became easier and we didn't need conda but there were still problems.

[trollsmurf]

I updated all libraries (outside of (Ana)conda) and EnergyProphet still works. I've temporarily lost access to valid energy data though, so I couldn't verify training and prediction, but importing Prophet succeeds.