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Quite simply, TSFresh provides very useful functions for many timeseries analysis needs - the issue with it is that it is very SLOOOOWWWWW.

What I'm struggling to understand about this getML, after clicking through pages of documentation, is how it compares to TSFresh which it is always comparing itself with.

These extracted time series features are what draw people to TSFresh:
https://tsfresh.readthedocs.io/en/latest/text/list_of_features.html

Is getML generating the same?
If so, where are these documented?

Many thanks.

Referencing our discussion in #17

@srnnkls

why have you introduced two runtimes? We have focused using 3.8 and 3.11 for testing purposes but I think we don’t need both runtimes to be public here

3.8 is the minimum version, and 3.11 the current maximum. 3.11 supports a few newer libraries. And with upcoming changes, support for newer versions, we can quickly start and test them.
It is not necessary to put both. But also the files and code for both are very few.
And when we need to quickly check something, they are there and prepared.

you are using manylknux as the baseimage for the runtimes (3.8 & 3.11), why? I think this is a huge image and not necessary for a getml runtime

That is about 460MB. (https://quay.io/repository/pypa/manylinux2014_x86_64?tab=tags&tag=latest)
The standard Python image is about 360MB. (https://hub.docker.com/_/python/tags)

python:-slim

This image does not contain the common Debian packages contained in the default tag and only contains the minimal Debian packages needed to run python. Unless you are working in an environment where only the python image will be deployed and you have space constraints, we highly recommend using the default image of this repository.

When using this image pip install will work if a suitable built distribution is available for the Python distribution package being installed. pip install may fail when installing a Python distribution package from a source distribution. This image does not contain the Debian packages required to compile extension modules written in other languages.

There is also Jupyter-Lab, getML engne, getML monitor running inside. I would need to try, if they still work in the slim one. (A quick runs in problems with missing curl and can't apt install it… And pysimdjson fails with error: command 'gcc' failed: No such file or directory)
But are ~500MB really that much for just quickly checking things out?

Okay, on disk it is more like 1.56 GB.
And the build notebook images (with installed requirements and things) are 4.53 GB
(The ones build from Python-images are 3.85 GB and 4 GB - not too much different, I think.)

Because of PEP513... PEP600... , manylinux sounded like a good base.

Originally posted by @Urfoex in #17 (comment)

In all the notebooks, there is a "Where is this running?" and "A web frontend for getML
" section.

https://notebooks.getml.com/github/getml/getml-demo/blob/master/interstate94.ipynb

Both seem very confusing, I think they should be removed. The link in "You can launch the getML monitor here" is not getting resolved on the website!

Add hint in the beginning of the website where the notebook is displayed (not part of the notebook), that tells the user that he can run the notebook by pressing the 3 Rings in the top right corner (Execute on binder).