The idea is you send a request when you start a run and when you end a run and in between you send metrics to the server.
The server handles these things and puts them into a database. (this is inspired by the MLflow python package that does this and more) I think this is most like MLFlow - Tracking.
You can find this project on gitlab and github.
Right now, clone this repo somewhere.
In the commandline go to this somewhere.
Start R in that location. run renv::restore()
move out of R.
In the terminal run the command Rscript run_server.R
MLFlow uses runs and experiments. A run is an execution of code. multple runs live under 1 experiment. A run also includes timing.
wow they improved the docs a lot in the past years! I love it, it is much easeir to understand.
So I did the same thing, but named it differently. I have ids for runs and optional group to combine several.