Chain.jl VS JLD2.jl

The [Chain.jl package](https://github.com/jkrumbiegel/Chain.jl) is becoming idiomatic for these kind of pipelines.

If you do have tabular data in a dataframe you have a few options for data manipulation, the most popular packages are probably DataFramesMeta and Query, although in my opinion the best way to manipulate dataframes is with the functions built in to DataFrames.jl and using a package like Chain.jl or Pipe.jl to pipe the functions into each other like magrittr in R.

The Julia community built a better piping method than any other language has AFAIK: Chain.jl.

@chain and @match.

Have you ever tried Infiltrator.jl and Chain.jl?

You are right. However, sometimes well used is very useful, and readable. One suggestion, in Julia I suggest Chain.jl, because it allows intercalate easily the output for debugging:

I also like pipe syntax and I've found there is nice support for it in Julia. There are some nice packages to improve it over base [1].

Have you checked queryverse [2]?

[1] https://github.com/jkrumbiegel/Chain.jl

First, you need to save the model from the notebook to a file. For this you can use JLD2.jl module. This module used to serialize Julia object to HDF5-compatible format (which is well known by Python data scientists) and save it to a file.

I didn't realize this was the Julia subreddit. HDF5 or multiple CSV files would be my suggestion. As a side note, check out the JLD2 package. It's a HDF5 compatible format where the package is written in pure Julia.