What Is The Recommended Way To Persist (pickle) Custom Sklearn Pipelines?

I have built an sklearn pipeline that combines a standard support vector regression component with some custom transformers that create features. This pipeline is then put into an

Solution 1:

OK, after some googling around it seems to be the case that the root cause is not pickling, it is simply a pyinstaller "hidden imports" issue, but for some reason it only shows up when pickling (don't ask me why).

The following solved the immediate issue for me: edit the .spec file to add the following hidden import with Scipy:

 hiddenimports=['scipy._lib.messagestream']

I also needed some other hidden imports related to other libraries

 hiddenimports=['sklearn.neighbors.typedefs',
                'scipy._lib.messagestream',
                'pandas._libs.tslibs.timedeltas'   ]

Solution 2:

If anyone just wants to do this via CLI argument instead of through the .spec file as presented in Roko's answer, this is the syntax:

pyinstaller --hidden-import scipy._lib.messagestream --onefile your_python_file_here.py