Description of the issue
Currently omi mainly works with CSV data as also the frictionless spec always uses CSV first. We also have functionality in place to initialize omi based metadata management when the user already got a directory with many csv files. This gets users startet quickly by setting up the base YAML structure specific to the user data.
As users might work with a database or pandas dataframes instead of CSV files it would be nice to offer extreaction functionality which enables the user to initialize form those sources.
Ideas of solution
Workflow checklist
Description of the issue
Currently omi mainly works with CSV data as also the frictionless spec always uses CSV first. We also have functionality in place to initialize omi based metadata management when the user already got a directory with many csv files. This gets users startet quickly by setting up the base YAML structure specific to the user data.
As users might work with a database or pandas dataframes instead of CSV files it would be nice to offer extreaction functionality which enables the user to initialize form those sources.
Ideas of solution
Add a extraction module and create new functionality to extract metadata as OEM form databse tables, including PK & FK constrains.
Add a extraction module and create new functionality to get metadata as OEM form pandas data frame.
Alternative lookup if frictionless-py already offers such functionality and add a wrapper in OMI.
Workflow checklist