Write plugins in R or Python

At the start of a research project, the data is initially in a "large" format, adhering to the OMOP CDM (Common Data Model) structure.

As the study progresses through its various phases, this data undergoes a transformation process, evolving into a "wider" format.

In this transformed state, each row represents a patient (or another relevant statistical unit, such as a hospital stay or a specific event during a patient's stay, depending on the study's focus) while the columns capture the specific attributes or features that are pertinent to the research study.

In LinkR, plugins can be developed using either R or Python, with the latter being executed within an R environment via the reticulate library.

To facilitate seamless integration between R and Python, it's crucial to ensure that data is compatible across both languages.

A potential strategy involves storing data in its expanded form in a file format that both R and Python can easily access and manipulate. The Feather file format seems to be a good choice for this purpose, as it is designed to be efficiently read and written by both R and Python.

Additionally, using SQL as a language for querying data presents a viable solution for executing queries in both R and Python environments, as referenced in issue #5.

We can discuss other possible alternatives here.