As an R user, have you ever wished for a more efficient way to interact with your database? Look no further than oRm, a new object relational model framework inspired by SQLAlchemy. With oRm, you can create a backend for interactive shiny tables or reproducible data entry, making your data analysis workflow more streamlined and efficient.
oRm is designed to provide a more intuitive and object-oriented approach to CRUD (Create, Read, Update, Delete) operations. By wrapping your DBI connection methods and dbplyr filtering syntax, oRm creates R6 mutable objects that make it easy to work with relationships between data.
One of the key benefits of oRm is its ability to manage transactions and provide automatic rollback in case of failure. Additionally, it supports on delete and on update actions for related objects, making it a powerful tool for managing complex data relationships.
To get started with oRm, you’ll need to define an Engine, which uses DBI under the hood. From there, you can create TableModels, which represent SQL tables, and Records, which represent individual rows in a table. With oRm, you can easily create, read, update, and delete data in your database, making it a valuable addition to your R toolkit.
If you’re interested in learning more about oRm and how it can improve your data analysis workflow, be sure to check out the documentation and examples on the pkdown site.