R2 Studio

The developers behind recently announced "R2 Deploy" – a feature that lets you highlight a block of code and instantly turn it into a REST API endpoint. This means the data scientist no longer has to hand off their notebook to an engineering team; they can operationalize the logic immediately.

# Switch to Python context seamlessly from my_models import IsolationForest model = IsolationForest() r2.assign("model", model) r2.run("transactions_modeled <- predict(model, transactions)") r2 studio

| Feature | Traditional RStudio (R) | Jupyter Notebooks (Python) | | | :--- | :--- | :--- | :--- | | Language Support | R only | Python (mostly) | Polyglot (R, Python, SQL, Scala) | | Big Data Handling | Struggles > 1M rows | Requires external Spark | Native Distributed Execution | | Visualization | Static or interactive | Static | Real-time, Bi-directional | | Collaboration | Git workarounds | Merge hell (JSON diffs) | Live Co-editing (like Google Docs) | | Environment State | Volatile | Volatile | Persistent & Durable | The developers behind recently announced "R2 Deploy" –