There are new updates to Mode’s Notebook environment to help you set up faster and manage memory better.
- Add public libraries to your Python and R notebooks using a simpler command. For Python, use
! pip installand for R, use the command
install.packages()to quickly install public libraries and set up your notebook environment faster. For more information about how to install public libraries in Mode's Notebook check out the help doc here.
- Python notebooks will only load query results into the notebook environment when explicitly referenced to avoid using up RAM from unused query results. Read our help doc for more information about Python memory management.
- Dask, DuckDb, and Pympler are new Python libraries available in Mode's Edge environment to help efficiently ingest data into the notebook environment and monitor memory usage. Tensorflow-decision-forests has also been added to train, run, and interpret decision forest models in Tensorflow. Additionally, new versions of Matplotlib, statsmodels, NetworkX, and XGBoost have been updated in Edge. See the full list of updated libraries on our help site.
Make sure to test out the compatibility of these new libraries in your reports and notebooks before they are rolled out to the standard environment on January 12th. Read this blog post for instructions on how to get started with Edge.