Comet R SDK

The Comet R SDK, called cometr, is an open source library. The source code can be found at We welcome any fixes or enhancements.

To install the stable CRAN version:

r install.packages("cometr")

To install the latest development version from GitHub:

r install.packages("remotes") remotes::install_github("comet-ml/cometr")

Please see the README for more information on how to setup and use.

Quick Setup

After you have aquired your Comet API key and done the one-time setup, then you are ready to dive into Machine Learning in R.

Specifically, you need to have defined your ~/.comet.yml file, which might look something like:

yml COMET_WORKSPACE: my-comet-user-name COMET_PROJECT_NAME: keras COMET_API_KEY: m93476k7WAa5t093476kIaJSjl8le

In R, you'll need to install the cometr package:

r install.packages("cometr")

Now you are ready to begin running Machine Learning R scripts with Comet.

Comet Machine Learning Examples in R

First, you might explore these Jupyter Notebooks demonstrating Comet with R:

Here are some basic R script examples to get you started:

Note that each example may require additional R packages. Please see the script's source for details.

After installing necessary packages, you can run each of those like the following:

shell $ Rscript keras-example.R

Each Comet R Experiment has a unique URL, and all Experiments are grouped under your workspace/project. There, you can interactively create visualizations, analyze the performance of many models, share your results, and work with collaborators.

If you have any questions, consider these resources:

The rest of this page dives into the Comet R Experiment, the object at the heart of your Machine Learning.

Comet R Experiment

The Experiment object is where the logging of the machine learning code occurs.

Comet R API

Functions for creating, deleting, and querying Comet.


Advanced functions for Comet R.