Getting started
Last updated
Last updated
The easiest way to get started with the redivis-r library is via a , which comes with the latest version of this library pre-installed. Additionally, authentication is automatically handled within the Redivis notebook environment.
If you'd like to use the client in another environment, you can install the redivis library from Github. Use devtools to install the latest version from the main branch:
When referencing datasets, workflows, and tables on Redivis, you should be familiar with the resource reference syntax.
If you are using the redivis-r library within a notebook on Redivis, you'll automatically be authenticated and have access to any data within your workflow.
If you are running the redivis-r library on another system (e.g., your laptop, Google Colab, or a shared compute cluster), you will be prompted to authenticate with your Redivis account the first time you run a command. Follow the printed instructions to authorize the R client to communicate with the Redivis API.
If you are developing a service that regularly interacts with Redivis without human intervention – for example, a recurring job that runs a data ingest pipeline – you can generate an API token to allow the service to act on your behalf.
API Tokens must be treated with extreme care, as a leaked token can allow somebody else to act on your behalf. These tokens should be treated like passwords, and never committed to source control or stored as strings in the text of your code.
API Tokens are only required for long-running services that operate without a human actor. If you are engaging with the Redivis API interactively, you should instead use the simpler and more secure OAuth flow mentioned above.
This API token must then be set as the REDIVIS_API_TOKEN environment variable before running your R script. You can set the variable for your current session by running the following in your terminal: