Automate the routine of processing datasets or updating dashboards, by running regular Python or R jobs and monitoring their progress. allows you to execute simple Python and R jobs right on – either on demand or automatically at a regular schedule. These jobs can run use basic scientific packages, such as pandas, numpy, plotly, and dstack, tidyverse, ggplot2, etc.

The jobs are ideal for processing data regularly and publishing the results in the form of stacks, e.g. data visualizations or datasets.

In addition to running jobs at a fixed schedule, jobs can be also used as an alternative to Jupyter notebooks when you need to quickly run a piece of code to push data to