You might want an entire dashboard to pull in the most recent data every morning. You may even want to run a Python cell every evening, so that you can write the output of a workflow to your database. Execution schedules are made to solve all of these use-cases.
An execution schedule can re-run a flow (a chain of cells) at a prescribed time interval, including charts, Python scripts, model executors, or even entire dashboards.
In a canvas, an operator can be scheduled to be executed at regular intervals. To create a schedule for an operator, right-click the cell itself (or in the cells left sidebar) and select
A dialog will allow you to view/edit existing schedules that target the operator, or you can create a new schedule for the operator.
Cells that have been scheduled will be marked in the cells sidebar.
Whenever a run happens, Einblick stores information about the run in the cell's execution logs. This allows you to keep track of previous executions of an cells, including erroneous and scheduled runs.
To view the execution logs of an operator, right-click the cell and select
View execution logs.
Data Sources in Execution Schedules
A common reason to create an execution schedule is to get the latest data from the data source of an operator. The execution schedule will automatically pull the latest data from the source as a part of the execution of its targets.