Simplified "For Each" Loop Element for Dataset Processing
Currently, when looping through a dataset/table, users need to create a copy of it, check if it is empty, fetch one row at a time, process it, and then exclude that row before continuing the loop. This process involves unnecessary steps and can be time-consuming. Therefore, I propose the implementation of an easy-to-use "For Each" loop element. This element should allow users to set the dataset and define the assignment of each row, simplifying the iteration process. It should automatically handle row traversal without requiring additional checks or dataset manipulation. This feature would enhance productivity by streamlining dataset processing and transitioning to the next step seamlessly.
Jonas Gabrielson commented
Great idea, loops are extremely common and it's easy to mess them up in current Flow programming, especially for newcomers. One idea would be to have an Iterator element on fragments and then run that fragment once per row in a table. Flow already allows for this on some Script Machine steps, why not for fragments?