Dissolving then Aggregating, concatenating attributes

Certainly, simpler than anything I’d have thought of, I have 5 separate streams I’m already dissolving and aggregating so I think I’m going to stick with my python solution for this which is building two lists and then combining, deduplicating and concatenating. But I knew there should be a more straightforward FME way but I was getting hung up on lists

import fme
import fmeobjects

def processFeature(feature):
    v = list(set(feature.getAttribute('dissolve{}.Value')+feature.getAttribute('aggregate{}.Value')))
    feature.setAttribute("Value",' / '.join(v))

I'm afraid that your solution could cause unexpected result, if the data flow consists of Dissolver, Aggregator, and PythonCaller connected in series.

For example, in the case of this screenshot,

after dissolving, resulting features will have these attributes.

• feature 1
  • Value = 'a'
  • dissolve{0}.Value = 'a'
  • dissolve{1}.Value = 'b'
• feature 2
  • Value = 'c'
  • dissolve{0}.Value = 'c'
  • dissolve{1}.Value = 'd'
• feature 3
  • Value = 'a'
  • dissolve{0}.Value = 'a'

Then, if you perform aggregating them with Aggregator, resulting feature will have these attributes.

• feature
  • Value = 'a'
  • dissolve{0}.Value = 'a'
  • dissolve{1}.Value = 'b'
  • aggregate{0}.Value = 'a'
  • aggregate{1}.Value = 'c'
  • aggregate{2}.Value = 'a'

The value 'd' is missing.

That scenario doesn’t actually occur in my data but a good warning. I’ve tweaked my workflow