Forum Discussion

MalcolmMcDonald's avatar
Qrew Cadet
2 years ago

Grouping and Listing fieldnames and values in Pipelines

I'm importing a flat file of workorders into a staging table, then looking to load it into the production tables. 

The file has about 24 columns of parts that could be installed, with a count.  Looks a bit like the below:

1       2
1   1   2

I'm not using this data for inventory .. it's purely informational.

Using pipelines - is there an easy way put all those columns into a single multi-line text block, separated into a list - skipping over the blank ones?  EG -- that first record would like the below or similar:

Doorbell Camera: 1 | Door / Window Sensor: 2


Malcolm McDonald

2 Replies

  • DougHenning1's avatar
    Community Manager

    Hi Malcolm, this block will output close to what you want.  You'll need to update the list of fields on line 2, and replace 'c' on lines 3 and 5 with the appropriate step letter in your pipeline:

    {# Define the list of fields to use -#}
    {% set fields = ['doorbell_camera', 'indoor_camera', 'outdoor_camera', 'takeout_camera', 'door_window_sensor'] -%}
    {% for field in fields if c[field]|int > 0  -%}
    {# Format/capitalize the field name -#}
    {{field.split('_') | map('capitalize')|join(' ') }}: {{c[field]}}{{ ' | ' if not loop.last }}
    {%- endfor -%}

    Sample output:

    Doorbell Camera: 1 | Takeout Camera: 3 | Door Window Sensor: 2

    The field names don't have the exact formatting (e.g. no slashes) since that info isn't available on the jinja field name. 

    Hope that helps!

    Doug Henning
    • MalcolmMcDonald's avatar
      Qrew Cadet

      Actual genius .. thank you Mr. Henning!

      And for future searchers on this topic .. I had quite a number of "illegal" characters in the field name, but the pipeline field picker showed me what to do .. so for eg - Doorlock(Brass-15) shows as {{a.doorlock_brass_15}} .. ie the jinja needs the open parenthesis as an underscore, but drops the close parenthesis entirely.

      Malcolm McDonald