"On demand" formulas

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@jqnatividad ya está trabajando en esto.

Desde el 29/5/2025.

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Descripción

DP+ DRUF currently supports two formula types:

  • formula (aka "direct formulas")
    the Jinja2 expression is evaluated at package creation/update and "directly" stored into the designated package/resource field.
  • suggestion_formula
    the Jinja2 expression is evaluated at package creation/update, and is stored in the dpp_suggestions package field (as a JSON object). The dpp_suggestions package field is used to power the Bootstrap-powered Suggestion UI popover

We should create a third formula type - On demand, which is a variant of suggestion_formula.

It is indicated by a new scheming keyword - ondemand_formula.

As the name implies, an ondemand formula is calculated on demand, i.e. while entering metadata in CKAN.

When an ondemand_formula is used, the Suggestion UI will have an "Recalculate" button in addition to "Apply Suggestion" button.

To enable this, DP+ will have a new Action API endpoint - dpp_ondemand_formula:

def dpp_ondemand_formula(context, data_dict):
'''
Evaluate the on_demand formula for the given package/resource field

:param formula: the Jinja2 expression to evaluate.
:param track_invocation: track the formula/result pair with a timestamp (default: false)
'''

When the "Recalculate" button is pressed, the Suggestion UI calls the dpp_ondemand_formula API for the associated field.

Ondemand formulas will be initially used for AI-powered formulas - as they often need repeated invocations while entering metadata.
We offer the ability to "track_invocation", so the user can possibly use/consult previous invocations.

Eventually, ondemand formulas can be also used to have "formula presets", similar to scheming's "presets".
"Formula presets" are traditional jinja2 templates that can render a custom UI for an associated formula that may require additional form controls beyond the generic Suggestion UI (e.g. a field picker to select which fields to use in a formula during data entry).

cc @minhajuddin2510 @samibaig @wardi

Lenguaje dominante
Python
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47
Forks
33
Merge medio
2 h 28 min
PR fusionados (30 d)
10

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