Feature Request: Rule metadata #208

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1. borchero commented on Oct 28, 2025

   

   Oliver Borchert (borchero)

   on Oct 28, 2025

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   Out of curiosity: what's your use case for the metadata argument?
2. danielcrane commented on Oct 29, 2025

   

   Daniel Crane (danielcrane)

   on Oct 29, 2025

   Last edited by danielcrane

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   Thanks for your response!

   Frankly right now the only use-case I have is for adding a description to the rule.

   This would be useful to allow me to for example (programmatically) walk through the Schema's rules and generate a catalogue of rules with descriptions.

   I'm currently storing descriptions in a config file, which works, but it'd be more elegant to be able to store it in-line with the function itself.

   The alternative I mentioned (using functools to propagate the doc from the validation function) would work fine too for my specific use-case.

   👍React with 👍1Reacted by Oliver Borchert
3. ozanozbeker commented on Aug 13, 2026

   

   Ozan Ozbeker (ozanozbeker)

   on Aug 13, 2026

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   Hey Daniel Crane (@danielcrane), I've done something similar:

   For a single rule, this works without functools:

   class Orders(dy.Schema):
       order_id = dy.String(primary_key=True)
       amount = dy.Float64(nullable=False, min=0.0)
   
       @dy.rule()
       def paid_orders_have_amount(cls) -> pl.Expr:
           """Paid orders must carry a positive amount."""
           return cls.amount.col > 0
   
   
   Orders.paid_orders_have_amount.validation_fn.__doc__
   # 'Paid orders must carry a positive amount.'

   To walk through all rules in a schema, you can do something like my _naming.rule_description:

   import inspect
   
   import dataframely as dy
   from dataframely._rule import RuleFactory
   
   
   def rule_description(schema: type[dy.Schema], rule_name: str) -> str | None:
       """A rule's docstring, or None for a rule with no place to carry one."""
       factory = getattr(schema, rule_name, None)
       if not isinstance(factory, RuleFactory):
           return None
       return inspect.getdoc(factory.validation_fn)
   
   descriptions = {
       rule: rule_description(Orders, rule)
       for rule in Orders._validation_rules(with_cast=False)
   }
   # {'paid_orders_have_amount': 'Paid orders must carry a positive amount.',
   #  'primary_key': None,
   #  'order_id|nullability': None,
   #  'amount|nullability': None,
   #  'amount|min': None,
   #  'amount|inf': None,
   #  'amount|nan': None}

   The Nones are from the column arguments, which have no function to hang a docstring on. The isinstance check is mainly for primary_key: getattr(Orders, "primary_key") gives Schema.primary_key which is a method of dy.Schema and gives an AttributeError without the check.
4. danielcrane commented on Aug 14, 2026

   

   Daniel Crane (danielcrane)

   on Aug 14, 2026

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   Thanks for your insight Ozan Ozbeker (@ozanozbeker) .

   I've ended up making a decorator that wraps @dy.rule() where I can give the rule a description, severity, and a few other things -- it's turned out to be quite useful in my validation results visualisation (having different severity levels is especially useful).