feat: Allow to skip validating members in collection filter & validate

[Oliver Borchert (borchero)]

Motivation

When validating collections with massive data frames, validation is potentially expensive. It would be nice to be able to skip it.

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 100.00%. Comparing base (005eb9a) to head (5820f8a).

Additional details and impacted files

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  Coverage   100.00%   100.00%           
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  Files           56        56           
  Lines         3481      3489    +8     
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+ Hits          3481      3489    +8     

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[Copilot]

Pull request overview

This PR introduces an opt-out path for member-level schema validation when working with dy.Collection, enabling performance-sensitive workflows (e.g., very large frames) to apply only collection-level filters while assuming members were validated elsewhere.

Changes:

• Add skip_member_validation parameter to Collection.validate() and Collection.filter() to bypass per-member schema validation/filtering.
• Add FailureInfo._create_empty() to support returning empty failure info when member validation is skipped.
• Add collection-level tests covering eager/lazy validate/filter behavior with and without member validation.

Reviewed changes

Copilot reviewed 3 out of 3 changed files in this pull request and generated 7 comments.

File	Description
tests/collection/test_skip_member_validation.py	Adds tests for eager/lazy Collection.validate and Collection.filter when skipping member validation.
dataframely/filter_result.py	Adds an internal helper to construct an empty FailureInfo with the expected rule columns.
dataframely/collection/collection.py	Plumbs skip_member_validation through collection validation/filtering to bypass member schema checks.

Comments suppressed due to low confidence (1)

dataframely/collection/collection.py:611

• The filter docstring says the result members are filtered for rows “passing validation”. With skip_member_validation=True, member schemas are intentionally not applied, so the Returns section should describe that only collection-level filters are applied (and failures will be empty).

            skip_member_validation: Whether to skip filtering individual members and only
                apply the collection filters. **Use this option with caution** as it
                requires the caller to ensure that the individual members have been
                validated. This option is particularly useful in performance-critical
                scenarios where the members are known to already be valid.
            kwargs: Keyword arguments passed directly to :meth:`polars.collect_all` and
                :meth:`polars.LazyFrame.collect` when `eager=True`.

        Returns:
            A named tuple with fields `result` and `failure`. The `result` field
            provides a collection with all members filtered for the rows passing
            validation. Just like for validation, all members are guaranteed to maintain
            their input order. The `failure` field provides a dictionary mapping member
            names to their respective failure information.