Release v0.2: offline profiling and verified rule baselines - #1
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This release adds offline dataset profiling and rule-based baseline cleaning. Baseline snapshots preserve stable row IDs and nulls; evaluation checks schema, CSV hashes, and removal ledgers and correctly handles deletions from the middle of a dataset. Legacy outputs without row mappings report unavailable metrics.
Validation: 136 tests pass on Python 3.11 and 3.12, together with Ruff, environment checks, locked dependencies, package builds, and isolated installed-wheel smoke tests. The offline demo processes 200 rows with 10 removals and no model calls.