docs: document numeric target workflow - #26
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📝 WalkthroughWalkthroughThe documentation adds numeric target creation and replacement semantics, backend support rules, examples, and bounded SQLite measurements with methodology, results, plan identities, and limitations. ChangesNumeric target documentation
Priority: ⬇️ Low Estimated code review effort: 1 (Trivial) | ~5 minutes Merge Risk: 🔵 Low · up to The new numeric-target guidance and bounded SQLite measurements are documentation-only, but the published measurement record may not fully represent its stated input cycle and does not clearly define fixture isolation for each trial. Clarifying these details would make the results reliably interpretable. 🚥 Pre-merge checks | ✅ 5✅ Passed checks (5 passed)
✨ Finishing Touches🧪 Generate unit tests (beta)
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Actionable comments posted: 2
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Inline comments:
In `@docs/transformations.md`:
- Around line 211-213: Update the 100-case workload description around the input
cycle so all eight fixtures are represented consistently: either change the case
count to a multiple of eight, or explicitly document and validate the intended
partial-cycle coverage, including the final four cases.
- Around line 203-210: Clarify the benchmark description to state that every
warm-up and timed apply started from a freshly reset fixture database,
preserving the existing per-variant and per-repetition setup details. If the
original harness reused databases across calls, rerun the benchmark matrix with
one correctly initialized fixture per trial before updating the documentation.
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docs/transformations.md
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Summary
COMPUTEcreate-versus-replace binding and sequentialIFsemantics;RECODE ... INTOcreate versus canonical replace behavior, including explicitELSE = SYSMISfor pre-provisioned targets;Scope
Documentation only:
docs/transformations.md. No production code, API, schema, dependency, fixture, CI, or benchmark artifacts changed.The measured evidence is local SQLite only at Python
63a66d6589aeb8fdc4820d5e7217fc13c61ef3b9with specification reference930345b922af4f43b0e622be02d4b12ebfeb08eb. It makes no service-latency or release-speedup claim.Verification
git diff --check.venv/bin/python -m pytest -p no:cacheprovider tests/test_conditional_inplace_transform.py::test_exact_bounded_program_applies_data_and_both_catalogs tests/test_conditional_inplace_transform.py::test_injected_boundary_failure_leaves_no_partial_apply tests/test_cli.py::test_cli_installs_schema_and_applies_plan_or_spss— 6 passed;.venv/bin/python -m pytest -p no:cacheprovider -m 'not services'— 408 passed, 9 skipped, 53 deselected.Review notes
No source tests or production behavior changed. Local read-only review completed with no findings after fixing recipe comments and documenting the measured fixture cycle/metadata. Please do not auto-merge; maintainer review/merge remains required.
Summary by CodeRabbit
COMPUTE,IF, andRECODE ... INTO.NULLhandling, and backend-specific support.