SQL diagnostics for purchase_trade business rules
These scripts are read-only diagnostics for a PostgreSQL test database.
They exist to support the same business rules enforced by Python guards. The expected workflow is:
- write the consultant/developer rule in the thematic documentation;
- enforce the invariant in the application code when feasible;
- provide a read-only SQL diagnostic to audit existing data.
quantity_consistency_checks.sql
Checks the two core lot quantity invariants documented in
lots-and-quantities.md and lots-and-quantities.en.md.
Zero lot_qt rows are ignored completely. They are treated as legitimate
memory of an open quantity consumed by a physical lot. This is required because
lot_qt represents usable open forecast and stops at zero, while the virtual
lot may become negative to compensate the difference between theoretical and
executed quantity. A non-zero lot_qt row without both lot_p and lot_s is
reported as anomalous.
Run it on a restored test database:
\i modules/purchase_trade/docs/business/sql/quantity_consistency_checks.sql
The script returns rows only when it finds a potential issue.
Main columns:
check_name: invariant or diagnostic that failed.contract_model:purchase.purchaseorsale.sale.contract_id: database id of the contract.contract_number: purchase or sale contract number.line_id:purchase.lineorsale.lineid depending on the check.virtual_lot_id: virtual lot involved in the inconsistency.observed_value: value found in the database.expected_value: value required by the business rule.diff: observed minus expected.detail: human-readable explanation.
Cross-category UoM rows are reported as manual-review diagnostics because the Python code may pass explicit conversion factors that cannot be inferred safely from SQL alone.