# 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:
1. write the consultant/developer rule in the thematic documentation;
2. enforce the invariant in the application code when feasible;
3. 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.purchase or sale.sale.
contract_id: database id of the contract.
contract_number: purchase or sale contract number.
line_id: purchase.line or sale.line id 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.