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