validate_data() accepted category values that are not {count?, index?}
objects. They slipped through to format_entry(), which then raised
AttributeError on a normal table lookup (or serialized a malformed shape
under --json). It also accepted duplicate company names silently.
- collect_validation_issues() now also flags a non-object category value
(and non-numeric count / non number-or-string index) as a hard error,
and duplicate company names as a warning.
- validate_data() keeps its eager-fail behavior (same messages), so
existing tests and load_data() are unchanged.
- --validate runs the checks standalone and prints an actionable report
(exit 1 on errors, 0 on warnings-only/clean), letting users pre-flight
their BYO salary_data.json.
Reproduced on master: validate_data({'companies':[{'company':'Acme',
'categories':{'eng':'not_a_dict'}}]}) returns without error, but
format_entry then raises AttributeError.
Co-authored-by: Tunic Assistant <assistant@tunic.local>
This commit improves the performance and consistency of the salary tools:
- Redundant query normalization and word extraction are eliminated in salary_lookup.py by pre-calculating representations once before the search loop.
- A match_score_optimized helper is introduced to perform the comparison using the pre-calculated query data, preserving full backward compatibility for match_score.
- Normalization in tools/convert_salary_excel.py is unified: paired column headers now consistently substitute spaces and dashes with underscores (e.g. 'software_engineering') to match the single-column formatting.
- Unit test coverage is significantly expanded in tests/test_salary_lookup.py and tests/test_convert_salary_excel.py to cover normalization, anglicization, search filtering, and matching behaviors.
