refactor(salary): optimize search match scoring and normalize Excel category keys (#101)

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.

tests/test_convert_salary_excel.py

@@ -77,6 +77,16 @@ class DetectColumnTypeTests(unittest.TestCase):
 
         self.assertEqual(companies[0]["categories"]["accounting"], {"count": 12, "index": 105.5})
 
+    def test_parse_sheet_normalizes_paired_category_name_with_underscores(self):
+        ws = FakeWorksheet([
+            ("Company", "Software Engineering Count", "Software Engineering Index"),
+            ("Example Corp", 8, 110.0),
+        ])
+
+        companies = parse_sheet(ws)
+
+        self.assertEqual(companies[0]["categories"]["software_engineering"], {"count": 8, "index": 110.0})
+
 
 if __name__ == "__main__":
     unittest.main()