fix(salary): validate category shape and add --validate preflight (#156)

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 is contained in:
Alaa-Taieb
2026-07-15 07:53:01 +02:00
committed by GitHub
co-authored by Tunic Assistant
parent 47118dcbf2
commit 55ba1c1652
3 changed files with 189 additions and 12 deletions
+102 -11
View File
@@ -51,39 +51,94 @@ def fail_data_error(message):
sys.exit(1)
def validate_data(data):
"""Validate the salary data shape before lookups use it."""
def collect_validation_issues(data):
"""Return (errors, warnings) for the salary data shape.
errors -> hard problems that make lookups crash or emit wrong output
(these cause validate_data() to exit(1)).
warnings -> usability concerns that still work (e.g. duplicate company
names); --validate reports them but exits 0.
"""
errors = []
warnings = []
if not isinstance(data, dict):
fail_data_error("top-level JSON value must be an object")
errors.append("top-level JSON value must be an object")
return errors, warnings
metadata = data.get("metadata", {})
if metadata is not None and not isinstance(metadata, dict):
fail_data_error("'metadata' must be an object when provided")
errors.append("'metadata' must be an object when provided")
companies = data.get("companies")
if not isinstance(companies, list):
fail_data_error("'companies' must be a list")
errors.append("'companies' must be a list")
return errors, warnings
seen_companies = {}
for index, entry in enumerate(companies, start=1):
if not isinstance(entry, dict):
fail_data_error(f"companies[{index}] must be an object")
errors.append(f"companies[{index}] must be an object")
continue
company = entry.get("company")
if not isinstance(company, str) or not company.strip():
fail_data_error(f"companies[{index}].company must be a non-empty string")
errors.append(f"companies[{index}].company must be a non-empty string")
else:
key = company.lower()
if key in seen_companies:
warnings.append(
f"Duplicate company name '{company}' "
f"(companies[{seen_companies[key]}] and companies[{index}])"
)
else:
seen_companies[key] = index
city = entry.get("city")
if city is not None and not isinstance(city, str):
fail_data_error(f"companies[{index}].city must be a string when provided")
errors.append(f"companies[{index}].city must be a string when provided")
categories = entry.get("categories", {})
if categories is not None and not isinstance(categories, dict):
fail_data_error(f"companies[{index}].categories must be an object when provided")
errors.append(f"companies[{index}].categories must be an object when provided")
elif categories:
for cat_label, cat_data in categories.items():
if not isinstance(cat_data, dict):
errors.append(
f"companies[{index}].categories.{cat_label} must be an object "
f"with 'count' and/or 'index' (got {type(cat_data).__name__})"
)
continue
count = cat_data.get("count")
if count is not None and not isinstance(count, (int, float)):
errors.append(
f"companies[{index}].categories.{cat_label}.count must be a "
f"number (got {type(count).__name__})"
)
index_val = cat_data.get("index")
if index_val is not None and not isinstance(index_val, (int, float, str)):
errors.append(
f"companies[{index}].categories.{cat_label}.index must be a "
f"number or string (got {type(index_val).__name__})"
)
return errors, warnings
def validate_data(data):
"""Validate the salary data shape before lookups use it.
Preserves historical behavior: exits(1) on the first hard error with the
same user-facing message, and returns data unchanged when valid.
"""
errors, _ = collect_validation_issues(data)
if errors:
fail_data_error(errors[0])
return data
def load_data():
def read_raw_data():
"""Load and JSON-parse salary_data.json; exit with a helpful message if missing/invalid."""
if not DATA_FILE.exists():
print("Error: salary_data.json not found.", file=sys.stderr)
print("", file=sys.stderr)
@@ -98,7 +153,12 @@ def load_data():
data = json.load(f)
except json.JSONDecodeError as exc:
fail_data_error(f"invalid JSON at line {exc.lineno}, column {exc.colno}: {exc.msg}")
return validate_data(data)
return data
def load_data():
"""Load, parse, and validate salary_data.json for lookups."""
return validate_data(read_raw_data())
def normalize(s):
@@ -292,14 +352,45 @@ def format_entry(entry, metadata):
return "\n".join(lines)
def print_validation_report(errors, warnings):
"""Print an actionable validation report. Returns the process exit code."""
if not errors and not warnings:
print("OK - no issues found.")
return 0
print(f"Found {len(errors) + len(warnings)} issue(s):")
if errors:
print(" Errors:")
for i, msg in enumerate(errors, start=1):
print(f" [{i}] {msg}")
if warnings:
print(" Warnings:")
for i, msg in enumerate(warnings, start=1):
print(f" [{i}] {msg}")
if errors:
print("")
print("Fix the errors above, then re-run. See tools/README_SALARY_TOOL.md "
"for the expected format.")
return 1
return 0
def main():
parser = argparse.ArgumentParser(description="Salary Benchmark Lookup")
parser.add_argument("company", nargs="?", help="Company name to search for")
parser.add_argument("--city", help="Filter by city name")
parser.add_argument("--json", action="store_true", help="Output as JSON")
parser.add_argument("--list-all", action="store_true", help="List all companies")
parser.add_argument("--validate", action="store_true",
help="Validate salary_data.json and print a report, then exit")
args = parser.parse_args()
if args.validate:
data = read_raw_data()
errors, warnings = collect_validation_issues(data)
print(f"Validating {DATA_FILE.name} ...")
print("")
sys.exit(print_validation_report(errors, warnings))
data = load_data()
metadata = data.get("metadata", {})
companies = data.get("companies", [])
+85 -1
View File
@@ -3,8 +3,9 @@
import io
import tempfile
import unittest
from contextlib import redirect_stderr
from contextlib import redirect_stderr, redirect_stdout
from pathlib import Path
from unittest import mock
import salary_lookup
from salary_lookup import (
@@ -15,6 +16,7 @@ from salary_lookup import (
match_score,
search_company,
validate_data,
collect_validation_issues,
)
@@ -241,6 +243,88 @@ class ValidateDataTests(unittest.TestCase):
)
class ValidateDataShapeTests(ValidateDataTests):
"""Category-shape and duplicate-name checks (reuses assert_invalid_data)."""
def test_malformed_category_value_rejected(self):
data = {"companies": [{"company": "Acme", "categories": {"eng": "not_a_dict"}}]}
self.assert_invalid_data(data, "must be an object with 'count' and/or 'index'")
def test_non_numeric_count_rejected(self):
data = {
"companies": [
{"company": "Acme", "categories": {"eng": {"count": "many"}}}
]
}
self.assert_invalid_data(data, "count must be a number")
def test_duplicate_company_name_is_warning(self):
data = {
"companies": [
{"company": "Acme"},
{"company": "Other Corp"},
{"company": "Acme"},
]
}
errors, warnings = collect_validation_issues(data)
self.assertEqual(errors, [])
self.assertEqual(len(warnings), 1)
self.assertIn("Duplicate company name 'Acme'", warnings[0])
def test_valid_categories_have_no_issues(self):
data = {
"companies": [
{"company": "Acme", "categories": {"eng": {"count": 5, "index": 108.5}}}
]
}
errors, warnings = collect_validation_issues(data)
self.assertEqual(errors, [])
self.assertEqual(warnings, [])
class ValidateFlagTests(unittest.TestCase):
"""End-to-end checks for the --validate pre-flight flow."""
def _run_validate(self, payload):
with tempfile.TemporaryDirectory() as tmpdir:
data_file = Path(tmpdir) / "salary_data.json"
data_file.write_text(payload, encoding="utf-8")
original_data_file = salary_lookup.DATA_FILE
salary_lookup.DATA_FILE = data_file
argv_patch = mock.patch("sys.argv", ["salary_lookup.py", "--validate"])
argv_patch.start()
try:
stdout = io.StringIO()
with self.assertRaises(SystemExit) as raised:
with redirect_stdout(stdout):
salary_lookup.main()
return raised.exception.code, stdout.getvalue()
finally:
argv_patch.stop()
salary_lookup.DATA_FILE = original_data_file
def test_validate_flag_exits_1_on_errors(self):
code, out = self._run_validate(
'{"companies": [{"company": "Acme", "categories": {"eng": "not_a_dict"}}]}'
)
self.assertEqual(code, 1)
self.assertIn("must be an object with 'count' and/or 'index'", out)
def test_validate_flag_exits_0_on_clean(self):
code, out = self._run_validate(
'{"companies": [{"company": "Acme", "categories": {"eng": {"count": 5}}}]}'
)
self.assertEqual(code, 0)
self.assertIn("OK", out)
def test_validate_flag_exits_0_on_duplicates_only(self):
code, out = self._run_validate(
'{"companies": [{"company": "Acme"}, {"company": "Acme"}]}'
)
self.assertEqual(code, 0)
self.assertIn("Duplicate company name", out)
class UtilityTests(unittest.TestCase):
def test_normalize_strips_suffix_and_noise(self):
self.assertEqual(normalize("Novo Nordisk A/S"), "novonordisk")
+2
View File
@@ -113,6 +113,7 @@ python3 salary_lookup.py "Novo Nordisk"
python3 salary_lookup.py "Ørsted" --city "Fredericia"
python3 salary_lookup.py "COWI" --json
python3 salary_lookup.py --list-all
python3 salary_lookup.py --validate # pre-flight check your salary_data.json
```
## Important notes
@@ -120,3 +121,4 @@ python3 salary_lookup.py --list-all
- The data file (`salary_data.json`) is **excluded from git** (see `.gitignore`). Your salary data may be proprietary or confidential.
- If the data file is missing, `salary_lookup.py` exits with a helpful error message and the `/apply` workflow skips the salary benchmark step.
- The fuzzy matcher handles Danish company name variations: legal suffixes, Nordic characters, anglicized spellings, and partial matches.
- `--validate` checks your data file for malformed category values and duplicate company names and prints a report, without performing a lookup.