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7cc1e71 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 | """Run the corrector against the bundled dataset and report per-category accuracy."""
import json
import time
from collections import defaultdict
from pathlib import Path
import pytest
from spelling.corrector import SpellingCorrector
DATASET = Path(__file__).parent.parent.parent / "dataset" / "samples.jsonl"
@pytest.fixture(scope="module")
def samples():
return [json.loads(line) for line in DATASET.read_text().splitlines() if line.strip()]
def test_dataset_accuracy(samples, capsys):
c = SpellingCorrector()
results = defaultdict(lambda: {"hits": 0, "total": 0, "ms": 0.0})
for ex in samples:
cat = ex["category"]
if ex.get("domain_terms"):
c.add_domain_terms(ex["domain_terms"])
start = time.perf_counter()
if cat == "spell":
out = c.correct(ex["original"])
elif cat == "grammar":
out = c.correct_compound(ex["original"])
elif cat == "phonetic":
out = c.correct_phonetic(ex["original"])
elif cat == "domain":
out = c.correct(ex["original"])
else:
continue
elapsed = (time.perf_counter() - start) * 1000
results[cat]["total"] += 1
results[cat]["ms"] += elapsed
if out.lower().strip() == ex["corrected"].lower().strip():
results[cat]["hits"] += 1
with capsys.disabled():
print()
print(f"{'category':<10} {'hits':>5} {'total':>6} {'acc':>7} {'mean ms':>8}")
print("-" * 42)
for cat, r in sorted(results.items()):
acc = r["hits"] / r["total"] if r["total"] else 0
mean_ms = r["ms"] / r["total"] if r["total"] else 0
print(f"{cat:<10} {r['hits']:>5} {r['total']:>6} {acc:>6.0%} {mean_ms:>7.2f}ms")
total_acc = sum(r["hits"] for r in results.values()) / sum(r["total"] for r in results.values())
assert total_acc >= 0.70, f"Total accuracy {total_acc:.0%} below 70% floor"
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