test: aggregator coverage for zero_feedback, long_on_market, significant_price_drop
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Add 10 new tests covering the three previously untested flag paths:
- zero_feedback: flag fires + composite capped at 35 even with all-20 signals
- long_on_market: fires at >=5 sightings + >=14 days; NOT at <5 sightings or <14 days
- significant_price_drop: fires at >=20% below first-seen; NOT at <20% or no prior price
- established_retailer: duplicate_photo suppressed at feedback>=1000; fires below threshold

Also fix datetime.utcnow() deprecation in aggregator._days_since() and test helper
— replaced with timezone-aware datetime.now(timezone.utc) throughout.
This commit is contained in:
pyr0ball 2026-04-16 13:14:20 -07:00
parent 873b9a1413
commit 7005be02c2
2 changed files with 128 additions and 4 deletions

View file

@ -2,7 +2,7 @@
from __future__ import annotations
import json
from datetime import datetime
from datetime import datetime, timezone
from typing import Optional
from app.db.models import Seller, TrustScore
@ -60,9 +60,9 @@ def _days_since(iso: Optional[str]) -> Optional[int]:
dt = datetime.fromisoformat(iso.replace("Z", "+00:00"))
# Normalize to naive UTC so both paths (timezone-aware ISO and SQLite
# CURRENT_TIMESTAMP naive strings) compare correctly.
if dt.tzinfo is not None:
dt = dt.replace(tzinfo=None)
return (datetime.utcnow() - dt).days
if dt.tzinfo is None:
dt = dt.replace(tzinfo=timezone.utc)
return (datetime.now(timezone.utc) - dt).days
except ValueError:
return None

View file

@ -1,6 +1,14 @@
from datetime import datetime, timedelta, timezone
from app.db.models import Seller
from app.trust.aggregator import Aggregator
_ALL_20 = {k: 20 for k in ["account_age", "feedback_count", "feedback_ratio", "price_vs_market", "category_history"]}
def _iso_days_ago(n: int) -> str:
return (datetime.now(timezone.utc) - timedelta(days=n)).isoformat()
def test_composite_sum_of_five_signals():
agg = Aggregator()
@ -132,3 +140,119 @@ def test_new_account_not_flagged_when_age_absent():
result = agg.aggregate(scores, photo_hash_duplicate=False, seller=scraper_seller)
assert "new_account" not in result.red_flags_json
assert "account_under_30_days" not in result.red_flags_json
# ── zero_feedback ─────────────────────────────────────────────────────────────
def test_zero_feedback_adds_flag():
"""seller.feedback_count == 0 must add zero_feedback flag."""
agg = Aggregator()
seller = Seller(
platform="ebay", platform_seller_id="u", username="u",
account_age_days=365, feedback_count=0, feedback_ratio=1.0,
category_history_json="{}",
)
result = agg.aggregate(_ALL_20.copy(), photo_hash_duplicate=False, seller=seller)
assert "zero_feedback" in result.red_flags_json
def test_zero_feedback_caps_composite_at_35():
"""Even with perfect other signals (all 20/20), zero feedback caps composite at 35."""
agg = Aggregator()
seller = Seller(
platform="ebay", platform_seller_id="u", username="u",
account_age_days=365, feedback_count=0, feedback_ratio=1.0,
category_history_json="{}",
)
result = agg.aggregate(_ALL_20.copy(), photo_hash_duplicate=False, seller=seller)
assert result.composite_score <= 35
# ── long_on_market ────────────────────────────────────────────────────────────
def test_long_on_market_flagged_when_thresholds_met():
"""times_seen >= 5 AND listing age >= 14 days → long_on_market fires."""
agg = Aggregator()
result = agg.aggregate(
_ALL_20.copy(), photo_hash_duplicate=False, seller=None,
times_seen=5, first_seen_at=_iso_days_ago(20),
)
assert "long_on_market" in result.red_flags_json
def test_long_on_market_not_flagged_when_too_few_sightings():
"""times_seen < 5 must NOT trigger long_on_market even if listing is old."""
agg = Aggregator()
result = agg.aggregate(
_ALL_20.copy(), photo_hash_duplicate=False, seller=None,
times_seen=4, first_seen_at=_iso_days_ago(30),
)
assert "long_on_market" not in result.red_flags_json
def test_long_on_market_not_flagged_when_too_recent():
"""times_seen >= 5 but only seen for < 14 days → long_on_market must NOT fire."""
agg = Aggregator()
result = agg.aggregate(
_ALL_20.copy(), photo_hash_duplicate=False, seller=None,
times_seen=10, first_seen_at=_iso_days_ago(5),
)
assert "long_on_market" not in result.red_flags_json
# ── significant_price_drop ────────────────────────────────────────────────────
def test_significant_price_drop_flagged():
"""price >= 20% below price_at_first_seen → significant_price_drop fires."""
agg = Aggregator()
result = agg.aggregate(
_ALL_20.copy(), photo_hash_duplicate=False, seller=None,
price=75.00, price_at_first_seen=100.00, # 25% drop
)
assert "significant_price_drop" in result.red_flags_json
def test_significant_price_drop_not_flagged_when_drop_is_small():
"""< 20% drop must NOT trigger significant_price_drop."""
agg = Aggregator()
result = agg.aggregate(
_ALL_20.copy(), photo_hash_duplicate=False, seller=None,
price=95.00, price_at_first_seen=100.00, # 5% drop
)
assert "significant_price_drop" not in result.red_flags_json
def test_significant_price_drop_not_flagged_when_no_prior_price():
"""price_at_first_seen=None (first sighting) must NOT fire significant_price_drop."""
agg = Aggregator()
result = agg.aggregate(
_ALL_20.copy(), photo_hash_duplicate=False, seller=None,
price=50.00, price_at_first_seen=None,
)
assert "significant_price_drop" not in result.red_flags_json
# ── established retailer ──────────────────────────────────────────────────────
def test_established_retailer_suppresses_duplicate_photo():
"""feedback_count >= 1000 (established retailer) must suppress duplicate_photo flag."""
agg = Aggregator()
retailer = Seller(
platform="ebay", platform_seller_id="u", username="u",
account_age_days=1800, feedback_count=5000, feedback_ratio=0.99,
category_history_json="{}",
)
result = agg.aggregate(_ALL_20.copy(), photo_hash_duplicate=True, seller=retailer)
assert "duplicate_photo" not in result.red_flags_json
def test_non_retailer_does_not_suppress_duplicate_photo():
"""feedback_count < 1000 — duplicate_photo must still fire when hash matches."""
agg = Aggregator()
seller = Seller(
platform="ebay", platform_seller_id="u", username="u",
account_age_days=365, feedback_count=50, feedback_ratio=0.99,
category_history_json="{}",
)
result = agg.aggregate(_ALL_20.copy(), photo_hash_duplicate=True, seller=seller)
assert "duplicate_photo" in result.red_flags_json