pyr0ball
bccedb1fe5
eBay omits the 12-month positive percentage for returning sellers and buyer-only accounts with no recent sales. Previously ratio=0.0 with count>0 triggered established_bad_actor; now it returns None from the scorer (score_is_partial=True) and emits a soft no_recent_seller_data flag instead. ratio=0.0 with count=0 is still treated as no-history.
332 lines
14 KiB
Python
332 lines
14 KiB
Python
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()
|
|
scores = {
|
|
"account_age": 18, "feedback_count": 16,
|
|
"feedback_ratio": 20, "price_vs_market": 15,
|
|
"category_history": 14,
|
|
}
|
|
result = agg.aggregate(scores, photo_hash_duplicate=False, seller=None)
|
|
assert result.composite_score == 83
|
|
|
|
|
|
def test_hard_filter_new_account():
|
|
agg = Aggregator()
|
|
scores = {k: 20 for k in ["account_age", "feedback_count",
|
|
"feedback_ratio", "price_vs_market", "category_history"]}
|
|
young_seller = Seller(
|
|
platform="ebay", platform_seller_id="u", username="u",
|
|
account_age_days=3, feedback_count=0,
|
|
feedback_ratio=1.0, category_history_json="{}",
|
|
)
|
|
result = agg.aggregate(scores, photo_hash_duplicate=False, seller=young_seller)
|
|
assert "new_account" in result.red_flags_json
|
|
|
|
|
|
def test_hard_filter_bad_actor_established_account():
|
|
"""Established account (count > 20) with very bad ratio → hard filter."""
|
|
agg = Aggregator()
|
|
scores = {k: 10 for k in ["account_age", "feedback_count",
|
|
"feedback_ratio", "price_vs_market", "category_history"]}
|
|
bad_seller = Seller(
|
|
platform="ebay", platform_seller_id="u", username="u",
|
|
account_age_days=730, feedback_count=25, # count > 20
|
|
feedback_ratio=0.70, # ratio < 80% → hard filter
|
|
category_history_json="{}",
|
|
)
|
|
result = agg.aggregate(scores, photo_hash_duplicate=False, seller=bad_seller)
|
|
assert "established_bad_actor" in result.red_flags_json
|
|
|
|
|
|
def test_partial_score_flagged_when_signals_missing():
|
|
agg = Aggregator()
|
|
scores = {
|
|
"account_age": 18, "feedback_count": None, # None = unavailable
|
|
"feedback_ratio": 20, "price_vs_market": 15,
|
|
"category_history": 14,
|
|
}
|
|
result = agg.aggregate(scores, photo_hash_duplicate=False, seller=None)
|
|
assert result.score_is_partial is True
|
|
|
|
|
|
def test_suspicious_price_not_flagged_when_market_data_absent():
|
|
"""None price_vs_market (no market comp) must NOT trigger suspicious_price.
|
|
|
|
Regression guard: clean[] replaces None with 0, so naive `clean[...] == 0`
|
|
would fire even when the signal is simply unavailable.
|
|
"""
|
|
agg = Aggregator()
|
|
scores = {
|
|
"account_age": 15, "feedback_count": 15,
|
|
"feedback_ratio": 20, "price_vs_market": None, # no market data
|
|
"category_history": 0,
|
|
}
|
|
result = agg.aggregate(scores, photo_hash_duplicate=False, seller=None)
|
|
assert "suspicious_price" not in result.red_flags_json
|
|
|
|
|
|
def test_suspicious_price_flagged_when_price_genuinely_low():
|
|
"""price_vs_market == 0 (explicitly, meaning >50% below median) → flag fires."""
|
|
agg = Aggregator()
|
|
scores = {
|
|
"account_age": 15, "feedback_count": 15,
|
|
"feedback_ratio": 20, "price_vs_market": 0, # price is scam-level low
|
|
"category_history": 0,
|
|
}
|
|
result = agg.aggregate(scores, photo_hash_duplicate=False, seller=None)
|
|
assert "suspicious_price" in result.red_flags_json
|
|
|
|
|
|
def test_scratch_dent_flagged_from_title_slash_variant():
|
|
"""Title containing 'parts/repair' (slash variant, no 'or') must trigger scratch_dent_mentioned."""
|
|
agg = Aggregator()
|
|
scores = {k: 15 for k in ["account_age", "feedback_count",
|
|
"feedback_ratio", "price_vs_market", "category_history"]}
|
|
result = agg.aggregate(
|
|
scores, photo_hash_duplicate=False, seller=None,
|
|
listing_title="Generic Widget XL - Parts/Repair",
|
|
)
|
|
assert "scratch_dent_mentioned" in result.red_flags_json
|
|
|
|
|
|
def test_scratch_dent_flagged_from_condition_field():
|
|
"""eBay formal condition 'for parts or not working' must trigger scratch_dent_mentioned
|
|
even when the listing title contains no damage keywords."""
|
|
agg = Aggregator()
|
|
scores = {k: 15 for k in ["account_age", "feedback_count",
|
|
"feedback_ratio", "price_vs_market", "category_history"]}
|
|
result = agg.aggregate(
|
|
scores, photo_hash_duplicate=False, seller=None,
|
|
listing_title="Generic Widget XL",
|
|
listing_condition="for parts or not working",
|
|
)
|
|
assert "scratch_dent_mentioned" in result.red_flags_json
|
|
|
|
|
|
def test_scratch_dent_not_flagged_for_clean_listing():
|
|
"""Clean title + 'New' condition must NOT trigger scratch_dent_mentioned."""
|
|
agg = Aggregator()
|
|
scores = {k: 15 for k in ["account_age", "feedback_count",
|
|
"feedback_ratio", "price_vs_market", "category_history"]}
|
|
result = agg.aggregate(
|
|
scores, photo_hash_duplicate=False, seller=None,
|
|
listing_title="Generic Widget XL",
|
|
listing_condition="new",
|
|
)
|
|
assert "scratch_dent_mentioned" not in result.red_flags_json
|
|
|
|
|
|
def test_new_account_not_flagged_when_age_absent():
|
|
"""account_age_days=None (scraper tier) must NOT trigger new_account or account_under_30_days."""
|
|
agg = Aggregator()
|
|
scores = {k: 10 for k in ["account_age", "feedback_count",
|
|
"feedback_ratio", "price_vs_market", "category_history"]}
|
|
scraper_seller = Seller(
|
|
platform="ebay", platform_seller_id="u", username="u",
|
|
account_age_days=None, # not fetched at scraper tier
|
|
feedback_count=50, feedback_ratio=0.99, category_history_json="{}",
|
|
)
|
|
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
|
|
|
|
|
|
# ── declining_ratio (high-volume seller edge case, snipe#52) ─────────────────
|
|
|
|
def test_declining_ratio_soft_flag_for_high_volume_seller():
|
|
"""High-volume seller (count > 500) with declining but not catastrophic ratio
|
|
gets declining_ratio soft flag, NOT the hard established_bad_actor flag.
|
|
|
|
Edge case: 12-month ratio may reflect only a small recent sample for sellers
|
|
with large lifetime feedback counts — hard-flagging is disproportionate.
|
|
"""
|
|
agg = Aggregator()
|
|
scores = {k: 10 for k in ["account_age", "feedback_count",
|
|
"feedback_ratio", "price_vs_market", "category_history"]}
|
|
high_vol = Seller(
|
|
platform="ebay", platform_seller_id="u", username="u",
|
|
account_age_days=2000, feedback_count=800, # count > 500
|
|
feedback_ratio=0.75, # < 0.80 but > 0.60
|
|
category_history_json="{}",
|
|
)
|
|
result = agg.aggregate(scores, photo_hash_duplicate=False, seller=high_vol)
|
|
assert "declining_ratio" in result.red_flags_json
|
|
assert "established_bad_actor" not in result.red_flags_json
|
|
|
|
|
|
def test_established_bad_actor_still_fires_for_catastrophic_high_volume_ratio():
|
|
"""High-volume seller (count > 500) with catastrophically bad ratio (< 60%)
|
|
still gets the hard established_bad_actor flag — not just declining_ratio."""
|
|
agg = Aggregator()
|
|
scores = {k: 10 for k in ["account_age", "feedback_count",
|
|
"feedback_ratio", "price_vs_market", "category_history"]}
|
|
bad_high_vol = Seller(
|
|
platform="ebay", platform_seller_id="u", username="u",
|
|
account_age_days=2000, feedback_count=800,
|
|
feedback_ratio=0.50, # < 0.60 threshold → still hard flag
|
|
category_history_json="{}",
|
|
)
|
|
result = agg.aggregate(scores, photo_hash_duplicate=False, seller=bad_high_vol)
|
|
assert "established_bad_actor" in result.red_flags_json
|
|
assert "declining_ratio" 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
|
|
|
|
|
|
# ── #52: buyer-only / returning seller (ratio=0.0, count>0) ──────────────────
|
|
|
|
def test_zero_ratio_with_count_gives_no_recent_seller_data_flag():
|
|
"""Seller with 117 lifetime feedbacks (buyer-only) has ratio=0.0 parsed from page.
|
|
Must get no_recent_seller_data soft flag, NOT established_bad_actor."""
|
|
agg = Aggregator()
|
|
scores = {k: 10 for k in ["account_age", "feedback_count",
|
|
"feedback_ratio", "price_vs_market", "category_history"]}
|
|
buyer_only = Seller(
|
|
platform="ebay", platform_seller_id="u", username="jjcpryz",
|
|
account_age_days=1200, feedback_count=117, feedback_ratio=0.0,
|
|
category_history_json="{}",
|
|
)
|
|
result = agg.aggregate(scores, photo_hash_duplicate=False, seller=buyer_only)
|
|
assert "no_recent_seller_data" in result.red_flags_json
|
|
assert "established_bad_actor" not in result.red_flags_json
|
|
|
|
|
|
|
|
def test_established_bad_actor_still_fires_for_genuinely_bad_ratio():
|
|
"""ratio=0.75 (not zero) with moderate count → established_bad_actor still fires."""
|
|
agg = Aggregator()
|
|
scores = {k: 10 for k in ["account_age", "feedback_count",
|
|
"feedback_ratio", "price_vs_market", "category_history"]}
|
|
bad = Seller(
|
|
platform="ebay", platform_seller_id="u", username="u",
|
|
account_age_days=500, feedback_count=100, feedback_ratio=0.75,
|
|
category_history_json="{}",
|
|
)
|
|
result = agg.aggregate(scores, photo_hash_duplicate=False, seller=bad)
|
|
assert "established_bad_actor" in result.red_flags_json
|
|
assert "no_recent_seller_data" not in result.red_flags_json
|