pyr0ball
2ab41219f8
Scraper can't fetch seller profile age without following each listing's seller link. Using 0 as sentinel caused every scraped seller to trigger new_account and account_under_30_days red flags erroneously. - Seller.account_age_days: int → Optional[int] (None = not yet fetched) - Migration 003: recreate sellers table without NOT NULL constraint - MetadataScorer: return None for unknown age → score_is_partial=True - Aggregator: gate age flags on is not None - Scraper: account_age_days=None instead of 0
67 lines
2.5 KiB
Python
67 lines
2.5 KiB
Python
"""Five metadata trust signals, each scored 0–20."""
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from __future__ import annotations
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import json
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from typing import Optional
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from app.db.models import Seller
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ELECTRONICS_CATEGORIES = {"ELECTRONICS", "COMPUTERS_TABLETS", "VIDEO_GAMES", "CELL_PHONES"}
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class MetadataScorer:
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def score(
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self,
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seller: Seller,
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market_median: Optional[float],
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listing_price: float,
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) -> dict[str, Optional[int]]:
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return {
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"account_age": self._account_age(seller.account_age_days) if seller.account_age_days is not None else None,
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"feedback_count": self._feedback_count(seller.feedback_count),
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"feedback_ratio": self._feedback_ratio(seller.feedback_ratio, seller.feedback_count),
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"price_vs_market": self._price_vs_market(listing_price, market_median),
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"category_history": self._category_history(seller.category_history_json),
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}
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def _account_age(self, days: int) -> int:
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if days < 7: return 0
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if days < 30: return 5
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if days < 90: return 10
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if days < 365: return 15
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return 20
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def _feedback_count(self, count: int) -> int:
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if count < 3: return 0
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if count < 10: return 5
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if count < 50: return 10
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if count < 200: return 15
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return 20
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def _feedback_ratio(self, ratio: float, count: int) -> int:
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if ratio < 0.80 and count > 20: return 0
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if ratio < 0.90: return 5
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if ratio < 0.95: return 10
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if ratio < 0.98: return 15
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return 20
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def _price_vs_market(self, price: float, median: Optional[float]) -> Optional[int]:
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if median is None: return None # data unavailable → aggregator sets score_is_partial
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if median <= 0: return None
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ratio = price / median
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if ratio < 0.50: return 0 # >50% below = scam
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if ratio < 0.70: return 5 # >30% below = suspicious
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if ratio < 0.85: return 10
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if ratio <= 1.20: return 20
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return 15 # above market = still ok, just expensive
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def _category_history(self, category_history_json: str) -> int:
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try:
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history = json.loads(category_history_json)
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except (ValueError, TypeError):
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return 0
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electronics_sales = sum(
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v for k, v in history.items() if k in ELECTRONICS_CATEGORIES
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)
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if electronics_sales == 0: return 0
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if electronics_sales < 5: return 8
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if electronics_sales < 20: return 14
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return 20
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