snipe/app/platforms/__init__.py
pyr0ball 98695b00f0 feat(snipe): eBay trust scoring MVP — search, filters, enrichment, comps
Core trust scoring:
- Five metadata signals (account age, feedback count/ratio, price vs market,
  category history), composited 0–100
- CV-based price signal suppression for heterogeneous search results
  (e.g. mixed laptop generations won't false-positive suspicious_price)
- Expanded scratch/dent title detection: evasive redirects, functional problem
  phrases, DIY/repair indicators
- Hard filters: new_account, established_bad_actor
- Soft flags: low_feedback, suspicious_price, duplicate_photo, scratch_dent,
  long_on_market, significant_price_drop

Search & filtering:
- Browse API adapter (up to 200 items/page) + Playwright scraper fallback
- OR-group query expansion for comprehensive variant coverage
- Must-include (AND/ANY/groups), must-exclude, category, price range filters
- Saved searches with full filter round-trip via URL params

Seller enrichment:
- Background BTF /itm/ scraping for account age (Kasada-safe headed Chromium)
- On-demand enrichment: POST /api/enrich + ListingCard ↻ button
- Category history derived from Browse API categories field (free, no extra calls)
- Shopping API GetUserProfile inline enrichment for API adapter

Market comps:
- eBay Marketplace Insights API with Browse API fallback (catches 403 + 404)
- Comps prioritised in ThreadPoolExecutor (submitted first)

Infrastructure:
- Staging DB fields: times_seen, first_seen_at, price_at_first_seen, category_name
- Migrations 004 (staging tracking) + 005 (listing category)
- eBay webhook handler stub
- Cloud compose stack (compose.cloud.yml)
- Vue frontend: search store, saved searches store, ListingCard, filter sidebar

Docs:
- README fully rewritten to reflect MVP status + full feature documentation
- Roadmap table linked to all 13 Forgejo issues
2026-03-26 23:37:09 -07:00

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1.2 KiB
Python

"""PlatformAdapter abstract base and shared types."""
from __future__ import annotations
from abc import ABC, abstractmethod
from dataclasses import dataclass, field
from typing import Optional
from app.db.models import Listing, Seller
@dataclass
class SearchFilters:
max_price: Optional[float] = None
min_price: Optional[float] = None
condition: Optional[list[str]] = field(default_factory=list)
location_radius_km: Optional[int] = None
pages: int = 1 # number of result pages to fetch (48 listings/page)
must_include: list[str] = field(default_factory=list) # client-side title filter
must_exclude: list[str] = field(default_factory=list) # forwarded to eBay -term AND client-side
category_id: Optional[str] = None # eBay category ID (e.g. "27386" = GPUs)
class PlatformAdapter(ABC):
@abstractmethod
def search(self, query: str, filters: SearchFilters) -> list[Listing]: ...
@abstractmethod
def get_seller(self, seller_platform_id: str) -> Optional[Seller]: ...
@abstractmethod
def get_completed_sales(self, query: str) -> list[Listing]:
"""Fetch recently completed/sold listings for price comp data."""
...