pyr0ball
6ec0f957b9
Auction metadata: - Listing model gains buying_format + ends_at fields - Migration 002 adds columns to existing databases - scraper.py: parse s-item__time-left → absolute ends_at ISO timestamp - normaliser.py: extract buyingOptions + itemEndDate from Browse API - store.py: save/get updated for new fields Easter eggs (app/ui/components/easter_eggs.py): - Konami code detector (JS → URL param → Streamlit rerun) - Web Audio API snipe call synthesis, gated behind sidebar checkbox (disabled by default for safety/accessibility) - "The Steal" gold shimmer: trust ≥ 90, price 15–30% below market, no suspicious_price flag - Auction de-emphasis: soft caption when > 1h remaining UI updates: - listing_row: steal banner + auction notice per row - Search: inject CSS, check snipe mode, "Ending soon" sort option, pass market_price from comp cache to row renderer - app.py: Konami detector + audio enable/disable sidebar toggle Tests: 22 new tests (72 total, all green)
86 lines
2.3 KiB
Python
86 lines
2.3 KiB
Python
"""Dataclasses for all Snipe domain objects."""
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from __future__ import annotations
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from dataclasses import dataclass, field
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from typing import Optional
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@dataclass
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class Seller:
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platform: str
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platform_seller_id: str
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username: str
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account_age_days: int
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feedback_count: int
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feedback_ratio: float # 0.0–1.0
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category_history_json: str # JSON blob of past category sales
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id: Optional[int] = None
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fetched_at: Optional[str] = None
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@dataclass
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class Listing:
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platform: str
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platform_listing_id: str
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title: str
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price: float
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currency: str
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condition: str
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seller_platform_id: str
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url: str
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photo_urls: list[str] = field(default_factory=list)
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listing_age_days: int = 0
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buying_format: str = "fixed_price" # "fixed_price", "auction", "best_offer"
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ends_at: Optional[str] = None # ISO8601 auction end time; None for fixed-price
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id: Optional[int] = None
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fetched_at: Optional[str] = None
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trust_score_id: Optional[int] = None
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@dataclass
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class TrustScore:
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listing_id: int
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composite_score: int # 0–100
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account_age_score: int # 0–20
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feedback_count_score: int # 0–20
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feedback_ratio_score: int # 0–20
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price_vs_market_score: int # 0–20
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category_history_score: int # 0–20
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photo_hash_duplicate: bool = False
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photo_analysis_json: Optional[str] = None
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red_flags_json: str = "[]"
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score_is_partial: bool = False
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id: Optional[int] = None
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scored_at: Optional[str] = None
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@dataclass
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class MarketComp:
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platform: str
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query_hash: str
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median_price: float
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sample_count: int
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expires_at: str # ISO8601 — checked against current time
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id: Optional[int] = None
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fetched_at: Optional[str] = None
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@dataclass
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class SavedSearch:
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"""Schema scaffolded in v0.1; background monitoring wired in v0.2."""
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name: str
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query: str
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platform: str
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filters_json: str = "{}"
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id: Optional[int] = None
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created_at: Optional[str] = None
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last_run_at: Optional[str] = None
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@dataclass
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class PhotoHash:
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"""Perceptual hash store for cross-search dedup (v0.2+). Schema scaffolded in v0.1."""
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listing_id: int
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photo_url: str
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phash: str # hex string from imagehash
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id: Optional[int] = None
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first_seen_at: Optional[str] = None
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