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
2.8 KiB
Python
86 lines
2.8 KiB
Python
"""Convert raw eBay API responses into Snipe domain objects."""
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from __future__ import annotations
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import json
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from datetime import datetime, timezone
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from app.db.models import Listing, Seller
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def normalise_listing(raw: dict) -> Listing:
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price_data = raw.get("price", {})
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photos = []
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if "image" in raw:
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photos.append(raw["image"].get("imageUrl", ""))
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for img in raw.get("additionalImages", []):
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url = img.get("imageUrl", "")
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if url and url not in photos:
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photos.append(url)
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photos = [p for p in photos if p]
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listing_age_days = 0
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created_raw = raw.get("itemCreationDate", "")
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if created_raw:
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try:
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created = datetime.fromisoformat(created_raw.replace("Z", "+00:00"))
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listing_age_days = (datetime.now(timezone.utc) - created).days
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except ValueError:
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pass
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options = raw.get("buyingOptions", [])
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if "AUCTION" in options:
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buying_format = "auction"
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elif "BEST_OFFER" in options:
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buying_format = "best_offer"
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else:
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buying_format = "fixed_price"
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ends_at = None
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end_raw = raw.get("itemEndDate", "")
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if end_raw:
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try:
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ends_at = datetime.fromisoformat(end_raw.replace("Z", "+00:00")).isoformat()
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except ValueError:
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pass
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seller = raw.get("seller", {})
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return Listing(
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platform="ebay",
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platform_listing_id=raw["itemId"],
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title=raw.get("title", ""),
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price=float(price_data.get("value", 0)),
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currency=price_data.get("currency", "USD"),
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condition=raw.get("condition", "").lower(),
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seller_platform_id=seller.get("username", ""),
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url=raw.get("itemWebUrl", ""),
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photo_urls=photos,
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listing_age_days=listing_age_days,
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buying_format=buying_format,
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ends_at=ends_at,
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)
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def normalise_seller(raw: dict) -> Seller:
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feedback_pct = float(raw.get("feedbackPercentage", "0").strip("%")) / 100.0
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account_age_days = 0
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reg_date_raw = raw.get("registrationDate", "")
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if reg_date_raw:
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try:
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reg_date = datetime.fromisoformat(reg_date_raw.replace("Z", "+00:00"))
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account_age_days = (datetime.now(timezone.utc) - reg_date).days
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except ValueError:
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pass
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category_history = {}
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summary = raw.get("sellerFeedbackSummary", {})
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for entry in summary.get("feedbackByCategory", []):
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category_history[entry.get("categorySite", "")] = int(entry.get("count", 0))
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return Seller(
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platform="ebay",
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platform_seller_id=raw["username"],
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username=raw["username"],
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account_age_days=account_age_days,
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feedback_count=int(raw.get("feedbackScore", 0)),
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feedback_ratio=feedback_pct,
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category_history_json=json.dumps(category_history),
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)
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