Audit high-volume power sellers, flippers, and merchant storefronts across GooFish (闲鱼). Extract entire merchant inventory catalogs, historical sold volumes, and credibility metrics.
{
"rowStatus": "ok",
"recordType": "item",
"sellerId": "2217730303960",
"sellerName": "数码电玩玩家",
"sellerCreditRating": "信用极好",
"sellerLocation": "广东深圳",
"itemId": "847291847192",
"title": "任天堂 Switch OLED 日版 续航增强版 白色 99新",
"price": 1450.0,
"originalPrice": 2199.0,
"status": "onsale",
"freeShipping": true,
"url": "https://www.goofish.com/item?id=847291847192"
}
Built specifically for high-throughput enterprise pipelines with zero credential leakage.
Extract every active item a seller has listed, including tiered pricing, descriptions, and uploaded photos.
Analyze sold item counts and transaction velocity to identify top-performing secondary market categories.
Collect seller average response times, active hours, and follower counts to gauge merchant professionalism.
Audit merchant account creation date, dispute ratios, and Zhima credit rating to identify dependable suppliers.
Trigger extractions via the official Apify Client or standard REST endpoints.
from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run_input = {
"sellerInputs": [
"https://www.goofish.com/personal?spm=a21ybx.item.itemHeader.1.740c3da6vQDa24&userId=2216555697343"
],
"includeListings": True,
"includeReviews": True,
"outputFormat": "nested",
"maxListings": 20,
"maxReviews": 30,
"detailLevel": "summary",
"statusFilter": "all"
}
run = client.actor("unitbytes/goofish-xianyu-seller-scraper").call(run_input=run_input)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item.get("title"), item.get("sellerName"), item.get("price"))
Yes. The scraper handles pagination automatically, extracting hundreds of listings per storefront up to your specified maximum.
By monitoring top power-sellers on Xianyu, you can detect underpriced inventory, bulk liquidation lots, and trending collector commodities.
Zero login required. Provide the seller profile URL or user ID and the scraper extracts public storefront data automatically.
Data is delivered in normalized JSON with nested listing arrays, or flattened tabular rows for easy Excel/CSV analysis.
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Our data engineering team provides private cluster deployments, custom webhook integrations, continuous schema monitoring, and high-frequency delivery directly to BigQuery, Snowflake, or AWS S3.
Start running immediately on UnitBytes Cloud with zero infrastructure setup, or contact our engineering team for dedicated S3/BigQuery delivery pipelines.