The definitive enterprise data engine for Xiaohongshu (小红书 / RedNote). Extract viral consumer trends, engagement metrics, and unwatermarked multimedia at scale without account bans or cookie degradation.
{
"id": "6a7568cc00000000050328d9",
"title": "Autumn Capsule Wardrobe: 5 Minimalist Outfits for Office & Daily Wear",
"desc": "Sharing my favorite autumn minimalist styling guide! Coat from vintage thrift store, trousers matched with loafers. #AutumnOOTD #CapsuleWardrobe #MinimalistStyle #OfficeFashion",
"type": "video",
"url": "https://www.xiaohongshu.com/explore/6a7568cc00000000050328d9?xsec_token=AB4829fa...&xsec_source=pc_feed",
"author": {
"id": "647b64a400000000120349b8",
"nickname": "Elena Daily Style",
"avatarUrl": "https://sns-avatar-qc.xhscdn.com/avatar/647b64a400000000120349b8.jpg",
"profileUrl": "https://www.xiaohongshu.com/user/profile/647b64a400000000120349b8",
"redId": "elena_fashion",
"bio": "Fashion & Lifestyle Creator in Shanghai | Daily Outfit Inspo",
"isVerified": false
},
"likedCount": 18450,
"collectedCount": 12890,
"commentCount": 420,
"sharedCount": 3150,
"canShare": true,
"viralScore": 62450.0,
"engagementRate": 89.21,
"imageCount": 2,
"hasVideo": true,
"isLivePhoto": false,
"coverUrl": "https://sns-img-qc.xhscdn.com/1040g008323luhj1vnk5g5qi11c5jv001abram18",
"coverDimensions": {
"width": 1080,
"height": 1440
},
"images": [
"https://sns-img-qc.xhscdn.com/1040g008323luhj1vnk5g5qi11c5jv001abram18",
"https://sns-img-qc.xhscdn.com/1040g2sg323jg6lprgmig5n7igt3h9u3s8t45lfo"
],
"videoUrl": "https://sns-video-qc.xhscdn.com/stream/110/259/01e479a83bc.mp4",
"videoDuration": 48,
"ipLocation": "上海",
"tags": [
"AutumnOOTD",
"CapsuleWardrobe",
"MinimalistStyle"
],
"tagCount": 4,
"tagList": [
{
"id": "5befe9e0ffd6080001cbb9cb",
"name": "AutumnOOTD",
"type": "topic"
},
{
"id": "53b4d29ab4c4d61b0ba2ee94",
"name": "CapsuleWardrobe",
"type": "topic"
}
],
"mentions": [],
"mentionCount": 0,
"atUsers": [],
"publishedAt": "2026-09-15T08:24:10+00:00",
"updatedAt": "2026-09-15T09:12:05+00:00",
"sentiment": {
"hasPurchaseIntent": true,
"hasInquiry": true,
"hasPraise": true,
"intentKeywords": [
"哪里买",
"求链接",
"多少钱"
],
"emojis": [
"✨",
"🍂",
"🧥"
]
},
"scrapedAt": "2026-09-18T01:43:26.549000+00:00"
}
Built specifically for high-throughput enterprise pipelines with zero credential leakage.
Extract real-time trend data without logging into personal Xiaohongshu accounts. Zero ban risk, zero session expiration.
Automatically extracts original unwatermarked 1080p photo carousels and high-bitrate MP4 video stream URLs.
Detailed likes, collections, comments, and share counts normalized into clean numeric types for instant analytics.
Engineered with cross-session caching and browser-grade TLS JA4 fingerprinting for 0.05-second startup latency.
Trigger extractions via the official Apify Client or standard REST endpoints.
from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run_input = {
"startUrls": [
{
"url": "https://www.xiaohongshu.com/search_result?keyword=OOTD&sort=popularity_descending"
}
],
"keywords": ["OOTD"],
"maxItems": 30,
"proxyConfiguration": {
"useApifyProxy": True,
"apifyProxyGroups": ["RESIDENTIAL"],
"apifyProxyCountry": "HK"
}
}
run = client.actor("unitbytes/xiaohongshu-rednote-trend-scraper").call(run_input=run_input)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item.get("title"), item.get("updatedAt"), item.get("url"))
No. The UnitBytes engine operates 100% anonymously using autonomous request orchestration. You never need to supply login credentials, session cookies, or phone numbers.
All extracted media links are normalized to permanent public CDN endpoints without expiring authorization signatures, preventing 403 Forbidden errors in your downstream applications.
This actor utilizes Apify Pay-Per-Event (PPE) model at $0.003 per extracted note. You only pay for successfully parsed records, with zero standby or compute time overhead.
Yes. You can schedule recurring runs directly in the Apify Console or trigger runs via Webhook or REST API from your own backend or Airflow DAGs.
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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.