We extract flight pricing, hotel inventory, train schedules, and user reviews from Qunar. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Flight Itineraries objects from qunar.com. All fields typed and schema-versioned.
"flight_number": "CA1831", "airline": "Air China", "departure_airport": "PEK", "arrival_airport": "SHA", "departure_time": "2026-08-14T08:30:00Z", "price": 1250.0, "currency": "CNY", "cabin_class": "Economy", "available_seats": 9
| # | route_id | airline | flight_number | departure_airport | arrival_airport | departure_time |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Hotel Inventory objects from qunar.com. All fields typed and schema-versioned.
"hotel_id": "H9823471", "name": "The Peninsula Shanghai", "city": "Shanghai", "star_rating": 5, "room_type": "Deluxe River View", "price_per_night": 3200.0, "currency": "CNY", "review_score": 4.8, "availability": true
| # | hotel_id | name | city | district | star_rating | room_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Train Schedules objects from qunar.com. All fields typed and schema-versioned.
"train_number": "G101", "train_type": "High-Speed", "origin_station": "Beijing South", "destination_station": "Shanghai Hongqiao", "departure_time": "2026-08-14T06:43:00Z", "seat_class": "Second Class", "price": 553.0, "available_tickets": 24
| # | train_number | train_type | origin_station | destination_station | departure_time | arrival_time |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Bus Routes objects from qunar.com. All fields typed and schema-versioned.
"origin_city": "Guangzhou", "destination_city": "Shenzhen", "departure_station": "Guangzhou Provincial Bus Station", "departure_time": "2026-08-14T09:00:00Z", "operator": "Guangdong Transport", "price": 65.0, "tickets_left": 15
| # | route_id | origin_city | destination_city | departure_station | arrival_station | departure_time |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for User Reviews objects from qunar.com. All fields typed and schema-versioned.
"review_id": "R839201", "hotel_id": "H9823471", "rating": 5.0, "travel_type": "Business Trip", "review_text": "Excellent location on the Bund. Service was impeccable.", "date_posted": "2026-07-22", "helpful_votes": 12, "room_booked": "Deluxe River View"
| # | review_id | hotel_id | user_id | user_name | rating | cleanliness_score |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Qunar scraper handles every layer of the platform: dynamic flight pricing, hotel inventory, high-speed rail schedules, and the review corpus — with JavaScript rendering, session management, and anti-bot circumvention built in.
Track domestic and international routes, capturing cabin classes, tax structures, available seats, and dynamic fare changes.
Extract room types, cancellation policies, breakfast inclusions, and pricing across thousands of properties.
Monitor train availability, seat classes, and pricing for China's extensive railway network.
Full review text, sub-scores for cleanliness and location, helpful vote counts, and user travel types.
Capture schedules, station details, operators, and ticket availability for regional bus transport.
Simulate searches from specific Chinese provinces or international locations to capture regional pricing discrepancies.
Monitor stock depth for flights and hotels to trigger alerts when inventory drops below critical thresholds.
Run one-off bulk exports or configure continuous pipelines at hourly, daily, or real-time cadences with change-detection diffing.
Automated resolution of Qunar's slider and behaviour-based CAPTCHAs using computer vision and telemetry spoofing.
Brief in. Clean data out.
Provide flight routes, hotel IDs, city pairs, or train segments. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for qunar.com.
Schema validation, null-rate checks, price-outlier detection, and sample reviews before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Qunar invests heavily in scraping detection. Here is how we stay resilient — and why teams choose managed infrastructure over DIY.
Qunar aggressively blocks datacenter IPs and non-Chinese geolocation requests. Our crawlers use mainland China residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management.
Qunar flight and hotel results are heavily JavaScript-rendered and rely on websocket connections for live pricing. We run full Playwright browser sessions to capture data that headless HTTP clients miss entirely.
Qunar deploys complex slider and trajectory-based CAPTCHAs during high-frequency searches. We integrate CapSolver and custom computer vision models to mimic human mouse movements and solve these challenges programmatically.
Qunar changes its DOM structure frequently. Our selector strategy uses multiple fallback chains per field — CSS selectors, XPath, and text-pattern matching — so a layout change does not break your data pipeline overnight.
For large hotel catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs — reducing compute cost, storage bloat, and downstream processing load.
Online travel agencies monitor Qunar pricing across identical routes and properties to maintain parity and adjust their own margins.
Airlines and hotel chains track competitor rates and inventory depth on Qunar to feed their revenue management algorithms.
Analysts correlate flight search pricing, train availability, and hotel booking velocity to predict regional tourism demand.
Metasearch engines ingest Qunar data to display comprehensive pricing options to end consumers.
Hospitality groups analyse Qunar reviews to track property performance, cleanliness trends, and guest satisfaction against competitors.
Hedge funds track aggregated booking volumes and pricing trends to model quarterly revenue for public travel and hospitality companies.
"Qunar holds the pulse of Chinese domestic and international travel, but extracting realtime pricing requires navigating aggressive rate limits and complex anti-bot layers."
Most teams underestimate the investment required: reliable Qunar scraping requires mainland China residential proxies, full JavaScript rendering, trajectory-based CAPTCHA handling, daily selector maintenance, and anomaly monitoring. DataFlirt absorbs that complexity so your engineers can focus on the analysis — not the infrastructure.
Everything supported by our qunar.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of mainland China residential ISP proxies. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About qunar.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available pricing, schedules, and reviews from Qunar is generally permissible under applicable law. DataFlirt targets only public, non-authenticated data. We do not extract personal data or circumvent authentication walls. Clients should review Qunar's ToS and consult legal counsel for specific use cases.
We utilise CapSolver and proprietary computer vision models to calculate slider trajectories, combined with human-like mouse movement generation in Playwright to simulate legitimate user behaviour.
Yes. While Qunar blocks or limits data for foreign IPs, our infrastructure routes all requests through mainland China residential ISP proxies, ensuring full access to domestic pricing and inventory.
For a defined set of routes, we can configure high-frequency pipelines that poll Qunar every 15-30 minutes, delivering updates via Webhook for real-time revenue management.
We primarily target the web and mobile-web endpoints using browser automation, which generally mirrors the app's inventory and pricing. App-exclusive API scraping requires custom scoping.
Our smallest packages start at a defined list of routes or hotel properties with daily delivery. For larger catalogues or real-time requirements, we price based on volume and delivery frequency.
Absolutely. We provide a sample run of up to 100 flight routes or 200 hotel properties as part of the pre-engagement scoping process — so you can validate schema fit and data quality before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily hotel pricing dump or a continuous flight-monitoring feed across 10,000 routes — we scope, build, and operate the pipeline. Tell us what you need.
