We extract residential and commercial listings, transaction histories, X-Value estimates, and agent profiles from SRX. 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 Sale Listings objects from srx.com.sg. All fields typed and schema-versioned.
"property_id": "LST-982341", "title": "Marina Bay Residences High Floor", "property_type": "Condominium", "price": 3200000.0, "psf": 2850.0, "area_sqft": 1123.0, "district": "D01", "tenure": "99-year Leasehold"
| # | property_id | title | property_type | price | psf | area_sqft |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Rental Listings objects from srx.com.sg. All fields typed and schema-versioned.
"listing_id": "RNT-445192", "title": "Tanjong Pagar Plaza 3-Room", "property_type": "HDB", "monthly_rent": 4200.0, "psf": 5.8, "area_sqft": 721.0, "furnishing": "Fully Furnished", "availability_date": "2026-07-01"
| # | listing_id | title | property_type | monthly_rent | psf | area_sqft |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Historical Transactions objects from srx.com.sg. All fields typed and schema-versioned.
"transaction_id": "TX-882910", "property_name": "The Sail @ Marina Bay", "transaction_date": "2026-03-14", "price": 2150000.0, "psf": 2420.0, "area_sqft": 888.0, "floor_level": "31-35"
| # | transaction_id | property_name | property_type | transaction_date | price | psf |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for X-Value Estimates objects from srx.com.sg. All fields typed and schema-versioned.
"property_id": "VAL-11029", "address": "12 Marina Boulevard", "x_value_estimate": 2200000.0, "x_value_range_low": 2100000.0, "x_value_range_high": 2300000.0, "valuation_date": "2026-05-12", "property_type": "Condominium"
| # | property_id | property_name | address | x_value_estimate | x_value_range_low | x_value_range_high |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Agent Profiles objects from srx.com.sg. All fields typed and schema-versioned.
"agent_id": "AGT-8841", "agent_name": "Sarah Tan", "agency_name": "PropNex Realty Pte Ltd", "cea_registration_number": "R123456A", "active_sale_listings": 14, "active_rent_listings": 8, "total_transactions": 142
| # | agent_id | agent_name | agency_name | cea_registration_number | phone_number | active_sale_listings |
|---|---|---|---|---|---|---|
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Our SRX scraper handles every layer of the platform: HDB listings, private condo sales, X-Value estimates, and transactional history - with JavaScript rendering, session management, and anti-bot circumvention built in.
Title, price, PSF, bedrooms, bathrooms, tenure, TOP year, and every metadata field SRX surfaces - scraped across all residential and commercial categories.
Capture SRX's proprietary X-Value automated valuations, including confidence ranges and historical valuation curves.
Extract decades of URA-backed transaction data for HDBs and private properties, including floor levels and exact block numbers.
Agent names, CEA registration numbers, agency affiliations, active listing counts, and transaction histories for every listed agent.
Extract proximity metrics to MRT stations, primary schools, supermarkets, and district boundaries.
Execute full browser sessions to scrape properties that only load via map-based API calls and JavaScript hydration.
Track both rental and sale listings concurrently to calculate implied rental yields across different districts and projects.
Run one-off bulk exports or configure continuous pipelines at hourly, daily, or real-time cadences with change-detection diffing.
Extract specific block numbers, flat models, lease remaining, and floor level ranges for all HDB resale listings and transactions.
Brief in. Clean data out.
Provide district codes, property types, or specific project names. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for srx.com.sg.
Schema validation, null-rate checks, price-outlier detection, and sample listings before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
SRX invests heavily in scraping detection. Here is how we stay resilient - and why teams choose managed infrastructure over DIY.
SRX employs strict Cloudflare protection and rate limiting. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full TLS fingerprint spoofing.
Many SRX listings and neighborhood insights are heavily JavaScript-rendered. We run full Playwright browser sessions with JavaScript execution and lazy-load triggering.
SRX updates its DOM structure frequently. Our selector strategy uses multiple fallback chains per field - CSS selectors, XPath, and JSON payload interception - so a layout change does not break your data pipeline.
For large property 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.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, schema drift, and coverage drops - and respond before you notice.
PropTech firms use historical transaction data and X-Value estimates to train their own Automated Valuation Models (AVMs).
Real estate funds track rental and sale prices concurrently to identify high-yield districts and arbitrage opportunities.
Mortgage brokers and property portals ingest SRX listing data to enrich their own user-facing applications.
Agencies monitor competitor agent listings and transaction volumes to recruit top performers and benchmark market share.
Analysts track PSF movements, inventory levels, and days-on-market metrics to forecast macro real estate trends.
Academic institutions and urban planners correlate property values with proximity to new MRT lines and infrastructure projects.
"SRX houses the most critical pricing signals for Singapore real estate - from live listing data to algorithmic X-Value estimates - but none of it is queryable unless you build the pipeline."
Most teams underestimate the investment required: reliable SRX scraping requires Singapore residential proxies, full JavaScript rendering for map-based interfaces, Cloudflare bypass, 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 srx.com.sg 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 residential ISP proxies across SG regions. 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 srx.com.sg scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from SRX is generally permissible under applicable law. DataFlirt targets only public, non-authenticated property listings, transaction data, and X-Value estimates. We do not extract personal data beyond public agent profiles, circumvent authentication walls, or violate PDPA. Clients should review SRX's ToS and consult legal counsel for specific use cases.
We use Singapore residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We monitor for 403 rate spikes in real time and trigger pool rotation or solver queues automatically.
Yes. We can extract the core X-Value estimate, the confidence range (high/low), and the valuation date for any property address or ID provided.
Real-time streaming pipelines achieve sub-60-minute latency for new listings and price changes on a defined district set. Full catalogue refreshes at daily cadence complete within a 4-8 hour window.
Yes. We extract the full historical ledger of HDB resale transactions available on SRX, including town, block number, flat model, floor area, and resale price.
Our smallest packages start at a defined district list or property type with weekly delivery. For larger catalogues or custom schema requirements, we price based on volume and delivery frequency. Contact us with your use case for a scoped quote.
Absolutely. We provide a sample run of up to 500 listings or transactions as part of the pre-engagement scoping process - so you can validate schema fit, field completeness, and data quality before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off historical transaction dump or a continuous listing feed across Singapore districts - we scope, build, and operate the pipeline. Tell us what you need.
