We extract residential and commercial property listings, agent profiles, price histories, and neighbourhood metrics from PrivateProperty. 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 Property Listings (Sale) objects from privateproperty.co.za. All fields typed and schema-versioned.
"property_id": "T4829104", "title": "3 Bedroom House for sale in Sandton", "price": 3450000, "property_type": "House", "bedrooms": 3, "bathrooms": 2.5, "suburb": "Bryanston", "city": "Sandton"
| # | property_id | title | price | property_type | bedrooms | bathrooms |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Rental Properties objects from privateproperty.co.za. All fields typed and schema-versioned.
"property_id": "R928174", "monthly_rent": 18500, "deposit_required": 18500, "pet_friendly": true, "furnished": false, "suburb": "Rondebosch", "available_date": "2026-01-01"
| # | property_id | title | monthly_rent | deposit_required | available_date | lease_term |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Agent Profiles objects from privateproperty.co.za. All fields typed and schema-versioned.
"agent_id": "A49201", "name": "Sarah Jenkins", "agency_name": "Pam Golding Properties", "contact_number": "+27 82 555 0192", "active_listings_count": 24, "areas_covered": "['Sandton', 'Rosebank']"
| # | agent_id | name | agency_name | agency_branch | contact_number | active_listings_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Commercial Listings objects from privateproperty.co.za. All fields typed and schema-versioned.
"property_id": "C882910", "property_type": "Office Space", "gross_lettable_area": 450, "price_per_sqm": 180, "zoning": "Commercial", "parking_bays": 12, "suburb": "Century City"
| # | property_id | title | price | property_type | gross_lettable_area | price_per_sqm |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Developments & Estates objects from privateproperty.co.za. All fields typed and schema-versioned.
"development_id": "D29104", "name": "Waterfall Equestrian Estate", "developer_name": "Century Property Developments", "price_from": 4500000, "total_units": 120, "units_available": 14, "amenities": "['Security', 'Clubhouse', 'Gym']"
| # | development_id | name | developer_name | phase | total_units | units_available |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our PrivateProperty scraper navigates complex location hierarchies, dynamic map interfaces, and paginated search results to deliver structured real estate data.
Extract bedrooms, bathrooms, erf sizes, floor sizes, levies, rates, and detailed property descriptions for every listing.
Capture the exact location hierarchy from province down to municipality, city, suburb, and street address.
Link properties to specific agents and agencies. Track listing volumes and market share by brokerage.
Monitor asking prices, rental rates, deposits, and price reductions over time across specific neighbourhoods.
Extract specialized fields for commercial real estate and agricultural properties, including zoning and gross lettable area.
Track unit availability, phase releases, and pricing tiers for new residential developments and estates.
Capture high-resolution image URLs, floor plan links, and virtual tour endpoints for property valuation models.
Run daily or weekly pipelines that only deliver new listings, price changes, or delisted properties to reduce storage costs.
Target extractions by specific criteria like pet-friendly rentals, properties with boreholes, or specific security features.
Brief in. Clean data out.
Provide target provinces, suburbs, property types, or specific agency URLs. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, session management, and JavaScript rendering for privateproperty.co.za.
Schema validation, null-rate checks, and location taxonomy verification before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Property portals deploy aggressive rate limiting. Here is how we maintain steady pipelines for South African real estate data.
Property portals rate-limit aggressive datacenter IPs. We route requests through residential proxies located in South Africa, matching local user behaviour to maintain uninterrupted extraction.
PrivateProperty relies heavily on client-side rendering for maps, image galleries, and contact reveals. We use Playwright to execute JavaScript and hydrate the DOM before extraction.
Real estate data is useless without accurate location mapping. We normalise the complex province-to-suburb hierarchy to ensure consistent reporting across all records.
We maintain a hash index of active listings. Subsequent runs only push diffs, allowing you to accurately track days-on-market, price reductions, and inventory turnover.
Every run emits structured logs. We alert on null-rate spikes in critical fields like price or erf size, ensuring your downstream valuation models receive complete data.
PropTech companies train AVMs using historical asking prices, erf sizes, and property features across specific South African suburbs.
REITs and private investors track gross rental yields by comparing asking prices against active rental listings in target nodes.
Real estate brokerages monitor competitor listing volumes, agent headcounts, and time-on-market metrics to optimise their strategies.
Retailers analyse residential development pipelines and housing density trends to select optimal locations for new stores.
Financial institutions track new development announcements and high-velocity suburbs to target their home loan marketing.
Analysts publish quarterly reports on South African property trends, driven by structured data on inventory levels and asking prices.
"PrivateProperty holds the most comprehensive record of South African real estate transactions and active listings, but extracting it requires navigating complex location taxonomies and dynamic rendering."
Most data engineering teams underestimate the complexity of scraping property portals. Extracting reliable data from PrivateProperty requires handling infinite scroll pagination, dynamic JavaScript payloads for property features, and residential proxies to avoid rate limits. DataFlirt manages this infrastructure so you can focus on building your valuation models and market analytics.
Everything supported by our privateproperty.co.za 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 and deduplication. Playwright handles JavaScript rendering for property maps and galleries.
We maintain pools of residential ISP proxies across South Africa. Rotation happens per-request to avoid rate limiting.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management. All state stored in Postgres.
Data delivered to where your team already works — no new tooling required.
About privateproperty.co.za scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available property listings is generally permissible for non-personal data. DataFlirt extracts only public real estate details, prices, and agency information. We do not extract private user data or circumvent authentication walls. Clients should review local regulations and platform terms of service.
We use South African residential ISP proxies and request timing modelled on human behaviour. This distributes the load and prevents the IP blocking commonly experienced with datacenter proxies.
Yes. We can configure the pipeline to target specific provinces, municipalities, or even individual suburbs based on your requirements.
We can configure pipelines to run daily, weekly, or monthly. Daily runs capture new listings and price updates within 24 hours of them appearing on the platform.
Yes. By running regular full-site or suburb-level sweeps, we identify listings that are no longer active, allowing you to calculate days-on-market and inventory turnover.
Our minimum engagement typically covers a defined set of suburbs or property types with weekly delivery. Contact us with your specific target locations for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off export of Gauteng commercial listings or a daily feed of residential properties across South Africa, we build and operate the infrastructure. Tell us what you need.
