We extract property listings, rent and sale pricing, IPTU taxes, condominium fees, and broker details from Zapimoveis. Delivered as clean JSON, CSV, or Parquet to S3 or BigQuery on your schedule.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Property Listings objects from zapimoveis.com.br. All fields typed and schema-versioned.
"property_id": "2589143092", "property_type": "Apartment", "transaction_type": "SALE", "usable_area_sqm": 85, "bedrooms": 3, "bathrooms": 2, "parking_spaces": 1, "neighbourhood": "Pinheiros", "city": "Sao Paulo"
| # | property_id | title | property_type | transaction_type | usable_area_sqm | total_area_sqm |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Fees objects from zapimoveis.com.br. All fields typed and schema-versioned.
"property_id": "2589143092", "sale_price": 850000.0, "iptu_yearly": 2400.0, "condominio_fee": 950.0, "price_per_sqm": 10000.0, "zapway_eligible": false, "currency": "BRL", "scraped_at": "2026-05-12T10:15:22Z"
| # | property_id | sale_price | rent_price | iptu_yearly | condominio_fee | price_per_sqm |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Amenities & Features objects from zapimoveis.com.br. All fields typed and schema-versioned.
"property_id": "2589143092", "has_pool": true, "has_gym": true, "has_elevator": true, "pet_friendly": true, "balcony": true, "security_24h": true, "unit_floor": 4
| # | property_id | has_pool | has_gym | has_elevator | pet_friendly | furnished |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Broker & Agency objects from zapimoveis.com.br. All fields typed and schema-versioned.
"broker_id": "B-99214", "agency_name": "Lopes Imobiliaria", "creci_number": "CRECI-12345-J", "contact_phone": "+5511999999999", "whatsapp_available": true, "active_listings_count": 412, "profile_url": "https://www.zapimoveis.com.br/imobiliaria/lopes-imobiliaria/"
| # | property_id | broker_id | broker_name | agency_name | creci_number | contact_phone |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Location & Media objects from zapimoveis.com.br. All fields typed and schema-versioned.
"property_id": "2589143092", "latitude": -23.5615, "longitude": -46.6893, "zone": "Zona Oeste", "image_urls": "['https://fotos.vivareal.com/1.jpg', 'https://fotos.vivareal.com/2.jpg']", "virtual_tour_url": "None", "poi_distances": "['Metro: 500m']"
| # | property_id | latitude | longitude | street_name | zone | image_urls |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Zapimoveis scraper handles every layer of the platform: property listings, dynamic pricing, IPTU data, broker intelligence, and media URLs - with JavaScript rendering and anti-bot circumvention built in.
Title, description, property type, usable area, bedrooms, bathrooms, and parking spaces extracted at the listing level.
Capture sale price, rent price, monthly condominio fees, and yearly IPTU taxes - timestamped per crawl.
Agency name, CRECI registration number, contact phone, and WhatsApp availability for every listing.
Identify properties eligible for the ZapWay digital rental process, useful for tracking market modernisation.
Pool, gym, elevator, pet policy, and 24-hour security flags normalised into structured booleans.
Latitude, longitude, neighbourhood boundaries, and zone mapping for precise spatial analysis.
Monitor price drops, rent increases, and time-on-market across specific neighbourhoods and property types.
High-resolution image arrays, video links, and virtual tour URLs captured directly from the listing source.
Run one-off bulk exports or configure continuous pipelines at daily or weekly cadences with change-detection diffing.
Brief in. Clean data out.
Provide target cities, neighbourhoods, property types, or agency IDs. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, Brazilian proxy rotation, and CAPTCHA handling for zapimoveis.com.br.
Schema validation, null-rate checks, price-outlier detection, and sample data review before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Postgres database on agreed cadence.
Zapimoveis invests heavily in scraping detection via Datadome. Here is how we stay resilient - and why teams choose managed infrastructure over DIY.
Zapimoveis uses strict bot protection. Our crawlers use Brazilian residential ISP proxies with realistic browser fingerprints and full cookie session management to bypass blocks.
The Zapimoveis frontend is heavily JavaScript-rendered. We run full Playwright browser sessions to trigger lazy-loaded pricing components and broker contact details.
The platform changes its DOM structure frequently. Our selector strategy uses multiple fallback chains so a layout change does not break your data pipeline overnight.
For large property catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs - reducing compute cost and storage bloat.
Every run emits structured logs. We alert on null-rate spikes for critical fields like IPTU or condominio fees, responding before you notice data gaps.
Proptech companies train Automated Valuation Models (AVMs) using historical pricing, IPTU taxes, and area metrics.
Real estate funds identify high-yield rental properties across specific Sao Paulo and Rio de Janeiro neighbourhoods.
Large agencies track competitor listing volume, market share, and pricing strategies in real time.
Analysts track housing density and price-per-sqm trends across Brazilian states to identify emerging markets.
B2B services extract agency details and CRECI numbers to build targeted outreach campaigns for real estate professionals.
Investors monitor time-on-market and price drop velocity per region to gauge macroeconomic housing trends.
"Zapimoveis holds the most comprehensive real estate dataset in Brazil, but extracting clean, structured pricing and IPTU data at scale requires bypassing enterprise-grade bot protection."
Most data teams underestimate the engineering required to reliably scrape Zapimoveis. Between strict Datadome bot protection, complex React-rendered frontends, and nested location schemas, DIY pipelines break weekly. DataFlirt manages the proxies, CAPTCHA solvers, and selector maintenance so your team can focus on training valuation models and analysing market trends.
Everything supported by our zapimoveis.com.br 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 and interaction flows for the React frontend.
We maintain pools of Brazilian residential ISP proxies to bypass geographic and IP-reputation blocking mechanisms.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About zapimoveis.com.br scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available property listings is generally permissible under applicable law, provided it complies with the Brazilian General Data Protection Law (LGPD). DataFlirt targets only public, non-authenticated property and broker data. We do not extract private user data or circumvent authentication walls.
We use Brazilian residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and automated solvers to bypass Datadome protection. Our selectors have multi-layer fallback chains to handle frontend updates.
Pipelines can be configured for daily or weekly runs depending on your target scope. A full refresh of a major city like Sao Paulo typically completes within a 12-hour window.
Yes. We parse the pricing block to separate the base rent or sale price from monthly condominio fees and yearly IPTU taxes, delivering them as distinct numerical fields.
Yes. Every pipeline run produces timestamped snapshots. We maintain a time-series record per property ID, allowing you to track price drops and time-on-market from the date your pipeline starts.
Our packages typically start at a defined geographic scope, such as specific states or major metropolitan areas, with weekly delivery. Contact us with your target regions for a scoped quote.
Absolutely. We provide a sample run of up to 500 property listings as part of the pre-engagement scoping process so you can validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off property dump for Sao Paulo or a continuous price-monitoring feed across Brazil - we scope, build, and operate the pipeline. Tell us what you need.
