We extract high-resolution project galleries, professional metadata, design editorials, and product catalogues from Dwell. 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 Architectural Projects objects from dwell.com. All fields typed and schema-versioned.
"project_id": "PRJ-98234", "title": "Desert Courtyard House", "architect": "Wendell Burnette", "firm_name": "Wendell Burnette Architects", "location": "Scottsdale, Arizona", "year_built": 2013, "materials": "['Rammed Earth', 'Glass', 'Steel']"
| # | project_id | title | architect | firm_name | location | year_built |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Professional Profiles objects from dwell.com. All fields typed and schema-versioned.
"profile_id": "PRO-45112", "name": "Olson Kundig", "firm_name": "Olson Kundig Architects", "location": "Seattle, Washington", "website": "https://olsonkundig.com", "project_count": 42, "followers": 18450
| # | profile_id | name | firm_name | location | website | contact_email |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Articles & Editorials objects from dwell.com. All fields typed and schema-versioned.
"article_id": "ART-77210", "headline": "A Midcentury Modern Revival in Palm Springs", "author": "Sarah Lonsdale", "publish_date": "2023-10-14T08:30:00Z", "category": "Home Tours", "tags": "['Midcentury', 'Renovation', 'California']", "read_time": "5 min"
| # | article_id | headline | author | publish_date | category | content_body |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Shop Products objects from dwell.com. All fields typed and schema-versioned.
"product_id": "SHP-10293", "name": "Eames Lounge Chair", "brand": "Herman Miller", "designer": "Charles and Ray Eames", "price": 6495.0, "currency": "USD", "in_stock": true
| # | product_id | name | brand | designer | price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Real Estate Listings objects from dwell.com. All fields typed and schema-versioned.
"listing_id": "RE-55821", "title": "Glass Pavilion House", "price": 4250000.0, "currency": "USD", "location": "Montecito, California", "bedrooms": 4, "bathrooms": 4.5, "sqft": 3800
| # | listing_id | title | price | currency | location | bedrooms |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Dwell scraper handles every layer of the platform: project galleries, professional directories, editorial content, and product catalogues — with JavaScript rendering, session management, and anti-bot circumvention built in.
Extract source URLs for high-resolution project photography, bypassing lazy-loaded thumbnails and responsive image wrappers.
Capture firm names, lead architects, contact information, and portfolio links from professional directory profiles.
Extract year built, square footage, budget data, material lists, and geolocation tags from architectural case studies.
Map the network of builders, designers, and architects, including follower counts and verified project histories.
Extract full text, author metadata, publish dates, and categorical tags from Dwell editorial articles and home tours.
Track pricing, designer attribution, brand details, and inventory status for modern furniture and decor listings.
Standardise city, state, and country data across projects and professional profiles for spatial analysis.
Monitor active modern homes for sale, capturing asking prices, agent details, and architectural provenance.
Run one-off bulk exports or configure continuous pipelines at weekly, daily, or real-time cadences with change-detection diffing.
Brief in. Clean data out.
Provide category URLs, professional firm lists, or search queries. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for dwell.com.
Schema validation, null-rate checks, and sample image gallery validations before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Dwell relies heavily on modern frontend frameworks and dynamic image loading. Here's how we stay resilient.
Dwell project galleries and infinite-scroll feeds are heavily JavaScript-rendered. We run full Playwright browser sessions with JavaScript execution and lazy-load triggering to capture images that headless HTTP clients miss entirely.
We use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management — trained on real user behaviour patterns to avoid rate limits.
Frontend structures change. Our selector strategy uses multiple fallback chains per field — CSS selectors, XPath, and JSON-LD extraction — so a layout change doesn't break your data pipeline overnight.
For large professional directories, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs — reducing compute cost and downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, missing image URLs, and schema drift — and respond before you notice.
Design brands and material manufacturers track material usage and architectural trends over time to forecast demand.
B2B suppliers extract architect and firm contact details to build targeted outreach lists based on project types.
Brokerages monitor high-end modern real estate listings to track pricing premiums associated with specific architects.
Retailers scrape the Dwell Shop to benchmark pricing, designer collaborations, and category assortments.
Computer vision teams use high-resolution architectural photography and associated tags to train image recognition models.
Architecture firms track peer portfolios, project counts, and editorial features to benchmark market positioning.
"Dwell represents the definitive digital archive of modern architecture, but extracting structured metadata from its visual-heavy interface requires purpose-built infrastructure."
Most teams underestimate the investment required: reliable Dwell scraping requires handling infinite scroll galleries, dynamic image hydration, residential proxies, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on the analysis — not the infrastructure.
Everything supported by our dwell.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 for dynamic galleries.
We maintain pools of residential ISP proxies across US regions. Rotation happens per-request with sticky sessions where required to bypass rate limits.
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 dwell.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible. DataFlirt targets only public, non-authenticated architectural, professional, and editorial data. We do not extract personal user data or circumvent authentication walls.
We use Playwright to execute JavaScript and simulate human scrolling behaviour, triggering the hydration of high-resolution image URLs before extraction.
No. Dwell+ premium content is gated behind a paywall and requires active user authentication. We only extract the publicly visible metadata and preview text for these URLs.
Pipelines can be configured to run daily or weekly depending on your requirements. Continuous change detection ensures you receive updates as soon as new projects or articles are published.
Our standard delivery provides the direct source URLs for images. If you require the binary files downloaded and transferred to your S3 bucket, we can configure a secondary pipeline for binary ingestion.
Absolutely. We provide a sample run of up to 500 projects or professional profiles as part of the pre-engagement scoping process to validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off project catalogue dump or a continuous professional directory feed — we scope, build, and operate the pipeline. Tell us what you need.
