We extract project details, firm profiles, material specifications, and image galleries from Arch2O. 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 Architecture Projects objects from arch2o.com. All fields typed and schema-versioned.
"project_id": "PRJ-99214", "title": "Museum of Modern Art Extension", "architect_firm": "Studio Libeskind", "location": "New York, United States", "area_sqm": 12500, "completion_year": 2024, "project_type": "Cultural > Museum", "manufacturers": "['Reynaers Aluminium', 'KONE']"
| # | project_id | title | architect_firm | location | area_sqm | completion_year |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Firm Profiles objects from arch2o.com. All fields typed and schema-versioned.
"firm_id": "FRM-1024", "firm_name": "Zaha Hadid Architects", "founded_year": 1980, "headquarters": "London, UK", "website_url": "zaha-hadid.com", "project_count": 950, "team_size": "500+", "awards": "['Pritzker Architecture Prize']"
| # | firm_id | firm_name | founded_year | headquarters | website_url | bio |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Materials & Products objects from arch2o.com. All fields typed and schema-versioned.
"product_id": "MAT-5512", "product_name": "Acoustic Wood Panels", "manufacturer": "Gustafs", "category": "Interior Finishes > Acoustics", "application_type": "Wall / Ceiling", "certifications": "['FSC Certified', 'LEED v4']", "project_references": "['PRJ-99214', 'PRJ-88120']"
| # | product_id | product_name | manufacturer | category | description | application_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Competitions objects from arch2o.com. All fields typed and schema-versioned.
"competition_id": "COMP-2025-01", "competition_name": "Future Housing Prototype", "status": "Closed", "deadline_date": "2025-11-15", "prize_pool": "50000 USD", "jury_members": "['Bjarke Ingels', 'Kazuyo Sejima']", "category": "Residential", "organizer": "Arch2O"
| # | competition_id | competition_name | status | deadline_date | prize_pool | jury_members |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for News & Articles objects from arch2o.com. All fields typed and schema-versioned.
"article_id": "ART-7732", "headline": "10 Sustainable Materials Shaping 2026", "author": "Elena Rossi", "publish_date": "2026-02-10T14:30:00Z", "category": "Materials", "tags": "['Sustainability', 'Innovation', 'Timber']", "view_count": 14205, "source_url": "arch2o.com/sustainable-materials-2026"
| # | article_id | headline | author | publish_date | category | tags |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Arch2O scraper parses complex editorial layouts, normalises disparate project metadata, and hydrates lazy-loaded image galleries to deliver structured architectural intelligence.
Extract and standardise project area, completion year, location coordinates, and project typologies from unstructured editorial text blocks.
Bypass lazy-loading to capture all full-resolution CDN image URLs, architectural plans, and section drawings associated with a project.
Map individual projects back to lead architects and firms, building a relational database of firm output and specialisation.
Identify specified materials, products, and manufacturers embedded in project descriptions to track material usage trends.
Isolate academic and student architectural projects from professional portfolios to analyse emerging design trends.
Monitor new architectural competitions, deadlines, jury panels, and extract winning entry data as it publishes.
Strip HTML formatting, ads, and related-post injections to deliver clean, readable project descriptions and article bodies.
Run daily or weekly pipelines that only extract newly published projects and articles, minimising compute overhead.
Link architects, photographers, and manufacturers via distinct IDs across the entire Arch2O catalogue.
Brief in. Clean data out.
Specify categories, project typologies, or firm names. We design the extraction schema together.
We configure Scrapy crawlers, handle pagination, and manage JavaScript execution for image galleries.
Schema validation, null-rate checks on critical fields like area and year, and text normalisation.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Architecture blogs use heavy visual DOMs and inconsistent post templates. Here is how we maintain data quality.
Arch2O has evolved its article structure over the years. Our parsers use chronological fallback chains, applying different extraction logic for legacy 2012 posts versus modern 2024 project templates to ensure high field completion rates.
Project pages contain dozens of high-resolution images that only load upon scroll. We use Playwright to simulate viewport scrolling and trigger all lazy-load events, capturing the underlying CDN URLs rather than low-res placeholders.
Project areas are listed inconsistently (sqm, sqft, m2). Our pipeline includes a normalisation layer that standardises all spatial metrics to square metres and parses raw text locations into structured City/Country fields.
Manufacturers are often buried within the project description text. We use regex and NLP models to identify and extract brand names and material specifications, turning unstructured text into categorical data.
Scraping media-heavy sites consumes massive bandwidth. We optimise our HTTP clients to block unnecessary asset downloads (like fonts and tracking scripts) while retaining the core DOM required for image URL extraction.
Design agencies analyse project typologies, material usage, and spatial metrics to identify macro trends in global architecture.
Building material manufacturers track competitor product placements in high-profile projects to understand market penetration.
Architectural firms monitor peer portfolios, competition wins, and publication frequency to benchmark industry standing.
AI teams ingest millions of tagged architectural images to train models for style classification, floorplan generation, and rendering.
Acoustic, lighting, and facade suppliers identify active firms designing specific project types to target outreach.
Universities analyse decades of student projects and urban interventions to study the evolution of academic design theory.
"Arch2O holds decades of architectural evolution and material specifications, but extracting standard metadata from editorial layouts requires dedicated infrastructure."
Architecture publications rely on heavy visual DOMs and unstructured editorial text. DataFlirt parses variable article templates, executes JavaScript to hydrate image galleries, and normalises project metadata into queryable schemas so your engineers avoid maintaining brittle CSS selectors.
Everything supported by our arch2o.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 manages crawl queues and deduplication. Playwright handles DOM hydration and lazy-load triggering for media-heavy project pages.
Custom Python pipelines strip HTML, standardise metric units, and use regex to extract structured data from editorial paragraphs.
Pipelines run on AWS infrastructure. Airflow handles daily scheduling to capture new publications. State stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About arch2o.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available editorial content, project metadata, and image URLs is generally permissible under applicable law. DataFlirt extracts only public data and does not bypass authentication for gated materials or CAD files. Clients must ensure their downstream use of copyrighted images complies with fair use or licensing agreements.
By default, we extract and deliver the high-resolution CDN URLs. If your use case requires binary files (e.g., for ML training), we can configure the pipeline to download images and push them directly to your S3 bucket.
Editorial sites often lack strict schemas. If a project post omits the 'completion year' or 'area', we return a null value for that field rather than guessing. Our validation layer monitors null-rates to ensure extraction logic hasn't failed.
Yes. We can run a full historical backfill traversing all pagination and category archives to extract projects dating back to the site's inception.
For editorial sites like Arch2O, daily or weekly runs are standard to capture new publications. We use incremental diffing to avoid re-scraping the entire historical catalogue.
Our minimum engagement typically starts at a full historical extraction of a specific category (e.g., all Residential projects) followed by a monthly maintenance contract for ongoing updates.
Yes. We provide a sample run of up to 100 project records during the scoping phase to validate field completeness and schema structure.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a historical backfill of architectural projects or a continuous feed of new material specifications — we scope, build, and operate the pipeline. Tell us what you need.
