We extract course catalogues, pricing tiers, instructor portfolios, student reviews, and final projects from Domestika. 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 Course Metadata objects from domestika.org. All fields typed and schema-versioned.
"course_id": "1234", "title": "Illustration for Patterns", "price_original": 39.9, "price_discounted": 9.9, "currency": "USD", "student_count": 45102, "positive_reviews_pct": 99, "is_plus_eligible": true
| # | course_id | title | category | sub_category | instructor_name | instructor_id |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Instructor Profiles objects from domestika.org. All fields typed and schema-versioned.
"instructor_id": "inst_882", "name": "Catalina Estrada", "location": "Barcelona", "country": "Spain", "courses_published": 3, "total_students": 120500, "follower_count": 45210
| # | instructor_id | name | username | location | country | profession |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Student Projects objects from domestika.org. All fields typed and schema-versioned.
"project_id": "proj_9912", "title": "My first pattern collection", "student_username": "art_student22", "course_id": "1234", "likes_count": 142, "views_count": 1024, "software_used": "['Adobe Illustrator', 'Photoshop']"
| # | project_id | title | student_username | course_id | likes_count | comments_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from domestika.org. All fields typed and schema-versioned.
"review_id": "rev_551", "course_id": "1234", "rating": 5, "review_text": "Clear instructions and great resources.", "helpful_votes": 12, "date_posted": "2023-10-14", "is_plus_member": true
| # | review_id | course_id | student_username | rating | review_text | date_posted |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Promotions objects from domestika.org. All fields typed and schema-versioned.
"course_id": "1234", "current_price": 9.9, "base_price": 39.9, "discount_pct": 75, "flash_sale_active": true, "region_code": "US", "crawl_timestamp": "2023-11-01T10:00:00Z"
| # | course_id | crawl_timestamp | base_price | current_price | currency | discount_pct |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our pipeline handles Domestika's dynamic pricing, multi-language variations, and paginated project galleries. Built with residential proxies and JavaScript rendering to bypass rate limits.
Title, category, level, duration, software requirements, and enrolment figures scraped systematically.
Monitor base prices, flash sale discounts, and Domestika Plus pricing tiers across different regions.
Extract biographies, portfolio links, follower counts, and historical course performance metrics.
Scrape project titles, image URLs, view counts, and software tags from the community showcase.
Capture full review text, helpful votes, and student completion status across all paginated reviews.
Extract localised pricing and availability for US, EU, UK, and LATAM markets.
Track audio languages and available subtitle options for accessibility analysis.
Map the entire hierarchy of creative disciplines, software tools, and craft categories.
Run daily pipelines that only emit updated courses, new projects, or changed prices to minimise storage.
Brief in. Clean data out.
Specify categories, instructor profiles, or regions. We map the required data schema.
We configure Scrapy spiders, Playwright renderers, and residential proxy rotation for domestika.org.
Null-rate checks, price normalisation, and schema validation against a sample dataset.
Clean records pushed to your S3 bucket, Snowflake stage, or via webhook on a daily or hourly schedule.
Scraping an image-heavy, dynamically priced platform requires specific infrastructure. Here is how we build it.
Domestika frequently runs flash sales and region-specific pricing. We use localised residential IPs to capture accurate regional pricing tiers across the US, EU, and LATAM markets.
Student projects load high-resolution images dynamically. We intercept XHR requests to extract CDN URLs directly without downloading the raw media, keeping pipelines fast and bandwidth low.
Course reviews and project feeds rely on infinite scroll. Our Playwright scripts handle pagination tokens to extract the full historical corpus rather than just the first page.
Domestika serves different content based on Accept-Language headers. We normalise requests to ensure consistent data extraction across locales.
Aggressive crawling triggers Cloudflare blocks. We distribute requests across a large IP pool with randomised delays to maintain high throughput.
EdTech platforms monitor Domestika discount frequencies and bundle pricing to adjust their own promotional strategies.
Track enrolment growth and review velocity across categories to identify trending software tools and creative skills.
Identify high-performing instructors by follower count and positive review ratios for talent acquisition.
Analyse the volume of courses in specific niches to find gaps in the market.
Map available audio languages and subtitles against regional sales to determine translation priorities.
Extract software tags from student projects to measure the adoption of tools like Figma, Blender, or Cinema 4D.
"Domestika's public catalogue holds deep signals on creative industry trends, software adoption, and global pricing strategies. We structure it so you can query it."
Building an internal scraper for Domestika means dealing with complex pagination, aggressive rate limits, and constantly shifting promotional pricing. DataFlirt manages the proxy rotation, session handling, and schema maintenance. You receive clean, structured records ready for your downstream analytics.
Everything supported by our domestika.org 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 clusters deployed on Kubernetes for high-throughput extraction of the course catalogue.
Playwright instances handle JavaScript execution for dynamic pricing widgets and infinite scroll feeds.
Airflow DAGs run schema validation and null-rate checks before pushing data to your warehouse.
Data delivered to where your team already works — no new tooling required.
About domestika.org scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available course metadata, pricing, and reviews is generally permissible. We do not bypass paywalls or extract private user data. Clients should consult legal counsel for specific applications.
Yes. We can configure pipelines to run daily or hourly to capture short-term promotional pricing and Domestika Plus discounts.
No. We extract public metadata, pricing, and text. We do not extract or host copyrighted video content or paid lesson materials.
We route requests through residential proxies located in your target regions to capture accurate localised pricing.
Yes. We scrape public project galleries, including image URLs, software tags, view counts, and likes.
We push structured JSON, CSV, or Parquet files directly to your S3 bucket, Snowflake stage, or via webhook on a defined schedule.
Our managed service includes constant monitoring. If DOM selectors break, our engineering team updates the pipeline, ensuring your data delivery remains uninterrupted.
20-minute scoping call. Pilot dataset within the week. Production within two. Stop manually tracking course prices and instructor metrics. We build and maintain the extraction pipeline so you can focus on analysis.
