We extract course catalogues, module structures, instructor profiles, and institution metrics from Canvas.Net. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake.
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 canvas.net. All fields typed and schema-versioned.
"course_id": "cvs_88492", "title": "Introduction to Python Programming", "institution_name": "Tech University", "instructor_name": "Dr. Alan Turing", "start_date": "2024-09-01", "format": "Self-paced", "language": "English", "tags": "['programming', 'python', 'computer science']"
| # | course_id | title | institution_name | instructor_name | start_date | end_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Syllabus & Modules objects from canvas.net. All fields typed and schema-versioned.
"course_id": "cvs_88492", "module_id": "mod_101", "module_name": "Week 1: Data Types", "module_order": 1, "reading_time_minutes": 45, "video_count": 3, "assignment_count": 1, "learning_objectives": "Understand basic data types in Python."
| # | course_id | module_id | module_name | module_order | reading_time_minutes | video_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Institution Data objects from canvas.net. All fields typed and schema-versioned.
"institution_id": "inst_442", "name": "Tech University", "website_url": "https://tech.edu", "country": "United States", "total_active_courses": 124, "active_instructors": 89, "contact_email": "openlearning@tech.edu"
| # | institution_id | name | website_url | country | total_active_courses | active_instructors |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Instructor Profiles objects from canvas.net. All fields typed and schema-versioned.
"instructor_id": "usr_9931", "name": "Dr. Alan Turing", "academic_title": "Professor of Computer Science", "biography": "Alan focuses on computational theory and machine learning.", "institution_id": "inst_442", "courses_taught_count": 4, "avatar_url": "https://canvas.net/avatars/9931.jpg"
| # | instructor_id | name | academic_title | biography | institution_id | courses_taught_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Enrollment Details objects from canvas.net. All fields typed and schema-versioned.
"course_id": "cvs_88492", "is_free": true, "price": 0.0, "currency": "USD", "enrollment_start_date": "2024-08-01", "enrollment_end_date": "2024-09-15", "capacity_limit": 5000, "enrollment_status": "Open"
| # | course_id | is_free | price | currency | enrollment_start_date | enrollment_end_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our scraper maps the entire Canvas.Net ecosystem: course metadata, deep syllabus structures, and institutional footprints, built for scale and schema stability.
Extract title, descriptions, tags, and category metadata across the entire public course directory.
Capture module hierarchies, reading times, video counts, and assignment structures from course syllabi.
Extract instructor names, academic credentials, bios, and historical course load.
Aggregate university and organisation profiles, tracking total course offerings and active faculty.
Monitor enrollment windows, course start dates, and capacity limits to gauge course availability.
Extract and normalise course data across Spanish, English, and other regional Canvas deployments.
Maintain a hash index of course modules to only emit records when a syllabus or enrollment date changes.
Execute JavaScript to render complex course modules and interactive syllabus components.
Link courses via prerequisite text parsing to build complete learning pathways.
Brief in. Clean data out.
Provide target categories, institution URLs, or keyword sets. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, and session management for canvas.net.
Schema validation, null-rate checks, and syllabus structure verification before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Educational platforms rely on complex JavaScript frameworks and dynamic rendering. We handle the infrastructure.
Canvas relies heavily on React and dynamic hydration for syllabus rendering. We use Playwright to execute JavaScript and trigger lazy-loaded course modules that headless HTTP clients miss entirely.
Course catalogues span hundreds of paginated views. Our crawlers systematically traverse these directories, handling infinite scrolls and AJAX pagination to ensure zero data loss.
Instructors format syllabi differently. We use heuristic parsing and text-pattern matching to normalise unstructured course descriptions into clean, relational database fields.
For large course catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing downstream processing load for your data engineering team.
We route requests through residential ISP proxies with realistic browser fingerprints and randomised request timing to avoid rate limits during large catalogue extractions.
Course discovery platforms ingest Canvas syllabi and metadata to populate their own search engines and recommendation systems.
Analysts track course topics, institution participation, and language trends to identify gaps in the open education market.
Universities monitor competitor curricula and instructor profiles to benchmark their own digital learning initiatives.
Machine learning teams use structured syllabus and learning objective data to train educational language models.
Learning and development departments map open courses to internal skill matrices for employee upskilling programs.
Background check providers verify course existence, dates, and institution details for open-certificate claims.
"Canvas Network contains thousands of structured syllabi and institutional footprints, representing a massive corpus of pedagogical data."
Extracting LMS data requires navigating deep pagination, dynamic module loading, and inconsistent syllabus formatting. DataFlirt normalises this unstructured content into clean relational schemas, letting your engineering team focus on product features instead of crawler maintenance.
Everything supported by our canvas.net 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 complex LMS interfaces.
We maintain pools of residential ISP proxies to bypass rate limits. Rotation happens per request with sticky sessions where required.
Pipelines run on AWS Lambda and Kubernetes. Airflow handles scheduling, dependency management, and SLA alerting.
Data delivered to where your team already works — no new tooling required.
About canvas.net scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available course catalogues and syllabi is generally permissible. DataFlirt targets only public, non-authenticated data. We do not extract personal student data or bypass authentication walls.
We use full Playwright browser sessions to execute JavaScript, ensuring all lazy-loaded syllabus modules and interactive components are fully rendered before extraction.
Yes. We parse syllabus text and structured metadata fields to map prerequisite courses, allowing you to build complete learning pathways.
Full catalogue refreshes at daily or weekly cadences complete within a 4-hour window, ensuring enrollment dates and capacity limits are accurate.
No. We solely target the public Canvas.Net open course directory. We do not scrape private university LMS portals.
Yes. We provide a sample run of up to 200 courses during the scoping phase so you can validate schema fit and syllabus completeness.
20-minute scoping call. Pilot dataset within the week. Production within two. Need a full export of open courses or a continuous feed of new syllabi? We scope, build, and operate the pipeline.
