We extract breeder directories, cattery profiles, recognised cat breeds, show schedules, and club data from cfa.org. Delivered as clean JSON, CSV, or Parquet to S3 or BigQuery 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 Breeder Directory objects from cfa.org. All fields typed and schema-versioned.
"name": "Jane Doe", "cattery_name": "FelineGrace", "breeds": "['Persian', 'Exotic']", "location": "Ohio, USA", "email": "jane@example.com", "status": "CFA Feline Council Member"
| # | name | cattery_name | breeds | location | website | |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Cat Breeds objects from cfa.org. All fields typed and schema-versioned.
"breed_name": "Maine Coon", "origin": "United States", "coat_length": "Longhair", "characteristics": "['Large', 'Tufted ears', 'Bushy tail']", "standard_url": "https://cfa.org/maine-coon/maine-coon-standard", "accepted_colors": "['Solid', 'Tabby', 'Bi-color']"
| # | breed_name | origin | description | coat_length | characteristics | standard_url |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Show Schedules objects from cfa.org. All fields typed and schema-versioned.
"show_name": "Midwest Feline Expo", "date": "2024-10-12", "location": "Chicago, IL", "club_name": "Great Lakes Cat Club", "judges": "['Smith', 'Johnson', 'Davis']", "format": "6AB, 2SP"
| # | show_name | date | location | club_name | judges | entry_clerk |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Clubs objects from cfa.org. All fields typed and schema-versioned.
"club_name": "Pacific Cat Fanciers", "region": "Region 5", "secretary": "Robert Brown", "contact_email": "info@pacificcatfanciers.org", "affiliated_breeds": "['Allbreed']", "charter_date": "1982-04-15"
| # | club_name | region | secretary | contact_email | website | affiliated_breeds |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Catteries objects from cfa.org. All fields typed and schema-versioned.
"cattery_name": "SilverPaws", "registration_number": "CAT-9921", "owner": "Alice Smith", "region": "Region 1", "breeds_focused": "['Siamese']", "active_status": true
| # | cattery_name | registration_number | owner | region | breeds_focused | established_year |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our cfa.org scraper handles the complexities of the association's directory architecture, parsing unstructured text into clean tabular data.
Extract contact details, cattery names, and associated breeds for thousands of registered breeders globally.
Monitor upcoming cat shows, capturing locations, dates, hosting clubs, and judging panels.
Pull official breed standards, point allocations, and accepted colour descriptions into structured formats.
Aggregate data on regional CFA clubs, including secretary contacts and affiliated regions.
Track approved judges, their licensing status (Allbreed vs Specialty), and regional assignments.
Segment breeders, clubs, and shows by the 9 official CFA regions automatically.
Render dynamic directory elements and interactive maps using headless Playwright sessions.
Traverse deep directory structures without missing records or hitting server limits.
Run monthly or quarterly syncs to capture new breeders, updated show dates, and revised standards.
Brief in. Clean data out.
Select target directories: breeders, shows, clubs, or breeds. We map the required schema.
We configure crawlers to handle cfa.org pagination, unstructured text parsing, and rate limits.
Schema validation, null-rate checks, and data normalisation before full deployment.
JSON, CSV, or Parquet pushed to your S3 bucket or data warehouse on schedule.
Extracting data from association websites often involves dealing with legacy HTML and inconsistent formatting. Here is how we handle it.
Breeder contact details on cfa.org are often formatted inconsistently. We use regex patterns and NLP to normalise phone numbers, separate names from cattery titles, and structure addresses.
Association websites typically run on limited infrastructure. We throttle concurrency and use residential proxies to prevent server strain while ensuring complete data extraction.
We monitor DOM changes on cfa.org. If the underlying WordPress or CMS structure shifts, our selector fallbacks ensure the pipeline continues delivering without interruption.
We automate the traversal of multi-page breeder and club directories, ensuring every record is captured even when pagination parameters are hidden in JavaScript.
Breeders often list themselves under multiple breeds or regions. Our pipeline deduplicates records based on cattery name and email, providing a clean, unique dataset.
Analyse breed popularity trends and geographic distribution of breeders for product targeting.
Pet marketplaces verify breeder credentials against official CFA registries to prevent fraud.
Researchers map regional breed concentrations for epidemiological and genetic studies.
Brands target specific breed clubs and show locations for sponsorships and specialised product launches.
Vendors track upcoming show schedules to plan travel and inventory allocation for events.
Global pet databases cross-reference CFA data with TICA and FIFe registries to build comprehensive profiles.
"The CFA database holds the most authoritative records on pedigreed cats globally, but extracting structured intelligence requires navigating legacy web architecture."
Extracting data from cfa.org requires handling inconsistent HTML structures, parsing unstructured contact blocks, and navigating paginated directories. DataFlirt manages this infrastructure so your team can focus on veterinary research, market analysis, or directory aggregation rather than building scrapers.
Everything supported by our cfa.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 handles orchestration and deduplication. Playwright handles JavaScript rendering and interaction flows for dynamic directory elements.
Custom Python modules clean and structure messy contact blocks, ensuring phone numbers and addresses fit strict database schemas.
Pipelines run on AWS infrastructure. Airflow handles scheduling for regular directory syncs. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About cfa.org scraping, legality, and pipeline operations.
Ask us directly →No. The eCat portal requires authenticated member access and payment for pedigree lookups. We only extract publicly available data from the main cfa.org directories.
We typically recommend a monthly or quarterly sync, as breeder information on cfa.org does not change rapidly. However, we can configure the pipeline to run at any required cadence.
While we capture the URL links to show flyers, we do not parse the internal text of the PDFs by default due to highly variable formatting. We extract the structured show data directly from the HTML schedule tables.
Our schema accepts null values for optional fields. If a breeder lists an email but no phone number, the record is still captured and structured accordingly.
Scraping publicly accessible, non-copyrighted factual data (like names, dates, and locations) is generally permissible. We do not bypass authentication walls or extract proprietary member-only data. Clients should ensure their specific use case complies with applicable laws.
Yes. We provide a sample export of up to 100 breeder records during the scoping phase so you can verify the data structure and normalisation quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off breeder directory export or continuous show schedule monitoring — we build and operate the pipeline. Tell us what you need.
