We extract pet listings, shelter details, breed characteristics, and availability status from Adoptapet. 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 Pet Listings objects from adoptapet.com. All fields typed and schema-versioned.
"pet_id": "38291044", "name": "Bella", "species": "Dog", "breed": "Labrador Retriever Mix", "age": "Young", "sex": "Female", "size": "Large", "status": "Available"
| # | pet_id | name | species | breed | age | sex |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Shelter Profiles objects from adoptapet.com. All fields typed and schema-versioned.
"shelter_id": "84729", "name": "City Animal Rescue", "type": "Private Rescue", "city": "Austin", "state": "TX", "zip_code": "78704", "active_pets": 42
| # | shelter_id | name | type | address | city | state |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Behavioural & Medical objects from adoptapet.com. All fields typed and schema-versioned.
"pet_id": "38291044", "spayed_neutered": true, "special_needs": false, "shots_current": true, "good_with_kids": true, "good_with_dogs": true, "housetrained": true
| # | pet_id | spayed_neutered | declawed | special_needs | shots_current | good_with_kids |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Media & Photos objects from adoptapet.com. All fields typed and schema-versioned.
"pet_id": "38291044", "primary_image_url": "https://images.adoptapet.com/large/38291044.jpg", "image_count": 4, "has_video": false, "thumbnail_url": "https://images.adoptapet.com/thumb/38291044.jpg", "media_updated_at": "2026-05-12T09:14:00Z"
| # | pet_id | primary_image_url | gallery_urls | video_urls | image_count | has_video |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search Results objects from adoptapet.com. All fields typed and schema-versioned.
"keyword": "Labrador", "zip_code": "78704", "radius": 50, "position": 1, "pet_id": "38291044", "scraped_at": "2026-05-12T09:14:33Z"
| # | keyword | zip_code | radius | position | pet_id | match_score |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Adoptapet scraper handles every layer of the platform: individual pet listings, shelter directories, location based search emulation, and dynamic media extraction, with JavaScript rendering and anti-bot circumvention built in.
Name, breed, age, size, primary colour, description, and status scraped at the individual listing level across all species categories.
Extract shelter names, contact information, physical addresses, operating hours, and active pet counts for thousands of registered organisations.
Iterate through zip code radii to map pet availability geographically, capturing exact distance metrics and regional availability trends.
Parse structured tags for spay/neuter status, vaccination records, special needs, and compatibility with kids or other pets.
Capture high-resolution primary image URLs, full gallery arrays, and video links associated with each pet listing.
Monitor listings over time to detect when a pet transitions from Available to Pending or Adopted, generating accurate velocity metrics.
Extract stated adoption fees and included services from unstructured description text or structured fields where available.
Run one-off bulk exports or configure continuous pipelines at daily cadences with change-detection diffing.
Bypass Cloudflare and aggressive rate limits using residential proxy rotation and realistic browser fingerprinting.
Brief in. Clean data out.
Provide target zip codes, radii, species preferences, or specific shelter IDs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for adoptapet.com.
Schema validation, null-rate checks, and sample data reviews before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Adoptapet invests heavily in scraping detection and location based rate limiting. Here is how we stay resilient.
Adoptapet uses modern bot protection that blocks standard data centre IPs. Our crawlers use US based residential ISP proxies with realistic browser fingerprints and full cookie session management.
Pet availability is strictly location bound. We maintain a master grid of US zip codes and programmatically iterate search queries across overlapping radii to ensure 100% national coverage without missing isolated shelters.
Search results and pagination on Adoptapet rely heavily on client side rendering. We run full Playwright browser sessions to hydrate dynamic pet grids and capture data that headless HTTP clients miss entirely.
For tracking adoption velocity, we maintain a hash index of last-seen status values per pet ID. 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, layout changes, and coverage drops, responding before you notice.
Analysts track breed popularity, average adoption times, and regional supply imbalances to forecast pet industry trends.
Animal welfare organisations monitor regional shelter intake volumes and adoption velocity to optimise resource allocation.
Third party pet search platforms ingest structured listings to provide unified search experiences across multiple adoption networks.
Computer vision teams use millions of tagged pet images to train breed recognition and phenotypic classification models.
Service providers map high density adoption regions to target new clinics, grooming services, or retail locations.
Researchers correlate adoption rates and breed preferences with local demographic and economic data.
"Adoptapet holds the most comprehensive registry of adoptable animals and shelter capacity metrics in North America. Extracting it requires navigating aggressive location based rate limits and dynamic search payloads."
Most teams underestimate the investment required: reliable Adoptapet scraping requires residential proxies, location based session handling, full JavaScript rendering for dynamic search results, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our adoptapet.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 and deduplication. Playwright handles JavaScript rendering, location mocking, and dynamic DOM interaction.
We maintain pools of US residential ISP proxies. Rotation happens per-request with sticky sessions where required to maintain location context.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About adoptapet.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Adoptapet is generally permissible under applicable law. DataFlirt targets only public, non-authenticated pet listings and shelter directory data. We do not extract personal user data or circumvent authentication walls.
We maintain a comprehensive grid of US zip codes and programmatically iterate search queries across overlapping radii. This ensures complete national coverage without triggering excessive request blocks from a single geographic point.
Yes. Every pipeline run produces timestamped snapshots. We compare current status fields against our historical database to detect when a listing changes from Available to Pending or Adopted.
Yes. We bypass the thumbnail grid and extract the full array of high-resolution image URLs and video links associated with each pet profile.
Full catalogue refreshes at daily cadence complete within a 6-12 hour window depending on the target geographic scope. Targeted zip code monitoring can be configured at higher frequencies.
Absolutely. We provide a sample run of up to 1,000 pet listings from a specified region as part of the pre-engagement scoping process so you can validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a national shelter directory export or continuous tracking across 300K pet listings, we scope, build, and operate the pipeline. Tell us what you need.
