We extract product listings, nutritional metadata, pricing signals, and stock availability from Petsy.Online. 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 Product Listings objects from petsy.online. All fields typed and schema-versioned.
"sku": "PT-DF-8921", "title": "Royal Canin Maxi Adult Dry Dog Food", "brand": "Royal Canin", "category": "Dry Food", "pet_type": "Dog", "price": 4250.0, "stock_status": "In Stock", "page_url": "https://www.petsy.online/products/royal-canin-maxi-adult"
| # | sku | title | brand | category | pet_type | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Offers objects from petsy.online. All fields typed and schema-versioned.
"sku": "PT-DF-8921", "mrp": 4500.0, "selling_price": 4250.0, "discount_pct": 5, "auto_delivery_price": 4037.5, "out_of_stock_flag": false, "price_timestamp": "2026-05-12T09:14:00Z"
| # | sku | mrp | selling_price | discount_pct | auto_delivery_price | stock_depth |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Reviews & Ratings objects from petsy.online. All fields typed and schema-versioned.
"review_id": "REV-99281", "sku": "PT-DF-8921", "rating": 4.5, "verified_purchase": true, "review_text": "My Golden Retriever loves this food.", "helpful_votes": 12, "date": "2026-04-18"
| # | review_id | sku | reviewer_name | rating | review_text | date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Nutritional Metadata objects from petsy.online. All fields typed and schema-versioned.
"sku": "PT-DF-8921", "life_stage": "Adult", "breed_size": "Large", "special_diet": "None", "flavor": "Chicken", "ingredients": "Dehydrated poultry protein, maize, maize flour...", "guaranteed_analysis": "Protein: 26.0% | Fat content: 17.0%"
| # | sku | ingredients | guaranteed_analysis | feeding_guide | life_stage | breed_size |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Categories & Brands objects from petsy.online. All fields typed and schema-versioned.
"category_id": "CAT-102", "category_name": "Dog Food", "pet_type": "Dog", "sub_category": "Dry Food", "brand_name": "Royal Canin", "total_products": 145, "scraped_at": "2026-05-12T09:14:33Z"
| # | category_id | category_name | pet_type | sub_category | brand_name | brand_url |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Petsy scraper handles the complete catalogue: dog food, cat litter, accessories, and pharmacy items. We track dynamic pricing, stock levels, and nutritional metadata with full JavaScript rendering built in.
Title, description, images, variants, and every metadata field Petsy surfaces, extracted at the SKU level.
Capture selling price, MRP, discount percentages, and auto-delivery subscription rates, timestamped per crawl.
Extract ingredients, guaranteed analysis, feeding guidelines, life stage, and breed size parameters.
Full review text, star ratings, helpful vote counts, and verified purchase flags across all review pages.
Monitor out-of-stock flags and stock depth indicators to track inventory levels and supply chain gaps.
Map SKUs to brands and track brand assortment, category dominance, and promotional share of voice.
Extract the full taxonomy tree, from pet type down to specific subcategories like grain-free dry food.
Monitor flash sales, bundle offers, and coupon applicability across the entire catalogue.
Run one-off bulk exports or configure continuous pipelines at daily or weekly cadences with change-detection.
Brief in. Clean data out.
Provide category URLs, brand sets, or keyword lists. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, and session management for petsy.online.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket or BigQuery dataset on agreed cadence.
eCommerce scraping requires handling dynamic DOMs and rate limits. Here is how we maintain data integrity.
We use residential ISP proxies with realistic browser fingerprints and randomised request timing to avoid IP bans and rate limiting.
Petsy product pages load pricing and stock data dynamically. We run full Playwright browser sessions to capture data that headless HTTP clients miss.
Our selector strategy uses multiple fallback chains per field, so a layout change or promotional banner does not break your data pipeline overnight.
For the full catalogue, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing downstream processing load.
Every run emits structured logs. We alert on null-rate spikes, price outliers, and coverage drops, responding before you notice.
Pet care retailers monitor pricing and discount strategies to adjust their own margins and promotional calendars.
Brands track their product visibility, out-of-stock rates, and category share against competitors on the platform.
Analysts track new product launches, nutritional trends, and category expansion in the Indian pet care market.
Supply chain teams correlate stock depth indicators and review velocity to forecast demand for specific pet food categories.
Product managers analyze review text and ratings to understand customer preferences regarding flavors, ingredients, and packaging.
D2C pet brands analyze auto-delivery subscription discounts on Petsy to optimise their own retention pricing models.
"Petsy represents a critical node in the Indian pet care market. Unstructured HTML is useless for pricing models until it becomes queryable data."
Most teams underestimate the maintenance required for eCommerce scraping. Layouts shift, promotional banners break selectors, and rate limits block IPs. DataFlirt handles the infrastructure so your engineers can focus on retail analytics and pricing models.
Everything supported by our petsy.online 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 dynamic product pages.
We maintain pools of residential ISP proxies. Rotation happens per-request to prevent rate limits and IP blocking during high-volume crawls.
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 petsy.online scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible under applicable law. DataFlirt targets only public, non-authenticated product, pricing, and review data. We do not extract personal data or circumvent authentication walls.
We use residential ISP proxies and request timing modelled on human behaviour. We monitor for 429 rate limit spikes in real time and trigger IP pool rotation automatically.
Yes. We can scope the pipeline to specific categories like dog food, cat litter, or specific brands, reducing processing time and data volume.
Full catalogue refreshes typically complete within a 2-4 hour window depending on scale. We can configure specific high-priority categories for more frequent daily updates.
Yes. We parse the product description and specification tabs to extract ingredients, guaranteed analysis, feeding guidelines, and life stage metadata.
Yes. We provide a sample run of up to 100 SKUs 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 one-off catalogue dump or a continuous price-monitoring feed across all categories, we scope, build, and operate the pipeline. Tell us what you need.
