We extract product specifications, ingredient hierarchies, nutritional breakdowns, and customer reviews from wellnesspetfood.com. 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 Product Specifications objects from wellnesspetfood.com. All fields typed and schema-versioned.
"product_id": "WP-DOG-CORE-01", "title": "CORE Original Deboned Turkey", "category": "Dog Food", "life_stage": "Adult", "breed_size": "All Breeds", "product_type": "Dry Food"
| # | product_id | title | category | sub_category | life_stage | breed_size |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Nutritional Analysis objects from wellnesspetfood.com. All fields typed and schema-versioned.
"product_id": "WP-DOG-CORE-01", "crude_protein": "34.0%", "crude_fat": "16.0%", "crude_fiber": "4.0%", "moisture": "10.0%", "calorie_content_me": "3,599 kcal/kg"
| # | product_id | guaranteed_analysis | crude_protein | crude_fat | crude_fiber | moisture |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Ingredients objects from wellnesspetfood.com. All fields typed and schema-versioned.
"product_id": "WP-DOG-CORE-01", "grain_free": true, "primary_ingredients": "['Deboned Turkey', 'Turkey Meal', 'Chicken Meal', 'Peas']", "artificial_colors_free": true, "artificial_flavors_free": true
| # | product_id | ingredient_list_raw | primary_ingredients | trace_ingredients | vitamins | minerals |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Feeding Guidelines objects from wellnesspetfood.com. All fields typed and schema-versioned.
"product_id": "WP-DOG-CORE-01", "weight_range_lbs": "15-20", "cups_per_day": "1 - 1.25", "transition_instructions": "Blend over 5-7 days", "mixed_feeding_instructions": "Reduce dry by 0.33 cup for every 6 oz of wet"
| # | product_id | weight_range_lbs | weight_range_kg | cups_per_day | grams_per_day | mixed_feeding_instructions |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Store Locator objects from wellnesspetfood.com. All fields typed and schema-versioned.
"store_id": "LOC-4829", "store_name": "Petco", "city": "Austin", "state": "TX", "zip_code": "78704", "distance_miles": 2.4
| # | store_id | store_name | address_line_1 | city | state | zip_code |
|---|---|---|---|---|---|---|
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Our pipeline handles the specific DOM structures of wellnesspetfood.com. We extract nested nutritional tables, feeding matrices, and third-party review widgets while maintaining strict schema compliance.
Convert HTML tables of nutritional data into strict key-value pairs for crude protein, fat, fibre, and moisture.
Extract raw ingredient text and tokenise it into primary ingredients, vitamins, minerals, and trace elements.
Structure complex feeding tables into weight-range arrays mapped to specific daily volume recommendations.
Reverse-engineer geographic API endpoints to extract complete retailer lists carrying Wellness products.
Paginate through embedded Bazaarvoice or Yotpo widgets to capture full review text, ratings, and user metadata.
Map bag sizes and packaging variants to parent products, capturing specific SKUs and barcode data where available.
Extract and normalise target demographic data including puppy, adult, senior, and specific breed sizes.
Extract legal nutritional adequacy statements for compliance auditing and product comparison.
Isolate ME (metabolisable energy) values per kilogram and per cup for precise nutritional modelling.
Brief in. Clean data out.
Provide target categories, product lines, or geographic regions for store locators. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and specific DOM parsers for nutritional tables.
Schema validation, null-rate checks, and ingredient list tokenisation verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting nutritional profiles requires more than simple text scraping. Here is how we normalise complex data structures.
Nutritional tables often use inconsistent row structures. We map these variations to a strict internal schema, ensuring crude protein and moisture always map to the correct float fields.
Instead of scraping map interfaces, we intercept the underlying XHR requests to the store locator backend, extracting exact coordinates and retailer metadata directly.
Reviews are loaded dynamically via third-party JavaScript. We execute these scripts in headless Playwright sessions to capture the full review corpus.
Different bag sizes or packaging formats sometimes feature slight variations in data. We hydrate all variants to ensure accurate mappings per SKU.
Raw ingredient strings are processed using regex and NLP to separate primary proteins from vitamin supplements and preservatives.
Pet food manufacturers compare protein levels, moisture content, and primary ingredients against their own formulations.
Sales teams monitor store locator data to map retail penetration and identify geographic distribution gaps.
App developers integrate calorie content and feeding guidelines into pet health and diet tracking applications.
Market researchers track available bag sizes, product lines, and variant offerings across the catalogue.
Analysts track the inclusion of specific superfoods, probiotics, or grain-free formulations over time.
Brand managers aggregate review text to analyse customer feedback on palatability, digestion, and coat health.
"Pet food composition is highly regulated. Extracting guaranteed analysis tables and ingredient arrays requires precise normalisation, not just raw text scraping."
Wellnesspetfood.com structures its nutritional data across complex DOM components and dynamic variants. DataFlirt parses these tables into strict numerical arrays, resolves feeding matrices, and reverse-engineers the store locator APIs. Your data science team gets clean schemas, not HTML soup.
Everything supported by our wellnesspetfood.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 for dynamic nutritional tabs and review widgets.
We trace internal XHR requests to extract structured JSON directly from the store locator backend, bypassing the need to scrape map tiles.
Pipelines run on AWS Lambda. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About wellnesspetfood.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available product catalogues, ingredients, and store locations is generally permissible. We do not bypass authentication walls or extract personal identifiable information.
We use specific DOM parsers mapped to known variations of their nutritional tables. The output is a strict numerical schema, converting percentages and units into consistent data types.
Yes. We reverse-engineer the store locator API and iterate through geographic grids to extract the complete list of retailers carrying their products.
For a catalogue of this size, we can easily run daily or weekly pipelines depending on your requirements for tracking new product launches or formulation changes.
Yes. We execute the third-party review widgets in headless browsers to paginate through and extract all historical reviews, ratings, and user feedback.
Yes. We tokenise the raw ingredient string and use pattern matching to separate the main protein and carbohydrate sources from the standard vitamin and mineral packs.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a complete catalogue of guaranteed analysis metrics or a continuous feed of product reviews, we scope, build, and operate the pipeline.
