We extract grocery catalogues, regional pricing, ingredient lists, and stock availability from FreshDirect. 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 Grocery Products objects from freshdirect.com. All fields typed and schema-versioned.
"sku": "FD-89211", "name": "Organic Honeycrisp Apples", "brand": "FreshDirect Produce", "category": "Fruit", "price": 6.99, "unit_price": "3.49/lb", "weight": "2 lbs", "in_stock": true
| # | sku | name | brand | category | sub_category | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Nutritional Info objects from freshdirect.com. All fields typed and schema-versioned.
"sku": "FD-44502", "serving_size": "1 cup (240ml)", "calories": 120, "total_fat": "5g", "sodium": "110mg", "ingredients": "Organic Whole Milk, Vitamin D3", "allergens": "Contains: Milk"
| # | sku | serving_size | calories | total_fat | cholesterol | sodium |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Pricing & Promos objects from freshdirect.com. All fields typed and schema-versioned.
"sku": "FD-11209", "zip_code": "10001", "base_price": 14.99, "promo_price": 12.99, "promo_desc": "Save $2.00", "multibuy_discount": "None", "scraped_timestamp": "2026-05-12T08:12:00Z"
| # | sku | zip_code | base_price | promo_price | promo_desc | multibuy_discount |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Meat & Seafood objects from freshdirect.com. All fields typed and schema-versioned.
"sku": "FD-77341", "cut_type": "Ribeye Steak", "source_farm": "Local NY Farms", "organic_certified": false, "preparation_tips": "Grill or pan-sear", "shelf_life": "3 days", "price_per_lb": 24.99
| # | sku | cut_type | source_farm | organic_certified | catch_method | preparation_tips |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Prepared Foods objects from freshdirect.com. All fields typed and schema-versioned.
"sku": "FD-99201", "meal_type": "Dinner Entree", "dietary_tags": "['Gluten-Free', 'High Protein']", "chef_notes": "Prepared fresh daily in our Bronx facility.", "spice_level": "Mild", "days_fresh": 4
| # | sku | meal_type | heating_instructions | dietary_tags | chef_notes | spice_level |
|---|---|---|---|---|---|---|
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Our FreshDirect scraper navigates zip-code walls, dynamic inventory states, and complex nutritional tables to deliver structured grocery intelligence.
Extract SKU, title, brand, weight, unit pricing, and high-resolution images across all grocery categories.
Simulate delivery zip codes to capture regional price variations and local tax applications.
Parse complex nutrition facts panels into structured JSON, including macro-nutrients and allergen warnings.
Capture local farm partnerships, organic certifications, and catch methods for meat and seafood.
Extract heating instructions, dietary tags, chef notes, and shelf-life indicators for ready-to-eat items.
Monitor active sales, multi-buy discounts, and coupon eligibility windows timestamped per run.
Track in-stock status and inventory depth indicators across different fulfillment centres.
Map full taxonomy trees from top-level departments down to specific product aisles.
Run continuous pipelines to capture high-frequency price and stock changes during peak shopping hours.
Brief in. Clean data out.
Provide target zip codes, category URLs, or specific SKUs. We design the extraction schema together.
We configure crawlers, session management for location data, and parsing logic for nutritional tables.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Grocery scraping requires managing session state across zip codes and parsing unstructured ingredient text.
FreshDirect requires a valid delivery zip code to display accurate pricing and inventory. We maintain active cookie sessions tied to specific regional proxies to ensure data reflects local availability.
Nutrition facts are often embedded in inconsistent HTML structures or images. We use computer vision and DOM parsing to extract macros, ingredients, and allergens into clean, typed fields.
Grocery inventory changes rapidly. We maintain a hash index of last-seen values per SKU, emitting only changed records to reduce downstream processing load.
We route requests through US-based residential ISP proxies with realistic browser fingerprints to bypass request limits and IP bans.
We traverse complex category trees to ensure full catalogue coverage, capturing parent-child relationships for every product.
Grocery retailers track FreshDirect pricing across zip codes to adjust their own regional pricing models.
Brands monitor product placement, promotional compliance, and out-of-stock rates for their SKUs.
Health tech applications ingest ingredient and macro data to power dietary recommendation engines.
Distributors track stock availability signals to forecast demand for specific product categories.
Economic analysts monitor basket prices over time to track regional food inflation trends.
Agencies analyse category expansion and new product introductions to identify consumer trends.
"FreshDirect holds some of the most detailed product sourcing and nutritional data in the US grocery market, but accessing it across regional boundaries requires dedicated infrastructure."
Grocery inventory changes daily. Relying on manual exports or brittle scripts fails when store layouts update or zip-code sessions expire. DataFlirt maintains the session states, parses the complex nutritional tables, and delivers clean, normalised data directly to your warehouse.
Everything supported by our freshdirect.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 retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows required for zip-code entry.
We maintain pools of US residential ISP proxies. Rotation happens per-request with sticky sessions required for location-based pricing.
Pipelines run on AWS Lambda and ECS. 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 freshdirect.com 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 nutritional data. We do not extract personal user data or circumvent authentication walls.
We initiate sessions using target zip codes provided by the client. Our infrastructure maintains these location-specific cookies throughout the crawl to ensure the captured pricing and inventory match the specified region.
Yes. We use custom parsing logic to normalise varying nutritional table formats across different brands, outputting clean, typed integers for calories, macros, and sodium levels.
We configure pipeline schedules based on client needs. For inventory monitoring, we can run high-frequency intra-day crawls to capture stock changes during peak shopping windows.
Yes. Allergen warnings are extracted and provided as a structured array within the product record, separating explicit 'Contains' warnings from 'Facility' warnings where available.
Our packages typically start at a defined category list or full-site crawl for a specific set of zip codes with daily delivery. Contact us with your requirements for a scoped quote.
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 multiple zip codes. Tell us what you need.
