We extract wine ratings, spirit reviews, tasting notes, cocktail recipes, and industry news from VinePair. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your schedule.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Drink Reviews objects from vinepair.com. All fields typed and schema-versioned.
"drink_name": "Chateau Montelena Chardonnay 2019", "category": "Wine", "sub_category": "White Wine", "rating": 94, "price_usd": 70.0, "tasting_notes": "Bright acidity with notes of green apple, lemon curd, and a hint of toasted almond.", "abv_percent": 13.8, "origin_region": "Napa Valley"
| # | review_url | drink_name | category | sub_category | brand | rating |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Cocktail Recipes objects from vinepair.com. All fields typed and schema-versioned.
"cocktail_name": "Classic Negroni", "base_spirit": "Gin", "ingredients": "['Gin', 'Campari', 'Sweet Vermouth']", "measurements": "['1 oz Gin', '1 oz Campari', '1 oz Sweet Vermouth']", "glass_type": "Rocks Glass", "garnish": "Orange Peel", "difficulty_level": "Beginner"
| # | recipe_url | cocktail_name | base_spirit | ingredients | measurements | instructions |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Articles & News objects from vinepair.com. All fields typed and schema-versioned.
"title": "The Rise of Agave Spirits Beyond Tequila", "author": "Tim McKirdy", "publish_date": "2026-03-14", "category": "Spirits", "tags": "['Mezcal', 'Sotol', 'Raicilla', 'Industry Trends']", "word_count": 1240, "read_time_mins": 6
| # | article_url | title | author | publish_date | category | tags |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Brand Profiles objects from vinepair.com. All fields typed and schema-versioned.
"brand_name": "Campari", "parent_company": "Campari Group", "origin_country": "Italy", "primary_spirit_type": "Liqueur", "founded_year": 1860, "flagship_products": "['Campari Bitter', 'Aperol']"
| # | brand_name | parent_company | origin_country | primary_spirit_type | description | flagship_products |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Buying Guides objects from vinepair.com. All fields typed and schema-versioned.
"guide_title": "The 50 Best Wines of 2025", "category": "Wine", "publish_date": "2025-12-01", "product_count": 50, "products_listed": "['Chateau Montelena 2019', 'Ridge Vineyards Zinfandel']", "author": "VinePair Staff"
| # | guide_url | guide_title | category | publish_date | product_count | products_listed |
|---|---|---|---|---|---|---|
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Our VinePair scraper parses unstructured tasting notes, normalises cocktail measurements, and extracts deep brand metadata across thousands of reviews and recipes.
Capture ratings, tasting notes, ABV, price points, and regional origin data from every wine, beer, and spirit review.
Extract structured ingredients, exact measurements, glass types, garnishes, and step-by-step instructions from cocktail pages.
Map parent companies, origin countries, and flagship products from detailed brand profiles and industry reports.
Parse 'Best Of' lists and buying guides into structured arrays of recommended products and their associated rankings.
Extract full article bodies, author metadata, tags, and publication dates to track industry trends and PR mentions.
Track which contributors and critics are reviewing specific categories or brands across the platform.
Collect episode titles, descriptions, guest names, and show notes from the VinePair podcast network.
Extract high-resolution image URLs for bottle shots, cocktail preparations, and editorial photography.
Run continuous pipelines to capture new reviews, updated buying guides, and fresh articles as they publish.
Brief in. Clean data out.
Provide target categories, specific brands, or content types. We design the extraction schema together.
We configure Scrapy crawlers, handle infinite scroll pagination, and build custom parsers for unstructured tasting notes.
Schema validation, null-rate checks, and normalisation testing for recipe measurements before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on an agreed cadence.
Extracting data from editorial content requires advanced parsing. Here is how we turn prose into structured datasets.
Editorial reviews often embed ABV, price, and origin data within paragraphs. We use custom regex and NLP pipelines to extract these specific entities into distinct, queryable schema fields.
Cocktail recipes use mixed measurements (ounces, dashes, parts). Our parsers isolate the numeric value, unit, and ingredient name, ensuring your database remains clean and uniform.
VinePair uses dynamic loading for article grids and review archives. We deploy Playwright to execute JavaScript, trigger lazy-loading, and capture every item in a category.
We maintain a hash index of previously scraped URLs. Subsequent runs only parse newly published articles and reviews, reducing compute overhead and delivering a clean changelog.
To prevent rate limiting during deep historical crawls, we route requests through residential ISP proxies with randomised request timing and realistic browser fingerprints.
Analysts track rating trends, price points, and emerging categories to identify consumer preferences and market gaps.
Online liquor retailers populate their product pages with expert tasting notes, ratings, and cocktail suggestions to drive conversions.
Machine learning teams use structured cocktail ingredient lists and measurements to train generative AI models for mixology.
Beverage companies track PR mentions, competitor reviews, and editorial coverage to measure brand sentiment.
Brands benchmark their portfolio ratings and price points against competitors within specific categories like Tequila or Bourbon.
Aggregator platforms and newsletter publishers use automated feeds of industry news and buying guides to curate content.
"VinePair holds the definitive archive of modern drinks culture - but its true value is only accessible when editorial prose is converted into structured data."
Extracting data from media sites requires more than simple HTTP requests. It requires handling infinite scroll, parsing unstructured text, normalising varied measurements, and maintaining selectors against frequent CMS updates. DataFlirt manages this entire process, delivering clean, structured records ready for immediate analysis.
Everything supported by our vinepair.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 and infinite scroll interactions. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies. Rotation happens per-request to prevent IP bans during extensive historical archive extraction.
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 vinepair.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from VinePair is generally permissible under applicable law. DataFlirt targets only public, non-authenticated editorial content, recipes, and reviews. We do not extract personal data or circumvent authentication walls. Clients should consult legal counsel for specific use cases.
We deploy custom parsing logic using regex and NLP techniques to isolate specific entities like ABV percentages, price points, and regional origins from within editorial paragraphs, outputting them as distinct JSON fields.
Yes. Our parsers split raw recipe strings into three distinct fields: measurement (e.g., 1.5), unit (e.g., oz), and ingredient (e.g., Gin). This ensures your database can perform accurate queries and conversions.
We can configure pipelines to run daily, weekly, or hourly. For news and articles, frequent change-detection runs ensure you capture new content shortly after publication.
Yes. We can perform deep crawls through category pagination to extract years of historical reviews, buying guides, and recipes to build a comprehensive baseline dataset.
We extract high-resolution image URLs for bottle shots, cocktail preparations, and article hero images. We do not host the image files directly, but provide the source URLs.
Absolutely. We provide a sample run of up to 500 reviews or recipes as part of the pre-engagement scoping process, allowing you to validate schema fit and parsing accuracy.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a complete historical archive of wine reviews or a continuous feed of new cocktail recipes, we scope, build, and operate the pipeline. Tell us what you need.
