We extract vendor profiles, real wedding metadata, style tags, and editorial features from Green Wedding Shoes. 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 Vendor Profiles objects from greenweddingshoes.com. All fields typed and schema-versioned.
"name": "Wildflower Photography", "category": "Photographer", "location": "Los Angeles, CA", "website_url": "https://example.com/wildflower", "instagram_handle": "@wildflowerphoto", "featured_weddings_count": 14
| # | vendor_id | name | category | location | region | website_url |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Real Weddings objects from greenweddingshoes.com. All fields typed and schema-versioned.
"title": "Boho Desert Wedding in Joshua Tree", "publish_date": "2023-09-14", "location": "Joshua Tree, CA", "theme_tags": "['Boho', 'Desert', 'Intimate']", "colour_palette": "['Terracotta', 'Sage', 'Mustard']", "venue_name": "Autocamp Joshua Tree"
| # | wedding_id | title | url | publish_date | location | venue_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Vendor Credits objects from greenweddingshoes.com. All fields typed and schema-versioned.
"wedding_id": "RW-8492", "vendor_role": "Floral Design", "vendor_name": "Desert Blooms", "gws_profile_url": "https://greenweddingshoes.com/vendors/desert-blooms", "is_premium_member": true, "mentioned_in_text": true
| # | wedding_id | vendor_role | vendor_name | vendor_url | gws_profile_url | is_premium_member |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Style Guides & Editorial objects from greenweddingshoes.com. All fields typed and schema-versioned.
"title": "Top 20 Fall Wedding Dresses", "category": "Fashion", "tags": "['Fall', 'Bridal Gowns', 'Lace']", "affiliate_links": "['https://rstyle.me/n/example']", "publish_date": "2023-10-02", "comment_count": 12
| # | article_id | title | author | category | tags | affiliate_links |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Venues & Locations objects from greenweddingshoes.com. All fields typed and schema-versioned.
"name": "The Fig House", "city": "Los Angeles", "state": "CA", "venue_type": "Industrial Event Space", "indoor_outdoor": "Both", "featured_articles": 8
| # | venue_id | name | city | state | country | venue_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our extraction pipeline targets the Green Wedding Shoes vendor directory and editorial corpus. We map vendor credits across real weddings, track style tags, and extract affiliate product data.
Extract business names, categories, locations, and contact URLs from the GWS Preferred Wedding Artists directory.
Parse locations, venues, colour palettes, and style tags from every featured real wedding.
Link featured weddings back to the exact photographers, planners, and florists credited in the editorial text.
Capture theme tags like boho, modern, rustic, or desert to track shifting bridal aesthetic trends.
Extract dress designers, product names, and outbound affiliate links from fashion roundups.
Compile venue profiles, including location data, venue type, and historical features on the platform.
Scrape hotel recommendations, destination tags, and travel itineraries from the lifestyle sections.
Monitor the site daily for new real wedding posts, vendor additions, and updated editorial content.
Strip WordPress shortcodes and editorial formatting to deliver pristine JSON arrays of structured text.
Brief in. Clean data out.
Select target categories: vendor directories, real weddings, or editorial content.
We configure Scrapy crawlers to navigate the WordPress taxonomy and bypass basic anti-scraping measures.
Schema validation ensures vendor links, Instagram handles, and image URLs match expected formats.
JSON, CSV, or Parquet pushed to your S3 bucket or Snowflake stage on your defined cadence.
Editorial blogs present unique extraction challenges. Content is unstructured, vendor credits are buried in text, and pagination relies on asynchronous loading.
Vendor lists in real wedding posts are often formatted inconsistently. We use custom regex pipelines and DOM traversal to reliably map vendor roles to their respective business names and URLs.
Category pages and galleries use JavaScript-based infinite scroll. We deploy headless Playwright sessions to trigger lazy loading and capture the complete dataset.
We extract the high-resolution source URLs for wedding photography, bypassing thumbnail versions and lazy-loaded placeholders.
Fashion and product features rely heavily on rewardStyle and Skimlinks. We extract the raw affiliate URLs to map product mentions accurately.
WordPress tags vary wildly. We normalise category and style tags into a consistent array format, fixing typos and consolidating duplicate themes.
Wedding software platforms and wholesale suppliers extract vendor lists to build targeted sales outreach campaigns.
Fashion brands and event planners analyse style tags and colour palettes to predict upcoming seasonal wedding trends.
Hospitality groups track which venues are featured frequently to benchmark marketing success and aesthetic appeal.
E-commerce brands monitor outbound affiliate links to understand which products perform well in bridal editorial content.
Marketplaces map co-occurrences of vendors in real weddings to understand referral networks between planners, venues, and photographers.
Bridal inspiration apps ingest structured metadata and high-resolution image links to populate their own discovery feeds.
"Editorial wedding data is incredibly rich but structurally chaotic. Transforming blog posts into a relational vendor database requires precise DOM targeting."
Most teams struggle to extract structured data from editorial WordPress sites. Vendor credits are formatted inconsistently, images are lazy-loaded, and taxonomies overlap. DataFlirt builds specific parsing logic for Green Wedding Shoes, turning unstructured blog features into a clean, queryable relational dataset of vendors, venues, and trends.
Everything supported by our greenweddingshoes.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 manages JavaScript rendering and infinite scroll pagination.
We deploy custom Python text parsing modules to untangle inconsistent editorial formatting and extract clean vendor metadata.
Pipelines run on AWS 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 greenweddingshoes.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available editorial content and vendor directories is generally permissible. DataFlirt targets only public, non-authenticated data. We do not extract personal user data or circumvent authentication walls.
We build custom regex and DOM parsing rules specific to the site's editorial formatting. This allows us to reliably separate vendor roles, business names, and URLs from standard paragraph text.
Yes. We bypass the lazy-loaded thumbnails and extract the source URLs for the highest resolution images available in the media library.
We typically configure pipelines to run weekly or daily to capture new real wedding features and directory additions. Full historical archives take longer to process initially.
Yes. For fashion and product roundups, we extract the raw outbound URLs, including rewardStyle and Skimlinks tracking links.
We build custom pipelines based on your specific data requirements. Contact us to scope the extraction volume and delivery frequency for a precise quote.
Yes. We provide a sample run of up to 100 posts or vendor profiles during the scoping process so you can validate the schema and text parsing accuracy.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a complete vendor directory dump or continuous trend monitoring across new real weddings. Tell us what you need.
