We extract clothing catalogues, homeware inventory, size variants, pricing signals, and stock levels from Riachuelo. Delivered as clean JSON, CSV, or Parquet.
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 riachuelo.com.br. All fields typed and schema-versioned.
"sku": "14285930", "title": "Camisa Manga Longa Masculina", "brand": "Pool by Riachuelo", "price_brl": 119.9, "discount_pct": 15, "in_stock": true, "available_sizes": "['P', 'M', 'G', 'GG']", "composition": "100% Algodao"
| # | sku | title | brand | category_path | price_brl | list_price_brl |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Pricing & Offers objects from riachuelo.com.br. All fields typed and schema-versioned.
"sku": "14285930", "price_brl": 119.9, "list_price_brl": 139.9, "midway_card_price": 109.9, "max_installments": 3, "installment_value": 39.96, "stock_status": "IN_STOCK", "scraped_at": "2026-05-12T10:15:00Z"
| # | sku | price_brl | list_price_brl | midway_card_price | discount_pct | promotion_name |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Variants & Inventory objects from riachuelo.com.br. All fields typed and schema-versioned.
"parent_sku": "14285930", "child_sku": "14285930-M-Azul", "size": "M", "colour": "Azul Marinho", "availability_status": "LOW_STOCK", "ean": "7891000234567", "store_availability": false
| # | parent_sku | child_sku | size | colour | stock_quantity | availability_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Casa Riachuelo objects from riachuelo.com.br. All fields typed and schema-versioned.
"sku": "15392011", "product_name": "Jogo de Lencol Casal Percal", "department": "Casa Riachuelo", "room_category": "Quarto", "material": "100% Algodao 200 Fios", "price_brl": 199.9, "dimensions": "138x188x30cm"
| # | sku | product_name | department | room_category | material | dimensions |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Search Results objects from riachuelo.com.br. All fields typed and schema-versioned.
"keyword": "jaqueta jeans", "position": 1, "sku": "13849201", "product_name": "Jaqueta Jeans Feminina Cropped", "brand": "AK by Riachuelo", "price_brl": 159.9, "rating": 4.5, "review_count": 42
| # | keyword | position | sku | product_name | brand | price_brl |
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Our Riachuelo scraper handles complex variant structures, dynamic inventory loading, and regional pricing differences. Built with full JavaScript rendering to capture exact stock states.
Title, brand, composition, care instructions, and metadata fields mapped at the SKU level.
Extract all parent-child variant relationships across clothing and footwear lines.
Capture base price, promotional discounts, and specific Midway card pricing tiers.
Monitor in-stock status and low-stock warnings across all size and colour permutations.
Dedicated extraction for homeware, bedding, and decor categories with dimensional specifications.
Extract maximum installment counts and minimum parcel values for high-ticket items.
Map the full breadcrumb trail from top-level department down to specific sub-categories.
Capture main product images, variant-specific angles, and lifestyle shots.
Run daily or hourly pipelines with change-detection diffing to reduce storage bloat.
Brief in. Clean data out.
Provide category URLs, brand names, or specific SKU lists. We map the extraction schema.
We configure Scrapy and Playwright crawlers with Brazilian residential proxies to bypass regional blocks.
Schema validation, null-rate checks, and variant mapping verification before full production launch.
JSON, CSV, or Parquet pushed to your S3 bucket or data warehouse on an agreed schedule.
Apparel sites rely heavily on dynamic frontends for variant selection. Here is how we ensure accurate data capture.
Size and colour selections trigger asynchronous stock and price updates. We use Playwright to simulate variant selection and capture the exact state for every permutation.
Riachuelo alters availability and delivery estimates based on location. We route requests through Brazilian residential IPs to ensure accurate local data representation.
Infinite scroll on category pages often drops items. We intercept underlying GraphQL and REST API calls to ensure 100% coverage of the product catalogue.
Retail sites update layouts for seasonal campaigns. We use CSS, XPath, and JSON-LD extraction methods to maintain pipeline stability during promotional events.
Tracking stock across thousands of SKUs generates massive datasets. We hash record states and only emit rows when price, stock, or promotional status changes.
Fashion retailers track Riachuelo pricing, promotional cadences, and discount depths to adjust their own strategies.
Brands analyze category depth, brand representation, and new product introductions across apparel and home departments.
Analysts monitor out-of-stock rates on key sizes and colours to estimate sales velocity and inventory health.
Researchers track material composition, colour prevalence, and style metadata to identify macro fashion trends.
Suppliers verify that their products are priced according to MAP agreements and featured correctly during sales events.
Machine learning teams use structured product descriptions, attributes, and images to train visual search and recommendation models.
"Apparel data is uniquely complex. A single shirt might have fifteen size and colour combinations, each with its own stock state and price point."
Extracting data from modern fashion retailers requires more than simple HTTP requests. You need full browser automation to trigger variant state changes, intercept backend API responses, and bypass regional bot protection. DataFlirt manages this entire infrastructure layer, delivering clean, normalised catalogues directly to your warehouse.
Everything supported by our riachuelo.com.br 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 manages request queues and deduplication, while Playwright handles JavaScript execution for complex variant selection.
Requests are routed through Brazilian residential proxy nodes to ensure accurate regional pricing and avoid geo-blocking.
Airflow schedules daily catalogue crawls, managing retries, dependency graphs, and data validation before warehouse delivery.
Data delivered to where your team already works — no new tooling required.
About riachuelo.com.br scraping, legality, and pipeline operations.
Ask us directly →Yes. Our pipeline maps the parent-child relationships, capturing specific stock levels, EANs, and prices for every available size and colour combination.
Yes. We extract both the standard retail price and any specific promotional pricing tiers available to Midway cardholders.
We use Playwright to execute JavaScript and intercept background API calls, ensuring we capture the complete product catalogue without missing items due to lazy-loading.
Yes. By configuring daily or hourly pipeline runs, we build a time-series dataset of stock status, allowing you to track inventory velocity.
Yes. The pipeline supports all departments across riachuelo.com.br, including apparel, electronics, beauty, and Casa Riachuelo homeware.
Yes. We parse the detailed product description and specification tabs to extract fabric composition, care instructions, and manufacturing origin where available.
Yes. We provide sample exports of up to 1,000 SKUs during the scoping phase to ensure the schema meets your analytical requirements.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily catalogue sync or continuous competitor price monitoring, we build and maintain the infrastructure. Provide your requirements.
