We extract supplier profiles, trade leads, machinery listings, and raw material pricing signals from Fibre2Fashion. 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 Supplier Profiles objects from fibre2fashion.com. All fields typed and schema-versioned.
"company_id": "SUP-847291", "company_name": "Arvind Limited", "category": "Denim Fabric Manufacturer", "country": "India", "verification_status": "Premium Member", "year_established": 1931, "product_range": "['Denim', 'Wovens', 'Knits', 'Voiles']", "employee_count": "10000+"
| # | company_id | company_name | category | country | verification_status | contact_person |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Trade Leads objects from fibre2fashion.com. All fields typed and schema-versioned.
"lead_id": "TL-99281", "lead_type": "Buy", "category": "100% Cotton Yarn", "posted_date": "2026-04-12", "expiry_date": "2026-05-12", "buyer_country": "Bangladesh", "required_quantity": "20 Metric Tons", "payment_terms": "L/C at sight"
| # | lead_id | lead_type | category | posted_date | expiry_date | buyer_country |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Market Pricing objects from fibre2fashion.com. All fields typed and schema-versioned.
"material_type": "Cotton", "variant": "Shankar-6", "origin": "India", "price": 61500.0, "currency": "INR", "unit": "Candy", "price_change_pct": 1.2, "recorded_date": "2026-05-12"
| # | material_type | variant | origin | price | currency | unit |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Machinery Listings objects from fibre2fashion.com. All fields typed and schema-versioned.
"listing_id": "MAC-4412", "machine_type": "Spinning Machine", "brand": "Rieter", "model": "G 32", "condition": "Used", "year_of_make": 2018, "location": "Turkey", "price": 45000.0, "currency": "USD"
| # | listing_id | machine_type | brand | model | condition | year_of_make |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Industry News objects from fibre2fashion.com. All fields typed and schema-versioned.
"article_id": "NW-10492", "headline": "Global Cotton Output Projected to Rise by 3%", "category": "Market Trends", "publish_date": "2026-05-11T14:30:00Z", "author": "Fibre2Fashion News Desk", "tags": "['Cotton', 'Agriculture', 'Yield']", "source_url": "https://www.fibre2fashion.com/news/..."
| # | article_id | headline | category | publish_date | author | summary |
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Our Fibre2Fashion scraper targets the core B2B data layers: supplier directories, dynamic raw material pricing, global trade leads, and machinery listings — built with anti-bot circumvention for reliable extraction.
Extract company profiles, contact details, product portfolios, and verification statuses across all textile and apparel categories.
Capture daily pricing for cotton, yarn, polyester, and viscose across global markets, timestamped per crawl.
Track buy and sell requirements, target prices, required quantities, and buyer locations to identify procurement opportunities.
Extract details on new and used textile machinery, including specifications, year of make, location, and seller details.
Scrape headlines, summaries, and full text from the news section to track macroeconomic trends affecting the textile sector.
Monitor upcoming global textile trade shows, participant lists, and event schedules.
Identify new supplier registrations, updated machinery listings, and fresh trade leads without re-downloading the entire catalogue.
Extract data specific to regional markets, isolating pricing and supplier data for India, Bangladesh, Vietnam, or Turkey.
Run one-off bulk exports or configure continuous pipelines at hourly, daily, or real-time cadences.
Brief in. Clean data out.
Provide target categories, material types, or specific supplier directories. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for fibre2fashion.com.
Schema validation, null-rate checks, price-outlier detection, and sample data review before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
B2B portals protect their directories and market data. Here's how we maintain reliable extraction pipelines.
B2B portals monitor request frequency and IP reputation. Our crawlers use residential ISP proxies with realistic browser fingerprints and randomised request timing to avoid rate limits.
Pricing charts and contact detail reveals often require JavaScript execution. We run full Playwright browser sessions to trigger lazy-loads and hydrate dynamic widgets.
Site layouts change. Our selector strategy uses multiple fallback chains per field — CSS selectors, XPath, and text-pattern matching — ensuring continuous data flow.
For large supplier directories, we maintain a hash index of last-seen values. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Every run emits structured logs. We alert on null-rate spikes, missing pricing data, and coverage drops — responding before you notice.
Apparel brands and manufacturers build alternative supplier databases to mitigate supply chain risks and negotiate better rates.
Commodity analysts track historical raw material pricing (cotton, yarn) to forecast manufacturing costs and optimise purchasing cycles.
Machinery manufacturers, chemical suppliers, and logistics firms extract verified company profiles to build targeted outbound sales lists.
Consultancies monitor trade leads and machinery sales to gauge regional manufacturing capacity and textile sector growth.
Textile mills track competitor product portfolios, certifications, and exhibition participation.
Sustainability teams map regional supplier networks to verify tier-2 and tier-3 vendor locations and capabilities.
"Fibre2Fashion holds the global textile industry's pricing and supplier network — but extracting it into queryable formats requires dedicated infrastructure."
Textile market intelligence requires continuous monitoring of fragmented supplier listings and volatile raw material prices. DataFlirt handles the complex scraping infrastructure so your procurement and analytics teams can focus on supply chain optimisation — not managing proxies and selector maintenance.
Everything supported by our fibre2fashion.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, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across global regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). 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 fibre2fashion.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 supplier, pricing, and trade lead data. We do not circumvent authentication walls for paid TexPro data. Clients should review the site's ToS and consult legal counsel for specific use cases.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. This prevents triggering IP bans or CAPTCHA walls during deep directory pagination.
Yes. We can configure daily runs targeting specific material categories and regional markets, delivering a structured time-series dataset of price fluctuations.
We extract all contact information that is publicly surfaced on the supplier profile pages, including phone numbers, websites, and listed contact persons.
No. DataFlirt does not bypass authentication walls or extract data that requires a paid premium subscription to view.
Absolutely. We provide a sample run of up to 500 supplier profiles or 50 trade leads as part of the pre-engagement scoping process — so you can validate schema fit and data quality.
Our smallest packages start at a defined category list with weekly delivery. For larger continuous monitoring of pricing or trade leads, we price based on volume and delivery frequency. Contact us for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off supplier directory dump or a continuous raw material price feed — we scope, build, and operate the pipeline. Tell us what you need.
