We extract market reports, factory profiles, sustainability metrics, and yarn pricing from TextileToday. Delivered as clean JSON, CSV, or Parquet to your data warehouse 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 News & Articles objects from textiletoday.com.bd. All fields typed and schema-versioned.
"article_id": "TT-94821", "title": "Bangladesh RMG export sees 12% growth in Q3", "author_name": "Rahim Uddin", "publish_date": "2026-10-14T08:30:00Z", "category": "Apparel Sourcing", "content_body": "The ready-made garment sector in Bangladesh recorded significant growth...", "tags": "['RMG', 'Export', 'Q3', 'Bangladesh']"
| # | article_id | title | author_name | publish_date | category | tags |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Market Reports objects from textiletoday.com.bd. All fields typed and schema-versioned.
"report_id": "MR-492", "title": "Global Cotton Price Index - October Update", "publication_date": "2026-10-01", "commodity_type": "Cotton", "price_data_extracted": "84.50 cents/lb", "market_trend": "Bullish", "region": "Global"
| # | report_id | title | publication_date | commodity_type | price_data_extracted | market_trend |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Company Directory objects from textiletoday.com.bd. All fields typed and schema-versioned.
"company_name": "Apex Textile Mills Ltd", "industry_segment": "Knitwear", "location": "Gazipur, Bangladesh", "established_year": 1993, "employee_count": "5000+", "certifications": "['OEKO-TEX', 'LEED Gold']"
| # | company_name | industry_segment | location | established_year | employee_count | machinery_used |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Machinery Updates objects from textiletoday.com.bd. All fields typed and schema-versioned.
"equipment_name": "EcoMaster Dyeing Machine v4", "manufacturer": "Fong's", "tech_specs": "Low liquor ratio 1:4, automated dosing", "application_area": "Wet Processing", "launch_date": "2026-08-15", "review_summary": "Reduces water consumption by 30% compared to previous models."
| # | equipment_name | manufacturer | tech_specs | application_area | launch_date | article_url |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Events & Exhibitions objects from textiletoday.com.bd. All fields typed and schema-versioned.
"event_name": "Dhaka International Textile & Garment Machinery Exhibition", "start_date": "2027-02-15", "end_date": "2027-02-18", "venue": "ICCB, Dhaka", "organizer": "BTMA", "status": "Upcoming"
| # | event_name | start_date | end_date | venue | organizer | exhibitor_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our infrastructure parses thousands of articles, reports, and factory profiles from TextileToday, converting unstructured editorial content into queryable datasets.
Capture headline, author, publish date, category, tags, and full body text for every news piece published on the portal.
Extract pricing signals, commodity trends, and export statistics embedded within unstructured report text.
Compile directories of textile mills, tracking their machinery updates, sustainability certifications, and production capacities.
Traverse years of historical textile data to build long-term trend models for yarn pricing and RMG exports.
Automated crawling across all sub-categories including spinning, weaving, dyeing, and apparel merchandising.
Track industry experts, columnists, and academic contributors across their published articles.
Download and map high-resolution machinery images, factory photos, and embedded infographics.
Monitor upcoming textile exhibitions, capturing dates, venues, and exhibitor lists.
Configure daily or weekly pipelines to capture newly published articles and market reports automatically.
Brief in. Clean data out.
Select target categories such as market reports, machinery updates, or the full historical news archive.
We deploy Scrapy crawlers configured to traverse TextileToday's CMS structure and handle pagination.
We test the extraction against various article templates to ensure body text and metadata are cleanly parsed.
Structured data is pushed to your preferred warehouse via S3, BigQuery, or API on your defined schedule.
TextileToday relies on varied article templates and unstructured text. We apply robust normalisation to ensure clean output.
Market prices and factory capacities are often buried in paragraphs. We use regex and pattern matching to pull quantitative data out of qualitative articles.
Editorial sites change their layouts frequently. Our selectors account for multiple article templates, ensuring the core text and author metadata are always captured.
We systematically crawl through thousands of paginated category pages to ensure no historical article is missed.
We extract image URLs and associate them with the correct article or machinery profile, enabling rich visual datasets.
Our pipelines hash existing records and only extract newly published articles or updated reports, saving compute and storage costs.
Brands and retailers monitor factory updates and sustainability certifications to identify new sourcing partners in Bangladesh.
Analysts aggregate yarn and cotton pricing reports to model raw material cost fluctuations.
Textile mills track machinery investments and capacity expansions announced by rival manufacturers.
Equipment manufacturers analyse technology adoption trends and factory upgrades across the RMG sector.
Researchers compile historical export data and policy changes to study the economic impact of the RMG industry.
Organisers track industry events to optimize scheduling and target potential exhibitors.
"TextileToday holds the most concentrated repository of Bangladesh apparel manufacturing data. You just need the infrastructure to extract it."
Extracting data from niche industry portals requires handling inconsistent CMS templates, unstructured report text, and embedded tables. DataFlirt normalises this editorial chaos into structured datasets so your analysts can track supply chain shifts without manual copy-pasting.
Everything supported by our textiletoday.com.bd 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 the traversal of WordPress and custom CMS structures, normalising inconsistent layouts into a single schema.
We utilize datacenter and residential proxies to bypass basic rate limiting and Cloudflare challenges without triggering blocks.
Airflow manages the scheduling of daily or weekly crawls, ensuring your data warehouse always has the latest industry news.
Data delivered to where your team already works — no new tooling required.
About textiletoday.com.bd scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available news articles, market reports, and directories is generally permissible. DataFlirt extracts only public, non-authenticated data and does not bypass paywalls or extract personal identifiable information beyond public author profiles.
We typically configure pipelines for TextileToday to run daily or weekly, capturing new articles and reports shortly after they are published.
Yes. Market reports often contain HTML tables detailing yarn prices or export volumes. We parse these tables and convert them into structured JSON arrays or CSV columns.
We extract the direct URLs for all images and PDF reports. We can also configure the pipeline to download these assets directly to your S3 bucket.
Yes. We can perform a one-off historical crawl to extract the entire archive of articles and reports, providing a baseline dataset before starting incremental daily updates.
We recommend JSON or Parquet for article data, as they handle long text bodies, nested tags, and multiple image URLs better than flat CSV files.
20-minute scoping call. Pilot dataset within the week. Production within two. Stop manually compiling industry reports. We build the pipeline to feed TextileToday data directly into your warehouse.
