We extract global news feeds, market quotes, company financials, and geopolitical reporting from Reuters. 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 Article Data objects from reuters.com. All fields typed and schema-versioned.
"article_id": "RTS29F1A", "headline": "Fed leaves rates unchanged", "authors": "['Ann Saphir', 'Howard Schneider']", "published_date": "2023-11-01T18:00:00Z", "category": "Markets", "tags": "['Federal Reserve', 'Interest Rates', 'US Economy']", "related_tickers": "['US10YT=RR']"
| # | article_id | url | headline | subheadline | authors | published_date |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Market Quotes objects from reuters.com. All fields typed and schema-versioned.
"ticker": "AAPL.O", "company_name": "Apple Inc", "exchange": "NASDAQ", "current_price": 185.64, "currency": "USD", "change_pct": 1.2, "volume": 54321000, "market_cap": 2910000000000
| # | ticker | company_name | exchange | current_price | currency | change_abs |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Company Profiles objects from reuters.com. All fields typed and schema-versioned.
"ticker": "TSLA.O", "company_name": "Tesla Inc", "sector": "Consumer Cyclicals", "industry": "Auto & Truck Manufacturers", "headquarters": "Austin, Texas", "employees": 127855, "esg_score": 42.1
| # | ticker | company_name | sector | industry | description | headquarters |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Earnings & Financials objects from reuters.com. All fields typed and schema-versioned.
"ticker": "MSFT.O", "period": "Q3 2023", "revenue": 56517000000, "net_income": 22291000000, "eps": 2.99, "eps_estimate": 2.65, "gross_margin": 71.2
| # | ticker | period | revenue | net_income | eps | eps_estimate |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Authors & Contributors objects from reuters.com. All fields typed and schema-versioned.
"name": "Jonathan Stempel", "role": "Correspondent", "location": "New York", "topics_covered": "['Legal', 'Courts', 'Corporate Law']", "article_count": 342, "twitter_handle": "@jonstempel"
| # | author_id | name | role | location | twitter_handle | article_count |
|---|---|---|---|---|---|---|
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Our Reuters scraper handles every layer of the platform. We extract global news feeds, market quotes, and company financials with full session management and anti-bot circumvention built in.
Extract headlines, full body text, authors, published and updated timestamps, and embedded media links across all news categories.
Capture real-time ticker prices, volume, market cap, and percentage changes across global exchanges directly from Reuters market pages.
Scrape decades of historical articles and press releases to build comprehensive datasets for backtesting and analysis.
Monitor specific journalists or beats. Extract author metadata, location, and historical publication records.
Extract income statements, balance sheets, and key ratios from Reuters company profile and financial pages.
Capture environmental, social, and governance scores assigned to public companies within the Reuters database.
Extract Reuters internal taxonomy, including topics, regions, and related company tickers attached to every article.
Extract localized news and market data from US, UK, Europe, and Asia-Pacific editions of Reuters.
Configure continuous pipelines at sub-minute cadences for breaking news alerts and real-time market updates.
Brief in. Clean data out.
Provide categories, ticker lists, or author profiles. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, session management, and CAPTCHA handling for reuters.com.
Schema validation, null-rate checks, and sample data review before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Scraping high-velocity news and market data requires strict latency controls and anti-bot circumvention.
Reuters employs strict anti-bot measures. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management to bypass Datadome protections.
Market data and interactive charts on Reuters are heavily JavaScript-rendered. We run full Playwright browser sessions with JavaScript execution to capture data that headless HTTP clients miss entirely.
Financial news loses value in minutes. Our infrastructure supports sub-minute polling on targeted RSS feeds and category pages to deliver breaking headlines with minimal latency.
News article layouts vary by category and media type. Our selector strategy uses multiple fallback chains per field so a special report layout does not break your data pipeline.
Reuters frequently updates articles as stories develop. We maintain a hash index of last-seen values and emit diffs, allowing you to track narrative shifts and factual corrections over time.
Quantitative funds run sentiment analysis on breaking news and earnings reports to execute automated trades.
Analysts track macroeconomic trends, central bank commentary, and sector-specific news to build investment theses.
Corporate strategy teams monitor company mentions, M&A rumours, and leadership changes across the global news cycle.
Compliance teams track corporate governance news, environmental controversies, and labor disputes to adjust ESG portfolios.
Machine learning teams use high-quality financial journalism datasets to train domain-specific Large Language Models.
Supply chain and risk officers monitor geopolitical reporting and regional conflicts to assess operational vulnerabilities.
"Reuters is the definitive source for global financial news. Extracting it as structured, machine-readable data requires overcoming aggressive rate limits and dynamic payloads."
Most teams underestimate the investment required. Reliable Reuters scraping requires Datadome bypass, full JavaScript rendering for market data, and sub-minute polling for breaking news. DataFlirt absorbs that complexity so your quants can focus on alpha, not infrastructure.
Everything supported by our reuters.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 and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About reuters.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Reuters is generally permissible for non-commercial research or internal analysis. DataFlirt targets only public, non-authenticated news and market data. We do not extract paywalled content. Clients should review Reuters Terms of Service and consult legal counsel for specific commercial use cases.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We monitor for CAPTCHA rate spikes in real time and trigger pool rotation automatically.
Real-time streaming pipelines achieve sub-minute latency for breaking news on targeted category pages and RSS feeds. Full site historical refreshes run at daily cadences.
Yes. Every pipeline run produces timestamped snapshots. We maintain a hash index per article and emit diff records when headlines or body text are updated by editors.
Yes. We extract income statements, balance sheets, key ratios, and ESG scores directly from public Reuters company profile pages.
Absolutely. We provide a sample run of up to 500 articles or market quotes as part of the pre-engagement scoping process so you can validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off historical news archive or a continuous market data feed, we scope, build, and operate the pipeline. Tell us what you need.
