We extract equities, options flow, futures contracts, commodities pricing, and Barchart Opinion indicators. 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 Equities & Stocks objects from barchart.com. All fields typed and schema-versioned.
"symbol": "AAPL", "company_name": "Apple Inc.", "last_price": 189.45, "price_change": 1.2, "percent_change": 0.64, "volume": 45892100, "barchart_opinion": "88% Buy"
| # | symbol | company_name | exchange | last_price | price_change | percent_change |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Options Data & Greeks objects from barchart.com. All fields typed and schema-versioned.
"symbol": "AAPL240119C00190000", "underlying_symbol": "AAPL", "expiration_date": "2024-01-19", "strike_price": 190.0, "option_type": "Call", "last_price": 4.55, "implied_volatility": 0.245, "delta": 0.52
| # | symbol | underlying_symbol | expiration_date | strike_price | option_type | last_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Futures & Commodities objects from barchart.com. All fields typed and schema-versioned.
"contract_symbol": "CLZ24", "commodity_name": "Crude Oil WTI", "expiration_month": "Dec 2024", "last_price": 78.45, "price_change": -0.32, "volume": 124500, "open_interest": 345000
| # | contract_symbol | commodity_name | expiration_month | last_price | price_change | high |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Unusual Options Activity objects from barchart.com. All fields typed and schema-versioned.
"symbol": "TSLA240216P00200000", "base_symbol": "TSLA", "option_type": "Put", "strike": 200.0, "volume": 15400, "open_interest": 1200, "vol_oi_ratio": 12.8, "implied_volatility": 0.58
| # | symbol | base_symbol | option_type | strike | expiration | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Barchart Opinion objects from barchart.com. All fields typed and schema-versioned.
"symbol": "NVDA", "overall_opinion": "100% Buy", "short_term_indicator": "Buy", "medium_term_indicator": "Buy", "long_term_indicator": "Buy", "rsi_14": 72.4, "50_day_ma": 425.6
| # | symbol | overall_opinion | short_term_indicator | medium_term_indicator | long_term_indicator | 20_day_ma |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Barchart scraper processes dynamic financial tables, XHR payloads, and historical charts to deliver structured market intelligence without the overhead of manual data engineering.
Capture high volume-to-open-interest ratios, sweep orders, and block trades across all US equity options.
Extract continuous front-month contracts, term structures, and settlement prices for energy, metals, and agriculture.
Track proprietary buy/sell signals, trend indicators, and technical strength scores across multiple timeframes.
Extract delta, gamma, theta, vega, and IV metrics for complete options chains at end-of-day or intraday intervals.
Monitor price action, volume leaders, sector performance, and detailed ETF holdings across global exchanges.
Paginate through historical daily, weekly, and monthly price charts to build comprehensive backtesting datasets.
Extract spot rates, forward curves, and trading volumes for major currency pairs and digital assets.
Track EPS estimates, earnings surprise history, dividend dates, and core financial ratios for publicly traded companies.
Scrape pre-market gainers, 52-week highs/lows, and gap up/down lists directly from Barchart's dynamic screeners.
Brief in. Clean data out.
Provide ticker lists, asset classes, or specific Barchart screener URLs. We map the extraction schema.
We configure Playwright spiders, proxy rotation, and anti-bot circumvention for barchart.com.
Schema validation, null-rate checks, and data type normalisation before full production launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Financial data sites employ aggressive rate limiting and complex dynamic rendering. Here is how we maintain data integrity at scale.
Barchart populates options chains and screener results via complex asynchronous requests. Our pipeline intercepts these XHR payloads directly, bypassing HTML parsing for faster, more reliable extraction.
Financial data sites aggressively throttle high-frequency requests. We distribute queries across a pool of ISP-grade residential proxies, preventing IP bans and ensuring continuous data flow during market hours.
Barchart's web interface restricts deep pagination on large result sets. We construct programmatic API queries to bypass UI limits, extracting the complete dataset rather than just the first 1,000 rows.
Raw financial data often contains mixed formats. We normalise volumes, dates, and strike prices into strict numeric and ISO-8601 formats before delivery.
During market open and close, the volume of unusual options activity spikes exponentially. Our Kubernetes-based infrastructure scales worker nodes dynamically to maintain latency SLAs during peak volatility.
Quant funds consume historical options data and futures term structures to backtest statistical arbitrage strategies.
Prop desks monitor Barchart's unusual options activity and volume leaders to gauge retail sentiment and institutional positioning.
Portfolio managers track implied volatility surfaces and Options Greeks to dynamically hedge equity exposure.
Supply chain teams monitor agriculture and energy futures to optimise physical commodity purchasing and lock in forward pricing.
Market data vendors integrate Barchart Opinion ratings and technical indicators into their own retail trading platforms.
Universities and economic researchers analyse long-term equities and futures datasets for macroeconomic studies.
"Barchart aggregates an immense volume of derivatives and commodities data, but institutional analysis requires that data in a queryable warehouse, not a web browser."
Extracting financial data at scale requires strict adherence to schema typing, latency management, and robust anti-bot circumvention. DataFlirt manages the proxy rotation, XHR interception, and infrastructure scaling so your quantitative analysts can focus on alpha generation, not pipeline maintenance.
Everything supported by our barchart.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 IN/US/UK/DE 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 barchart.com scraping, legality, and pipeline operations.
Ask us directly →Web scraping is bound by HTTP latency and caching layers. We provide high-frequency intraday snapshots (e.g., 5-minute or 15-minute intervals), but sub-second tick data requires direct exchange API feeds.
Yes. We extract the overall percentage rating alongside the short, medium, and long-term technical indicators for any specified list of equities or ETFs.
We utilise ISP-grade residential proxies, realistic TLS fingerprinting, and automated CAPTCHA solving. For complex dynamic tables, we intercept the underlying XHR requests rather than simulating browser clicks.
Yes. We monitor and extract the Unusual Options Activity screeners, capturing strike, expiration, volume-to-open-interest ratios, and implied volatility metrics.
We can extract historical daily, weekly, or monthly OHLCV data as presented on Barchart's historical data pages, paginating through the available date ranges.
Our pipelines use resilient fallback selectors and API endpoint targeting. If a structural change causes a failure, our alerting stack notifies our engineering team immediately to deploy a fix, ensuring minimal downtime.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need daily options flow data or a continuous feed of futures pricing — we scope, build, and operate the pipeline. Tell us what you need.
