We extract market screeners, published ideas, Pine Script metadata, and technical indicator values from TradingView. 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 Screener Data objects from tradingview.com. All fields typed and schema-versioned.
"ticker": "AAPL", "exchange": "NASDAQ", "close_price": 185.92, "volume": 54291000, "market_cap": 2940000000000, "pe_ratio": 29.4, "sector": "Electronic Technology", "rating": "Strong Buy"
| # | ticker | exchange | close_price | volume | market_cap | pe_ratio |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Published Ideas objects from tradingview.com. All fields typed and schema-versioned.
"idea_id": "TV-98274A", "title": "Bitcoin Macro Accumulation Phase", "author": "CryptoQuant", "asset": "BTCUSD", "direction": "Long", "likes": 1240, "published_at": "2026-05-12T08:14:00Z", "tags": "['Bitcoin', 'Macro', 'Accumulation']"
| # | idea_id | title | author | author_url | asset | timeframe |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Financial Statements objects from tradingview.com. All fields typed and schema-versioned.
"ticker": "MSFT", "period": "Q1 2026", "revenue": 62400000000, "gross_profit": 42100000000, "net_income": 22300000000, "eps_diluted": 2.99, "currency": "USD", "free_cash_flow": 18400000000
| # | ticker | period | revenue | gross_profit | operating_income | net_income |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Pine Scripts objects from tradingview.com. All fields typed and schema-versioned.
"script_id": "PUB-8832", "name": "SuperTrend Multi-Timeframe", "author": "KivancOzbilgic", "is_open_source": true, "likes": 45192, "category": "Trend Analysis", "version": "v4.2"
| # | script_id | name | author | is_open_source | is_protected | likes |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Economic Calendar objects from tradingview.com. All fields typed and schema-versioned.
"event_id": "EC-9921", "country": "US", "event_name": "Non Farm Payrolls", "actual": "215K", "forecast": "190K", "previous": "185K", "impact": "High", "currency": "USD"
| # | event_id | country | event_name | actual | forecast | previous |
|---|---|---|---|---|---|---|
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Our TradingView scraper handles every layer of the platform: stock screeners, user-published ideas, financial statements, and custom Pine Script metadata, with JavaScript rendering and anti-bot circumvention built in.
Extract full screener tables across equities, crypto, and forex with all 150+ available filter columns.
Capture text, tags, asset class, and directional bias from user-published trading ideas.
Pull quarterly and annual income statements, balance sheets, and cash flow metrics for any listed ticker.
Index public indicators and strategies, capturing author details, like counts, and open-source status.
Monitor macroeconomic events, forecasts, and actual prints mapped to specific currencies and timezones.
Track top gainers, losers, and volume leaders across global exchanges in real time.
Extract reputation scores, follower counts, and historical idea accuracy for top TradingView contributors.
Unified extraction schema across NASDAQ, NYSE, LSE, NSE, Binance, and 50+ other supported exchanges.
Run one-off bulk exports or configure continuous pipelines at hourly or daily cadences.
Brief in. Clean data out.
Provide ticker lists, screener URLs, or author profiles. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and session management for tradingview.com.
Schema validation, null-rate checks, and data type normalisation before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
TradingView employs strict rate limits and complex WebSocket connections. Here is how we maintain reliable extraction and why teams choose managed infrastructure.
TradingView blocks datacentre IPs rapidly. We route requests through residential proxies with realistic TLS fingerprints and managed cookie sessions.
Screener tables and idea charts require heavy client-side rendering. We execute full browser sessions to hydrate data before extraction.
Real-time price updates load via WebSockets rather than HTTP requests. Our pipeline intercepts WSS frames to capture live tick data where required.
To prevent shadow-banning, our crawlers dynamically adjust request concurrency based on response headers and 429 status codes.
We use multiple fallback chains per field, including JSON-LD extraction and regex pattern matching on inline state objects.
Hedge funds and prop desks ingest screener data and technical indicator signals to feed algorithmic execution models.
NLP models parse published ideas and comments to gauge retail sentiment on specific equities or crypto pairs.
Data vendors aggregate Pine Script popularity and author reputation to build proprietary retail engagement metrics.
Equity researchers pull historical financial statements and valuation ratios across thousands of global tickers simultaneously.
Macro funds ingest economic calendar prints and forecasts to model currency pair volatility.
Retail brokerages track top-performing TradingView authors to identify trending assets and potential partnership opportunities.
"TradingView hosts the largest repository of retail trading sentiment and custom indicators, but extracting it requires navigating complex WebSockets and strict rate limits."
Most teams underestimate the engineering required to scrape TradingView reliably. It demands intercepting WebSocket frames, executing heavy JavaScript for dynamic screeners, and rotating residential proxies to avoid instant bans. DataFlirt absorbs this infrastructure burden so your quants can focus on alpha generation.
Everything supported by our tradingview.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. Playwright handles JavaScript rendering and WebSocket interception.
We maintain pools of residential ISP proxies. Rotation happens per-request with sticky sessions.
Pipelines run on AWS ECS. Airflow handles scheduling and dependency management. State stored in Postgres.
Data delivered to where your team already works — no new tooling required.
About tradingview.com scraping, legality, and pipeline operations.
Ask us directly →Scraping public data is generally permissible. We target non-authenticated ideas, public scripts, and delayed screener data.
We extract what TradingView displays. For assets requiring paid exchange subscriptions, we only capture the delayed public feed.
We extract source code for open-source scripts. Invite-only or closed-source scripts only yield metadata.
Our Playwright integration intercepts WSS frames to capture live updates on active browser sessions.
Yes. We extract all macro events, forecasts, and actual prints normalised to your preferred timezone.
Pipelines can run at hourly or daily cadences. Continuous execution is available for specific ticker subsets.
Yes. We provide a sample run of up to 500 tickers or ideas to validate schema fit before contracting.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily screener export or a continuous feed of published trading ideas, we scope, build, and operate the pipeline. Tell us what you need.
