Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Developer Tools
yahooquery
Access Yahoo Finance data including real-time pricing, fundamentals, analyst estimates, options, news, and historical data via the yahooquery Python library.
skill openclawclawhub Free
Access Yahoo Finance data including real-time pricing, fundamentals, analyst estimates, options, news, and historical data via the yahooquery Python library.
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Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
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Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, references/research.md, references/keyword_arguments.md, references/index.md, references/advanced.md, references/misc.md
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Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- 512z
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Documentation
yahooquery Skill
Comprehensive access to Yahoo Finance data via the yahooquery Python library. This library provides programmatic access to nearly all Yahoo Finance endpoints, including real-time pricing, fundamentals, analyst estimates, options, news, and premium research.
1. Ticker (Company-Specific Data)
The primary interface for retrieving data about one or more securities. from yahooquery import Ticker # Single or multiple symbols aapl = Ticker('AAPL') tickers = Ticker('AAPL MSFT NVDA', asynchronous=True)
2. Screener (Predefined Stock Lists)
Access to pre-built screeners for discovering stocks by criteria. from yahooquery import Screener s = Screener() screeners = s.available_screeners # List all available screeners data = s.get_screeners(['day_gainers', 'most_actives'], count=10)
3. Research (Premium Subscription Required)
Access proprietary research reports and trade ideas. from yahooquery import Research r = Research(username='you@email.com', password='password') reports = r.reports(report_type='Analyst Report', report_date='Last Week') trades = r.trades(trend='Bullish', term='Short term')
Ticker Class: Data Modules
The Ticker class exposes dozens of data endpoints via properties and methods.
๐ Financial Statements
.income_statement(frequency='a', trailing=True) - Income statement (annual/quarterly) .balance_sheet(frequency='a', trailing=True) - Balance sheet .cash_flow(frequency='a', trailing=True) - Cash flow statement .all_financial_data(frequency='a') - Combined financials + valuation measures .valuation_measures - EV/EBITDA, P/E, P/B, P/S across periods
๐ Pricing & Market Data
.price - Current pricing, market cap, 52-week range .history(period='1y', interval='1d', start=None, end=None) - Historical OHLC period: 1d, 5d, 1mo, 3mo, 6mo, 1y, 2y, 5y, 10y, ytd, max interval: 1m, 2m, 5m, 15m, 30m, 60m, 90m, 1h, 1d, 5d, 1wk, 1mo, 3mo .option_chain - Full options chain (all expirations)
๐ Analysis & Estimates
.calendar_events - Next earnings date, EPS/revenue estimates .earning_history - Actual vs. estimated EPS (last 4 quarters) .earnings - Historical quarterly/annual earnings and revenue .earnings_trend - Analyst estimates for upcoming periods .recommendation_trend - Buy/Sell/Hold rating changes over time .gradings - Recent analyst upgrades/downgrades
๐ข Company Fundamentals
.asset_profile - Address, industry, sector, business summary, officers .company_officers - Executives with compensation details .summary_profile - Condensed company information .key_stats - Forward P/E, profit margin, beta, shares outstanding .financial_data - Financial KPIs (ROE, ROA, debt-to-equity, margins)
๐ฅ Ownership & Governance
.insider_holders - List of insider holders and positions .insider_transactions - Recent buy/sell transactions by insiders .institution_ownership - Top institutional holders .fund_ownership - Top mutual fund holders .major_holders - Ownership summary (institutional %, insider %, float)
๐ ESG & Ratings
.esg_scores - Environmental, Social, Governance scores and controversies .recommendation_rating - Analyst consensus (Strong Buy โ Strong Sell)
๐ฐ News & Insights
.news() - Recent news articles .technical_insights - Bullish/bearish technical patterns
๐ฐ Funds & ETFs Only
.fund_holding_info - Top holdings, bond/equity breakdown .fund_performance - Historical performance and returns .fund_bond_holdings / .fund_bond_ratings - Bond maturity and credit ratings .fund_equity_holdings - P/E, P/B, P/S for equity holdings
๐ Other Modules
.summary_detail - Trading stats (day high/low, volume, avg volume) .default_key_statistics - Enterprise value, trailing P/E, forward P/E .index_trend - Performance relative to a benchmark index .quote_type - Security type, exchange, market
Global Functions
import yahooquery as yq # Search results = yq.search('NVIDIA') # Market Data market = yq.get_market_summary(country='US') # Major indices snapshot trending = yq.get_trending(country='US') # Trending tickers # Utilities currencies = yq.get_currencies() # List of supported currencies exchanges = yq.get_exchanges() # List of exchanges rate = yq.currency_converter('USD', 'EUR') # Exchange rate
Configuration & Keyword Arguments
The Ticker, Screener, and Research classes accept these optional parameters:
Performance & Reliability
asynchronous=True - Make requests asynchronously (for multiple symbols) max_workers=8 - Number of concurrent workers (when async) retry=5 - Number of retry attempts backoff_factor=0.3 - Exponential backoff between retries status_forcelist=[429, 500, 502, 503, 504] - HTTP codes to retry timeout=5 - Request timeout in seconds
Data Format & Validation
formatted=False - If True, returns data with {raw, fmt, longFmt} structure validate=True - Validate symbols on instantiation (invalid โ .invalid_symbols) country='United States' - Regional data/news (france, germany, canada, etc.)
Network & Auth
proxies={'http': 'http://proxy:port'} - HTTP/HTTPS proxy user_agent='...' - Custom user agent string verify=True - SSL certificate verification username='you@email.com' / password='...' - Yahoo Finance Premium login
Advanced (Shared Sessions)
session=... / crumb=... - Share auth between Research and Ticker instances
1. Async for Multiple Symbols
tickers = Ticker('AAPL MSFT NVDA TSLA', asynchronous=True) prices = tickers.price # Returns dict keyed by symbol
2. Handling DataFrames
Most financial methods return pandas.DataFrame. Convert for JSON output: df = aapl.income_statement() print(df.to_json(orient='records', date_format='iso'))
3. Historical Data - 1-Minute Intervals
Yahoo limits 1-minute data to 7 days per request. For 30 days: tickers = Ticker('AAPL', asynchronous=True) df = tickers.history(period='1mo', interval='1m') # Makes 4 requests automatically
4. Premium Users: Combining Research + Ticker
r = Research(username='...', password='...') reports = r.reports(sector='Technology', investment_rating='Bullish') # Reuse session for Ticker tickers = Ticker('AAPL', session=r.session, crumb=r.crumb) data = tickers.asset_profile
Portfolio Analysis
portfolio = Ticker('AAPL MSFT NVDA', asynchronous=True) summary = portfolio.summary_detail earnings = portfolio.earnings history = portfolio.history(period='1y')
Screening & Discovery
s = Screener() gainers = s.get_screeners(['day_gainers'], count=20) # Returns DataFrame with price, volume, % change, etc.
Options Analysis
nvda = Ticker('NVDA') options = nvda.option_chain # Filter for calls/puts, strikes, expirations
Earnings Calendar
tickers = Ticker('AAPL MSFT NVDA') calendar = tickers.calendar_events # Shows next earnings date + analyst estimates
Reference Documentation
Full API docs at: /Users/henryzha/.openclaw/workspace-research/skills/yahooquery/references/ index.md - Overview of classes and functions ticker/ - Detailed breakdown of all Ticker methods screener.md - Screener class guide research.md - Research class (Premium) keyword_arguments.md - Complete list of configuration options misc.md - Global utility functions advanced.md - Sharing sessions between Research and Ticker
Environment
Installation: python3 -m pip install yahooquery Dependencies: pandas, requests-futures, tqdm, beautifulsoup4, lxml Python Version: 3.7+
Notes
Yahoo Finance may rate-limit or block requests. Use retry, backoff_factor, and status_forcelist for robustness. Premium features (Research class) require a paid Yahoo Finance Premium subscription. Data accuracy and availability depend on Yahoo Finance's upstream data providers.
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
6 Docs
- SKILL.md
- references/advanced.md
- references/index.md
- references/keyword_arguments.md
- references/misc.md
- references/research.md