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This library provides programmatic access to nearly all Yahoo Finance endpoints, including real-time pricing, fundamentals, analyst estimates, options, news, and premium research.\n\n## Core Classes\n\n### 1. **Ticker** (Company-Specific Data)\nThe primary interface for retrieving data about one or more securities.\n\n```python\nfrom yahooquery import Ticker\n\n# Single or multiple symbols\naapl = Ticker('AAPL')\ntickers = Ticker('AAPL MSFT NVDA', asynchronous=True)\n```\n\n### 2. **Screener** (Predefined Stock Lists)\nAccess to pre-built screeners for discovering stocks by criteria.\n\n```python\nfrom yahooquery import Screener\n\ns = Screener()\nscreeners = s.available_screeners  # List all available screeners\ndata = s.get_screeners(['day_gainers', 'most_actives'], count=10)\n```\n\n### 3. **Research** (Premium Subscription Required)\nAccess proprietary research reports and trade ideas.\n\n```python\nfrom yahooquery import Research\n\nr = Research(username='you@email.com', password='password')\nreports = r.reports(report_type='Analyst Report', report_date='Last Week')\ntrades = r.trades(trend='Bullish', term='Short term')\n```\n\n---\n\n## Ticker Class: Data Modules\n\nThe `Ticker` class exposes dozens of data endpoints via properties and methods.\n\n### 📊 **Financial Statements**\n- `.income_statement(frequency='a', trailing=True)` - Income statement (annual/quarterly)\n- `.balance_sheet(frequency='a', trailing=True)` - Balance sheet\n- `.cash_flow(frequency='a', trailing=True)` - Cash flow statement\n- `.all_financial_data(frequency='a')` - Combined financials + valuation measures\n- `.valuation_measures` - EV/EBITDA, P/E, P/B, P/S across periods\n\n### 📈 **Pricing & Market Data**\n- `.price` - Current pricing, market cap, 52-week range\n- `.history(period='1y', interval='1d', start=None, end=None)` - Historical OHLC\n  - **period**: `1d`, `5d`, `1mo`, `3mo`, `6mo`, `1y`, `2y`, `5y`, `10y`, `ytd`, `max`\n  - **interval**: `1m`, `2m`, `5m`, `15m`, `30m`, `60m`, `90m`, `1h`, `1d`, `5d`, `1wk`, `1mo`, `3mo`\n- `.option_chain` - Full options chain (all expirations)\n\n### 🔍 **Analysis & Estimates**\n- `.calendar_events` - Next earnings date, EPS/revenue estimates\n- `.earning_history` - Actual vs. estimated EPS (last 4 quarters)\n- `.earnings` - Historical quarterly/annual earnings and revenue\n- `.earnings_trend` - Analyst estimates for upcoming periods\n- `.recommendation_trend` - Buy/Sell/Hold rating changes over time\n- `.gradings` - Recent analyst upgrades/downgrades\n\n### 🏢 **Company Fundamentals**\n- `.asset_profile` - Address, industry, sector, business summary, officers\n- `.company_officers` - Executives with compensation details\n- `.summary_profile` - Condensed company information\n- `.key_stats` - Forward P/E, profit margin, beta, shares outstanding\n- `.financial_data` - Financial KPIs (ROE, ROA, debt-to-equity, margins)\n\n### 👥 **Ownership & Governance**\n- `.insider_holders` - List of insider holders and positions\n- `.insider_transactions` - Recent buy/sell transactions by insiders\n- `.institution_ownership` - Top institutional holders\n- `.fund_ownership` - Top mutual fund holders\n- `.major_holders` - Ownership summary (institutional %, insider %, float)\n\n### 🌍 **ESG & Ratings**\n- `.esg_scores` - Environmental, Social, Governance scores and controversies\n- `.recommendation_rating` - Analyst consensus (Strong Buy → Strong Sell)\n\n### 📰 **News & Insights**\n- `.news()` - Recent news articles\n- `.technical_insights` - Bullish/bearish technical patterns\n\n### 💰 **Funds & ETFs Only**\n- `.fund_holding_info` - Top holdings, bond/equity breakdown\n- `.fund_performance` - Historical performance and returns\n- `.fund_bond_holdings` / `.fund_bond_ratings` - Bond maturity and credit ratings\n- `.fund_equity_holdings` - P/E, P/B, P/S for equity holdings\n\n### 📊 **Other Modules**\n- `.summary_detail` - Trading stats (day high/low, volume, avg volume)\n- `.default_key_statistics` - Enterprise value, trailing P/E, forward P/E\n- `.index_trend` - Performance relative to a benchmark index\n- `.quote_type` - Security type, exchange, market\n\n---\n\n## Global Functions\n\n```python\nimport yahooquery as yq\n\n# Search\nresults = yq.search('NVIDIA')\n\n# Market Data\nmarket = yq.get_market_summary(country='US')  # Major indices snapshot\ntrending = yq.get_trending(country='US')  # Trending tickers\n\n# Utilities\ncurrencies = yq.get_currencies()  # List of supported currencies\nexchanges = yq.get_exchanges()  # List of exchanges\nrate = yq.currency_converter('USD', 'EUR')  # Exchange rate\n```\n\n---\n\n## Configuration & Keyword Arguments\n\nThe `Ticker`, `Screener`, and `Research` classes accept these optional parameters:\n\n### Performance & Reliability\n- `asynchronous=True` - Make requests asynchronously (for multiple symbols)\n- `max_workers=8` - Number of concurrent workers (when async)\n- `retry=5` - Number of retry attempts\n- `backoff_factor=0.3` - Exponential backoff between retries\n- `status_forcelist=[429, 500, 502, 503, 504]` - HTTP codes to retry\n- `timeout=5` - Request timeout in seconds\n\n### Data Format & Validation\n- `formatted=False` - If `True`, returns data with `{raw, fmt, longFmt}` structure\n- `validate=True` - Validate symbols on instantiation (invalid → `.invalid_symbols`)\n- `country='United States'` - Regional data/news (france, germany, canada, etc.)\n\n### Network & Auth\n- `proxies={'http': 'http://proxy:port'}` - HTTP/HTTPS proxy\n- `user_agent='...'` - Custom user agent string\n- `verify=True` - SSL certificate verification\n- `username='you@email.com'` / `password='...'` - Yahoo Finance Premium login\n\n### Advanced (Shared Sessions)\n- `session=...` / `crumb=...` - Share auth between `Research` and `Ticker` instances\n\n---\n\n## Best Practices\n\n### 1. **Async for Multiple Symbols**\n```python\ntickers = Ticker('AAPL MSFT NVDA TSLA', asynchronous=True)\nprices = tickers.price  # Returns dict keyed by symbol\n```\n\n### 2. **Handling DataFrames**\nMost financial methods return `pandas.DataFrame`. Convert for JSON output:\n```python\ndf = aapl.income_statement()\nprint(df.to_json(orient='records', date_format='iso'))\n```\n\n### 3. **Historical Data - 1-Minute Intervals**\nYahoo limits 1-minute data to 7 days per request. For 30 days:\n```python\ntickers = Ticker('AAPL', asynchronous=True)\ndf = tickers.history(period='1mo', interval='1m')  # Makes 4 requests automatically\n```\n\n### 4. **Premium Users: Combining Research + Ticker**\n```python\nr = Research(username='...', password='...')\nreports = r.reports(sector='Technology', investment_rating='Bullish')\n\n# Reuse session for Ticker\ntickers = Ticker('AAPL', session=r.session, crumb=r.crumb)\ndata = tickers.asset_profile\n```\n\n---\n\n## Common Use Cases\n\n### Portfolio Analysis\n```python\nportfolio = Ticker('AAPL MSFT NVDA', asynchronous=True)\nsummary = portfolio.summary_detail\nearnings = portfolio.earnings\nhistory = portfolio.history(period='1y')\n```\n\n### Screening & Discovery\n```python\ns = Screener()\ngainers = s.get_screeners(['day_gainers'], count=20)\n# Returns DataFrame with price, volume, % change, etc.\n```\n\n### Options Analysis\n```python\nnvda = Ticker('NVDA')\noptions = nvda.option_chain\n# Filter for calls/puts, strikes, expirations\n```\n\n### Earnings Calendar\n```python\ntickers = Ticker('AAPL MSFT NVDA')\ncalendar = tickers.calendar_events\n# Shows next earnings date + analyst estimates\n```\n\n---\n\n## Reference Documentation\n\nFull API docs at: `/Users/henryzha/.openclaw/workspace-research/skills/yahooquery/references/`\n\n- `index.md` - Overview of classes and functions\n- `ticker/` - Detailed breakdown of all Ticker methods\n- `screener.md` - Screener class guide\n- `research.md` - Research class (Premium)\n- `keyword_arguments.md` - Complete list of configuration options\n- `misc.md` - Global utility functions\n- `advanced.md` - Sharing sessions between Research and Ticker\n\n---\n\n## Environment\n\n- **Installation**: `python3 -m pip install yahooquery`\n- **Dependencies**: pandas, requests-futures, tqdm, beautifulsoup4, lxml\n- **Python Version**: 3.7+\n\n---\n\n## Notes\n\n- Yahoo Finance may rate-limit or block requests. Use `retry`, `backoff_factor`, and `status_forcelist` for robustness.\n- Premium features (Research class) require a paid Yahoo Finance Premium subscription.\n- Data accuracy and availability depend on Yahoo Finance's upstream data providers.\n","readmeExcerpt":"--- name: yahooquery description: Access Yahoo Finance data including real-time pricing, fundamentals, analyst estimates, options, news, and historical data via the yahooquery Python library. --- yahooquery Skill Comprehensive access to Yahoo Finance data via the yahooquery Python library. 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