yfinance Skill
Overview
The yfinance skill provides a convenient client for querying US and Hong Kong stock data using Yahoo Finance. It wraps the yfinance library to offer a simplified interface for retrieving financial data, market information, and analyst insights.
Features
Supported Markets
- US Stocks: Symbols like AAPL, MSFT, GOOGL, etc.
- Hong Kong Stocks: Symbols like 0700.HK (Tencent), 9988.HK (Alibaba), etc. Can use either 4-digit (0700) or full format (0700.HK)
Data Types
| Category | Methods |
|---|---|
| Price & History | get_price, get_history, get_fast_info |
| Company Info | get_company_info, get_company_summary, get_major_holders |
| Financials | get_financials, get_balance_sheet, get_cashflow, get_earnings |
| Analyst Data | get_recommendations, get_analyst_price_targets, get_earnings_estimate |
| Insider & News | get_insider_transactions, get_news |
| Dividends & Splits | get_dividends, get_splits, get_actions |
| Sector & Industry | get_sector, get_industry |
| Screener | get_screener (predefined queries like day_gainers, most_actives) |
| Options | get_options, get_option_chain |
| Search | search |
Usage
Installation
pip install yfinance pandasBasic Usage
from yfinance_skill import YFinanceClient
# Create client
client = YFinanceClient()
# Get stock price
price = client.get_price("AAPL")
print(f"AAPL price: ${price}")
# Get historical data
history = client.get_history("AAPL", period="1mo")
print(history.tail())
# Get company info
info = client.get_company_info("AAPL")
print(f"Industry: {info.get('industry')}")
print(f"Sector: {info.get('sector')}")
# Get recommendations
recs = client.get_recommendations("MSFT")
print(recs)
# Get day gainers
gainers = client.get_screener("day_gainers")
print(gainers.head())
# Hong Kong stocks
hk_price = client.get_price("0700.HK") # Tencent
hk_info = client.get_company_info("0700")Key Methods
get_price(symbol)
Returns the current stock price as a float.
get_history(symbol, period="1mo", interval="1d", start=None, end=None)
Returns historical OHLCV data.
period: 1d, 5d, 1mo, 3mo, 6mo, 1y, 2y, 5y, 10y, ytd, maxinterval: 1m, 2m, 5m, 15m, 30m, 60m, 90m, 1h, 1d, 1wk, 1mo
get_company_info(symbol)
Returns a dictionary with comprehensive company information including:
- Company name, industry, sector
- Market cap, PE ratio, dividend yield
- 52-week high/low, 50-day average
- Analyst ratings, target price
- And many more fields
get_screener(query_name)
Returns screener results. Available queries:
day_gainers- Top gaining stocks todayday_losers- Top losing stocks todaymost_actives- Most actively traded stocksmost_shorted_stocks- Most shorted stocksgrowth_technology_stocks- Technology growth stocksundervalued_large_caps- Undervalued large caps- And more...
get_sector(sector_name) / get_industry(industry_key)
Returns sector/industry information with top companies.
Error Handling
The client may raise exceptions for invalid symbols or network errors. Always handle exceptions appropriately in production code.
from yfinance_skill import YFinanceClient
client = YFinanceClient()
try:
price = client.get_price("INVALID_SYMBOL")
except Exception as e:
print(f"Error: {e}")Notes
- Some data may not be available for all stocks, especially HK stocks
- Rate limiting may apply for frequent requests
- Delayed quotes may be returned for some data types
- Options data is only available for US stocks