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import yfinance as yf
from typing import Annotated, Callable, Any, Optional
from pandas import DataFrame
from functools import wraps
from ..utils import save_output, SavePathType, decorate_all_methods
def init_ticker(func: Callable) -> Callable:
"""Decorator to initialize yf.Ticker and pass it to the function."""
@wraps(func)
def wrapper(symbol: Annotated[str, "ticker symbol"], *args, **kwargs) -> Any:
ticker = yf.Ticker(symbol)
return func(ticker, *args, **kwargs)
return wrapper
@decorate_all_methods(init_ticker)
class YFinanceUtils:
def get_stock_data(
symbol: Annotated[str, "ticker symbol"],
start_date: Annotated[
str, "start date for retrieving stock price data, YYYY-mm-dd"
],
end_date: Annotated[
str, "end date for retrieving stock price data, YYYY-mm-dd"
],
save_path: SavePathType = None,
) -> DataFrame:
ticker = symbol
stock_data = ticker.history(start=start_date, end=end_date)
save_output(stock_data, f"Stock data for {ticker.ticker}", save_path)
return stock_data
def get_stock_info(
symbol: Annotated[str, "ticker symbol"],
) -> dict:
"""Fetches and returns stock information."""
ticker = symbol
stock_info = ticker.info
return stock_info
def get_company_info(
self,
symbol: Annotated[str, "ticker symbol"],
save_path: Optional[str] = None,
) -> DataFrame:
"""Fetches and returns company information as a DataFrame."""
ticker = symbol
info = ticker.info
company_info = {
"Company Name": info.get("shortName", "N/A"),
"Industry": info.get("industry", "N/A"),
"Sector": info.get("sector", "N/A"),
"Country": info.get("country", "N/A"),
"Website": info.get("website", "N/A"),
}
company_info_df = DataFrame([company_info])
if save_path:
company_info_df.to_csv(save_path)
print(f"Company info for {ticker.ticker} saved to {save_path}")
return company_info_df
def get_stock_dividends(
self,
symbol: Annotated[str, "ticker symbol"],
save_path: Optional[str] = None,
) -> DataFrame:
"""Fetches and returns the dividends data as a DataFrame."""
ticker = symbol
dividends = ticker.dividends
if save_path:
dividends.to_csv(save_path)
print(f"Dividends for {ticker.ticker} saved to {save_path}")
return dividends
def get_income_stmt(symbol: Annotated[str, "ticker symbol"]) -> DataFrame:
"""Fetches and returns the income statement of the company as a DataFrame."""
ticker = symbol
income_stmt = ticker.financials
return income_stmt
def get_balance_sheet(symbol: Annotated[str, "ticker symbol"]) -> DataFrame:
"""Fetches and returns the balance sheet of the company as a DataFrame."""
ticker = symbol
balance_sheet = ticker.balance_sheet
return balance_sheet
def get_cash_flow(symbol: Annotated[str, "ticker symbol"]) -> DataFrame:
"""Fetches and returns the cash flow statement of the company as a DataFrame."""
ticker = symbol
cash_flow = ticker.cashflow
return cash_flow
def get_analyst_recommendations(symbol: Annotated[str, "ticker symbol"]) -> tuple:
"""Fetches the latest analyst recommendations and returns the most common recommendation and its count."""
ticker = symbol
recommendations = ticker.recommendations
if recommendations.empty:
return None, 0 # No recommendations available
# Assuming 'period' column exists and needs to be excluded
row_0 = recommendations.iloc[0, 1:] # Exclude 'period' column if necessary
# Find the maximum voting result
max_votes = row_0.max()
majority_voting_result = row_0[row_0 == max_votes].index.tolist()
return majority_voting_result[0], max_votes
if __name__ == "__main__":
print(YFinanceUtils.get_stock_data("AAPL", "2021-01-01", "2021-12-31"))
# print(YFinanceUtils.get_stock_data())
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