106 lines
3.3 KiB
Python
106 lines
3.3 KiB
Python
import logging
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import yfinance as yf
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from typing import Annotated, Callable, Any, Optional
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from pandas import DataFrame
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import pandas as pd
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from functools import wraps
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from .utils import SavePathType, decorate_all_methods
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logger = logging.getLogger(__name__)
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def init_ticker(func: Callable) -> Callable:
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@wraps(func)
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def wrapper(symbol: Annotated[str, "ticker symbol"], *args, **kwargs) -> Any:
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ticker = yf.Ticker(symbol)
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return func(ticker, *args, **kwargs)
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return wrapper
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@decorate_all_methods(init_ticker)
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class YFinanceUtils:
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def get_stock_data(
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symbol: Annotated[str, "ticker symbol"],
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start_date: Annotated[
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str, "start date for retrieving stock price data, YYYY-mm-dd"
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],
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end_date: Annotated[
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str, "end date for retrieving stock price data, YYYY-mm-dd"
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],
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save_path: SavePathType = None,
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) -> DataFrame:
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ticker = symbol
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end_date = pd.to_datetime(end_date) + pd.DateOffset(days=1)
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end_date = end_date.strftime("%Y-%m-%d")
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stock_data = ticker.history(start=start_date, end=end_date)
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return stock_data
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def get_stock_info(
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symbol: Annotated[str, "ticker symbol"],
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) -> dict:
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ticker = symbol
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stock_info = ticker.info
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return stock_info
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def get_company_info(
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symbol: Annotated[str, "ticker symbol"],
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save_path: Optional[str] = None,
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) -> DataFrame:
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ticker = symbol
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info = ticker.info
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company_info = {
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"Company Name": info.get("shortName", "N/A"),
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"Industry": info.get("industry", "N/A"),
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"Sector": info.get("sector", "N/A"),
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"Country": info.get("country", "N/A"),
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"Website": info.get("website", "N/A"),
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}
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company_info_df = DataFrame([company_info])
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if save_path:
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company_info_df.to_csv(save_path)
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logger.info("Company info for %s saved to %s", ticker.ticker, save_path)
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return company_info_df
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def get_stock_dividends(
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symbol: Annotated[str, "ticker symbol"],
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save_path: Optional[str] = None,
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) -> DataFrame:
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ticker = symbol
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dividends = ticker.dividends
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if save_path:
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dividends.to_csv(save_path)
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logger.info("Dividends for %s saved to %s", ticker.ticker, save_path)
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return dividends
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def get_income_stmt(symbol: Annotated[str, "ticker symbol"]) -> DataFrame:
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ticker = symbol
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income_stmt = ticker.financials
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return income_stmt
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def get_balance_sheet(symbol: Annotated[str, "ticker symbol"]) -> DataFrame:
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ticker = symbol
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balance_sheet = ticker.balance_sheet
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return balance_sheet
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def get_cash_flow(symbol: Annotated[str, "ticker symbol"]) -> DataFrame:
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ticker = symbol
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cash_flow = ticker.cashflow
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return cash_flow
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def get_analyst_recommendations(symbol: Annotated[str, "ticker symbol"]) -> tuple:
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ticker = symbol
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recommendations = ticker.recommendations
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if recommendations.empty:
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return None, 0
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row_0 = recommendations.iloc[0, 1:]
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max_votes = row_0.max()
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majority_voting_result = row_0[row_0 == max_votes].index.tolist()
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return majority_voting_result[0], max_votes
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