import yfinance as yf import pandas as pd class SimpleStockData: def __init__(self, ticker_list: list, period_start: str, period_end: str, to_currency: str = ""): """ :param period_start: start date (format YYYY-MM-DD) :param period_end: end date (format YYYY-MM-DD) :param ticker_list: list that contains all stocks/exchange rates (yfinance considers both as "Tickers") :param to_currency: currency to convert rates to """ self.ticker_list = ticker_list self.to_currency = to_currency self._from_currency_list = [] self._period_start = period_start self._period_end = period_end def _get_history(self, idx, interval="1d"): """ Function for internal use; Just a wrapper around the .history method of the yfinance Ticker class :param idx: the index of the share :param interval: granularity of data - valid values are 1m, 2m, 5m, 15m, 30m, 60m, 90m, 1h, 1d, 5d, 1wk, 1mo, 3mo :return: pandas.DataFrame """ return yf.Ticker(self.ticker_list[idx]).history(interval=interval, start=self._period_start, end=self._period_end) def _generate_exchange_dataframe(self, add_currency=""): """ The class has two separate attributes, one to store the plain convert list (_from_currency_list), and one containing the real mapping needed to convert. The mapping is recreated by this function following the information in the _from_currency_list. :param add_currency: OPTIONAL. Add a given currency directly to the internal list before regenerating the mapping (dataframe). Format: CCC (to_currency) return: boolean """ # just add the currency if add_currency is given if add_currency != "": if len(add_currency) != 3: raise ValueError( f"The given currency \"{add_currency}\" to add before regenerating is not in the right format.") self._from_currency_list.append(f"{add_currency}{self.to_currency}=X") # now the real process begins tickers = yf.Tickers( ' '.join(self._from_currency_list)) # create a new Ticker instance with all wanted currencies exchange_rates = [] for i in tickers.tickers: # get all the history of each currency conversion factors exchange_rates.append(tickers.tickers[i].history(start=self._period_start, end=self._period_end)) self.exchange_df = pd.DataFrame( exchange_rates).T # transpose the dataframe (imagine just switching rows and columns) self.exchange_df.columns = self._from_currency_list # set the right names for the columns in the dataframe return True def get_info(self, idx, key=""): """ :param idx: the index of the share :param key: OPTIONAL. gives which specific datum is wanted :return: """ info = yf.Ticker(self.ticker_list[idx]).info if key != "": # if just one specific information is wanted return info[key] return info def get_history(self, idx, interval="1d"): """ Just a wrapper around the .history method of the yfinance Ticker class :param idx: the index of the share :param interval: granularity of data - valid values are 1m, 2m, 5m, 15m, 30m, 60m, 90m, 1h, 1d, 5d, 1wk, 1mo, 3mo :return: pandas.DataFrame """ ret = self._get_history(idx, interval) return ret