SimpleStockData/SimpleStockData.py

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