Implemented _generate_exchange_dataframe creating or updating an internal conversion table.

SimpleStockData.py

@@ -1,31 +1,71 @@
 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 = ""):
-    Function __init__
+        """
-        - ticker_list: list that contains all stocks/exchange rates (yfinance considers both as "Tickers")
+        :param period_start:
-        - to_currency: currency to convert rates to
+            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
+        """
 
-    def __init__(self, ticker_list: list, to_currency: str = ""):
         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, start, end, interval="1d"):
+    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 start:
-            start date (format YYYY-MM-DD)
-        :param end:
-            end date (format YYYY-MM-DD)
         :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=start, end=end)
+
+        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=""):
         """
@@ -35,7 +75,21 @@ class SimpleStockData:
             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

example1.py

@@ -1,6 +1,6 @@
 from SimpleStockData import SimpleStockData
 
-ssd = SimpleStockData(["BAS.DE", "AMZN"])
+ssd = SimpleStockData(["BAS.DE", "AMZN"], "2023-11-24", "2023-11-25")
 
 print(ssd.get_info(0))
 print(ssd.get_info(0, "address1"))
@@ -11,4 +11,4 @@ print()
 print(ssd.get_info(1))
 print(ssd.get_info(1, "currency"))
 print(ssd.get_info(1, "website"))
-print(ssd._get_history(0, "2023-11-24", "2023-11-25", "1h"))
+print(ssd.get_history(0, "1h"))