Now using the new method (renamed to _create_exchange_dataframe).

Also, some optimizations and fixes were added.

SimpleStockData.py

@@ -10,17 +10,19 @@ class SimpleStockData:
         :param period_end:
             end date (format YYYY-MM-DD)
         :param ticker_list:
-            list that contains all stocks/exchange rates (yfinance considers both as "Tickers")
+            list containing 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
 
+        self._exchange_df = None  # Mapping: time mapped to conversion factor, to get the right converted value per date
+        self._create_exchange_dataframe()  # initialize self.exchange_df attribute
+
     def _get_history(self, idx, interval="1d"):
         """
         Function for internal use; Just a wrapper around the .history method of the yfinance Ticker class
@@ -34,36 +36,42 @@ class SimpleStockData:
         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=""):
+    def _create_exchange_dataframe(self):
         """
         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")
+        # check if a to_currency is even given
+        if self.to_currency == "":
+            return False
+
+        # create the list of currencies based on all the stocks of the class
+        _from_currency_list = []
+        for i in range(len(self.ticker_list)):  # to get all indexes; this adds an entry for each currency
+            add_currency = f"{self.get_info(i, 'currency')}{self.to_currency}=X"  # Format: "fffttt=X" f=from, t=to
+            # for the case that FROM and TO are equal, just don't download the data (as conversion factor's 1)
+            if add_currency == f"{self.to_currency}{self.to_currency}=X":
+                pass
+            elif add_currency not in _from_currency_list:  # add a new item if not already there
+                _from_currency_list.append(add_currency)
+
+            print(_from_currency_list)
 
         # now the real process begins
-        tickers = yf.Tickers(
-            ' '.join(self._from_currency_list))  # create a new Ticker instance with all wanted currencies
+        tickers = yf.Tickers(" ".join(_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))
+            # for simplicity: using the conversion factor of closing (.Close at the end)
+            exchange_rates.append(tickers.tickers[i].history(start=self._period_start, end=self._period_end).Close)
 
-        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
+        self._exchange_df = pd.DataFrame(exchange_rates).T  # transpose the dataframe (imagine just switching rows and columns)
+        self._exchange_df.columns = _from_currency_list  # set the right names for the columns in the dataframe
+        self._exchange_df[f"{self.to_currency}{self.to_currency}=X"] = 1.0  # for FROM and TO being equal: set factor to 1
 
         return True
 

example1.py

@@ -1,6 +1,6 @@
 from SimpleStockData import SimpleStockData
 
-ssd = SimpleStockData(["BAS.DE", "AMZN"], "2023-11-24", "2023-11-25")
+ssd = SimpleStockData(["BAS.DE", "AMZN"], "2023-11-20", "2023-11-24", "EUR")
 
 print(ssd.get_info(0))
 print(ssd.get_info(0, "address1"))
@@ -12,3 +12,4 @@ print(ssd.get_info(1))
 print(ssd.get_info(1, "currency"))
 print(ssd.get_info(1, "website"))
 print(ssd.get_history(0, "1h"))
+print(ssd._exchange_df)