Bump yfinance to 0.2.4 and fix tests

openbb_terminal/futures/yfinance_model.py

@@ -106,11 +106,14 @@ def get_historical_futures(symbols: List[str], expiry: str = "") -> pd.DataFrame
 
         return yf.download(symbols_with_expiry, progress=False, period="max")
 
-    df = yf.download([t + "=F" for t in symbols], progress=False, period="max")
+    df = yf.download(
+        [t + "=F" for t in symbols], progress=False, period="max", ignore_tz=True
+    )
     if len(symbols) > 1:
         df.columns = pd.MultiIndex.from_tuples(
             [(tup[0], tup[1].replace("=F", "")) for tup in df.columns]
         )
+
     return df
 
 

openbb_terminal/portfolio/portfolio_engine.py

@@ -514,6 +514,7 @@ def set_benchmark(self, symbol: str = "SPY", full_shares: bool = False):
             start=self.inception_date - datetime.timedelta(days=1),
             threads=False,
             progress=False,
+            ignore_tz=True,
         )["Adj Close"]
 
         p_bar.n += 1
@@ -650,9 +651,9 @@ def __load_portfolio_historical_prices(self, use_close: bool = False):
         p_bar = tqdm(range(len(self.tickers)), desc="        Loading price data")
 
         for ticker_type, data in self.tickers.items():
-            price_data = yf.download(data, start=self.inception_date, progress=False)[
-                "Close" if use_close or ticker_type == "CRYPTO" else "Adj Close"
-            ]
+            price_data = yf.download(
+                data, start=self.inception_date, progress=False, ignore_tz=True
+            )["Close" if use_close or ticker_type == "CRYPTO" else "Adj Close"]
 
             # Set up column name if only 1 ticker (pd.DataFrame only does this if >1 ticker)
             if len(data) == 1:

openbb_terminal/stocks/backtesting/bt_model.py

@@ -10,8 +10,8 @@
 import yfinance as yf
 
 from openbb_terminal.decorators import log_start_end
-from openbb_terminal.helper_funcs import is_intraday
 from openbb_terminal.common.technical_analysis import ta_helpers
+from openbb_terminal.helper_funcs import is_intraday
 
 logger = logging.getLogger(__name__)
 
@@ -32,13 +32,14 @@ def get_data(symbol: str, start_date: str = "2019-01-01") -> pd.DataFrame:
     prices: pd.DataFrame
         Dataframe of Adj Close with columns = [ticker]
     """
-    data = yf.download(symbol, start=start_date, progress=False)
+    data = yf.download(symbol, start=start_date, progress=False, ignore_tz=True)
     close_col = ta_helpers.check_columns(data, high=False, low=False)
     if close_col is None:
         return pd.DataFrame()
-    prices = pd.DataFrame(data[close_col])
-    prices.columns = [symbol]
-    return prices
+    df = pd.DataFrame(data[close_col])
+    df.columns = [symbol]
+
+    return df
 
 
 @log_start_end(log=logger)

openbb_terminal/stocks/comparison_analysis/yahoo_finance_model.py

@@ -80,7 +80,7 @@ def get_historical(
     # To avoid having to recursively append, just do a single yfinance call.  This will give dataframe
     # where all tickers are columns.
     similar_tickers_dataframe = yf.download(
-        similar, start=start_date, progress=False, threads=False
+        similar, start=start_date, progress=False, threads=False, ignore_tz=True
     )[d_candle_types[candle_type]]
 
     returnable = (
@@ -195,10 +195,16 @@ def get_1y_sp500() -> pd.DataFrame:
     pd.DataFrame
         DataFrame containing last 1 year of closes for all SP500 stocks.
     """
-    return pd.read_csv(
+    df = pd.read_csv(
         "https://raw.githubusercontent.com/jmaslek/daily_sp_500/main/SP500_prices_1yr.csv",
         index_col=0,
     )
+    df.reset_index(inplace=True)
+    df["Date"] = pd.to_datetime(df["Date"], format="%Y-%m-%d", utc=True).dt.strftime(
+        "%Y-%m-%d"
+    )
+    df.set_index("Date", inplace=True)
+    return df
 
 
 # pylint:disable=E1137,E1101
@@ -230,10 +236,11 @@ def get_sp500_comps_tsne(
 
     # Adding the type makes pylint stop yelling
     close_vals: pd.DataFrame = get_1y_sp500()
+
     if symbol not in close_vals.columns:
-        df_symbol = yf.download(symbol, start=close_vals.index[0], progress=False)[
-            "Adj Close"
-        ].to_frame()
+        df_symbol = yf.download(
+            symbol, start=close_vals.index[0], progress=False, ignore_tz=True
+        )["Adj Close"].to_frame()
         df_symbol.columns = [symbol]
         df_symbol.index = df_symbol.index.astype(str)
         close_vals = close_vals.join(df_symbol)

openbb_terminal/stocks/due_diligence/ark_model.py

@@ -61,6 +61,7 @@ def get_ark_trades_by_ticker(symbol: str) -> pd.DataFrame:
         end=df_orders.Date.iloc[0],
         start=df_orders.Date.iloc[-1],
         progress=False,
+        ignore_tz=True,
     )["Close"]
 
     df_orders.set_index("Date", inplace=True)

openbb_terminal/stocks/fundamental_analysis/yahoo_finance_model.py

@@ -309,7 +309,9 @@ def get_mktcap(
         start_date = (datetime.now() - timedelta(days=3 * 366)).strftime("%Y-%m-%d")
 
     currency = ""
-    df_data = yf.download(symbol, start=start_date, progress=False, threads=False)
+    df_data = yf.download(
+        symbol, start=start_date, progress=False, threads=False, ignore_tz=True
+    )
     if not df_data.empty:
 
         data = yf.Ticker(symbol).info

openbb_terminal/stocks/stocks_helper.py

@@ -813,9 +813,12 @@ def load_ticker(
     >>> from openbb_terminal.sdk import openbb
     >>> msft_df = openbb.stocks.load("MSFT")
     """
-    df_data = yf.download(ticker, start=start_date, end=end_date, progress=False)
+    df_data = yf.download(
+        ticker, start=start_date, end=end_date, progress=False, ignore_tz=True
+    )
 
     df_data.index = pd.to_datetime(df_data.index)
+
     df_data["date_id"] = (df_data.index.date - df_data.index.date.min()).astype(
         "timedelta64[D]"
     )

openbb_terminal/stocks/stocks_model.py

@@ -90,7 +90,12 @@ def load_stock_yf(
 
     # Adding a dropna for weekly and monthly because these include weird NaN columns.
     df_stock_candidate = yf.download(
-        symbol, start=start_date, end=end_date, progress=False, interval=int_
+        symbol,
+        start=start_date,
+        end=end_date,
+        progress=False,
+        interval=int_,
+        ignore_tz=True,
     ).dropna(axis=0)
 
     # Check that loading a stock was not successful

pyproject.toml

@@ -25,7 +25,7 @@ alpha-vantage = "^2.3.1"
 finviz = "^1.3.4"
 bs4 = "^0.0.1"
 rapidfuzz = "^1.1.1"
-yfinance = "^0.2.1"
+yfinance = "0.2.4"
 psaw = "^0.0.12"
 praw = "^7.1.4"
 Quandl = "^3.6.0"

requirements-full.txt

@@ -355,6 +355,6 @@ xarray==2022.11.0; python_version >= "3.8"
 xgboost==1.7.2; python_version >= "3.8"
 xlsxwriter==3.0.3; python_version >= "3.7"
 yarl==1.8.1; python_version >= "3.7" and python_full_version >= "3.7.0"
-yfinance==0.2.3
+yfinance==0.2.4
 zipp==3.10.0; python_version >= "3.7" and python_full_version < "3.9.7" and python_version < "3.10" or python_full_version > "3.9.7" and python_version >= "3.7" and python_version < "3.10"
 zope.interface==5.5.0; python_version >= "3.5" and python_full_version < "3.0.0" or python_full_version >= "3.5.0" and python_version >= "3.5"