Config

doc/source/advanced/config.rst

@@ -0,0 +1,20 @@
+======
+Config
+======
+
+`yfinance` allows you to set configurations for requests.
+
+You can set:
+* proxy
+* timeout
+* lang
+* region
+* session
+* url
+
+.. code-block:: python
+
+    yf.set_config(proxy=None, timeout=30, lang="en-US", region="US", session=None, url="finance.yahoo.com")
+
+.. important::
+    DO NOT ADD `https://` to start of url. This will cause an error.

doc/source/advanced/index.rst

@@ -8,4 +8,5 @@ Advanced
    logging
    proxy
    caching
-   multi_level_columns
+   multi_level_columns
+   config

doc/source/index.rst

@@ -4,6 +4,12 @@ yfinance documentation
 Download Market Data from Yahoo! Finance's API
 ----------------------------------------------
 
+.. warning::
+
+   `session`, `proxy`, and `timeout` are deprecated.
+   Use `yfinance.set_config()` instead.
+   See :doc: `advanced/config` for more information.
+
 .. admonition:: IMPORTANT LEGAL DISCLAIMER
 
    **Yahoo!, Y!Finance, and Yahoo! finance are registered trademarks of Yahoo, Inc.**

tests/test_price_repair.py

@@ -14,7 +14,8 @@ class TestPriceRepairAssumptions(unittest.TestCase):
 
     @classmethod
     def setUpClass(cls):
-        cls.session = session_gbl
+        config = yf.set_config(session=session_gbl)
+        cls.session = config["session"]
         cls.dp = os.path.dirname(__file__)
 
     @classmethod
@@ -24,7 +25,7 @@ def tearDownClass(cls):
 
     def test_resampling(self):
         for tkr in ['GOOGL', 'GLEN.L', '2330.TW']:
-            dat = yf.Ticker(tkr, session=self.session)
+            dat = yf.Ticker(tkr)
 
             intervals = ['1d', '1wk', '1mo', '3mo']
             periods = ['1d', '5d', '1mo', '3mo', '6mo', '1y', '2y', '5y', '10y', 'ytd']#, 'max']
@@ -94,7 +95,8 @@ class TestPriceRepair(unittest.TestCase):
 
     @classmethod
     def setUpClass(cls):
-        cls.session = session_gbl
+        config = yf.set_config(session=session_gbl)
+        cls.session = config["session"]
         cls.dp = os.path.dirname(__file__)
 
     @classmethod
@@ -104,7 +106,7 @@ def tearDownClass(cls):
 
     def test_types(self):
         tkr = 'INTC'
-        dat = yf.Ticker(tkr, session=self.session)
+        dat = yf.Ticker(tkr)
 
         data = dat.history(period="3mo", interval="1d", prepost=True, repair=True)
         self.assertIsInstance(data, _pd.DataFrame, "data has wrong type")
@@ -128,15 +130,15 @@ def test_reconstruct_2m(self):
         dt_now = dt_now.ceil("1h")
 
         for tkr in tkrs:
-            dat = yf.Ticker(tkr, session=self.session)
+            dat = yf.Ticker(tkr)
             end_dt = dt_now
             start_dt = end_dt - td_60d
             dat.history(start=start_dt, end=end_dt, interval="2m", repair=True)
 
     def test_repair_100x_random_weekly(self):
         # Setup:
         tkr = "PNL.L"
-        dat = yf.Ticker(tkr, session=self.session)
+        dat = yf.Ticker(tkr)
         tz_exchange = dat.fast_info["timezone"]
         hist = dat._lazy_load_price_history()
 
@@ -191,7 +193,7 @@ def test_repair_100x_random_weekly_preSplit(self):
         # PNL.L has a stock-split in 2022. Sometimes requesting data before 2022 is not split-adjusted.
 
         tkr = "PNL.L"
-        dat = yf.Ticker(tkr, session=self.session)
+        dat = yf.Ticker(tkr)
         tz_exchange = dat.fast_info["timezone"]
         hist = dat._lazy_load_price_history()
 
@@ -250,7 +252,7 @@ def test_repair_100x_random_weekly_preSplit(self):
 
     def test_repair_100x_random_daily(self):
         tkr = "PNL.L"
-        dat = yf.Ticker(tkr, session=self.session)
+        dat = yf.Ticker(tkr)
         tz_exchange = dat.fast_info["timezone"]
         hist = dat._lazy_load_price_history()
 
@@ -308,7 +310,7 @@ def test_repair_100x_block_daily(self):
 
         for tkr in tkrs:
             for interval in intervals:
-                dat = yf.Ticker(tkr, session=self.session)
+                dat = yf.Ticker(tkr)
                 tz_exchange = dat.fast_info["timezone"]
                 hist = dat._lazy_load_price_history()
 
@@ -357,7 +359,7 @@ def test_repair_100x_block_daily(self):
 
     def test_repair_zeroes_daily(self):
         tkr = "BBIL.L"
-        dat = yf.Ticker(tkr, session=self.session)
+        dat = yf.Ticker(tkr)
         hist = dat._lazy_load_price_history()
         tz_exchange = dat.fast_info["timezone"]
 
@@ -405,7 +407,7 @@ def test_repair_zeroes_daily_adjClose(self):
                                                   _dt.datetime(2023, 2, 2)]))
         df = df.sort_index()
         df.index.name = "Date"
-        dat = yf.Ticker(tkr, session=self.session)
+        dat = yf.Ticker(tkr)
         tz_exchange = dat.fast_info["timezone"]
         df.index = df.index.tz_localize(tz_exchange)
         hist = dat._lazy_load_price_history()
@@ -425,7 +427,7 @@ def test_repair_zeroes_daily_adjClose(self):
 
     def test_repair_zeroes_hourly(self):
         tkr = "INTC"
-        dat = yf.Ticker(tkr, session=self.session)
+        dat = yf.Ticker(tkr)
         tz_exchange = dat.fast_info["timezone"]
         hist = dat._lazy_load_price_history()
 
@@ -467,7 +469,7 @@ def test_repair_bad_stock_splits(self):
         intervals = ['1d', '1wk', '1mo', '3mo']
         for tkr in good_tkrs:
             for interval in intervals:
-                dat = yf.Ticker(tkr, session=self.session)
+                dat = yf.Ticker(tkr)
                 tz_exchange = dat.fast_info["timezone"]
                 hist = dat._lazy_load_price_history()
 
@@ -491,7 +493,7 @@ def test_repair_bad_stock_splits(self):
         bad_tkrs = ['4063.T', 'ALPHA.PA', 'AV.L', 'CNE.L', 'MOB.ST', 'SPM.MI']
         bad_tkrs.append('LA.V')  # special case - stock split error is 3 years ago! why not fixed?
         for tkr in bad_tkrs:
-            dat = yf.Ticker(tkr, session=self.session)
+            dat = yf.Ticker(tkr)
             tz_exchange = dat.fast_info["timezone"]
             hist = dat._lazy_load_price_history()
 
@@ -531,7 +533,7 @@ def test_repair_bad_stock_splits(self):
         intervals = ['1wk']
         for tkr in sketchy_tkrs:
             for interval in intervals:
-                dat = yf.Ticker(tkr, session=self.session)
+                dat = yf.Ticker(tkr)
                 tz_exchange = dat.fast_info["timezone"]
                 hist = dat._lazy_load_price_history()
 
@@ -613,7 +615,7 @@ def test_repair_bad_div_adjusts(self):
 
         for tkr in false_positives:
             # Nothing should change
-            dat = yf.Ticker(tkr, session=self.session)
+            dat = yf.Ticker(tkr)
             hist = dat._lazy_load_price_history()
             hist.history(period='1mo')  # init metadata for currency
             currency = hist._history_metadata['currency']
@@ -645,7 +647,7 @@ def test_repair_bad_div_adjusts(self):
                 raise
 
         for tkr in bad_tkrs:
-            dat = yf.Ticker(tkr, session=self.session)
+            dat = yf.Ticker(tkr)
             hist = dat._lazy_load_price_history()
             hist.history(period='1mo')  # init metadata for currency
             currency = hist._history_metadata['currency']

tests/test_prices.py

@@ -12,7 +12,7 @@
 class TestPriceHistory(unittest.TestCase):
     @classmethod
     def setUpClass(cls):
-        cls.session = session_gbl
+        cls.session = yf.set_config(session=session_gbl)["session"]
 
     @classmethod
     def tearDownClass(cls):
@@ -23,7 +23,7 @@ def test_daily_index(self):
         tkrs = ["BHP.AX", "IMP.JO", "BP.L", "PNL.L", "INTC"]
         intervals = ["1d", "1wk", "1mo"]
         for tkr in tkrs:
-            dat = yf.Ticker(tkr, session=self.session)
+            dat = yf.Ticker(tkr)
 
             for interval in intervals:
                 df = dat.history(period="5y", interval=interval)
@@ -64,7 +64,7 @@ def test_download_with_invalid_ticker(self):
     def test_duplicatingHourly(self):
         tkrs = ["IMP.JO", "BHG.JO", "SSW.JO", "BP.L", "INTC"]
         for tkr in tkrs:
-            dat = yf.Ticker(tkr, session=self.session)
+            dat = yf.Ticker(tkr)
             tz = dat._get_ticker_tz(proxy=None, timeout=None)
 
             dt_utc = _pd.Timestamp.utcnow()
@@ -84,7 +84,7 @@ def test_duplicatingDaily(self):
         tkrs = ["IMP.JO", "BHG.JO", "SSW.JO", "BP.L", "INTC"]
         test_run = False
         for tkr in tkrs:
-            dat = yf.Ticker(tkr, session=self.session)
+            dat = yf.Ticker(tkr)
             tz = dat._get_ticker_tz(proxy=None, timeout=None)
 
             dt_utc = _pd.Timestamp.utcnow()
@@ -110,7 +110,7 @@ def test_duplicatingWeekly(self):
         tkrs = ['MSFT', 'IWO', 'VFINX', '^GSPC', 'BTC-USD']
         test_run = False
         for tkr in tkrs:
-            dat = yf.Ticker(tkr, session=self.session)
+            dat = yf.Ticker(tkr)
             tz = dat._get_ticker_tz(proxy=None, timeout=None)
 
             dt = _tz.timezone(tz).localize(_dt.datetime.now())
@@ -136,7 +136,7 @@ def test_pricesEventsMerge(self):
         tkr = 'INTC'
         start_d = _dt.date(2022, 1, 1)
         end_d = _dt.date(2023, 1, 1)
-        df = yf.Ticker(tkr, session=self.session).history(interval='1d', start=start_d, end=end_d)
+        df = yf.Ticker(tkr).history(interval='1d', start=start_d, end=end_d)
         div = 1.0
         future_div_dt = df.index[-1] + _dt.timedelta(days=1)
         if future_div_dt.weekday() in [5, 6]:
@@ -173,14 +173,14 @@ def test_intraDayWithEvents(self):
         for tkr in tkrs:
             start_d = _dt.date.today() - _dt.timedelta(days=59)
             end_d = None
-            df_daily = yf.Ticker(tkr, session=self.session).history(start=start_d, end=end_d, interval="1d", actions=True)
+            df_daily = yf.Ticker(tkr).history(start=start_d, end=end_d, interval="1d", actions=True)
             df_daily_divs = df_daily["Dividends"][df_daily["Dividends"] != 0]
             if df_daily_divs.shape[0] == 0:
                 continue
 
             start_d = df_daily_divs.index[0].date()
             end_d = df_daily_divs.index[-1].date() + _dt.timedelta(days=1)
-            df_intraday = yf.Ticker(tkr, session=self.session).history(start=start_d, end=end_d, interval="15m", actions=True)
+            df_intraday = yf.Ticker(tkr).history(start=start_d, end=end_d, interval="15m", actions=True)
             self.assertTrue((df_intraday["Dividends"] != 0.0).any())
 
             df_intraday_divs = df_intraday["Dividends"][df_intraday["Dividends"] != 0]
@@ -200,14 +200,14 @@ def test_intraDayWithEvents_tase(self):
         for tkr in tase_tkrs:
             start_d = _dt.date.today() - _dt.timedelta(days=59)
             end_d = None
-            df_daily = yf.Ticker(tkr, session=self.session).history(start=start_d, end=end_d, interval="1d", actions=True)
+            df_daily = yf.Ticker(tkr).history(start=start_d, end=end_d, interval="1d", actions=True)
             df_daily_divs = df_daily["Dividends"][df_daily["Dividends"] != 0]
             if df_daily_divs.shape[0] == 0:
                 continue
 
             start_d = df_daily_divs.index[0].date()
             end_d = df_daily_divs.index[-1].date() + _dt.timedelta(days=1)
-            df_intraday = yf.Ticker(tkr, session=self.session).history(start=start_d, end=end_d, interval="15m", actions=True)
+            df_intraday = yf.Ticker(tkr).history(start=start_d, end=end_d, interval="15m", actions=True)
             self.assertTrue((df_intraday["Dividends"] != 0.0).any())
 
             df_intraday_divs = df_intraday["Dividends"][df_intraday["Dividends"] != 0]
@@ -231,7 +231,7 @@ def test_dailyWithEvents(self):
                                   _dt.date(2022, 2, 4)]}
 
         for tkr, dates in tkr_div_dates.items():
-            df = yf.Ticker(tkr, session=self.session).history(interval='1d', start=start_d, end=end_d)
+            df = yf.Ticker(tkr).history(interval='1d', start=start_d, end=end_d)
             df_divs = df[df['Dividends'] != 0].sort_index(ascending=False)
             try:
                 self.assertTrue((df_divs.index.date == dates).all())
@@ -265,8 +265,8 @@ def test_dailyWithEvents_bugs(self):
         # Test that index same with and without events:
         tkrs = [tkr1, tkr2]
         for tkr in tkrs:
-            df1 = yf.Ticker(tkr, session=self.session).history(start=start_d, end=end_d, interval="1d", actions=True)
-            df2 = yf.Ticker(tkr, session=self.session).history(start=start_d, end=end_d, interval="1d", actions=False)
+            df1 = yf.Ticker(tkr).history(start=start_d, end=end_d, interval="1d", actions=True)
+            df2 = yf.Ticker(tkr).history(start=start_d, end=end_d, interval="1d", actions=False)
             self.assertTrue(((df1["Dividends"] > 0) | (df1["Stock Splits"] > 0)).any())
             try:
                 self.assertTrue(df1.index.equals(df2.index))
@@ -308,8 +308,8 @@ def test_weeklyWithEvents(self):
         # Test that index same with and without events:
         tkrs = [tkr1, tkr2]
         for tkr in tkrs:
-            df1 = yf.Ticker(tkr, session=self.session).history(start=start_d, end=end_d, interval="1wk", actions=True)
-            df2 = yf.Ticker(tkr, session=self.session).history(start=start_d, end=end_d, interval="1wk", actions=False)
+            df1 = yf.Ticker(tkr).history(start=start_d, end=end_d, interval="1wk", actions=True)
+            df2 = yf.Ticker(tkr).history(start=start_d, end=end_d, interval="1wk", actions=False)
             self.assertTrue(((df1["Dividends"] > 0) | (df1["Stock Splits"] > 0)).any())
             try:
                 self.assertTrue(df1.index.equals(df2.index))
@@ -341,8 +341,8 @@ def test_monthlyWithEvents(self):
         # Test that index same with and without events:
         tkrs = [tkr1, tkr2]
         for tkr in tkrs:
-            df1 = yf.Ticker(tkr, session=self.session).history(start=start_d, end=end_d, interval="1mo", actions=True)
-            df2 = yf.Ticker(tkr, session=self.session).history(start=start_d, end=end_d, interval="1mo", actions=False)
+            df1 = yf.Ticker(tkr).history(start=start_d, end=end_d, interval="1mo", actions=True)
+            df2 = yf.Ticker(tkr).history(start=start_d, end=end_d, interval="1mo", actions=False)
             self.assertTrue(((df1["Dividends"] > 0) | (df1["Stock Splits"] > 0)).any())
             try:
                 self.assertTrue(df1.index.equals(df2.index))
@@ -365,7 +365,7 @@ def test_monthlyWithEvents2(self):
     def test_tz_dst_ambiguous(self):
         # Reproduce issue #1100
         try:
-            yf.Ticker("ESLT.TA", session=self.session).history(start="2002-10-06", end="2002-10-09", interval="1d")
+            yf.Ticker("ESLT.TA").history(start="2002-10-06", end="2002-10-09", interval="1d")
         except _tz.exceptions.AmbiguousTimeError:
             raise Exception("Ambiguous DST issue not resolved")
 
@@ -378,7 +378,7 @@ def test_dst_fix(self):
         # The correction is successful if no days are weekend, and weekly data begins Monday
 
         tkr = "AGRO3.SA"
-        dat = yf.Ticker(tkr, session=self.session)
+        dat = yf.Ticker(tkr)
         start = "2021-01-11"
         end = "2022-11-05"
 
@@ -403,7 +403,7 @@ def test_prune_post_intraday_us(self):
         tkr = "AMZN"
         special_day = _dt.date(2023, 11, 24)
         time_early_close = _dt.time(13)
-        dat = yf.Ticker(tkr, session=self.session)
+        dat = yf.Ticker(tkr)
 
         # Run
         start_d = special_day - _dt.timedelta(days=7)
@@ -424,7 +424,7 @@ def test_prune_post_intraday_asx(self):
         # Setup
         tkr = "BHP.AX"
         # No early closes in 2023
-        dat = yf.Ticker(tkr, session=self.session)
+        dat = yf.Ticker(tkr)
 
         # Test no other afternoons (or mornings) were pruned
         start_d = _dt.date(2023, 1, 1)
@@ -446,7 +446,7 @@ def test_weekly_2rows_fix(self):
     def test_aggregate_capital_gains(self):
         # Setup
         tkr = "FXAIX"
-        dat = yf.Ticker(tkr, session=self.session)
+        dat = yf.Ticker(tkr)
         start = "2017-12-31"
         end = "2019-12-31"
         interval = "3mo"