Version 0.2.37

Dev

.github/ISSUE_TEMPLATE/bug_report.yaml

@@ -6,23 +6,13 @@ body:
   - type: markdown
     attributes:
       value: |
-        # IMPORTANT - Read and follow these instructions carefully. Help us help you.
-
-        ### Does issue already exist?
-
-        Use the search tool. Don't annoy everyone by duplicating existing Issues.
+        # !!! IMPORTANT !!! FOLLOW THESE INSTRUCTIONS CAREFULLY !!!
 
         ### Are you up-to-date?
 
-        Upgrade to the latest version and confirm the issue/bug is still there.
+        Upgrade to the latest version: `$ pip install yfinance --upgrade --no-cache-dir`
 
-        `$ pip install yfinance --upgrade --no-cache-dir`
-
-        Confirm by running:
-
-        `import yfinance as yf ; print(yf.__version__)`
-
-        and comparing against [PIP](https://pypi.org/project/yfinance/#history).
+        Confirm latest version by running: `import yfinance as yf ; print(yf.__version__)` and comparing against [PyPI](https://pypi.org/project/yfinance/#history).
 
         ### Does Yahoo actually have the data?
 
@@ -34,6 +24,10 @@ body:
 
         Yahoo Finance free service has rate-limiting https://github.com/ranaroussi/yfinance/discussions/1513. Once limit hit, Yahoo can delay, block, or return bad data -> not a `yfinance` bug.
         
+        ### Does issue already exist?
+
+        Use the search tool. Don't duplicate existing issues.
+        
   - type: markdown
     attributes:
       value: |
@@ -61,7 +55,7 @@ body:
     id: debug-log
     attributes:
       label: "Debug log"
-      description: "Run code with debug logging enabled and post the full output. Instructions: https://github.com/ranaroussi/yfinance/tree/main#logging"
+      description: "Run code with debug logging enabled and post the full output. IMPORTANT INSTRUCTIONS: https://github.com/ranaroussi/yfinance/tree/main#logging"
     validations:
       required: true
 

CHANGELOG.rst

@@ -1,6 +1,13 @@
 Change Log
 ===========
 
+0.2.37
+------
+Small fixes:
+- Fix Pandas warnings #1838 #1844
+- Fix price repair bug, typos, refactor #1866 #1865 #1849
+- Stop disabling logging #1841
+
 0.2.36
 ------
 Small fixes:

meta.yaml

@@ -1,5 +1,5 @@
 {% set name = "yfinance" %}
-{% set version = "0.2.36" %}
+{% set version = "0.2.37" %}
 
 package:
   name: "{{ name|lower }}"

tests/prices.py

@@ -277,7 +277,7 @@ class TestPriceHistory(unittest.TestCase):
         # Reproduce issue #1634 - 1d dividend out-of-range, should be prepended to prices
         div_dt = _pd.Timestamp(2022, 7, 21).tz_localize("America/New_York")
         df_dividends = _pd.DataFrame(data={"Dividends":[1.0]}, index=[div_dt])
-        df_prices = _pd.DataFrame(data={c:[1.0] for c in yf.const.price_colnames}|{'Volume':0}, index=[div_dt+_dt.timedelta(days=1)])
+        df_prices = _pd.DataFrame(data={c:[1.0] for c in yf.const._PRICE_COLNAMES_}|{'Volume':0}, index=[div_dt+_dt.timedelta(days=1)])
         df_merged = yf.utils.safe_merge_dfs(df_prices, df_dividends, '1d')
         self.assertEqual(df_merged.shape[0], 2)
         self.assertTrue(df_merged[df_prices.columns].iloc[1:].equals(df_prices))
@@ -470,6 +470,18 @@ class TestPriceRepair(unittest.TestCase):
         if cls.session is not None:
             cls.session.close()
 
+    def test_types(self):
+        tkr = 'INTC'
+        dat = yf.Ticker(tkr, session=self.session)
+
+        data = dat.history(period="3mo", interval="1d", prepost=True, repair=True)
+        self.assertIsInstance(data, _pd.DataFrame, "data has wrong type")
+        self.assertFalse(data.empty, "data is empty")
+
+        reconstructed = dat._lazy_load_price_history()._reconstruct_intervals_batch(data, "1wk", True)
+        self.assertIsInstance(reconstructed, _pd.DataFrame, "data has wrong type")
+        self.assertFalse(data.empty, "data is empty")
+
     def test_reconstruct_2m(self):
         # 2m repair requires 1m data.
         # Yahoo restricts 1m fetches to 7 days max within last 30 days.
@@ -494,6 +506,7 @@ class TestPriceRepair(unittest.TestCase):
         tkr = "PNL.L"
         dat = yf.Ticker(tkr, session=self.session)
         tz_exchange = dat.fast_info["timezone"]
+        hist = dat._lazy_load_price_history()
 
         data_cols = ["Low", "High", "Open", "Close", "Adj Close"]
         df = _pd.DataFrame(data={"Open":      [470.5, 473.5, 474.5, 470],
@@ -517,7 +530,7 @@ class TestPriceRepair(unittest.TestCase):
 
         # Run test
 
-        df_repaired = dat._fix_unit_random_mixups(df_bad, "1wk", tz_exchange, prepost=False)
+        df_repaired = hist._fix_unit_random_mixups(df_bad, "1wk", tz_exchange, prepost=False)
 
         # First test - no errors left
         for c in data_cols:
@@ -548,6 +561,7 @@ class TestPriceRepair(unittest.TestCase):
         tkr = "PNL.L"
         dat = yf.Ticker(tkr, session=self.session)
         tz_exchange = dat.fast_info["timezone"]
+        hist = dat._lazy_load_price_history()
 
         data_cols = ["Low", "High", "Open", "Close", "Adj Close"]
         df = _pd.DataFrame(data={"Open":      [400,    398,    392.5,  417],
@@ -574,7 +588,7 @@ class TestPriceRepair(unittest.TestCase):
         df.index = df.index.tz_localize(tz_exchange)
         df_bad.index = df_bad.index.tz_localize(tz_exchange)
 
-        df_repaired = dat._fix_unit_random_mixups(df_bad, "1wk", tz_exchange, prepost=False)
+        df_repaired = hist._fix_unit_random_mixups(df_bad, "1wk", tz_exchange, prepost=False)
 
         # First test - no errors left
         for c in data_cols:
@@ -606,6 +620,7 @@ class TestPriceRepair(unittest.TestCase):
         tkr = "PNL.L"
         dat = yf.Ticker(tkr, session=self.session)
         tz_exchange = dat.fast_info["timezone"]
+        hist = dat._lazy_load_price_history()
 
         data_cols = ["Low", "High", "Open", "Close", "Adj Close"]
         df = _pd.DataFrame(data={"Open":      [478,    476,   476,   472],
@@ -627,7 +642,7 @@ class TestPriceRepair(unittest.TestCase):
         df.index = df.index.tz_localize(tz_exchange)
         df_bad.index = df_bad.index.tz_localize(tz_exchange)
 
-        df_repaired = dat._fix_unit_random_mixups(df_bad, "1d", tz_exchange, prepost=False)
+        df_repaired = hist._fix_unit_random_mixups(df_bad, "1d", tz_exchange, prepost=False)
 
         # First test - no errors left
         for c in data_cols:
@@ -656,6 +671,7 @@ class TestPriceRepair(unittest.TestCase):
             for interval in ['1d', '1wk']:
                 dat = yf.Ticker(tkr, session=self.session)
                 tz_exchange = dat.fast_info["timezone"]
+                hist = dat._lazy_load_price_history()
 
                 data_cols = ["Low", "High", "Open", "Close", "Adj Close"]
                 _dp = os.path.dirname(__file__)
@@ -672,7 +688,7 @@ class TestPriceRepair(unittest.TestCase):
                 df.index = _pd.to_datetime(df.index, utc=True).tz_convert(tz_exchange)
                 df = df.sort_index()
 
-                df_repaired = dat._fix_unit_switch(df_bad, interval, tz_exchange)
+                df_repaired = hist._fix_unit_switch(df_bad, interval, tz_exchange)
                 df_repaired = df_repaired.sort_index()
 
                 # First test - no errors left
@@ -704,6 +720,7 @@ class TestPriceRepair(unittest.TestCase):
     def test_repair_zeroes_daily(self):
         tkr = "BBIL.L"
         dat = yf.Ticker(tkr, session=self.session)
+        hist = dat._lazy_load_price_history()
         tz_exchange = dat.fast_info["timezone"]
 
         df_bad = _pd.DataFrame(data={"Open":      [0,      102.04, 102.04],
@@ -719,7 +736,7 @@ class TestPriceRepair(unittest.TestCase):
         df_bad.index.name = "Date"
         df_bad.index = df_bad.index.tz_localize(tz_exchange)
 
-        repaired_df = dat._fix_zeroes(df_bad, "1d", tz_exchange, prepost=False)
+        repaired_df = hist._fix_zeroes(df_bad, "1d", tz_exchange, prepost=False)
 
         correct_df = df_bad.copy()
         correct_df.loc["2022-11-01", "Open"] = 102.080002
@@ -753,6 +770,7 @@ class TestPriceRepair(unittest.TestCase):
         dat = yf.Ticker(tkr, session=self.session)
         tz_exchange = dat.fast_info["timezone"]
         df.index = df.index.tz_localize(tz_exchange)
+        hist = dat._lazy_load_price_history()
 
         rtol = 5e-3
         for i in [0, 1, 2]:
@@ -761,7 +779,7 @@ class TestPriceRepair(unittest.TestCase):
                 df_slice_bad = df_slice.copy()
                 df_slice_bad.loc[df_slice_bad.index[j], "Adj Close"] = 0.0
 
-                df_slice_bad_repaired = dat._fix_zeroes(df_slice_bad, "1d", tz_exchange, prepost=False)
+                df_slice_bad_repaired = hist._fix_zeroes(df_slice_bad, "1d", tz_exchange, prepost=False)
                 for c in ["Close", "Adj Close"]:
                     self.assertTrue(_np.isclose(df_slice_bad_repaired[c], df_slice[c], rtol=rtol).all())
                 self.assertTrue("Repaired?" in df_slice_bad_repaired.columns)
@@ -771,8 +789,9 @@ class TestPriceRepair(unittest.TestCase):
         tkr = "INTC"
         dat = yf.Ticker(tkr, session=self.session)
         tz_exchange = dat.fast_info["timezone"]
+        hist = dat._lazy_load_price_history()
 
-        correct_df = dat.history(period="1wk", interval="1h", auto_adjust=False, repair=True)
+        correct_df = hist.history(period="1wk", interval="1h", auto_adjust=False, repair=True)
 
         df_bad = correct_df.copy()
         bad_idx = correct_df.index[10]
@@ -783,7 +802,7 @@ class TestPriceRepair(unittest.TestCase):
         df_bad.loc[bad_idx, "Adj Close"] = _np.nan
         df_bad.loc[bad_idx, "Volume"] = 0
 
-        repaired_df = dat._fix_zeroes(df_bad, "1h", tz_exchange, prepost=False)
+        repaired_df = hist._fix_zeroes(df_bad, "1h", tz_exchange, prepost=False)
 
         for c in ["Open", "Low", "High", "Close"]:
             try:
@@ -812,11 +831,12 @@ class TestPriceRepair(unittest.TestCase):
             for interval in intervals:
                 dat = yf.Ticker(tkr, session=self.session)
                 tz_exchange = dat.fast_info["timezone"]
+                hist = dat._lazy_load_price_history()
 
                 _dp = os.path.dirname(__file__)
                 df_good = dat.history(start='2020-01-01', end=_dt.date.today(), interval=interval, auto_adjust=False)
 
-                repaired_df = dat._fix_bad_stock_split(df_good, interval, tz_exchange)
+                repaired_df = hist._fix_bad_stock_split(df_good, interval, tz_exchange)
 
                 # Expect no change from repair
                 df_good = df_good.sort_index()
@@ -836,6 +856,7 @@ class TestPriceRepair(unittest.TestCase):
         for tkr in bad_tkrs:
             dat = yf.Ticker(tkr, session=self.session)
             tz_exchange = dat.fast_info["timezone"]
+            hist = dat._lazy_load_price_history()
 
             _dp = os.path.dirname(__file__)
             interval = '1d'
@@ -846,7 +867,7 @@ class TestPriceRepair(unittest.TestCase):
             df_bad = _pd.read_csv(fp, index_col="Date")
             df_bad.index = _pd.to_datetime(df_bad.index, utc=True)
 
-            repaired_df = dat._fix_bad_stock_split(df_bad, "1d", tz_exchange)
+            repaired_df = hist._fix_bad_stock_split(df_bad, "1d", tz_exchange)
 
             fp = os.path.join(_dp, "data", tkr.replace('.','-')+'-'+interval+"-bad-stock-split-fixed.csv")
             correct_df = _pd.read_csv(fp, index_col="Date")
@@ -876,11 +897,12 @@ class TestPriceRepair(unittest.TestCase):
             for interval in intervals:
                 dat = yf.Ticker(tkr, session=self.session)
                 tz_exchange = dat.fast_info["timezone"]
+                hist = dat._lazy_load_price_history()
 
                 _dp = os.path.dirname(__file__)
-                df_good = dat.history(start='2020-11-30', end='2021-04-01', interval=interval, auto_adjust=False)
+                df_good = hist.history(start='2020-11-30', end='2021-04-01', interval=interval, auto_adjust=False)
 
-                repaired_df = dat._fix_bad_stock_split(df_good, interval, tz_exchange)
+                repaired_df = hist._fix_bad_stock_split(df_good, interval, tz_exchange)
 
                 # Expect no change from repair
                 df_good = df_good.sort_index()
@@ -900,12 +922,13 @@ class TestPriceRepair(unittest.TestCase):
 
         dat = yf.Ticker(tkr, session=self.session)
         tz_exchange = dat.fast_info["timezone"]
+        hist = dat._lazy_load_price_history()
 
         _dp = os.path.dirname(__file__)
         df_bad = _pd.read_csv(os.path.join(_dp, "data", tkr.replace('.','-')+"-1d-missing-div-adjust.csv"), index_col="Date")
         df_bad.index = _pd.to_datetime(df_bad.index)
 
-        repaired_df = dat._fix_missing_div_adjust(df_bad, "1d", tz_exchange)
+        repaired_df = hist._fix_missing_div_adjust(df_bad, "1d", tz_exchange)
 
         correct_df = _pd.read_csv(os.path.join(_dp, "data", tkr.replace('.','-')+"-1d-missing-div-adjust-fixed.csv"), index_col="Date")
         correct_df.index = _pd.to_datetime(correct_df.index)

tests/ticker.py

@@ -247,15 +247,6 @@ class TestTickerHistory(unittest.TestCase):
         self.assertIsInstance(data, pd.DataFrame, "data has wrong type")
         self.assertFalse(data.empty, "data is empty")
 
-    def test_reconstruct_intervals_batch(self):
-        data = self.ticker.history(period="3mo", interval="1d", prepost=True, repair=True)
-        self.assertIsInstance(data, pd.DataFrame, "data has wrong type")
-        self.assertFalse(data.empty, "data is empty")
-
-        reconstructed = self.ticker._reconstruct_intervals_batch(data, "1wk", True)
-        self.assertIsInstance(reconstructed, pd.DataFrame, "data has wrong type")
-        self.assertFalse(data.empty, "data is empty")
-
 
 class TestTickerEarnings(unittest.TestCase):
     session = None

tests/utils.py

@@ -8,6 +8,8 @@ Specific test class:
    python -m unittest tests.utils.TestTicker
 
 """
+from unittest import TestSuite
+
 # import pandas as pd
 # import numpy as np
 
@@ -34,16 +36,16 @@ class TestCache(unittest.TestCase):
         tkr = 'AMZN'
         tz1 = "America/New_York"
         tz2 = "London/Europe"
-        cache = yf.utils.get_tz_cache()
+        cache = yf.cache.get_tz_cache()
         cache.store(tkr, tz1)
         cache.store(tkr, tz2)
 
     def test_setTzCacheLocation(self):
-        self.assertEqual(yf.utils._DBManager.get_location(), self.tempCacheDir.name)
+        self.assertEqual(yf.cache._TzDBManager.get_location(), self.tempCacheDir.name)
 
         tkr = 'AMZN'
         tz1 = "America/New_York"
-        cache = yf.utils.get_tz_cache()
+        cache = yf.cache.get_tz_cache()
         cache.store(tkr, tz1)
 
         self.assertTrue(os.path.exists(os.path.join(self.tempCacheDir.name, "tkr-tz.db")))
@@ -60,10 +62,10 @@ class TestCacheNoPermission(unittest.TestCase):
         tz1 = "America/New_York"
 
         # During attempt to store, will discover cannot write
-        yf.utils.get_tz_cache().store(tkr, tz1)
+        yf.cache.get_tz_cache().store(tkr, tz1)
 
         # Handling the store failure replaces cache with a dummy
-        cache = yf.utils.get_tz_cache()
+        cache = yf.cache.get_tz_cache()
         self.assertTrue(cache.dummy)
         cache.store(tkr, tz1)
 
@@ -71,19 +73,19 @@ class TestCacheNoPermission(unittest.TestCase):
         # Test that if cache path in read-only filesystem, no exception.
         tkr = 'AMZN'
         # During attempt to lookup, will discover cannot write
-        yf.utils.get_tz_cache().lookup(tkr)
+        yf.cache.get_tz_cache().lookup(tkr)
 
         # Handling the lookup failure replaces cache with a dummy
-        cache = yf.utils.get_tz_cache()
+        cache = yf.cache.get_tz_cache()
         self.assertTrue(cache.dummy)
         cache.lookup(tkr)
 
 
 def suite():
-    suite = unittest.TestSuite()
-    suite.addTest(TestCache('Test cache'))
-    suite.addTest(TestCacheNoPermission('Test cache no permission'))
-    return suite
+    ts: TestSuite = unittest.TestSuite()
+    ts.addTest(TestCache('Test cache'))
+    ts.addTest(TestCacheNoPermission('Test cache no permission'))
+    return ts
 
 
 if __name__ == '__main__':

yfinance/const.py

@@ -115,7 +115,7 @@ fundamentals_keys = {
                   "PaymentstoSuppliersforGoodsandServices", "ClassesofCashReceiptsfromOperatingActivities",
                   "OtherCashReceiptsfromOperatingActivities", "ReceiptsfromGovernmentGrants", "ReceiptsfromCustomers"]}
 
-price_colnames = ['Open', 'High', 'Low', 'Close', 'Adj Close']
+_PRICE_COLNAMES_ = ['Open', 'High', 'Low', 'Close', 'Adj Close']
 
 quote_summary_valid_modules = (
     "summaryProfile",  # contains general information about the company

yfinance/scrapers/quote.py

@@ -1,6 +1,5 @@
 import datetime
 import json
-import logging
 import warnings
 from collections.abc import MutableMapping
 
@@ -182,10 +181,7 @@ class FastInfo:
 
     def _get_1y_prices(self, fullDaysOnly=False):
         if self._prices_1y is None:
-            # Temporarily disable error printing
-            logging.disable(logging.CRITICAL)
             self._prices_1y = self._tkr.history(period="380d", auto_adjust=False, keepna=True, proxy=self.proxy)
-            logging.disable(logging.NOTSET)
             self._md = self._tkr.get_history_metadata(proxy=self.proxy)
             try:
                 ctp = self._md["currentTradingPeriod"]
@@ -211,18 +207,12 @@ class FastInfo:
 
     def _get_1wk_1h_prepost_prices(self):
         if self._prices_1wk_1h_prepost is None:
-            # Temporarily disable error printing
-            logging.disable(logging.CRITICAL)
             self._prices_1wk_1h_prepost = self._tkr.history(period="1wk", interval="1h", auto_adjust=False, prepost=True, proxy=self.proxy)
-            logging.disable(logging.NOTSET)
         return self._prices_1wk_1h_prepost
 
     def _get_1wk_1h_reg_prices(self):
         if self._prices_1wk_1h_reg is None:
-            # Temporarily disable error printing
-            logging.disable(logging.CRITICAL)
             self._prices_1wk_1h_reg = self._tkr.history(period="1wk", interval="1h", auto_adjust=False, prepost=False, proxy=self.proxy)
-            logging.disable(logging.NOTSET)
         return self._prices_1wk_1h_reg
 
     def _get_exchange_metadata(self):
@@ -261,8 +251,6 @@ class FastInfo:
         if self._currency is not None:
             return self._currency
 
-        if self._tkr._history_metadata is None:
-            self._get_1y_prices()
         md = self._tkr.get_history_metadata(proxy=self.proxy)
         self._currency = md["currency"]
         return self._currency
@@ -272,8 +260,6 @@ class FastInfo:
         if self._quote_type is not None:
             return self._quote_type
 
-        if self._tkr._history_metadata is None:
-            self._get_1y_prices()
         md = self._tkr.get_history_metadata(proxy=self.proxy)
         self._quote_type = md["instrumentType"]
         return self._quote_type

yfinance/ticker.py

@@ -27,6 +27,7 @@ from collections import namedtuple as _namedtuple
 import pandas as _pd
 
 from .base import TickerBase
+from .const import _BASE_URL_
 
 
 class Ticker(TickerBase):
@@ -40,9 +41,9 @@ class Ticker(TickerBase):
 
     def _download_options(self, date=None):
         if date is None:
-            url = f"{self._base_url}/v7/finance/options/{self.ticker}"
+            url = f"{_BASE_URL_}/v7/finance/options/{self.ticker}"
         else:
-            url = f"{self._base_url}/v7/finance/options/{self.ticker}?date={date}"
+            url = f"{_BASE_URL_}/v7/finance/options/{self.ticker}?date={date}"
 
         r = self._data.get(url=url, proxy=self.proxy).json()
         if len(r.get('optionChain', {}).get('result', [])) > 0:

yfinance/utils.py

@@ -689,7 +689,7 @@ def safe_merge_dfs(df_main, df_sub, interval):
                 df_main['Dividends'] = 0.0
                 return df_main
         else:
-            empty_row_data = {**{c:[_np.nan] for c in const.price_colnames}, 'Volume':[0]}
+            empty_row_data = {**{c:[_np.nan] for c in const._PRICE_COLNAMES_}, 'Volume':[0]}
             if interval == '1d':
                 # For 1d, add all out-of-range event dates
                 for i in _np.where(f_outOfRange)[0]:
@@ -772,7 +772,7 @@ def fix_Yahoo_dst_issue(df, interval):
         f_pre_midnight = (df.index.minute == 0) & (df.index.hour.isin([22, 23]))
         dst_error_hours = _np.array([0] * df.shape[0])
         dst_error_hours[f_pre_midnight] = 24 - df.index[f_pre_midnight].hour
-        df.index += _pd.TimedeltaIndex(dst_error_hours, 'h')
+        df.index += _pd.to_timedelta(dst_error_hours, 'h')
     return df
 
 

yfinance/version.py

@@ -1 +1 @@
-version = "0.2.36"
+version = "0.2.37"