Version 0.2.40

sync dev -> main

.github/workflows/ci.yml

@@ -8,7 +8,7 @@ jobs:
   deploy:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
       - uses: actions/setup-python@v4
         with:
           python-version: 3.x

CHANGELOG.rst

@@ -1,6 +1,26 @@
 Change Log
 ===========
 
+0.2.40
+------
+Fix typo in 0.2.39 c7af213
+
+0.2.39
+------
+Fixes:
+- Fix switching session from/to requests_cache #1930
+Price repair:
+- Fix potential for price repair to discard price=0 rows #1874
+- Don't price-repair FX volume=0, is normal #1920
+- Improve 'sudden change' repair for splits & currency  #1931
+Information:
+- Fix help(yf.download) not showing the information about the function #1913 @vittoboa
+- Add more specific error throwing based on PR 1918 #1928 @elibroftw @marcofognog
+Maintenance:
+- Replace dead 'appdirs' package with 'platformdirs' #1896
+- Deprecate 'pandas_datareader', remove a deprecated argument #1897
+- Fix: datetime.datetime.utcnow() is deprecated ... #1922
+
 0.2.38
 ------
 Fix holders & insiders #1908

README.md

@@ -42,6 +42,14 @@ Yahoo! finance API is intended for personal use only.**
 
 ---
 
+- [Installation](#installation)
+- [Quick start](#quick-start)
+- [Advanced](#logging)
+- [Wiki](https://github.com/ranaroussi/yfinance/wiki)
+- [Contribute](#developers-want-to-contribute)
+
+---
+
 ## Installation
 
 Install `yfinance` using `pip`:
@@ -116,7 +124,7 @@ msft.recommendations
 msft.recommendations_summary
 msft.upgrades_downgrades
 
-# Show future and historic earnings dates, returns at most next 4 quarters and last 8 quarters by default. 
+# Show future and historic earnings dates, returns at most next 4 quarters and last 8 quarters by default.
 # Note: If more are needed use msft.get_earnings_dates(limit=XX) with increased limit argument.
 msft.earnings_dates
 
@@ -183,7 +191,7 @@ data = yf.download("SPY AAPL", period="1mo")
 
 ### Smarter scraping
 
-Install the `nospam` packages for smarter scraping using `pip` (see [Installation](#installation)). These packages help cache calls such that Yahoo is not spammed with requests. 
+Install the `nospam` packages for smarter scraping using `pip` (see [Installation](#installation)). These packages help cache calls such that Yahoo is not spammed with requests.
 
 To use a custom `requests` session, pass a `session=` argument to
 the Ticker constructor. This allows for caching calls to the API as well as a custom way to modify requests via  the `User-agent` header.
@@ -228,31 +236,16 @@ yfinance?](https://stackoverflow.com/questions/63107801)
         -   How to download single or multiple tickers into a single
             dataframe with single level column names and a ticker column
 
-### `pandas_datareader` override
-
-If your code uses `pandas_datareader` and you want to download data
-faster, you can "hijack" `pandas_datareader.data.get_data_yahoo()`
-method to use **yfinance** while making sure the returned data is in the
-same format as **pandas\_datareader**'s `get_data_yahoo()`.
-
-```python
-from pandas_datareader import data as pdr
-
-import yfinance as yf
-yf.pdr_override() # <== that's all it takes :-)
-
-# download dataframe
-data = pdr.get_data_yahoo("SPY", start="2017-01-01", end="2017-04-30")
-```
-
 ### Persistent cache store
 
 To reduce Yahoo, yfinance store some data locally: timezones to localize dates, and cookie. Cache location is:
+
 - Windows = C:/Users/\<USER\>/AppData/Local/py-yfinance
 - Linux = /home/\<USER\>/.cache/py-yfinance
 - MacOS = /Users/\<USER\>/Library/Caches/py-yfinance
 
 You can direct cache to use a different location with `set_tz_cache_location()`:
+
 ```python
 import yfinance as yf
 yf.set_tz_cache_location("custom/cache/location")
@@ -279,7 +272,7 @@ intended for research and educational purposes. You should refer to Yahoo!'s ter
 ([here](https://policies.yahoo.com/us/en/yahoo/terms/product-atos/apiforydn/index.htm),
 [here](https://legal.yahoo.com/us/en/yahoo/terms/otos/index.html), and
 [here](https://policies.yahoo.com/us/en/yahoo/terms/index.htm)) for
-detailes on your rights to use the actual data downloaded.
+details on your rights to use the actual data downloaded.
 
 ---
 

meta.yaml

@@ -1,5 +1,5 @@
 {% set name = "yfinance" %}
-{% set version = "0.2.38" %}
+{% set version = "0.2.40" %}
 
 package:
   name: "{{ name|lower }}"
@@ -21,7 +21,7 @@ requirements:
     - requests >=2.31
     - multitasking >=0.0.7
     - lxml >=4.9.1
-    - appdirs >=1.4.4
+    - platformdirs >=2.0.0
     - pytz >=2022.5
     - frozendict >=2.3.4
     - beautifulsoup4 >=4.11.1
@@ -37,7 +37,7 @@ requirements:
     - requests >=2.31
     - multitasking >=0.0.7
     - lxml >=4.9.1
-    - appdirs >=1.4.4
+    - platformdirs >=2.0.0
     - pytz >=2022.5
     - frozendict >=2.3.4
     - beautifulsoup4 >=4.11.1

requirements.txt

@@ -3,7 +3,7 @@ numpy>=1.16.5
 requests>=2.31
 multitasking>=0.0.7
 lxml>=4.9.1
-appdirs>=1.4.4
+platformdirs>=2.0.0
 pytz>=2022.5
 frozendict>=2.3.4
 beautifulsoup4>=4.11.1

setup.py

@@ -61,7 +61,7 @@ setup(
     packages=find_packages(exclude=['contrib', 'docs', 'tests', 'examples']),
     install_requires=['pandas>=1.3.0', 'numpy>=1.16.5',
                       'requests>=2.31', 'multitasking>=0.0.7',
-                      'lxml>=4.9.1', 'appdirs>=1.4.4', 'pytz>=2022.5',
+                      'lxml>=4.9.1', 'platformdirs>=2.0.0', 'pytz>=2022.5',
                       'frozendict>=2.3.4', 'peewee>=3.16.2',
                       'beautifulsoup4>=4.11.1', 'html5lib>=1.1'],
     extras_require={

tests/__init__.py

@@ -1 +0,0 @@
-#!/usr/bin/env python

tests/context.py

@@ -1,6 +1,6 @@
 # -*- coding: utf-8 -*-
 
-import appdirs as _ad
+import platformdirs as _ad
 import datetime as _dt
 import sys
 import os

tests/data/AV-L-1wk-bad-stock-split-fixed.csv

@@ -1,27 +1,27 @@
 Date,Open,High,Low,Close,Adj Close,Volume,Dividends,Stock Splits
-2021-12-13 00:00:00+00:00,393.999975585938,406.6,391.4,402.899916992188,291.232287597656,62714764.4736842,0,0
-2021-12-20 00:00:00+00:00,393.999975585938,412.199990234375,392.502983398438,409.899997558594,296.292243652344,46596651.3157895,0,0
-2021-12-27 00:00:00+00:00,409.899997558594,416.550971679688,408.387001953125,410.4,296.653642578125,10818482.8947368,0,0
-2022-01-03 00:00:00+00:00,410.4,432.199995117188,410.4,432.099985351563,312.339265136719,44427327.6315789,0,0
-2022-01-10 00:00:00+00:00,431.3,439.199982910156,429.099970703125,436.099912109375,315.230618896484,29091400,0,0
-2022-01-17 00:00:00+00:00,437.999912109375,445.199965820313,426.999997558594,431.999975585938,312.267017822266,43787351.3157895,0,0
-2022-01-24 00:00:00+00:00,430.099975585938,440.999973144531,420.999968261719,433.499982910156,313.351237792969,58487296.0526316,0,0
-2022-01-31 00:00:00+00:00,436.199968261719,443.049987792969,432.099985351563,435.199916992188,314.580045166016,43335806.5789474,0,0
-2022-02-07 00:00:00+00:00,437.899995117188,448.799992675781,436.051994628906,444.39998046875,321.230207519531,39644061.8421053,0,0
-2022-02-14 00:00:00+00:00,437.699975585938,441.999978027344,426.699968261719,432.199995117188,312.411558837891,49972693.4210526,0,0
-2022-02-21 00:00:00+00:00,435.499992675781,438.476999511719,408.29998046875,423.399970703125,306.050571289063,65719596.0526316,0,0
-2022-02-28 00:00:00+00:00,415.099995117188,427.999909667969,386.199932861328,386.799945068359,279.594578857422,94057936.8421053,4.1875,0
-2022-03-07 00:00:00+00:00,374.999952392578,417.299978027344,361.101981201172,409.599968261719,298.389248046875,71269101.3157895,0,0
-2022-03-14 00:00:00+00:00,413.099985351563,426.699968261719,408.899992675781,422.399965820313,307.713929443359,55431927.6315789,0,0
-2022-03-21 00:00:00+00:00,422.699995117188,442.7,422.399965820313,437.799985351563,318.932696533203,39896352.6315789,0,0
-2022-03-28 00:00:00+01:00,442.49998046875,460.999978027344,440.097983398438,444.6,323.886403808594,56413515.7894737,0,0
-2022-04-04 00:00:00+01:00,439.699985351563,445.399985351563,421.999973144531,425.799973144531,310.190817871094,49415836.8421053,19.342106,0
-2022-04-11 00:00:00+01:00,425.39998046875,435.599909667969,420.799995117188,434.299968261719,327.211427001953,29875081.5789474,0,0
-2022-04-18 00:00:00+01:00,434.299968261719,447.799987792969,433.599992675781,437.799985351563,329.848419189453,49288272.3684211,0,0
-2022-04-25 00:00:00+01:00,430.699987792969,438.799990234375,423.999982910156,433.299916992188,326.457967529297,44656776.3157895,0,0
-2022-05-02 00:00:00+01:00,433.299916992188,450.999975585938,414.499982910156,414.899975585938,312.595018310547,29538167.1052632,0,0
-2022-05-09 00:00:00+01:00,413.199995117188,417.449992675781,368.282923583984,408.199970703125,307.547099609375,73989611.8421053,0,0
-2022-05-16 00:00:00+01:00,384,423.600006103516,384,412.100006103516,310.485473632813,81938261,101.69,0.76
+2021-12-13 00:00:00+00:00,518.421020507813,535,515,530.131469726563,383.200378417969,47663221,0,0
+2021-12-20 00:00:00+00:00,518.421020507813,542.368408203125,516.451293945313,539.342102050781,389.858215332031,35413455,0,0
+2021-12-27 00:00:00+00:00,539.342102050781,548.093383789063,537.351318359375,540,390.333740234375,8222047,0,0
+2022-01-03 00:00:00+00:00,540,568.684204101563,540,568.552612304688,410.972717285156,33764769,0,0
+2022-01-10 00:00:00+00:00,567.5,577.894714355469,564.605224609375,573.815673828125,414.777130126953,22109464,0,0
+2022-01-17 00:00:00+00:00,576.315673828125,585.789428710938,561.842102050781,568.421020507813,410.877655029297,33278387,0,0
+2022-01-24 00:00:00+00:00,565.921020507813,580.263122558594,553.947326660156,570.394714355469,412.304260253906,44450345,0,0
+2022-01-31 00:00:00+00:00,573.947326660156,582.960510253906,568.552612304688,572.631469726563,413.921112060547,32935213,0,0
+2022-02-07 00:00:00+00:00,576.184204101563,590.526306152344,573.752624511719,584.73681640625,422.671325683594,30129487,0,0
+2022-02-14 00:00:00+00:00,575.921020507813,581.578918457031,561.447326660156,568.684204101563,411.067840576172,37979247,0,0
+2022-02-21 00:00:00+00:00,573.026306152344,576.943420410156,537.23681640625,557.105224609375,402.698120117188,49946893,0,0
+2022-02-28 00:00:00+00:00,546.184204101563,563.157775878906,508.157806396484,508.947296142578,367.887603759766,71484032,4.1875,0
+2022-03-07 00:00:00+00:00,493.420989990234,549.078918457031,475.134185791016,538.947326660156,392.617431640625,54164517,0,0
+2022-03-14 00:00:00+00:00,543.552612304688,561.447326660156,538.026306152344,555.789428710938,404.886749267578,42128265,0,0
+2022-03-21 00:00:00+00:00,556.184204101563,582.5,555.789428710938,576.052612304688,419.648284912109,30321228,0,0
+2022-03-28 00:00:00+01:00,582.23681640625,606.578918457031,579.076293945313,585,426.166320800781,42874272,0,0
+2022-04-04 00:00:00+01:00,578.552612304688,586.052612304688,555.263122558594,560.263122558594,408.145812988281,37556036,19.342106,0
+2022-04-11 00:00:00+01:00,559.73681640625,573.157775878906,553.684204101563,571.447326660156,430.541351318359,22705062,0,0
+2022-04-18 00:00:00+01:00,571.447326660156,589.210510253906,570.526306152344,576.052612304688,434.011077880859,37459087,0,0
+2022-04-25 00:00:00+01:00,566.710510253906,577.368408203125,557.894714355469,570.131469726563,429.549957275391,33939150,0,0
+2022-05-02 00:00:00+01:00,570.131469726563,593.421020507813,545.394714355469,545.921020507813,411.309234619141,22449007,0,0
+2022-05-09 00:00:00+01:00,543.684204101563,549.276306152344,484.582794189453,537.105224609375,404.667236328125,56232105,0,0
+2022-05-16 00:00:00+01:00,505.263157894737,557.368429083573,505.263157894737,542.236850136205,408.533517937911,62273078.36,101.69,0.76
 2022-05-23 00:00:00+01:00,416.100006103516,442.399993896484,341.915008544922,440.899993896484,409.764678955078,45432941,0,0
 2022-05-30 00:00:00+01:00,442.700012207031,444.200012207031,426.600006103516,428.700012207031,398.426239013672,37906659,0,0
 2022-06-06 00:00:00+01:00,425.299987792969,434.010009765625,405.200012207031,405.399993896484,376.771606445313,40648810,0,0

tests/test_prices.py

@@ -43,14 +43,14 @@ class TestPriceHistory(unittest.TestCase):
 
             df_tkrs = df.columns.levels[1]
             self.assertEqual(sorted(tkrs), sorted(df_tkrs))
-    
+
     def test_download_with_invalid_ticker(self):
         #Checks if using an invalid symbol gives the same output as not using an invalid symbol in combination with a valid symbol (AAPL)
         #Checks to make sure that invalid symbol handling for the date column is the same as the base case (no invalid symbols)
 
         invalid_tkrs = ["AAPL", "ATVI"] #AAPL exists and ATVI does not exist
         valid_tkrs = ["AAPL", "INTC"] #AAPL and INTC both exist
-        
+
         data_invalid_sym = yf.download(invalid_tkrs, start='2023-11-16', end='2023-11-17')
         data_valid_sym = yf.download(valid_tkrs, start='2023-11-16', end='2023-11-17')
 
@@ -62,7 +62,7 @@ class TestPriceHistory(unittest.TestCase):
             dat = yf.Ticker(tkr, session=self.session)
             tz = dat._get_ticker_tz(proxy=None, timeout=None)
 
-            dt_utc = _tz.timezone("UTC").localize(_dt.datetime.utcnow())
+            dt_utc = _pd.Timestamp.utcnow()
             dt = dt_utc.astimezone(_tz.timezone(tz))
             start_d = dt.date() - _dt.timedelta(days=7)
             df = dat.history(start=start_d, interval="1h")
@@ -82,7 +82,7 @@ class TestPriceHistory(unittest.TestCase):
             dat = yf.Ticker(tkr, session=self.session)
             tz = dat._get_ticker_tz(proxy=None, timeout=None)
 
-            dt_utc = _tz.timezone("UTC").localize(_dt.datetime.utcnow())
+            dt_utc = _pd.Timestamp.utcnow()
             dt = dt_utc.astimezone(_tz.timezone(tz))
             if dt.time() < _dt.time(17, 0):
                 continue
@@ -359,13 +359,6 @@ class TestPriceHistory(unittest.TestCase):
         dfd_divs = dfd[dfd['Dividends'] != 0]
         self.assertEqual(dfm_divs.shape[0], dfd_divs.shape[0])
 
-        dfm = yf.Ticker("F").history(period="50mo", interval="1mo")
-        dfd = yf.Ticker("F").history(period="50mo", interval="1d")
-        dfd = dfd[dfd.index > dfm.index[0]]
-        dfm_divs = dfm[dfm['Dividends'] != 0]
-        dfd_divs = dfd[dfd['Dividends'] != 0]
-        self.assertEqual(dfm_divs.shape[0], dfd_divs.shape[0])
-
     def test_tz_dst_ambiguous(self):
         # Reproduce issue #1100
         try:
@@ -791,7 +784,7 @@ class TestPriceRepair(unittest.TestCase):
         tz_exchange = dat.fast_info["timezone"]
         hist = dat._lazy_load_price_history()
 
-        correct_df = hist.history(period="1wk", interval="1h", auto_adjust=False, repair=True)
+        correct_df = hist.history(period="5d", interval="1h", auto_adjust=False, repair=True)
 
         df_bad = correct_df.copy()
         bad_idx = correct_df.index[10]
@@ -820,7 +813,7 @@ class TestPriceRepair(unittest.TestCase):
         self.assertTrue("Repaired?" in repaired_df.columns)
         self.assertFalse(repaired_df["Repaired?"].isna().any())
 
-    def test_repair_bad_stock_split(self):
+    def test_repair_bad_stock_splits(self):
         # Stocks that split in 2022 but no problems in Yahoo data,
         # so repair should change nothing
         good_tkrs = ['AMZN', 'DXCM', 'FTNT', 'GOOG', 'GME', 'PANW', 'SHOP', 'TSLA']
@@ -836,7 +829,7 @@ class TestPriceRepair(unittest.TestCase):
                 _dp = os.path.dirname(__file__)
                 df_good = dat.history(start='2020-01-01', end=_dt.date.today(), interval=interval, auto_adjust=False)
 
-                repaired_df = hist._fix_bad_stock_split(df_good, interval, tz_exchange)
+                repaired_df = hist._fix_bad_stock_splits(df_good, interval, tz_exchange)
 
                 # Expect no change from repair
                 df_good = df_good.sort_index()
@@ -867,7 +860,7 @@ 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 = hist._fix_bad_stock_split(df_bad, "1d", tz_exchange)
+            repaired_df = hist._fix_bad_stock_splits(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")
@@ -902,7 +895,7 @@ class TestPriceRepair(unittest.TestCase):
                 _dp = os.path.dirname(__file__)
                 df_good = hist.history(start='2020-11-30', end='2021-04-01', interval=interval, auto_adjust=False)
 
-                repaired_df = hist._fix_bad_stock_split(df_good, interval, tz_exchange)
+                repaired_df = hist._fix_bad_stock_splits(df_good, interval, tz_exchange)
 
                 # Expect no change from repair
                 df_good = df_good.sort_index()

tests/test_ticker.py

@@ -12,7 +12,7 @@ import pandas as pd
 
 from .context import yfinance as yf
 from .context import session_gbl
-from yfinance.exceptions import YFNotImplementedError
+from yfinance.exceptions import YFChartError, YFInvalidPeriodError, YFNotImplementedError, YFTickerMissingError, YFTzMissingError
 
 
 import unittest
@@ -100,13 +100,13 @@ class TestTicker(unittest.TestCase):
         tkr = "DJI"  # typo of "^DJI"
         dat = yf.Ticker(tkr, session=self.session)
 
-        dat.history(period="1wk")
+        dat.history(period="5d")
         dat.history(start="2022-01-01")
         dat.history(start="2022-01-01", end="2022-03-01")
-        yf.download([tkr], period="1wk", threads=False, ignore_tz=False)
-        yf.download([tkr], period="1wk", threads=True, ignore_tz=False)
-        yf.download([tkr], period="1wk", threads=False, ignore_tz=True)
-        yf.download([tkr], period="1wk", threads=True, ignore_tz=True)
+        yf.download([tkr], period="5d", threads=False, ignore_tz=False)
+        yf.download([tkr], period="5d", threads=True, ignore_tz=False)
+        yf.download([tkr], period="5d", threads=False, ignore_tz=True)
+        yf.download([tkr], period="5d", threads=True, ignore_tz=True)
 
         for k in dat.fast_info:
             dat.fast_info[k]
@@ -129,6 +129,30 @@ class TestTicker(unittest.TestCase):
         assert isinstance(dat.actions, pd.DataFrame)
         assert dat.actions.empty
 
+    def test_invalid_period(self):
+        tkr = 'VALE'
+        dat = yf.Ticker(tkr, session=self.session)
+        with self.assertRaises(YFInvalidPeriodError):
+            dat.history(period="2wks", interval="1d", raise_errors=True)
+        with self.assertRaises(YFInvalidPeriodError):
+            dat.history(period="2mo", interval="1d", raise_errors=True)
+
+
+    def test_prices_missing(self):
+        # this test will need to be updated every time someone wants to run a test
+        # hard to find a ticker that matches this error other than options
+        # META call option, 2024 April 26th @ strike of 180000
+        tkr = 'META240426C00180000'
+        dat = yf.Ticker(tkr, session=self.session)
+        with self.assertRaises(YFChartError):
+            dat.history(period="5d", interval="1m", raise_errors=True)
+
+    def test_ticker_missing(self):
+        tkr = 'ATVI'
+        dat = yf.Ticker(tkr, session=self.session)
+        # A missing ticker can trigger either a niche error or the generalized error
+        with self.assertRaises((YFTickerMissingError, YFTzMissingError, YFChartError)):
+            dat.history(period="3mo", interval="1d", raise_errors=True)
 
     def test_goodTicker(self):
         # that yfinance works when full api is called on same instance of ticker
@@ -138,32 +162,32 @@ class TestTicker(unittest.TestCase):
         for tkr in tkrs:
             dat = yf.Ticker(tkr, session=self.session)
 
-            dat.history(period="1wk")
+            dat.history(period="5d")
             dat.history(start="2022-01-01")
             dat.history(start="2022-01-01", end="2022-03-01")
-            yf.download([tkr], period="1wk", threads=False, ignore_tz=False)
-            yf.download([tkr], period="1wk", threads=True, ignore_tz=False)
-            yf.download([tkr], period="1wk", threads=False, ignore_tz=True)
-            yf.download([tkr], period="1wk", threads=True, ignore_tz=True)
+            yf.download([tkr], period="5d", threads=False, ignore_tz=False)
+            yf.download([tkr], period="5d", threads=True, ignore_tz=False)
+            yf.download([tkr], period="5d", threads=False, ignore_tz=True)
+            yf.download([tkr], period="5d", threads=True, ignore_tz=True)
 
             for k in dat.fast_info:
                 dat.fast_info[k]
 
             for attribute_name, attribute_type in ticker_attributes:
-                assert_attribute_type(self, dat, attribute_name, attribute_type) 
-            
+                assert_attribute_type(self, dat, attribute_name, attribute_type)
+
     def test_goodTicker_withProxy(self):
         tkr = "IBM"
         dat = yf.Ticker(tkr, session=self.session, proxy=self.proxy)
 
         dat._fetch_ticker_tz(proxy=None, timeout=5)
         dat._get_ticker_tz(proxy=None, timeout=5)
-        dat.history(period="1wk")
+        dat.history(period="5d")
 
         for attribute_name, attribute_type in ticker_attributes:
             assert_attribute_type(self, dat, attribute_name, attribute_type)
 
-        
+
 class TestTickerHistory(unittest.TestCase):
     session = None
 
@@ -370,7 +394,7 @@ class TestTickerHolders(unittest.TestCase):
 
         data_cached = self.ticker.insider_transactions
         self.assertIs(data, data_cached, "data not cached")
-    
+
     def test_insider_purchases(self):
         data = self.ticker.insider_purchases
         self.assertIsInstance(data, pd.DataFrame, "data has wrong type")
@@ -402,9 +426,9 @@ class TestTickerMiscFinancials(unittest.TestCase):
 
     def setUp(self):
         self.ticker = yf.Ticker("GOOGL", session=self.session)
-        
-        # For ticker 'BSE.AX' (and others), Yahoo not returning 
-        # full quarterly financials (usually cash-flow) with all entries, 
+
+        # For ticker 'BSE.AX' (and others), Yahoo not returning
+        # full quarterly financials (usually cash-flow) with all entries,
         # instead returns a smaller version in different data store.
         self.ticker_old_fmt = yf.Ticker("BSE.AX", session=self.session)
 
@@ -713,7 +737,7 @@ class TestTickerAnalysts(unittest.TestCase):
 
     def setUp(self):
         self.ticker = yf.Ticker("GOOGL", session=self.session)
-        
+
     def tearDown(self):
         self.ticker = None
 
@@ -813,7 +837,6 @@ class TestTickerInfo(unittest.TestCase):
         # This one should have a trailing PEG ratio
         data2 = self.tickers[2].info
         self.assertIsInstance(data2['trailingPegRatio'], float)
-        pass
 
     # def test_fast_info_matches_info(self):
     #     fast_info_keys = set()
@@ -851,7 +874,7 @@ class TestTickerInfo(unittest.TestCase):
     #             key_rename_map[yf.utils.snake_case_2_camelCase(k)] = key_rename_map[k]
 
     #     # Note: share count items in info[] are bad. Sometimes the float > outstanding!
-    #     # So often fast_info["shares"] does not match. 
+    #     # So often fast_info["shares"] does not match.
     #     # Why isn't fast_info["shares"] wrong? Because using it to calculate market cap always correct.
     #     bad_keys = {"shares"}
 

yfinance/__init__.py

@@ -35,6 +35,8 @@ def pdr_override():
     make pandas datareader optional
     otherwise can be called via fix_yahoo_finance.download(...)
     """
+    from .utils import print_once
+    print_once("yfinance: pandas_datareader support is deprecated & semi-broken so will be removed in a future verison. Just use yfinance.")
     try:
         import pandas_datareader
         pandas_datareader.data.get_data_yahoo = download

yfinance/base.py

@@ -32,6 +32,7 @@ import requests
 
 from . import utils, cache
 from .data import YfData
+from .exceptions import YFEarningsDateMissing
 from .scrapers.analysis import Analysis
 from .scrapers.fundamentals import Fundamentals
 from .scrapers.holders import Holders
@@ -192,7 +193,7 @@ class TickerBase:
             if as_dict:
                 return data.to_dict()
             return data
-    
+
     def get_insider_purchases(self, proxy=None, as_dict=False):
         self._holders.proxy = proxy or self.proxy
         data = self._holders.insider_purchases
@@ -567,7 +568,8 @@ class TickerBase:
                 page_size = min(limit - len(dates), page_size)
 
         if dates is None or dates.shape[0] == 0:
-            err_msg = "No earnings dates found, symbol may be delisted"
+            _exception = YFEarningsDateMissing(self.ticker)
+            err_msg = str(_exception)
             logger.error(f'{self.ticker}: {err_msg}')
             return None
         dates = dates.reset_index(drop=True)

yfinance/cache.py

@@ -1,7 +1,7 @@
 import peewee as _peewee
 from threading import Lock
 import os as _os
-import appdirs as _ad
+import platformdirs as _ad
 import atexit as _atexit
 import datetime as _datetime
 import pickle as _pkl

yfinance/data.py

@@ -60,7 +60,23 @@ class YfData(metaclass=SingletonMeta):
         'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/39.0.2171.95 Safari/537.36'}
 
     def __init__(self, session=None):
-        self._session = session or requests.Session()
+        self._crumb = None
+        self._cookie = None
+
+        # Default to using 'basic' strategy
+        self._cookie_strategy = 'basic'
+        # If it fails, then fallback method is 'csrf'
+        # self._cookie_strategy = 'csrf'
+
+        self._cookie_lock = threading.Lock()
+
+        self._set_session(session or requests.Session())
+
+    def _set_session(self, session):
+        if session is None:
+            return
+        with self._cookie_lock:
+            self._session = session
 
         try:
             self._session.cache
@@ -74,23 +90,6 @@ class YfData(metaclass=SingletonMeta):
             self._session_is_caching = True
             from requests_cache import DO_NOT_CACHE
             self._expire_after = DO_NOT_CACHE
-        self._crumb = None
-        self._cookie = None
-        if self._session_is_caching and self._cookie is None:
-            utils.print_once("WARNING: cookie & crumb does not work well with requests_cache. Am experimenting with 'expire_after=DO_NOT_CACHE', but you need to help stress-test.")
-
-        # Default to using 'basic' strategy
-        self._cookie_strategy = 'basic'
-        # If it fails, then fallback method is 'csrf'
-        # self._cookie_strategy = 'csrf'
-
-        self._cookie_lock = threading.Lock()
-
-    def _set_session(self, session):
-        if session is None:
-            return
-        with self._cookie_lock:
-            self._session = session
 
     def _set_cookie_strategy(self, strategy, have_lock=False):
         if strategy == self._cookie_strategy:

yfinance/exceptions.py

@@ -1,12 +1,50 @@
-class YFinanceException(Exception):
+class YFException(Exception):
+    def __init__(self, description=""):
+        super().__init__(description)
+
+
+class YFDataException(YFException):
     pass
 
 
-class YFinanceDataException(YFinanceException):
-    pass
+class YFChartError(YFException):
+    def __init__(self, ticker, description):
+        self.ticker = ticker
+        super().__init__(f"{self.ticker}: {description}")
 
 
 class YFNotImplementedError(NotImplementedError):
     def __init__(self, method_name):
         super().__init__(f"Have not implemented fetching '{method_name}' from Yahoo API")
 
+
+class YFTickerMissingError(YFException):
+    def __init__(self, ticker, rationale):
+        super().__init__(f"${ticker}: possibly delisted; {rationale}")
+        self.rationale = rationale
+        self.ticker = ticker
+
+
+class YFTzMissingError(YFTickerMissingError):
+    def __init__(self, ticker):
+        super().__init__(ticker, "No timezone found")
+
+
+class YFPricesMissingError(YFTickerMissingError):
+    def __init__(self, ticker, debug_info):
+        self.debug_info = debug_info
+        super().__init__(ticker, f"No price data found {debug_info}")
+
+
+class YFEarningsDateMissing(YFTickerMissingError):
+    # note that this does not get raised. Added in case of raising it in the future
+    def __init__(self, ticker):
+        super().__init__(ticker, "No earnings dates found")
+
+
+class YFInvalidPeriodError(YFException):
+    def __init__(self, ticker, invalid_period, valid_ranges):
+        self.ticker = ticker
+        self.invalid_period = invalid_period
+        self.valid_ranges = valid_ranges
+        super().__init__(f"{self.ticker}: Period '{invalid_period}' is invalid, must be one of {valid_ranges}")

yfinance/multi.py

@@ -36,7 +36,7 @@ from . import shared
 @utils.log_indent_decorator
 def download(tickers, start=None, end=None, actions=False, threads=True, ignore_tz=None,
              group_by='column', auto_adjust=False, back_adjust=False, repair=False, keepna=False,
-             progress=True, period="max", show_errors=None, interval="1d", prepost=False,
+             progress=True, period="max", interval="1d", prepost=False,
              proxy=None, rounding=False, timeout=10, session=None):
     """Download yahoo tickers
     :Parameters:
@@ -80,9 +80,6 @@ def download(tickers, start=None, end=None, actions=False, threads=True, ignore_
             Optional. Proxy server URL scheme. Default is None
         rounding: bool
             Optional. Round values to 2 decimal places?
-        show_errors: bool
-            Optional. Doesn't print errors if False
-            DEPRECATED, will be removed in future version
         timeout: None or float
             If not None stops waiting for a response after given number of
             seconds. (Can also be a fraction of a second e.g. 0.01)
@@ -91,14 +88,6 @@ def download(tickers, start=None, end=None, actions=False, threads=True, ignore_
     """
     logger = utils.get_yf_logger()
 
-    if show_errors is not None:
-        if show_errors:
-            utils.print_once(f"yfinance: download(show_errors={show_errors}) argument is deprecated and will be removed in future version. Do this instead: logging.getLogger('yfinance').setLevel(logging.ERROR)")
-            logger.setLevel(logging.ERROR)
-        else:
-            utils.print_once(f"yfinance: download(show_errors={show_errors}) argument is deprecated and will be removed in future version. Do this instead to suppress error messages: logging.getLogger('yfinance').setLevel(logging.CRITICAL)")
-            logger.setLevel(logging.CRITICAL)
-
     if logger.isEnabledFor(logging.DEBUG):
         if threads:
             # With DEBUG, each thread generates a lot of log messages.

yfinance/scrapers/fundamentals.py

@@ -5,7 +5,7 @@ import pandas as pd
 
 from yfinance import utils, const
 from yfinance.data import YfData
-from yfinance.exceptions import YFinanceException, YFNotImplementedError
+from yfinance.exceptions import YFException, YFNotImplementedError
 
 
 class Fundamentals:
@@ -70,7 +70,7 @@ class Financials:
     @utils.log_indent_decorator
     def _fetch_time_series(self, name, timescale, proxy=None):
         # Fetching time series preferred over scraping 'QuoteSummaryStore',
-        # because it matches what Yahoo shows. But for some tickers returns nothing, 
+        # because it matches what Yahoo shows. But for some tickers returns nothing,
         # despite 'QuoteSummaryStore' containing valid data.
 
         allowed_names = ["income", "balance-sheet", "cash-flow"]
@@ -86,7 +86,7 @@ class Financials:
 
             if statement is not None:
                 return statement
-        except YFinanceException as e:
+        except YFException as e:
             utils.get_yf_logger().error(f"{self._symbol}: Failed to create {name} financials table for reason: {e}")
         return pd.DataFrame()
 

yfinance/scrapers/history.py

@@ -1,4 +1,3 @@
-
 import datetime as _datetime
 import dateutil as _dateutil
 import logging
@@ -8,6 +7,7 @@ import time as _time
 
 from yfinance import shared, utils
 from yfinance.const import _BASE_URL_, _PRICE_COLNAMES_
+from yfinance.exceptions import YFChartError, YFInvalidPeriodError, YFPricesMissingError, YFTzMissingError
 
 class PriceHistory:
     def __init__(self, data, ticker, tz, session=None, proxy=None):
@@ -23,7 +23,7 @@ class PriceHistory:
 
         # Limit recursion depth when repairing prices
         self._reconstruct_start_interval = None
-        
+
     @utils.log_indent_decorator
     def history(self, period="1mo", interval="1d",
                 start=None, end=None, prepost=False, actions=True,
@@ -80,14 +80,15 @@ class PriceHistory:
             # Check can get TZ. Fail => probably delisted
             tz = self.tz
             if tz is None:
-                # Every valid ticker has a timezone. Missing = problem
-                err_msg = "No timezone found, symbol may be delisted"
+                # Every valid ticker has a timezone. A missing timezone is a problem.
+                _exception = YFTzMissingError(self.ticker)
+                err_msg = str(_exception)
                 shared._DFS[self.ticker] = utils.empty_df()
-                shared._ERRORS[self.ticker] = err_msg
+                shared._ERRORS[self.ticker] = err_msg.split(': ', 1)[1]
                 if raise_errors:
-                    raise Exception(f'{self.ticker}: {err_msg}')
+                    raise _exception
                 else:
-                    logger.error(f'{self.ticker}: {err_msg}')
+                    logger.error(err_msg)
                 return utils.empty_df()
 
             if end is None:
@@ -159,48 +160,54 @@ class PriceHistory:
             self._history_metadata = {}
 
         intraday = params["interval"][-1] in ("m", 'h')
-        err_msg = "No price data found, symbol may be delisted"
+        _price_data_debug = ''
+        _exception = YFPricesMissingError(self.ticker, '')
         if start or period is None or period.lower() == "max":
-            err_msg += f' ({params["interval"]} '
+            _price_data_debug += f' ({params["interval"]} '
             if start_user is not None:
-                err_msg += f'{start_user}'
+                _price_data_debug += f'{start_user}'
             elif not intraday:
-                err_msg += f'{pd.Timestamp(start, unit="s").tz_localize("UTC").tz_convert(tz).date()}'
+                _price_data_debug += f'{pd.Timestamp(start, unit="s").tz_localize("UTC").tz_convert(tz).date()}'
             else:
-                err_msg += f'{pd.Timestamp(start, unit="s").tz_localize("UTC").tz_convert(tz)}'
-            err_msg += ' -> '
+                _price_data_debug += f'{pd.Timestamp(start, unit="s").tz_localize("UTC").tz_convert(tz)}'
+            _price_data_debug += ' -> '
             if end_user is not None:
-                err_msg += f'{end_user})'
+                _price_data_debug += f'{end_user})'
             elif not intraday:
-                err_msg += f'{pd.Timestamp(end, unit="s").tz_localize("UTC").tz_convert(tz).date()})'
+                _price_data_debug += f'{pd.Timestamp(end, unit="s").tz_localize("UTC").tz_convert(tz).date()})'
             else:
-                err_msg += f'{pd.Timestamp(end, unit="s").tz_localize("UTC").tz_convert(tz)})'
+                _price_data_debug += f'{pd.Timestamp(end, unit="s").tz_localize("UTC").tz_convert(tz)})'
         else:
-            err_msg += f' (period={period})'
+            _price_data_debug += f' (period={period})'
 
         fail = False
         if data is None or not isinstance(data, dict):
             fail = True
         elif isinstance(data, dict) and 'status_code' in data:
-            err_msg += f"(Yahoo status_code = {data['status_code']})"
+            _price_data_debug += f"(Yahoo status_code = {data['status_code']})"
             fail = True
         elif "chart" in data and data["chart"]["error"]:
-            err_msg = data["chart"]["error"]["description"]
+            _exception = YFChartError(self.ticker, data["chart"]["error"]["description"])
             fail = True
         elif "chart" not in data or data["chart"]["result"] is None or not data["chart"]["result"]:
             fail = True
-        elif period is not None and "timestamp" not in data["chart"]["result"][0] and period not in \
-                self._history_metadata["validRanges"]:
+        elif period is not None and period not in self._history_metadata["validRanges"]:
+            # even if timestamp is in the data, the data doesn't encompass the period requested
             # User provided a bad period. The minimum should be '1d', but sometimes Yahoo accepts '1h'.
-            err_msg = f"Period '{period}' is invalid, must be one of {self._history_metadata['validRanges']}"
+            _exception = YFInvalidPeriodError(self.ticker, period, self._history_metadata['validRanges'])
             fail = True
+
+        if isinstance(_exception, YFPricesMissingError):
+            _exception = YFPricesMissingError(self.ticker, _price_data_debug)
+
+        err_msg = str(_exception)
         if fail:
             shared._DFS[self.ticker] = utils.empty_df()
-            shared._ERRORS[self.ticker] = err_msg
+            shared._ERRORS[self.ticker] = err_msg.split(': ', 1)[1]
             if raise_errors:
-                raise Exception(f'{self.ticker}: {err_msg}')
+                raise _exception
             else:
-                logger.error(f'{self.ticker}: {err_msg}')
+                logger.error(err_msg)
             if self._reconstruct_start_interval is not None and self._reconstruct_start_interval == interval:
                 self._reconstruct_start_interval = None
             return utils.empty_df()
@@ -210,16 +217,17 @@ class PriceHistory:
             quotes = utils.parse_quotes(data["chart"]["result"][0])
             # Yahoo bug fix - it often appends latest price even if after end date
             if end and not quotes.empty:
-                endDt = pd.to_datetime(_datetime.datetime.utcfromtimestamp(end))
+                endDt = pd.to_datetime(end, unit='s')
                 if quotes.index[quotes.shape[0] - 1] >= endDt:
                     quotes = quotes.iloc[0:quotes.shape[0] - 1]
         except Exception:
             shared._DFS[self.ticker] = utils.empty_df()
-            shared._ERRORS[self.ticker] = err_msg
+            print(err_msg)
+            shared._ERRORS[self.ticker] = err_msg.split(': ', 1)[1]
             if raise_errors:
-                raise Exception(f'{self.ticker}: {err_msg}')
+                raise _exception
             else:
-                logger.error(f'{self.ticker}: {err_msg}')
+                logger.error(err_msg)
             if self._reconstruct_start_interval is not None and self._reconstruct_start_interval == interval:
                 self._reconstruct_start_interval = None
             return shared._DFS[self.ticker]
@@ -330,7 +338,7 @@ class PriceHistory:
             # Do this before auto/back adjust
             logger.debug(f'{self.ticker}: checking OHLC for repairs ...')
             df = self._fix_unit_mixups(df, interval, tz_exchange, prepost)
-            df = self._fix_bad_stock_split(df, interval, tz_exchange)
+            df = self._fix_bad_stock_splits(df, interval, tz_exchange)
             # Must repair 100x and split errors before price reconstruction
             df = self._fix_zeroes(df, interval, tz_exchange, prepost)
             df = self._fix_missing_div_adjust(df, interval, tz_exchange)
@@ -852,7 +860,7 @@ class PriceHistory:
         if f_zeroes.any():
             df2_zeroes = df2[f_zeroes]
             df2 = df2[~f_zeroes]
-            df = df[~f_zeroes]  # all row slicing must be applied to both df and df2
+            df_orig = df[~f_zeroes]  # all row slicing must be applied to both df and df2
         else:
             df2_zeroes = None
         if df2.shape[0] <= 1:
@@ -954,7 +962,7 @@ class PriceHistory:
             fj = f_either[:, j]
             if fj.any():
                 c = data_cols[j]
-                df2.loc[fj, c] = df.loc[fj, c]
+                df2.loc[fj, c] = df_orig.loc[fj, c]
         if df2_zeroes is not None:
             if "Repaired?" not in df2_zeroes.columns:
                 df2_zeroes["Repaired?"] = False
@@ -973,7 +981,12 @@ class PriceHistory:
         # This function fixes the second.
         # Eventually Yahoo fixes but could take them 2 weeks.
 
-        return self._fix_prices_sudden_change(df, interval, tz_exchange, 100.0)
+        if self._history_metadata['currency'] == 'KWF':
+            # Kuwaiti Dinar divided into 1000 not 100
+            n = 1000
+        else:
+            n = 100
+        return self._fix_prices_sudden_change(df, interval, tz_exchange, n)
 
     @utils.log_indent_decorator
     def _fix_zeroes(self, df, interval, tz_exchange, prepost):
@@ -1014,9 +1027,13 @@ class PriceHistory:
             df2 = df2[~f_zero_or_nan_ignore]
             f_prices_bad = (df2[price_cols] == 0.0) | df2[price_cols].isna()
 
-        f_high_low_good = (~df2["High"].isna().to_numpy()) & (~df2["Low"].isna().to_numpy())
         f_change = df2["High"].to_numpy() != df2["Low"].to_numpy()
-        f_vol_bad = (df2["Volume"] == 0).to_numpy() & f_high_low_good & f_change
+        if self.ticker.endswith("=X"):
+            # FX, volume always 0
+            f_vol_bad = None
+        else:
+            f_high_low_good = (~df2["High"].isna().to_numpy()) & (~df2["Low"].isna().to_numpy())
+            f_vol_bad = (df2["Volume"] == 0).to_numpy() & f_high_low_good & f_change
 
         # If stock split occurred, then trading must have happened.
         # I should probably rename the function, because prices aren't zero ...
@@ -1029,7 +1046,9 @@ class PriceHistory:
 
         # Check whether worth attempting repair
         f_prices_bad = f_prices_bad.to_numpy()
-        f_bad_rows = f_prices_bad.any(axis=1) | f_vol_bad
+        f_bad_rows = f_prices_bad.any(axis=1)
+        if f_vol_bad is not None:
+            f_bad_rows = f_bad_rows | f_vol_bad
         if not f_bad_rows.any():
             logger.info("price-repair-missing: No price=0 errors to repair")
             if "Repaired?" not in df.columns:
@@ -1157,9 +1176,12 @@ class PriceHistory:
         return df2
 
     @utils.log_indent_decorator
-    def _fix_bad_stock_split(self, df, interval, tz_exchange):
-        # Repair idea is to look for BIG daily price changes that closely match the
-        # most recent stock split ratio. This indicates Yahoo failed to apply a new
+    def _fix_bad_stock_splits(self, df, interval, tz_exchange):
+        # Original logic only considered latest split adjustment could be missing, but 
+        # actually **any** split adjustment can be missing. So check all splits in df.
+        #
+        # Improved logic looks for BIG daily price changes that closely match the
+        # **nearest future** stock split ratio. This indicates Yahoo failed to apply a new
         # stock split to old price data.
         #
         # There is a slight complication, because Yahoo does another stupid thing.
@@ -1176,22 +1198,39 @@ class PriceHistory:
         if not interday:
             return df
 
-        # Find the most recent stock split
-        df = df.sort_index(ascending=False)
+        df = df.sort_index()   # scan splits oldest -> newest
         split_f = df['Stock Splits'].to_numpy() != 0
         if not split_f.any():
             logger.debug('price-repair-split: No splits in data')
             return df
-        most_recent_split_day = df.index[split_f].max()
-        split = df.loc[most_recent_split_day, 'Stock Splits']
-        if most_recent_split_day == df.index[0]:
-            logger.info(
-                "price-repair-split: Need 1+ day of price data after split to determine true price. Won't repair")
-            return df
 
-        logger.debug(f'price-repair-split: Most recent split = {split:.4f} @ {most_recent_split_day.date()}')
+        logger.debug(f'price-repair-split: Splits: {str(df["Stock Splits"][split_f].to_dict())}')
 
-        return self._fix_prices_sudden_change(df, interval, tz_exchange, split, correct_volume=True)
+        if 'Repaired?' not in df.columns:
+            df['Repaired?'] = False
+        for split_idx in np.where(split_f)[0]:
+            split_dt = df.index[split_idx]
+            split = df.loc[split_dt, 'Stock Splits']
+            if split_dt == df.index[0]:
+                continue
+
+            # Add on a week:
+            if interval in ['1wk', '1mo', '3mo']:
+                split_idx += 1
+            else:
+                split_idx += 5
+            cutoff_idx = min(df.shape[0], split_idx)  # add one row after to detect big change
+            df_pre_split = df.iloc[0:cutoff_idx+1]
+            logger.debug(f'price-repair-split: split_idx={split_idx} split_dt={split_dt}')
+            logger.debug(f'price-repair-split: df dt range: {df_pre_split.index[0].date()} -> {df_pre_split.index[-1].date()}')
+
+            df_pre_split_repaired = self._fix_prices_sudden_change(df_pre_split, interval, tz_exchange, split, correct_volume=True)
+            # Merge back in:
+            if cutoff_idx == df.shape[0]-1:
+                df = df_pre_split_repaired
+            else:
+                df = pd.concat([df_pre_split_repaired.sort_index(), df.iloc[cutoff_idx+1:]])
+        return df
 
     @utils.log_indent_decorator
     def _fix_prices_sudden_change(self, df, interval, tz_exchange, change, correct_volume=False):
@@ -1212,7 +1251,7 @@ class PriceHistory:
             # start_min = 1 year before oldest split
             f = df['Stock Splits'].to_numpy() != 0.0
             start_min = (df.index[f].min() - _dateutil.relativedelta.relativedelta(years=1)).date()
-            logger.debug(f'price-repair-split: start_min={start_min}')
+        logger.debug(f'price-repair-split: start_min={start_min} change={change}')
 
         OHLC = ['Open', 'High', 'Low', 'Close']
 
@@ -1288,10 +1327,12 @@ class PriceHistory:
             # average change
             _1d_change_minx = np.average(_1d_change_x, axis=1)
         else:
-            # change nearest to 1.0
-            diff = np.abs(_1d_change_x - 1.0)
-            j_indices = np.argmin(diff, axis=1)
-            _1d_change_minx = _1d_change_x[np.arange(n), j_indices]
+            # # change nearest to 1.0
+            # diff = np.abs(_1d_change_x - 1.0)
+            # j_indices = np.argmin(diff, axis=1)
+            # _1d_change_minx = _1d_change_x[np.arange(n), j_indices]
+            # Still sensitive to extreme-low low. Try median:
+            _1d_change_minx = np.median(_1d_change_x, axis=1)
         f_na = np.isnan(_1d_change_minx)
         if f_na.any():
             # Possible if data was too old for reconstruction.
@@ -1408,8 +1449,13 @@ class PriceHistory:
         # if logger.isEnabledFor(logging.DEBUG):
         #     df_debug['i'] = list(range(0, df_debug.shape[0]))
         #     df_debug['i_rev'] = df_debug.shape[0]-1 - df_debug['i']
+        #     if correct_columns_individually:
+        #         f_change = df_debug[[c+'_f_down' for c in debug_cols]].any(axis=1) | df_debug[[c+'_f_up' for c in debug_cols]].any(axis=1)
+        #     else:
+        #         f_change = df_debug['f_down'] | df_debug['f_up']
+        #     f_change = f_change | np.roll(f_change, -1) | np.roll(f_change, 1) | np.roll(f_change, -2) | np.roll(f_change, 2)
         #     with pd.option_context('display.max_rows', None, 'display.max_columns', 10, 'display.width', 1000):  # more options can be specified also
-        #         logger.debug(f"price-repair-split: my workings:" + '\n' + str(df_debug))
+        #         logger.debug(f"price-repair-split: my workings:" + '\n' + str(df_debug[f_change]))
 
         def map_signals_to_ranges(f, f_up, f_down):
             # Ensure 0th element is False, because True is nonsense

yfinance/scrapers/holders.py

@@ -6,7 +6,7 @@ import requests
 from yfinance import utils
 from yfinance.data import YfData
 from yfinance.const import _BASE_URL_
-from yfinance.exceptions import YFinanceDataException
+from yfinance.exceptions import YFDataException
 
 _QUOTE_SUMMARY_URL_ = f"{_BASE_URL_}/v10/finance/quoteSummary/"
 
@@ -104,7 +104,7 @@ class Holders:
             self._parse_insider_holders(data["insiderHolders"])
             self._parse_net_share_purchase_activity(data["netSharePurchaseActivity"])
         except (KeyError, IndexError):
-            raise YFinanceDataException("Failed to parse holders json data.")
+            raise YFDataException("Failed to parse holders json data.")
 
     @staticmethod
     def _parse_raw_values(data):
@@ -189,7 +189,7 @@ class Holders:
         if not df.empty:
             df["positionDirectDate"] = pd.to_datetime(df["positionDirectDate"], unit="s")
             df["latestTransDate"] = pd.to_datetime(df["latestTransDate"], unit="s")
-            
+
             df.rename(columns={
                 "name": "Name",
                 "relation": "Position",
@@ -242,5 +242,3 @@ class Holders:
             }
         ).convert_dtypes()
         self._insider_purchases = df
-
-    

yfinance/scrapers/quote.py

@@ -10,7 +10,7 @@ import requests
 from yfinance import utils
 from yfinance.data import YfData
 from yfinance.const import quote_summary_valid_modules, _BASE_URL_
-from yfinance.exceptions import YFNotImplementedError, YFinanceDataException, YFinanceException
+from yfinance.exceptions import YFNotImplementedError, YFDataException, YFException
 
 info_retired_keys_price = {"currentPrice", "dayHigh", "dayLow", "open", "previousClose", "volume", "volume24Hr"}
 info_retired_keys_price.update({"regularMarket"+s for s in ["DayHigh", "DayLow", "Open", "PreviousClose", "Price", "Volume"]})
@@ -181,7 +181,7 @@ class FastInfo:
 
     def _get_1y_prices(self, fullDaysOnly=False):
         if self._prices_1y is None:
-            self._prices_1y = self._tkr.history(period="380d", auto_adjust=False, keepna=True, proxy=self.proxy)
+            self._prices_1y = self._tkr.history(period="1y", auto_adjust=False, keepna=True, proxy=self.proxy)
             self._md = self._tkr.get_history_metadata(proxy=self.proxy)
             try:
                 ctp = self._md["currentTradingPeriod"]
@@ -207,12 +207,12 @@ class FastInfo:
 
     def _get_1wk_1h_prepost_prices(self):
         if self._prices_1wk_1h_prepost is None:
-            self._prices_1wk_1h_prepost = self._tkr.history(period="1wk", interval="1h", auto_adjust=False, prepost=True, proxy=self.proxy)
+            self._prices_1wk_1h_prepost = self._tkr.history(period="5d", interval="1h", auto_adjust=False, prepost=True, proxy=self.proxy)
         return self._prices_1wk_1h_prepost
 
     def _get_1wk_1h_reg_prices(self):
         if self._prices_1wk_1h_reg is None:
-            self._prices_1wk_1h_reg = self._tkr.history(period="1wk", interval="1h", auto_adjust=False, prepost=False, proxy=self.proxy)
+            self._prices_1wk_1h_reg = self._tkr.history(period="5d", interval="1h", auto_adjust=False, prepost=False, proxy=self.proxy)
         return self._prices_1wk_1h_reg
 
     def _get_exchange_metadata(self):
@@ -578,7 +578,7 @@ class Quote:
                 try:
                     data = result["quoteSummary"]["result"][0]["recommendationTrend"]["trend"]
                 except (KeyError, IndexError):
-                    raise YFinanceDataException(f"Failed to parse json response from Yahoo Finance: {result}")
+                    raise YFDataException(f"Failed to parse json response from Yahoo Finance: {result}")
                 self._recommendations = pd.DataFrame(data)
         return self._recommendations
 
@@ -592,14 +592,14 @@ class Quote:
                 try:
                     data = result["quoteSummary"]["result"][0]["upgradeDowngradeHistory"]["history"]
                     if len(data) == 0:
-                        raise YFinanceDataException(f"No upgrade/downgrade history found for {self._symbol}")
+                        raise YFDataException(f"No upgrade/downgrade history found for {self._symbol}")
                     df = pd.DataFrame(data)
                     df.rename(columns={"epochGradeDate": "GradeDate", 'firm': 'Firm', 'toGrade': 'ToGrade', 'fromGrade': 'FromGrade', 'action': 'Action'}, inplace=True)
                     df.set_index('GradeDate', inplace=True)
                     df.index = pd.to_datetime(df.index, unit='s')
                     self._upgrades_downgrades = df
                 except (KeyError, IndexError):
-                    raise YFinanceDataException(f"Failed to parse json response from Yahoo Finance: {result}")
+                    raise YFDataException(f"Failed to parse json response from Yahoo Finance: {result}")
         return self._upgrades_downgrades
 
     @property
@@ -614,11 +614,11 @@ class Quote:
 
     def _fetch(self, proxy, modules: list):
         if not isinstance(modules, list):
-            raise YFinanceException("Should provide a list of modules, see available modules using `valid_modules`")
+            raise YFException("Should provide a list of modules, see available modules using `valid_modules`")
 
         modules = ','.join([m for m in modules if m in quote_summary_valid_modules])
         if len(modules) == 0:
-            raise YFinanceException("No valid modules provided, see available modules using `valid_modules`")
+            raise YFException("No valid modules provided, see available modules using `valid_modules`")
         params_dict = {"modules": modules, "corsDomain": "finance.yahoo.com", "formatted": "false", "symbol": self._symbol}
         try:
             result = self._data.get_raw_json(_QUOTE_SUMMARY_URL_ + f"/{self._symbol}", user_agent_headers=self._data.user_agent_headers, params=params_dict, proxy=proxy)
@@ -721,7 +721,7 @@ class Quote:
             json_data = json.loads(json_str)
             json_result = json_data.get("timeseries") or json_data.get("finance")
             if json_result["error"] is not None:
-                raise YFinanceException("Failed to parse json response from Yahoo Finance: " + str(json_result["error"]))
+                raise YFException("Failed to parse json response from Yahoo Finance: " + str(json_result["error"]))
             for k in keys:
                 keydict = json_result["result"][0]
                 if k in keydict:
@@ -754,4 +754,4 @@ class Quote:
                 self._calendar['Revenue Low'] = earnings.get('revenueLow', None)
                 self._calendar['Revenue Average'] = earnings.get('revenueAverage', None)
         except (KeyError, IndexError):
-            raise YFinanceDataException(f"Failed to parse json response from Yahoo Finance: {result}")
+            raise YFDataException(f"Failed to parse json response from Yahoo Finance: {result}")

yfinance/ticker.py

@@ -21,7 +21,6 @@
 
 from __future__ import print_function
 
-import datetime as _datetime
 from collections import namedtuple as _namedtuple
 
 import pandas as _pd
@@ -48,8 +47,7 @@ class Ticker(TickerBase):
         r = self._data.get(url=url, proxy=self.proxy).json()
         if len(r.get('optionChain', {}).get('result', [])) > 0:
             for exp in r['optionChain']['result'][0]['expirationDates']:
-                self._expirations[_datetime.datetime.utcfromtimestamp(
-                    exp).strftime('%Y-%m-%d')] = exp
+                self._expirations[_pd.Timestamp(exp, unit='s').strftime('%Y-%m-%d')] = exp
 
             self._underlying = r['optionChain']['result'][0].get('quote', {})
 

yfinance/utils.py

@@ -26,7 +26,7 @@ import logging
 import re as _re
 import sys as _sys
 import threading
-from functools import lru_cache
+from functools import lru_cache, wraps
 from inspect import getmembers
 from types import FunctionType
 from typing import List, Optional
@@ -95,6 +95,7 @@ def get_indented_logger(name=None):
 
 
 def log_indent_decorator(func):
+    @wraps(func)
     def wrapper(*args, **kwargs):
         logger = get_indented_logger('yfinance')
         logger.debug(f'Entering {func.__name__}()')

yfinance/version.py

@@ -1 +1 @@
-version = "0.2.38"
+version = "0.2.40"