Merge pull request #1834 from ranaroussi/dev

sync dev -> main

README.md

@@ -55,7 +55,7 @@ $ pip install yfinance --upgrade --no-cache-dir
 To install with optional dependencies, replace `optional` with: `nospam` for [caching-requests](#smarter-scraping), `repair` for [price repair](https://github.com/ranaroussi/yfinance/wiki/Price-repair), or `nospam,repair` for both:
 
 ``` {.sourceCode .bash}
-$ pip install yfinance[optional]
+$ pip install "yfinance[optional]"
 ```
 
 [Required dependencies](./requirements.txt) , [all dependencies](./setup.py#L62).

requirements.txt

@@ -8,4 +8,4 @@ pytz>=2022.5
 frozendict>=2.3.4
 beautifulsoup4>=4.11.1
 html5lib>=1.1
-peewee>=3.16.2
+peewee>=3.16.2

tests/ticker.py

@@ -112,8 +112,24 @@ class TestTicker(unittest.TestCase):
             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)
-       
+
+        with self.assertRaises(YFNotImplementedError):
+            assert isinstance(dat.earnings, pd.Series)
+            assert dat.earnings.empty
+        assert isinstance(dat.dividends, pd.Series)
+        assert dat.dividends.empty
+        assert isinstance(dat.splits, pd.Series)
+        assert dat.splits.empty
+        assert isinstance(dat.capital_gains, pd.Series)
+        assert dat.capital_gains.empty
+        with self.assertRaises(YFNotImplementedError):
+            assert isinstance(dat.shares, pd.DataFrame)
+            assert dat.shares.empty
+        assert isinstance(dat.actions, pd.DataFrame)
+        assert dat.actions.empty
+
+
     def test_goodTicker(self):
         # that yfinance works when full api is called on same instance of ticker
 

yfinance/base.py

@@ -27,7 +27,7 @@ import json as _json
 import logging
 import time as _time
 import warnings
-from typing import Optional
+from typing import Optional, Union
 from urllib.parse import quote as urlencode
 
 import dateutil as _dateutil
@@ -42,7 +42,10 @@ from .scrapers.fundamentals import Fundamentals
 from .scrapers.holders import Holders
 from .scrapers.quote import Quote, FastInfo
 
-from .const import _BASE_URL_, _ROOT_URL_
+from .const import _BASE_URL_, _ROOT_URL_, price_colnames
+
+
+_empty_series = pd.Series()
 
 
 class TickerBase:
@@ -426,7 +429,9 @@ class TickerBase:
         if not actions:
             df = df.drop(columns=["Dividends", "Stock Splits", "Capital Gains"], errors='ignore')
         if not keepna:
-            mask_nan_or_zero = (df.isna() | (df == 0)).all(axis=1)
+            data_colnames = price_colnames + ['Volume'] + ['Dividends', 'Stock Splits', 'Capital Gains']
+            data_colnames = [c for c in data_colnames if c in df.columns]
+            mask_nan_or_zero = (df[data_colnames].isna() | (df[data_colnames] == 0)).all(axis=1)
             df = df.drop(mask_nan_or_zero.index[mask_nan_or_zero])
 
         logger.debug(f'{self.ticker}: yfinance returning OHLC: {df.index[0]} -> {df.index[-1]}')
@@ -455,7 +460,7 @@ class TickerBase:
         else:
             intraday = True
 
-        price_cols = [c for c in ["Open", "High", "Low", "Close", "Adj Close"] if c in df]
+        price_cols = [c for c in price_colnames if c in df]
         data_cols = price_cols + ["Volume"]
 
         # If interval is weekly then can construct with daily. But if smaller intervals then
@@ -1011,7 +1016,7 @@ class TickerBase:
         elif df2.index.tz != tz_exchange:
             df2.index = df2.index.tz_convert(tz_exchange)
 
-        price_cols = [c for c in ["Open", "High", "Low", "Close", "Adj Close"] if c in df2.columns]
+        price_cols = [c for c in price_colnames if c in df2.columns]
         f_prices_bad = (df2[price_cols] == 0.0) | df2[price_cols].isna()
         df2_reserve = None
         if intraday:
@@ -1916,7 +1921,7 @@ class TickerBase:
     def get_balancesheet(self, proxy=None, as_dict=False, pretty=False, freq="yearly"):
         return self.get_balance_sheet(proxy, as_dict, pretty, freq)
 
-    def get_cash_flow(self, proxy=None, as_dict=False, pretty=False, freq="yearly"):
+    def get_cash_flow(self, proxy=None, as_dict=False, pretty=False, freq="yearly") -> Union[pd.DataFrame, dict]:
         """
         :Parameters:
             as_dict: bool
@@ -1946,31 +1951,31 @@ class TickerBase:
     def get_cashflow(self, proxy=None, as_dict=False, pretty=False, freq="yearly"):
         return self.get_cash_flow(proxy, as_dict, pretty, freq)
 
-    def get_dividends(self, proxy=None):
+    def get_dividends(self, proxy=None) -> pd.Series:
         if self._history is None:
             self.history(period="max", proxy=proxy)
         if self._history is not None and "Dividends" in self._history:
             dividends = self._history["Dividends"]
             return dividends[dividends != 0]
-        return []
+        return pd.Series()
 
-    def get_capital_gains(self, proxy=None):
+    def get_capital_gains(self, proxy=None) -> pd.Series:
         if self._history is None:
             self.history(period="max", proxy=proxy)
         if self._history is not None and "Capital Gains" in self._history:
             capital_gains = self._history["Capital Gains"]
             return capital_gains[capital_gains != 0]
-        return []
+        return _empty_series
 
-    def get_splits(self, proxy=None):
+    def get_splits(self, proxy=None) -> pd.Series:
         if self._history is None:
             self.history(period="max", proxy=proxy)
         if self._history is not None and "Stock Splits" in self._history:
             splits = self._history["Stock Splits"]
             return splits[splits != 0]
-        return []
+        return pd.Series()
 
-    def get_actions(self, proxy=None):
+    def get_actions(self, proxy=None) -> pd.Series:
         if self._history is None:
             self.history(period="max", proxy=proxy)
         if self._history is not None and "Dividends" in self._history and "Stock Splits" in self._history:
@@ -1979,9 +1984,9 @@ class TickerBase:
                 action_columns.append("Capital Gains")
             actions = self._history[action_columns]
             return actions[actions != 0].dropna(how='all').fillna(0)
-        return []
+        return _empty_series
 
-    def get_shares(self, proxy=None, as_dict=False):
+    def get_shares(self, proxy=None, as_dict=False) -> Union[pd.DataFrame, dict]:
         self._fundamentals.proxy = proxy or self.proxy
         data = self._fundamentals.shares
         if as_dict:
@@ -2078,7 +2083,7 @@ class TickerBase:
         self._isin = data.split(search_str)[1].split('"')[0].split('|')[0]
         return self._isin
 
-    def get_news(self, proxy=None):
+    def get_news(self, proxy=None) -> list:
         if self._news:
             return self._news
 

yfinance/cache.py

@@ -145,7 +145,14 @@ class _TzCache:
 
         db.connect()
         tz_db_proxy.initialize(db)
-        db.create_tables([_KV])
+        try:
+            db.create_tables([_KV])
+        except _peewee.OperationalError as e:
+            if 'WITHOUT' in str(e):
+                _KV._meta.without_rowid = False
+                db.create_tables([_KV])
+            else:
+                raise
         self.initialised = 1  # success
 
     def lookup(self, key):
@@ -344,7 +351,14 @@ class _CookieCache:
 
         db.connect()
         Cookie_db_proxy.initialize(db)
-        db.create_tables([_CookieSchema])
+        try:
+            db.create_tables([_CookieSchema])
+        except _peewee.OperationalError as e:
+            if 'WITHOUT' in str(e):
+                _CookieSchema._meta.without_rowid = False
+                db.create_tables([_CookieSchema])
+            else:
+                raise
         self.initialised = 1  # success
 
     def lookup(self, strategy):

yfinance/multi.py

@@ -217,11 +217,11 @@ def download(tickers, start=None, end=None, actions=False, threads=True, ignore_
 
     try:
         data = _pd.concat(shared._DFS.values(), axis=1, sort=True,
-                          keys=shared._DFS.keys())
+                          keys=shared._DFS.keys(), names=['Ticker', 'Price'])
     except Exception:
         _realign_dfs()
         data = _pd.concat(shared._DFS.values(), axis=1, sort=True,
-                          keys=shared._DFS.keys())
+                          keys=shared._DFS.keys(), names=['Ticker', 'Price'])
     data.index = _pd.to_datetime(data.index)
     # switch names back to isins if applicable
     data.rename(columns=shared._ISINS, inplace=True)

yfinance/scrapers/quote.py

@@ -733,10 +733,11 @@ class Quote:
 
             json_str = self._data.cache_get(url=url, proxy=proxy).text
             json_data = json.loads(json_str)
-            if json_data["timeseries"]["error"] is not None:
+            json_result = json_data.get("timeseries") or json_data.get("finance")
-                raise YFinanceException("Failed to parse json response from Yahoo Finance: " + json_data["error"])
+            if json_result["error"] is not None:
+                raise YFinanceException("Failed to parse json response from Yahoo Finance: " + str(json_result["error"]))
             for k in keys:
-                keydict = json_data["timeseries"]["result"][0]
+                keydict = json_result["result"][0]
                 if k in keydict:
                     self._info[k] = keydict[k][-1]["reportedValue"]["raw"]
                 else:

yfinance/ticker.py

@@ -134,7 +134,7 @@ class Ticker(TickerBase):
         return self.get_dividends()
 
     @property
-    def capital_gains(self):
+    def capital_gains(self) -> _pd.Series:
         return self.get_capital_gains()
 
     @property
@@ -146,7 +146,7 @@ class Ticker(TickerBase):
         return self.get_actions()
 
     @property
-    def shares(self) -> _pd.DataFrame :
+    def shares(self) -> _pd.DataFrame:
         return self.get_shares()
 
     @property
@@ -259,7 +259,7 @@ class Ticker(TickerBase):
         return tuple(self._expirations.keys())
 
     @property
-    def news(self):
+    def news(self) -> list:
         return self.get_news()
 
     @property