Update to 0.1.78

Add 'ignore_tz' arg to download()

.travis.yml

@@ -6,7 +6,6 @@ fast_finish: true
 matrix:
   include:
     - python: 2.7
-    - python: 3.5
     - python: 3.6
     - python: 3.7
     - python: 3.8

CHANGELOG.rst

@@ -1,6 +1,61 @@
 Change Log
 ===========
 
+0.1.78
+------
+- Fix download() when different timezones #1085
+
+0.1.77
+------
+- Fix user experience bug #1078
+
+0.1.75
+------
+- Fixed datetime-related issues: #1048
+- Add 'keepna' argument #1032
+- Speedup Ticker() creation #1042
+- Improve a bugfix #1033
+
+0.1.74
+------
+- Fixed bug introduced in 0.1.73 (sorry :/)
+
+0.1.73
+------
+- Merged several PR that fixed misc issues
+
+0.1.72
+------
+- Misc bugfixs
+
+0.1.71
+------
+- Added Tickers(…).news()
+- Return empty DF if YF missing earnings dates
+- Fix EPS % to 0->1
+- Fix timezone handling
+- Fix handling of missing data
+- Clean&format earnings_dates table
+- Add ``.get_earnings_dates()`` to retreive earnings calendar
+- Added ``.get_earnings_history()`` to fetch earnings data
+
+0.1.70
+------
+- Bug fixed - Closes #937
+
+0.1.69
+------
+- Bug fixed - #920
+
+0.1.68
+------
+- Upgraded requests dependency
+- Removed Python 3.5 support
+
+0.1.67
+------
+- Added legal disclaimers to make sure people are aware that this library is not affiliated, endorsed, or vetted by Yahoo, Inc.
+
 0.1.66
 ------
 - Merged PR to allow yfinance to be pickled

README.md

@@ -0,0 +1,301 @@
+# Download market data from Yahoo! Finance's API
+
+<table border=1 cellpadding=10><tr><td>
+
+#### \*\*\* IMPORTANT LEGAL DISCLAIMER \*\*\*
+
+---
+
+**Yahoo!, Y!Finance, and Yahoo! finance are registered trademarks of
+Yahoo, Inc.**
+
+yfinance is **not** affiliated, endorsed, or vetted by Yahoo, Inc. It's
+an open-source tool that uses Yahoo's publicly available APIs, and is
+intended for research and educational purposes.
+
+**You should refer to Yahoo!'s terms of use**
+([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
+details on your rights to use the actual data downloaded. Remember - the
+Yahoo! finance API is intended for personal use only.**
+
+</td></tr></table>
+
+---
+
+<a target="new" href="https://pypi.python.org/pypi/yfinance"><img border=0 src="https://img.shields.io/badge/python-2.7,%203.6+-blue.svg?style=flat" alt="Python version"></a>
+<a target="new" href="https://pypi.python.org/pypi/yfinance"><img border=0 src="https://img.shields.io/pypi/v/yfinance.svg?maxAge=60%" alt="PyPi version"></a>
+<a target="new" href="https://pypi.python.org/pypi/yfinance"><img border=0 src="https://img.shields.io/pypi/status/yfinance.svg?maxAge=60" alt="PyPi status"></a>
+<a target="new" href="https://pypi.python.org/pypi/yfinance"><img border=0 src="https://img.shields.io/pypi/dm/yfinance.svg?maxAge=2592000&label=installs&color=%2327B1FF" alt="PyPi downloads"></a>
+<a target="new" href="https://travis-ci.com/github/ranaroussi/yfinance"><img border=0 src="https://img.shields.io/travis/ranaroussi/yfinance/main.svg?maxAge=1" alt="Travis-CI build status"></a>
+<a target="new" href="https://www.codefactor.io/repository/github/ranaroussi/yfinance"><img border=0 src="https://www.codefactor.io/repository/github/ranaroussi/yfinance/badge" alt="CodeFactor"></a>
+<a target="new" href="https://github.com/ranaroussi/yfinance"><img border=0 src="https://img.shields.io/github/stars/ranaroussi/yfinance.svg?style=social&label=Star&maxAge=60" alt="Star this repo"></a>
+<a target="new" href="https://twitter.com/aroussi"><img border=0 src="https://img.shields.io/twitter/follow/aroussi.svg?style=social&label=Follow&maxAge=60" alt="Follow me on twitter"></a>
+
+
+**yfinance** offers a threaded and Pythonic way to download market data from [Yahoo!Ⓡ finance](https://finance.yahoo.com).
+
+→ Check out this [Blog post](https://aroussi.com/#post/python-yahoo-finance) for a detailed tutorial with code examples.
+
+[Changelog »](https://github.com/ranaroussi/yfinance/blob/main/CHANGELOG.rst)
+
+---
+
+## Quick Start
+
+### The Ticker module
+
+The `Ticker` module, which allows you to access ticker data in a more Pythonic way:
+
+Note: yahoo finance datetimes are received as UTC.
+
+```python
+import yfinance as yf
+
+msft = yf.Ticker("MSFT")
+
+# get stock info
+msft.info
+
+# get historical market data
+hist = msft.history(period="max")
+
+# show actions (dividends, splits)
+msft.actions
+
+# show dividends
+msft.dividends
+
+# show splits
+msft.splits
+
+# show financials
+msft.financials
+msft.quarterly_financials
+
+# show major holders
+msft.major_holders
+
+# show institutional holders
+msft.institutional_holders
+
+# show balance sheet
+msft.balance_sheet
+msft.quarterly_balance_sheet
+
+# show cashflow
+msft.cashflow
+msft.quarterly_cashflow
+
+# show earnings
+msft.earnings
+msft.quarterly_earnings
+
+# show sustainability
+msft.sustainability
+
+# show analysts recommendations
+msft.recommendations
+
+# show next event (earnings, etc)
+msft.calendar
+
+# show all earnings dates
+msft.earnings_dates
+
+# show ISIN code - *experimental*
+# ISIN = International Securities Identification Number
+msft.isin
+
+# show options expirations
+msft.options
+
+# show news
+msft.news
+
+# get option chain for specific expiration
+opt = msft.option_chain('YYYY-MM-DD')
+# data available via: opt.calls, opt.puts
+```
+
+If you want to use a proxy server for downloading data, use:
+
+```python
+import yfinance as yf
+
+msft = yf.Ticker("MSFT")
+
+msft.history(..., proxy="PROXY_SERVER")
+msft.get_actions(proxy="PROXY_SERVER")
+msft.get_dividends(proxy="PROXY_SERVER")
+msft.get_splits(proxy="PROXY_SERVER")
+msft.get_balance_sheet(proxy="PROXY_SERVER")
+msft.get_cashflow(proxy="PROXY_SERVER")
+msft.option_chain(..., proxy="PROXY_SERVER")
+...
+```
+
+To use a custom `requests` session (for example to cache calls to the
+API or customize the `User-agent` header), pass a `session=` argument to
+the Ticker constructor.
+
+```python
+import requests_cache
+session = requests_cache.CachedSession('yfinance.cache')
+session.headers['User-agent'] = 'my-program/1.0'
+ticker = yf.Ticker('msft aapl goog', session=session)
+# The scraped response will be stored in the cache
+ticker.actions
+```
+
+To initialize multiple `Ticker` objects, use
+
+```python
+import yfinance as yf
+
+tickers = yf.Tickers('msft aapl goog')
+# ^ returns a named tuple of Ticker objects
+
+# access each ticker using (example)
+tickers.tickers.MSFT.info
+tickers.tickers.AAPL.history(period="1mo")
+tickers.tickers.GOOG.actions
+```
+
+### Fetching data for multiple tickers
+
+```python
+import yfinance as yf
+data = yf.download("SPY AAPL", start="2017-01-01", end="2017-04-30")
+```
+
+I've also added some options to make life easier :)
+
+```python
+data = yf.download(  # or pdr.get_data_yahoo(...
+        # tickers list or string as well
+        tickers = "SPY AAPL MSFT",
+
+        # use "period" instead of start/end
+        # valid periods: 1d,5d,1mo,3mo,6mo,1y,2y,5y,10y,ytd,max
+        # (optional, default is '1mo')
+        period = "ytd",
+
+        # fetch data by interval (including intraday if period < 60 days)
+        # valid intervals: 1m,2m,5m,15m,30m,60m,90m,1h,1d,5d,1wk,1mo,3mo
+        # (optional, default is '1d')
+        interval = "1m",
+
+        # Whether to ignore timezone when aligning ticker data from 
+        # different timezones. Default is True. False may be useful for 
+        # minute/hourly data.
+        ignore_tz = False,
+
+        # group by ticker (to access via data['SPY'])
+        # (optional, default is 'column')
+        group_by = 'ticker',
+
+        # adjust all OHLC automatically
+        # (optional, default is False)
+        auto_adjust = True,
+
+        # download pre/post regular market hours data
+        # (optional, default is False)
+        prepost = True,
+
+        # use threads for mass downloading? (True/False/Integer)
+        # (optional, default is True)
+        threads = True,
+
+        # proxy URL scheme use use when downloading?
+        # (optional, default is None)
+        proxy = None
+    )
+```
+
+### Managing Multi-Level Columns
+
+The following answer on Stack Overflow is for [How to deal with
+multi-level column names downloaded with
+yfinance?](https://stackoverflow.com/questions/63107801)
+
+-   `yfinance` returns a `pandas.DataFrame` with multi-level column
+    names, with a level for the ticker and a level for the stock price
+    data
+    -   The answer discusses:
+        -   How to correctly read the the multi-level columns after
+            saving the dataframe to a csv with `pandas.DataFrame.to_csv`
+        -   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")
+```
+
+---
+
+## Installation
+
+Install `yfinance` using `pip`:
+
+``` {.sourceCode .bash}
+$ pip install yfinance --upgrade --no-cache-dir
+```
+
+To install `yfinance` using `conda`, see
+[this](https://anaconda.org/ranaroussi/yfinance).
+
+### Requirements
+
+-   [Python](https://www.python.org) \>= 2.7, 3.4+
+-   [Pandas](https://github.com/pydata/pandas) (tested to work with
+    \>=0.23.1)
+-   [Numpy](http://www.numpy.org) \>= 1.11.1
+-   [requests](http://docs.python-requests.org/en/master/) \>= 2.14.2
+-   [lxml](https://pypi.org/project/lxml/) \>= 4.5.1
+-   [appdirs](https://pypi.org/project/appdirs) \>=1.4.4
+
+### Optional (if you want to use `pandas_datareader`)
+
+-   [pandas\_datareader](https://github.com/pydata/pandas-datareader)
+    \>= 0.4.0
+
+---
+
+### Legal Stuff
+
+**yfinance** is distributed under the **Apache Software License**. See
+the [LICENSE.txt](./LICENSE.txt) file in the release for details.
+
+
+AGAIN - yfinance is **not** affiliated, endorsed, or vetted by Yahoo, Inc. It's
+an open-source tool that uses Yahoo's publicly available APIs, and is
+intended for research and educational purposes. You should refer to Yahoo!'s terms of use
+([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.
+
+---
+
+### P.S.
+
+Please drop me an note with any feedback you have.
+
+**Ran Aroussi**

README.rst

@@ -1,301 +0,0 @@
-Yahoo! Finance market data downloader
-=====================================
-
-.. image:: https://img.shields.io/badge/python-2.7,%203.4+-blue.svg?style=flat
-    :target: https://pypi.python.org/pypi/yfinance
-    :alt: Python version
-
-.. image:: https://img.shields.io/pypi/v/yfinance.svg?maxAge=60
-    :target: https://pypi.python.org/pypi/yfinance
-    :alt: PyPi version
-
-.. image:: https://img.shields.io/pypi/status/yfinance.svg?maxAge=60
-    :target: https://pypi.python.org/pypi/yfinance
-    :alt: PyPi status
-
-.. image:: https://img.shields.io/pypi/dm/yfinance.svg?maxAge=2592000&label=installs&color=%2327B1FF
-    :target: https://pypi.python.org/pypi/yfinance
-    :alt: PyPi downloads
-
-.. image:: https://img.shields.io/travis/ranaroussi/yfinance/main.svg?maxAge=1
-    :target: https://travis-ci.com/github/ranaroussi/yfinance
-    :alt: Travis-CI build status
-
-.. image:: https://www.codefactor.io/repository/github/ranaroussi/yfinance/badge
-    :target: https://www.codefactor.io/repository/github/ranaroussi/yfinance
-    :alt: CodeFactor
-
-.. image:: https://img.shields.io/github/stars/ranaroussi/yfinance.svg?style=social&label=Star&maxAge=60
-    :target: https://github.com/ranaroussi/yfinance
-    :alt: Star this repo
-
-.. image:: https://img.shields.io/twitter/follow/aroussi.svg?style=social&label=Follow&maxAge=60
-    :target: https://twitter.com/aroussi
-    :alt: Follow me on twitter
-
-\
-
-Ever since `Yahoo! finance <https://finance.yahoo.com>`_ decommissioned
-their historical data API, many programs that relied on it to stop working.
-
-**yfinance** aims to solve this problem by offering a reliable, threaded,
-and Pythonic way to download historical market data from Yahoo! finance.
-
-
-NOTE
-~~~~
-
-The library was originally named ``fix-yahoo-finance``, but
-I've since renamed it to ``yfinance`` as I no longer consider it a mere "fix".
-For reasons of backward-compatibility, ``fix-yahoo-finance`` now import and
-uses ``yfinance``, but you should install and use ``yfinance`` directly.
-
-`Changelog » <https://github.com/ranaroussi/yfinance/blob/main/CHANGELOG.rst>`__
-
------
-
-==> Check out this `Blog post <https://aroussi.com/#post/python-yahoo-finance>`_ for a detailed tutorial with code examples.
-
------
-
-Quick Start
-===========
-
-The Ticker module
-~~~~~~~~~~~~~~~~~
-
-The ``Ticker`` module, which allows you to access
-ticker data in a more Pythonic way:
-
-Note: yahoo finance datetimes are received as UTC.
-
-.. code:: python
-
-    import yfinance as yf
-
-    msft = yf.Ticker("MSFT")
-
-    # get stock info
-    msft.info
-
-    # get historical market data
-    hist = msft.history(period="max")
-
-    # show actions (dividends, splits)
-    msft.actions
-
-    # show dividends
-    msft.dividends
-
-    # show splits
-    msft.splits
-
-    # show financials
-    msft.financials
-    msft.quarterly_financials
-
-    # show major holders
-    msft.major_holders
-
-    # show institutional holders
-    msft.institutional_holders
-
-    # show balance sheet
-    msft.balance_sheet
-    msft.quarterly_balance_sheet
-
-    # show cashflow
-    msft.cashflow
-    msft.quarterly_cashflow
-
-    # show earnings
-    msft.earnings
-    msft.quarterly_earnings
-
-    # show sustainability
-    msft.sustainability
-
-    # show analysts recommendations
-    msft.recommendations
-
-    # show next event (earnings, etc)
-    msft.calendar
-
-    # show ISIN code - *experimental*
-    # ISIN = International Securities Identification Number
-    msft.isin
-
-    # show options expirations
-    msft.options
-
-    # show news
-    msft.news
-
-    # get option chain for specific expiration
-    opt = msft.option_chain('YYYY-MM-DD')
-    # data available via: opt.calls, opt.puts
-
-If you want to use a proxy server for downloading data, use:
-
-.. code:: python
-
-    import yfinance as yf
-
-    msft = yf.Ticker("MSFT")
-
-    msft.history(..., proxy="PROXY_SERVER")
-    msft.get_actions(proxy="PROXY_SERVER")
-    msft.get_dividends(proxy="PROXY_SERVER")
-    msft.get_splits(proxy="PROXY_SERVER")
-    msft.get_balance_sheet(proxy="PROXY_SERVER")
-    msft.get_cashflow(proxy="PROXY_SERVER")
-    msft.option_chain(..., proxy="PROXY_SERVER")
-    ...
-
-To use a custom ``requests`` session (for example to cache calls to the API
-or customize the ``User-agent`` header), pass a ``session=`` argument to the
-Ticker constructor.
-
-.. code:: python
-
-    import requests_cache
-    session = requests_cache.CachedSession('yfinance.cache')
-    session.headers['User-agent'] = 'my-program/1.0'
-    ticker = yf.Ticker('msft aapl goog', session=session)
-    # The scraped response will be stored in the cache
-    ticker.actions
-
-To initialize multiple ``Ticker`` objects, use
-
-.. code:: python
-
-    import yfinance as yf
-
-    tickers = yf.Tickers('msft aapl goog')
-    # ^ returns a named tuple of Ticker objects
-
-    # access each ticker using (example)
-    tickers.tickers.MSFT.info
-    tickers.tickers.AAPL.history(period="1mo")
-    tickers.tickers.GOOG.actions
-
-
-Fetching data for multiple tickers
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-.. code:: python
-
-    import yfinance as yf
-    data = yf.download("SPY AAPL", start="2017-01-01", end="2017-04-30")
-
-
-I've also added some options to make life easier :)
-
-.. code:: python
-
-    data = yf.download(  # or pdr.get_data_yahoo(...
-            # tickers list or string as well
-            tickers = "SPY AAPL MSFT",
-
-            # use "period" instead of start/end
-            # valid periods: 1d,5d,1mo,3mo,6mo,1y,2y,5y,10y,ytd,max
-            # (optional, default is '1mo')
-            period = "ytd",
-
-            # fetch data by interval (including intraday if period < 60 days)
-            # valid intervals: 1m,2m,5m,15m,30m,60m,90m,1h,1d,5d,1wk,1mo,3mo
-            # (optional, default is '1d')
-            interval = "1m",
-
-            # group by ticker (to access via data['SPY'])
-            # (optional, default is 'column')
-            group_by = 'ticker',
-
-            # adjust all OHLC automatically
-            # (optional, default is False)
-            auto_adjust = True,
-
-            # download pre/post regular market hours data
-            # (optional, default is False)
-            prepost = True,
-
-            # use threads for mass downloading? (True/False/Integer)
-            # (optional, default is True)
-            threads = True,
-
-            # proxy URL scheme use use when downloading?
-            # (optional, default is None)
-            proxy = None
-        )
-
-
-Managing Multi-Level Columns
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-The following answer on Stack Overflow is for `How to deal with multi-level column names downloaded with yfinance? <https://stackoverflow.com/questions/63107801>`_
-
-* ``yfinance`` returns a ``pandas.DataFrame`` with multi-level column names, with a level for the ticker and a level for the stock price data
-
-  * The answer discusses:
-
-    * How to correctly read the the multi-level columns after saving the dataframe to a csv with ``pandas.DataFrame.to_csv``
-    * 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()``.
-
-.. code:: 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")
-
-
-Installation
-------------
-
-Install ``yfinance`` using ``pip``:
-
-.. code:: bash
-
-    $ pip install yfinance --upgrade --no-cache-dir
-
-
-To install ``yfinance`` using ``conda``, see `this <https://anaconda.org/ranaroussi/yfinance>`_.
-
-Requirements
-------------
-
-* `Python <https://www.python.org>`_ >= 2.7, 3.4+
-* `Pandas <https://github.com/pydata/pandas>`_ (tested to work with >=0.23.1)
-* `Numpy <http://www.numpy.org>`_ >= 1.11.1
-* `requests <http://docs.python-requests.org/en/master/>`_ >= 2.14.2
-* `lxml <https://pypi.org/project/lxml/>`_ >= 4.5.1
-
-Optional (if you want to use ``pandas_datareader``)
----------------------------------------------------
-
-* `pandas_datareader <https://github.com/pydata/pandas-datareader>`_ >= 0.4.0
-
-Legal Stuff
-------------
-
-**yfinance** is distributed under the **Apache Software License**. See the `LICENSE.txt <./LICENSE.txt>`_ file in the release for details.
-
-
-P.S.
-------------
-
-Please drop me an note with any feedback you have.
-
-**Ran Aroussi**

docs/Ticker.md

@@ -1,3 +0,0 @@
-# Ticker
-
-::: yfinance.ticker.Ticker

docs/TickerBase.md

@@ -1,3 +0,0 @@
-# TickerBase Reference
-
-::: yfinance.base.TickerBase

docs/Tickers.md

@@ -1,3 +0,0 @@
-# Tickers Reference
-
-::: yfinance.tickers.Tickers

docs/index.md

@@ -1,18 +0,0 @@
-Yahoo! Finance market data downloader
-=====================================
-
-Ever since [Yahoo! finance](https://finance.yahoo.com) decommissioned
-their historical data API, many programs that relied on it to stop
-working.
-
-**yfinance** aims to solve this problem by offering a reliable,
-threaded, and Pythonic way to download historical market data from
-Yahoo! finance.
-
-NOTE
-----
-
-The library was originally named `fix-yahoo-finance`, but I've since
-renamed it to `yfinance` as I no longer consider it a mere "fix". For
-reasons of backward-compatibility, `fix-yahoo-finance` now import and
-uses `yfinance`, but you should install and use `yfinance` directly.

docs/installation.md

@@ -1,28 +0,0 @@
-Installation
-============
-
-Install `yfinance` using `pip`:
-
-``` {.sourceCode .bash}
-$ pip install yfinance --upgrade --no-cache-dir
-```
-
-Install `yfinance` using `conda`:
-
-``` {.sourceCode .bash}
-$ conda install -c ranaroussi yfinance
-```
-
-### Requirements
-
--   [Python](https://www.python.org) \>= 2.7, 3.4+
--   [Pandas](https://github.com/pydata/pandas) (tested to work with
-    \>=0.23.1)
--   [Numpy](http://www.numpy.org) \>= 1.11.1
--   [requests](http://docs.python-requests.org/en/master/) \>= 2.14.2
--   [lxml](https://pypi.org/project/lxml/) \>= 4.5.1
-
-### Optional (if you want to use `pandas_datareader`)
-
--   [pandas\_datareader](https://github.com/pydata/pandas-datareader)
-    \>= 0.4.0

docs/multi.md

@@ -1,3 +0,0 @@
-# multi.py Reference
-
-::: yfinance.multi

docs/quickstart.md

@@ -1,201 +0,0 @@
-Quick Start
-===========
-
-The Ticker module
------------------
-
-The `Ticker` module, which allows you to access ticker data in a more
-Pythonic way:
-
-Note: yahoo finance datetimes are received as UTC.
-
-``` {.sourceCode .python}
-import yfinance as yf
-
-msft = yf.Ticker("MSFT")
-
-# get stock info
-msft.info
-
-# get historical market data
-hist = msft.history(period="max")
-
-# show actions (dividends, splits)
-msft.actions
-
-# show dividends
-msft.dividends
-
-# show splits
-msft.splits
-
-# show financials
-msft.financials
-msft.quarterly_financials
-
-# show major holders
-msft.major_holders
-
-# show institutional holders
-msft.institutional_holders
-
-# show balance sheet
-msft.balance_sheet
-msft.quarterly_balance_sheet
-
-# show cashflow
-msft.cashflow
-msft.quarterly_cashflow
-
-# show earnings
-msft.earnings
-msft.quarterly_earnings
-
-# show sustainability
-msft.sustainability
-
-# show analysts recommendations
-msft.recommendations
-
-# show next event (earnings, etc)
-msft.calendar
-
-# show ISIN code - *experimental*
-# ISIN = International Securities Identification Number
-msft.isin
-
-# show options expirations
-msft.options
-
-# show news
-msft.news
-
-# get option chain for specific expiration
-opt = msft.option_chain('YYYY-MM-DD')
-# data available via: opt.calls, opt.puts
-```
-
-If you want to use a proxy server for downloading data, use:
-
-``` {.sourceCode .python}
-import yfinance as yf
-
-msft = yf.Ticker("MSFT")
-
-msft.history(..., proxy="PROXY_SERVER")
-msft.get_actions(proxy="PROXY_SERVER")
-msft.get_dividends(proxy="PROXY_SERVER")
-msft.get_splits(proxy="PROXY_SERVER")
-msft.get_balance_sheet(proxy="PROXY_SERVER")
-msft.get_cashflow(proxy="PROXY_SERVER")
-msft.option_chain(..., proxy="PROXY_SERVER")
-...
-```
-
-To use a custom `requests` session (for example to cache calls to the
-API or customize the `User-agent` header), pass a `session=` argument to
-the Ticker constructor.
-
-``` {.sourceCode .python}
-import requests_cache
-session = requests_cache.CachedSession('yfinance.cache')
-session.headers['User-agent'] = 'my-program/1.0'
-ticker = yf.Ticker('msft aapl goog', session=session)
-# The scraped response will be stored in the cache
-ticker.actions
-```
-
-To initialize multiple `Ticker` objects, use
-
-``` {.sourceCode .python}
-import yfinance as yf
-
-tickers = yf.Tickers('msft aapl goog')
-# ^ returns a named tuple of Ticker objects
-
-# access each ticker using (example)
-tickers.tickers.MSFT.info
-tickers.tickers.AAPL.history(period="1mo")
-tickers.tickers.GOOG.actions
-```
-
-Fetching data for multiple tickers
-----------------------------------
-
-``` {.sourceCode .python}
-import yfinance as yf
-data = yf.download("SPY AAPL", start="2017-01-01", end="2017-04-30")
-```
-
-I've also added some options to make life easier :)
-
-``` {.sourceCode .python}
-data = yf.download(  # or pdr.get_data_yahoo(...
-        # tickers list or string as well
-        tickers = "SPY AAPL MSFT",
-
-        # use "period" instead of start/end
-        # valid periods: 1d,5d,1mo,3mo,6mo,1y,2y,5y,10y,ytd,max
-        # (optional, default is '1mo')
-        period = "ytd",
-
-        # fetch data by interval (including intraday if period < 60 days)
-        # valid intervals: 1m,2m,5m,15m,30m,60m,90m,1h,1d,5d,1wk,1mo,3mo
-        # (optional, default is '1d')
-        interval = "1m",
-
-        # group by ticker (to access via data['SPY'])
-        # (optional, default is 'column')
-        group_by = 'ticker',
-
-        # adjust all OHLC automatically
-        # (optional, default is False)
-        auto_adjust = True,
-
-        # download pre/post regular market hours data
-        # (optional, default is False)
-        prepost = True,
-
-        # use threads for mass downloading? (True/False/Integer)
-        # (optional, default is True)
-        threads = True,
-
-        # proxy URL scheme use use when downloading?
-        # (optional, default is None)
-        proxy = None
-    )
-```
-
-Managing Multi-Level Columns
-----------------------------
-
-The following answer on Stack Overflow is for [How to deal with
-multi-level column names downloaded with
-yfinance?](https://stackoverflow.com/questions/63107801)
-
--   `yfinance` returns a `pandas.DataFrame` with multi-level column
-    names, with a level for the ticker and a level for the stock price
-    data
-    -   The answer discusses:
-        -   How to correctly read the the multi-level columns after
-            saving the dataframe to a csv with `pandas.DataFrame.to_csv`
-        -   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()`.
-
-``` {.sourceCode .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")
-```

docs/utils.md

@@ -1,3 +0,0 @@
-# utils.py Reference
-
-::: yfinance.utils

meta.yaml

@@ -21,6 +21,7 @@ requirements:
     - requests >=2.21
     - multitasking >=0.0.7
     - lxml >=4.5.1
+    - appdirs >= 1.4.4
     - pip
     - python
 
@@ -30,6 +31,7 @@ requirements:
     - requests >=2.21
     - multitasking >=0.0.7
     - lxml >=4.5.1
+    - appdirs >= 1.4.4
     - python
 
 test:

requirements.txt

@@ -1,5 +1,6 @@
 pandas>=0.24.0
 numpy>=1.16.5
-requests>=2.21
+requests>=2.26
 multitasking>=0.0.7
 lxml>=4.5.1
+appdirs>=1.4.4

setup.py

@@ -1,10 +1,10 @@
 #!/usr/bin/env python
 # -*- coding: UTF-8 -*-
 #
-# Yahoo! Finance market data downloader (+fix for Pandas Datareader)
+# yfinance - market data downloader
 # https://github.com/ranaroussi/yfinance
 
-"""Yahoo! Finance market data downloader (+fix for Pandas Datareader)"""
+"""yfinance - market data downloader"""
 
 from setuptools import setup, find_packages
 # from codecs import open
@@ -22,14 +22,15 @@ with open("yfinance/version.py") as f:
 here = path.abspath(path.dirname(__file__))
 
 # Get the long description from the README file
-with io.open(path.join(here, 'README.rst'), encoding='utf-8') as f:
+with io.open(path.join(here, 'README.md'), encoding='utf-8') as f:
     long_description = f.read()
 
 setup(
     name='yfinance',
     version=version,
-    description='Yahoo! Finance market data downloader',
+    description='Download market data from Yahoo! Finance API',
     long_description=long_description,
+    long_description_content_type='text/markdown',
     url='https://github.com/ranaroussi/yfinance',
     author='Ran Aroussi',
     author_email='ran@aroussi.com',
@@ -52,7 +53,7 @@ setup(
         'Programming Language :: Python :: 2.7',
         'Programming Language :: Python :: 3.4',
         'Programming Language :: Python :: 3.5',
-        'Programming Language :: Python :: 3.6',
+        # 'Programming Language :: Python :: 3.6',
         'Programming Language :: Python :: 3.7',
         'Programming Language :: Python :: 3.8',
         'Programming Language :: Python :: 3.9',
@@ -60,12 +61,18 @@ setup(
     platforms=['any'],
     keywords='pandas, yahoo finance, pandas datareader',
     packages=find_packages(exclude=['contrib', 'docs', 'tests', 'examples']),
-    install_requires=['pandas>=0.24', 'numpy>=1.15',
-                      'requests>=2.20', 'multitasking>=0.0.7',
-                      'lxml>=4.5.1'],
+    install_requires=['pandas>=0.24.0', 'numpy>=1.15',
+                      'requests>=2.26', 'multitasking>=0.0.7',
+                      'lxml>=4.5.1', 'appdirs>=1.4.4'],
     entry_points={
         'console_scripts': [
             'sample=sample:main',
         ],
     },
 )
+
+print("""
+NOTE: yfinance is not affiliated, endorsed, or vetted by Yahoo, Inc.
+
+You should refer to Yahoo!'s terms of use for details on your rights
+to use the actual data downloaded.""")

test_yfinance.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python
 # -*- coding: UTF-8 -*-
 #
-# Yahoo! Finance market data downloader (+fix for Pandas Datareader)
+# yfinance - market data downloader
 # https://github.com/ranaroussi/yfinance
 
 """
@@ -25,7 +25,8 @@ class TestTicker(unittest.TestCase):
         for ticker in tickers:
             # always should have info and history for valid symbols
             assert(ticker.info is not None and ticker.info != {})
-            assert(ticker.history(period="max").empty is False)
+            history = ticker.history(period="max")
+            assert(history.empty is False and history is not None)
 
     def test_attributes(self):
         for ticker in tickers:
@@ -50,6 +51,9 @@ class TestTicker(unittest.TestCase):
             ticker.sustainability
             ticker.options
             ticker.news
+            ticker.shares
+            ticker.earnings_history
+            ticker.earnings_dates
 
     def test_holders(self):
         for ticker in tickers:

yfinance/__init__.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
 #
-# Yahoo! Finance market data downloader (+fix for Pandas Datareader)
+# yfinance - market data downloader
 # https://github.com/ranaroussi/yfinance
 #
 # Copyright 2017-2019 Ran Aroussi

yfinance/base.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
 #
-# Yahoo! Finance market data downloader (+fix for Pandas Datareader)
+# yfinance - market data downloader
 # https://github.com/ranaroussi/yfinance
 #
 # Copyright 2017-2019 Ran Aroussi
@@ -23,6 +23,7 @@ from __future__ import print_function
 
 import time as _time
 import datetime as _datetime
+import pytz as _tz
 import requests as _requests
 import pandas as _pd
 import numpy as _np
@@ -35,7 +36,7 @@ except ImportError:
 
 from . import utils
 
-# import json as _json
+import json as _json
 # import re as _re
 # import sys as _sys
 
@@ -43,6 +44,8 @@ from . import shared
 
 _BASE_URL_ = 'https://query2.finance.yahoo.com'
 _SCRAPE_URL_ = 'https://finance.yahoo.com/quote'
+_ROOT_URL_ = 'https://finance.yahoo.com'
+
 
 class TickerBase():
     def __init__(self, ticker, session=None):
@@ -51,6 +54,7 @@ class TickerBase():
         self._history = None
         self._base_url = _BASE_URL_
         self._scrape_url = _SCRAPE_URL_
+        self._tz = None
 
         self._fundamentals = False
         self._info = None
@@ -62,22 +66,17 @@ class TickerBase():
         self._mutualfund_holders = None
         self._isin = None
         self._news = []
+        self._shares = None
 
         self._calendar = None
         self._expirations = {}
+        self._earnings_dates = None
+        self._earnings_history = None
 
-        self._earnings = {
-            "yearly": utils.empty_df(),
-            "quarterly": utils.empty_df()}
-        self._financials = {
-            "yearly": utils.empty_df(),
-            "quarterly": utils.empty_df()}
-        self._balancesheet = {
-            "yearly": utils.empty_df(),
-            "quarterly": utils.empty_df()}
-        self._cashflow = {
-            "yearly": utils.empty_df(),
-            "quarterly": utils.empty_df()}
+        self._earnings = None
+        self._financials = None
+        self._balancesheet = None
+        self._cashflow = None
 
         # accept isin as ticker
         if utils.is_isin(self.ticker):
@@ -101,8 +100,8 @@ class TickerBase():
 
     def history(self, period="1mo", interval="1d",
                 start=None, end=None, prepost=False, actions=True,
-                auto_adjust=True, back_adjust=False,
-                proxy=None, rounding=False, tz=None, timeout=None, **kwargs):
+                auto_adjust=True, back_adjust=False, keepna=False,
+                proxy=None, rounding=False, timeout=None, **kwargs):
         """
         :Parameters:
             period : str
@@ -124,14 +123,14 @@ class TickerBase():
                 Adjust all OHLC automatically? Default is True
             back_adjust: bool
                 Back-adjusted data to mimic true historical prices
+            keepna: bool
+                Keep NaN rows returned by Yahoo?
+                Default is False
             proxy: str
                 Optional. Proxy server URL scheme. Default is None
             rounding: bool
                 Round values to 2 decimal places?
                 Optional. Default is False = precision suggested by Yahoo!
-            tz: str
-                Optional timezone locale for dates.
-                (default data is returned as non-localized dates)
             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)
@@ -142,21 +141,38 @@ class TickerBase():
                     error message printing to console.
         """
 
+        # Work with errors
+        debug_mode = True
+        if "debug" in kwargs and isinstance(kwargs["debug"], bool):
+            debug_mode = kwargs["debug"]
+
+        err_msg = "No data found for this date range, symbol may be delisted"
+
         if start or period is None or period.lower() == "max":
-            if start is None:
-                start = -631159200
-            elif isinstance(start, _datetime.datetime):
-                start = int(_time.mktime(start.timetuple()))
-            else:
-                start = int(_time.mktime(
-                    _time.strptime(str(start), '%Y-%m-%d')))
+            # Check can get TZ. Fail => probably delisted
+            try:
+                tz = self._get_ticker_tz()
+            except KeyError as e:
+                if "exchangeTimezoneName" in str(e):
+                    shared._DFS[self.ticker] = utils.empty_df()
+                    shared._ERRORS[self.ticker] = err_msg
+                    if "many" not in kwargs and debug_mode:
+                        print('- %s: %s' % (self.ticker, err_msg))
+                    return utils.empty_df()
+                else:
+                    raise
+
             if end is None:
                 end = int(_time.time())
-            elif isinstance(end, _datetime.datetime):
-                end = int(_time.mktime(end.timetuple()))
             else:
-                end = int(_time.mktime(_time.strptime(str(end), '%Y-%m-%d')))
-
+                end = utils._parse_user_dt(end, tz)
+            if start is None:
+                if interval == "1m":
+                    start = end - 604800  # Subtract 7 days
+                else:
+                    start = -631159200
+            else:
+                start = utils._parse_user_dt(start, tz)
             params = {"period1": start, "period2": end}
         else:
             period = period.lower()
@@ -180,25 +196,32 @@ class TickerBase():
         url = "{}/v8/finance/chart/{}".format(self._base_url, self.ticker)
 
         session = self.session or _requests
-        data = session.get(
-            url=url,
-            params=params,
-            proxies=proxy,
-            headers=utils.user_agent_headers,
-            timeout=timeout
-        )
-        if "Will be right back" in data.text:
-            raise RuntimeError("*** YAHOO! FINANCE IS CURRENTLY DOWN! ***\n"
-                               "Our engineers are working quickly to resolve "
-                               "the issue. Thank you for your patience.")
-        data = data.json()
+        data = None
 
-        # Work with errors
-        debug_mode = True
-        if "debug" in kwargs and isinstance(kwargs["debug"], bool):
-            debug_mode = kwargs["debug"]
+        try:
+            data = session.get(
+                url=url,
+                params=params,
+                proxies=proxy,
+                headers=utils.user_agent_headers,
+                timeout=timeout
+            )
+            if "Will be right back" in data.text or data is None:
+                raise RuntimeError("*** YAHOO! FINANCE IS CURRENTLY DOWN! ***\n"
+                                   "Our engineers are working quickly to resolve "
+                                   "the issue. Thank you for your patience.")
+
+            data = data.json()
+        except Exception:
+            pass
+
+        if data is None or not type(data) is dict or 'status_code' in data.keys():
+            shared._DFS[self.ticker] = utils.empty_df()
+            shared._ERRORS[self.ticker] = err_msg
+            if "many" not in kwargs and debug_mode:
+                print('- %s: %s' % (self.ticker, err_msg))
+            return utils.empty_df()
 
-        err_msg = "No data found for this date range, symbol may be delisted"
         if "chart" in data and data["chart"]["error"]:
             err_msg = data["chart"]["error"]["description"]
             shared._DFS[self.ticker] = utils.empty_df()
@@ -217,7 +240,12 @@ class TickerBase():
 
         # parse quotes
         try:
-            quotes = utils.parse_quotes(data["chart"]["result"][0], tz)
+            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))
+                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
@@ -265,10 +293,13 @@ class TickerBase():
                 "chart"]["result"][0]["meta"]["priceHint"])
         quotes['Volume'] = quotes['Volume'].fillna(0).astype(_np.int64)
 
-        quotes.dropna(inplace=True)
+        if not keepna:
+            quotes.dropna(inplace=True)
 
         # actions
-        dividends, splits = utils.parse_actions(data["chart"]["result"][0], tz)
+        dividends, splits = utils.parse_actions(data["chart"]["result"][0])
+
+        tz_exchange = data["chart"]["result"][0]["meta"]["exchangeTimezoneName"]
 
         # combine
         df = _pd.concat([quotes, dividends, splits], axis=1, sort=True)
@@ -276,17 +307,16 @@ class TickerBase():
         df["Stock Splits"].fillna(0, inplace=True)
 
         # index eod/intraday
-        df.index = df.index.tz_localize("UTC").tz_convert(
-            data["chart"]["result"][0]["meta"]["exchangeTimezoneName"])
+        df.index = df.index.tz_localize("UTC").tz_convert(tz_exchange)
 
+        df = utils.fix_Yahoo_dst_issue(df, params["interval"])
+            
         if params["interval"][-1] == "m":
             df.index.name = "Datetime"
         elif params["interval"] == "1h":
             pass
         else:
-            df.index = _pd.to_datetime(df.index.date)
-            if tz is not None:
-                df.index = df.index.tz_localize(tz)
+            df.index = _pd.to_datetime(df.index.date).tz_localize(tz_exchange)
             df.index.name = "Date"
 
         # duplicates and missing rows cleanup
@@ -302,32 +332,30 @@ class TickerBase():
 
     # ------------------------
 
-    def _get_fundamentals(self, kind=None, proxy=None):
-        def cleanup(data):
-            df = _pd.DataFrame(data).drop(columns=['maxAge'])
-            for col in df.columns:
-                df[col] = _np.where(
-                    df[col].astype(str) == '-', _np.nan, df[col])
+    def _get_ticker_tz(self):
+        if not self._tz is None:
+            return self._tz
 
-            df.set_index('endDate', inplace=True)
-            try:
-                df.index = _pd.to_datetime(df.index, unit='s')
-            except ValueError:
-                df.index = _pd.to_datetime(df.index)
-            df = df.T
-            df.columns.name = ''
-            df.index.name = 'Breakdown'
+        tkr_tz = utils.cache_lookup_tkr_tz(self.ticker)
+        if tkr_tz is None:
+            tkr_tz = self.info["exchangeTimezoneName"]
+            # info fetch is relatively slow so cache timezone
+            utils.cache_store_tkr_tz(self.ticker, tkr_tz)
 
-            df.index = utils.camel2title(df.index)
-            return df
+        self._tz = tkr_tz
+        return tkr_tz
 
+    def _get_info(self, proxy=None):
         # setup proxy in requests format
         if proxy is not None:
             if isinstance(proxy, dict) and "https" in proxy:
                 proxy = proxy["https"]
             proxy = {"https": proxy}
 
-        if self._fundamentals:
+        if (self._info is None) or (self._sustainability is None) or (self._recommendations is None):
+            ## Need to fetch
+            pass
+        else:
             return
 
         ticker_url = "{}/{}".format(self._scrape_url, self.ticker)
@@ -335,42 +363,6 @@ class TickerBase():
         # get info and sustainability
         data = utils.get_json(ticker_url, proxy, self.session)
 
-        # holders
-        try:
-            resp = utils.get_html(ticker_url + '/holders', proxy, self.session)
-            holders = _pd.read_html(resp)
-        except Exception:
-            holders = []
-
-        if len(holders) >= 3:
-            self._major_holders = holders[0]
-            self._institutional_holders = holders[1]
-            self._mutualfund_holders = holders[2]
-        elif len(holders) >= 2:
-            self._major_holders = holders[0]
-            self._institutional_holders = holders[1]
-        elif len(holders) >= 1:
-            self._major_holders = holders[0]
-
-        # self._major_holders = holders[0]
-        # self._institutional_holders = holders[1]
-
-        if self._institutional_holders is not None:
-            if 'Date Reported' in self._institutional_holders:
-                self._institutional_holders['Date Reported'] = _pd.to_datetime(
-                    self._institutional_holders['Date Reported'])
-            if '% Out' in self._institutional_holders:
-                self._institutional_holders['% Out'] = self._institutional_holders[
-                    '% Out'].str.replace('%', '').astype(float) / 100
-
-        if self._mutualfund_holders is not None:
-            if 'Date Reported' in self._mutualfund_holders:
-                self._mutualfund_holders['Date Reported'] = _pd.to_datetime(
-                    self._mutualfund_holders['Date Reported'])
-            if '% Out' in self._mutualfund_holders:
-                self._mutualfund_holders['% Out'] = self._mutualfund_holders[
-                    '% Out'].str.replace('%', '').astype(float) / 100
-
         # sustainability
         d = {}
         try:
@@ -401,7 +393,7 @@ class TickerBase():
         except Exception:
             pass
 
-       # For ETFs, provide this valuable data: the top holdings of the ETF
+        # For ETFs, provide this valuable data: the top holdings of the ETF
         try:
             if 'topHoldings' in data:
                 self._info.update(data['topHoldings'])
@@ -462,10 +454,85 @@ class TickerBase():
         except Exception:
             pass
 
+    def _get_fundamentals(self, proxy=None):
+        def cleanup(data):
+            df = _pd.DataFrame(data).drop(columns=['maxAge'])
+            for col in df.columns:
+                df[col] = _np.where(
+                    df[col].astype(str) == '-', _np.nan, df[col])
+
+            df.set_index('endDate', inplace=True)
+            try:
+                df.index = _pd.to_datetime(df.index, unit='s')
+            except ValueError:
+                df.index = _pd.to_datetime(df.index)
+            df = df.T
+            df.columns.name = ''
+            df.index.name = 'Breakdown'
+
+            # rename incorrect yahoo key
+            df.rename(index={'treasuryStock': 'Gains Losses Not Affecting Retained Earnings'}, inplace=True)
+
+            df.index = utils.camel2title(df.index)
+            return df
+
+        # setup proxy in requests format
+        if proxy is not None:
+            if isinstance(proxy, dict) and "https" in proxy:
+                proxy = proxy["https"]
+            proxy = {"https": proxy}
+
+        if self._fundamentals:
+            return
+
+        ticker_url = "{}/{}".format(self._scrape_url, self.ticker)
+
+        # holders
+        try:
+            resp = utils.get_html(ticker_url + '/holders', proxy, self.session)
+            holders = _pd.read_html(resp)
+        except Exception:
+            holders = []
+
+        if len(holders) >= 3:
+            self._major_holders = holders[0]
+            self._institutional_holders = holders[1]
+            self._mutualfund_holders = holders[2]
+        elif len(holders) >= 2:
+            self._major_holders = holders[0]
+            self._institutional_holders = holders[1]
+        elif len(holders) >= 1:
+            self._major_holders = holders[0]
+
+        # self._major_holders = holders[0]
+        # self._institutional_holders = holders[1]
+
+        if self._institutional_holders is not None:
+            if 'Date Reported' in self._institutional_holders:
+                self._institutional_holders['Date Reported'] = _pd.to_datetime(
+                    self._institutional_holders['Date Reported'])
+            if '% Out' in self._institutional_holders:
+                self._institutional_holders['% Out'] = self._institutional_holders[
+                    '% Out'].str.replace('%', '').astype(float) / 100
+
+        if self._mutualfund_holders is not None:
+            if 'Date Reported' in self._mutualfund_holders:
+                self._mutualfund_holders['Date Reported'] = _pd.to_datetime(
+                    self._mutualfund_holders['Date Reported'])
+            if '% Out' in self._mutualfund_holders:
+                self._mutualfund_holders['% Out'] = self._mutualfund_holders[
+                    '% Out'].str.replace('%', '').astype(float) / 100
+
+        self._get_info(proxy)
+
         # get fundamentals
         data = utils.get_json(ticker_url + '/financials', proxy, self.session)
 
         # generic patterns
+        self._earnings = {"yearly": utils.empty_df(), "quarterly": utils.empty_df()}
+        self._cashflow = {"yearly": utils.empty_df(), "quarterly": utils.empty_df()}
+        self._balancesheet = {"yearly": utils.empty_df(), "quarterly": utils.empty_df()}
+        self._financials = {"yearly": utils.empty_df(), "quarterly": utils.empty_df()}
         for key in (
             (self._cashflow, 'cashflowStatement', 'cashflowStatements'),
             (self._balancesheet, 'balanceSheet', 'balanceSheetStatements'),
@@ -503,6 +570,21 @@ class TickerBase():
             except Exception:
                 pass
 
+        # shares outstanding
+        try:
+            # keep only years with non None data
+            available_shares = [shares_data for shares_data in data['annualBasicAverageShares'] if shares_data]
+            shares = _pd.DataFrame(available_shares)
+            shares['Year'] = shares['asOfDate'].agg(lambda x: int(x[:4]))
+            shares.set_index('Year', inplace=True)
+            shares.drop(columns=['dataId', 'asOfDate',
+                        'periodType', 'currencyCode'], inplace=True)
+            shares.rename(
+                columns={'reportedValue': "BasicShares"}, inplace=True)
+            self._shares = shares
+        except Exception:
+            pass
+
         # Analysis
         data = utils.get_json(ticker_url + '/analysis', proxy, self.session)
 
@@ -522,24 +604,68 @@ class TickerBase():
                         if isinstance(colval, dict):
                             dict_cols.append(colname)
                             for k, v in colval.items():
-                                new_colname = colname + ' ' + utils.camel2title([k])[0]
+                                new_colname = colname + ' ' + \
+                                    utils.camel2title([k])[0]
                                 analysis.loc[idx, new_colname] = v
 
-                self._analysis = analysis[[c for c in analysis.columns if c not in dict_cols]]
+                self._analysis = analysis[[
+                    c for c in analysis.columns if c not in dict_cols]]
             except Exception:
                 pass
 
+        # Complementary key-statistics (currently fetching the important trailingPegRatio which is the value shown in the website)
+        res = {}
+        try:
+            my_headers = {'user-agent': 'curl/7.55.1', 'accept': 'application/json', 'content-type': 'application/json',
+                          'referer': 'https://finance.yahoo.com/', 'cache-control': 'no-cache', 'connection': 'close'}
+            p = _re.compile(r'root\.App\.main = (.*);')
+            r = _requests.session().get('https://finance.yahoo.com/quote/{}/key-statistics?p={}'.format(self.ticker,
+                                                                                                        self.ticker), headers=my_headers)
+            q_results = {}
+            my_qs_keys = ['pegRatio']  # QuoteSummaryStore
+            # , 'quarterlyPegRatio']  # QuoteTimeSeriesStore
+            my_ts_keys = ['trailingPegRatio']
+
+            # Complementary key-statistics
+            data = _json.loads(p.findall(r.text)[0])
+            key_stats = data['context']['dispatcher']['stores']['QuoteTimeSeriesStore']
+            q_results.setdefault(self.ticker, [])
+            for i in my_ts_keys:
+                # j=0
+                try:
+                    # res = {i: key_stats['timeSeries'][i][1]['reportedValue']['raw']}
+                    # We need to loop over multiple items, if they exist: 0,1,2,..
+                    zzz = key_stats['timeSeries'][i]
+                    for j in range(len(zzz)):
+                        if key_stats['timeSeries'][i][j]:
+                            res = {i: key_stats['timeSeries']
+                                   [i][j]['reportedValue']['raw']}
+                            q_results[self.ticker].append(res)
+
+                # print(res)
+                # q_results[ticker].append(res)
+                except:
+                    q_results[ticker].append({i: np.nan})
+
+            res = {'Company': ticker}
+            q_results[ticker].append(res)
+        except Exception:
+            pass
+
+        if 'trailingPegRatio' in res:
+            self._info['trailingPegRatio'] = res['trailingPegRatio']
+
         self._fundamentals = True
 
     def get_recommendations(self, proxy=None, as_dict=False, *args, **kwargs):
-        self._get_fundamentals(proxy=proxy)
+        self._get_info(proxy)
         data = self._recommendations
         if as_dict:
             return data.to_dict()
         return data
 
     def get_calendar(self, proxy=None, as_dict=False, *args, **kwargs):
-        self._get_fundamentals(proxy=proxy)
+        self._get_info(proxy)
         data = self._calendar
         if as_dict:
             return data.to_dict()
@@ -569,14 +695,14 @@ class TickerBase():
             return data
 
     def get_info(self, proxy=None, as_dict=False, *args, **kwargs):
-        self._get_fundamentals(proxy=proxy)
+        self._get_info(proxy)
         data = self._info
         if as_dict:
             return data.to_dict()
         return data
 
     def get_sustainability(self, proxy=None, as_dict=False, *args, **kwargs):
-        self._get_fundamentals(proxy=proxy)
+        self._get_info(proxy)
         data = self._sustainability
         if as_dict:
             return data.to_dict()
@@ -646,6 +772,13 @@ class TickerBase():
             return actions[actions != 0].dropna(how='all').fillna(0)
         return []
 
+    def get_shares(self, proxy=None, as_dict=False, *args, **kwargs):
+        self._get_fundamentals(proxy=proxy)
+        data = self._shares
+        if as_dict:
+            return data.to_dict()
+        return data
+
     def get_isin(self, proxy=None):
         # *** experimental ***
         if self._isin is not None:
@@ -719,3 +852,121 @@ class TickerBase():
         # parse news
         self._news = data.get("news", [])
         return self._news
+
+    def get_earnings_dates(self, proxy=None):
+        if self._earnings_dates is not None:
+            return self._earnings_dates
+
+        # setup proxy in requests format
+        if proxy is not None:
+            if isinstance(proxy, dict) and "https" in proxy:
+                proxy = proxy["https"]
+            proxy = {"https": proxy}
+
+        page_size = 100  # YF caps at 100, don't go higher
+        page_offset = 0
+        dates = None
+        while True:
+            url = "{}/calendar/earnings?symbol={}&offset={}&size={}".format(
+                _ROOT_URL_, self.ticker, page_offset, page_size)
+
+            session = self.session or _requests
+            data = session.get(
+                url=url,
+                proxies=proxy,
+                headers=utils.user_agent_headers
+            ).text
+
+            if "Will be right back" in data:
+                raise RuntimeError("*** YAHOO! FINANCE IS CURRENTLY DOWN! ***\n"
+                                   "Our engineers are working quickly to resolve "
+                                   "the issue. Thank you for your patience.")
+
+            try:
+                data = _pd.read_html(data)[0]
+            except ValueError:
+                if page_offset == 0:
+                    # Should not fail on first page
+                    if "Showing Earnings for:" in data:
+                        # Actually YF was successful, problem is company doesn't have earnings history
+                        dates = utils.empty_earnings_dates_df()
+                break
+
+            if dates is None:
+                dates = data
+            else:
+                dates = _pd.concat([dates, data], axis=0)
+            page_offset += page_size
+
+        if dates is None:
+            raise Exception("No data found, symbol may be delisted")
+        dates = dates.reset_index(drop=True)
+
+        # Drop redundant columns
+        dates = dates.drop(["Symbol", "Company"], axis=1)
+
+        # Convert types
+        for cn in ["EPS Estimate", "Reported EPS", "Surprise(%)"]:
+            dates.loc[dates[cn] == '-', cn] = "NaN"
+            dates[cn] = dates[cn].astype(float)
+
+        # Convert % to range 0->1:
+        dates["Surprise(%)"] *= 0.01
+
+        # Parse earnings date string
+        cn = "Earnings Date"
+        # - remove AM/PM and timezone from date string
+        tzinfo = dates[cn].str.extract('([AP]M[a-zA-Z]*)$')
+        dates[cn] = dates[cn].replace(' [AP]M[a-zA-Z]*$', '', regex=True)
+        # - split AM/PM from timezone
+        tzinfo = tzinfo[0].str.extract('([AP]M)([a-zA-Z]*)', expand=True)
+        tzinfo.columns = ["AM/PM", "TZ"]
+        # - combine and parse
+        dates[cn] = dates[cn] + ' ' + tzinfo["AM/PM"]
+        dates[cn] = _pd.to_datetime(dates[cn], format="%b %d, %Y, %I %p")
+        # - instead of attempting decoding of ambiguous timezone abbreviation, just use 'info':
+        dates[cn] = dates[cn].dt.tz_localize(
+            tz=self.info["exchangeTimezoneName"])
+
+        dates = dates.set_index("Earnings Date")
+
+        self._earnings_dates = dates
+
+        return dates
+
+    def get_earnings_history(self, proxy=None):
+        if self._earnings_history:
+            return self._earnings_history
+
+        # setup proxy in requests format
+        if proxy is not None:
+            if isinstance(proxy, dict) and "https" in proxy:
+                proxy = proxy["https"]
+            proxy = {"https": proxy}
+
+        url = "{}/calendar/earnings?symbol={}".format(_ROOT_URL_, self.ticker)
+        session = self.session or _requests
+        data = session.get(
+            url=url,
+            proxies=proxy,
+            headers=utils.user_agent_headers
+        ).text
+
+        if "Will be right back" in data:
+            raise RuntimeError("*** YAHOO! FINANCE IS CURRENTLY DOWN! ***\n"
+                               "Our engineers are working quickly to resolve "
+                               "the issue. Thank you for your patience.")
+
+        try:
+            # read_html returns a list of pandas Dataframes of all the tables in `data`
+            data = _pd.read_html(data)[0]
+            data.replace("-", _np.nan, inplace=True)
+
+            data['EPS Estimate'] = _pd.to_numeric(data['EPS Estimate'])
+            data['Reported EPS'] = _pd.to_numeric(data['Reported EPS'])
+            self._earnings_history = data
+        # if no tables are found a ValueError is thrown
+        except ValueError:
+            print("Could not find data for {}.".format(self.ticker))
+            return
+        return data

yfinance/multi.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
 #
-# Yahoo! Finance market data downloader (+fix for Pandas Datareader)
+# yfinance - market data downloader
 # https://github.com/ranaroussi/yfinance
 #
 # Copyright 2017-2019 Ran Aroussi
@@ -29,8 +29,8 @@ from . import Ticker, utils
 from . import shared
 
 
-def download(tickers, start=None, end=None, actions=False, threads=True,
-             group_by='column', auto_adjust=False, back_adjust=False,
+def download(tickers, start=None, end=None, actions=False, threads=True, ignore_tz=True, 
+             group_by='column', auto_adjust=False, back_adjust=False, keepna=False,
              progress=True, period="max", show_errors=True, interval="1d", prepost=False,
              proxy=None, rounding=False, timeout=None, **kwargs):
     """Download yahoo tickers
@@ -56,16 +56,22 @@ def download(tickers, start=None, end=None, actions=False, threads=True,
             Default is False
         auto_adjust: bool
             Adjust all OHLC automatically? Default is False
+        keepna: bool
+            Keep NaN rows returned by Yahoo?
+            Default is False
         actions: bool
             Download dividend + stock splits data. Default is False
         threads: bool / int
             How many threads to use for mass downloading. Default is True
+        ignore_tz: bool
+            When combining from different timezones, ignore that part of datetime.
+            Default is True
         proxy: str
             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 True
+            Optional. Doesn't print errors if False
         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)
@@ -105,7 +111,7 @@ def download(tickers, start=None, end=None, actions=False, threads=True,
             _download_one_threaded(ticker, period=period, interval=interval,
                                    start=start, end=end, prepost=prepost,
                                    actions=actions, auto_adjust=auto_adjust,
-                                   back_adjust=back_adjust,
+                                   back_adjust=back_adjust, keepna=keepna,
                                    progress=(progress and i > 0), proxy=proxy,
                                    rounding=rounding, timeout=timeout)
         while len(shared._DFS) < len(tickers):
@@ -117,7 +123,7 @@ def download(tickers, start=None, end=None, actions=False, threads=True,
             data = _download_one(ticker, period=period, interval=interval,
                                  start=start, end=end, prepost=prepost,
                                  actions=actions, auto_adjust=auto_adjust,
-                                 back_adjust=back_adjust, proxy=proxy,
+                                 back_adjust=back_adjust, keepna=keepna, proxy=proxy,
                                  rounding=rounding, timeout=timeout)
             shared._DFS[ticker.upper()] = data
             if progress:
@@ -137,12 +143,17 @@ def download(tickers, start=None, end=None, actions=False, threads=True,
         ticker = tickers[0]
         return shared._DFS[shared._ISINS.get(ticker, ticker)]
 
+    if ignore_tz:
+        for tkr in shared._DFS.keys():
+            if (shared._DFS[tkr] is not None) and (shared._DFS[tkr].shape[0]>0):
+                shared._DFS[tkr].index = shared._DFS[tkr].index.tz_localize(None)
+
     try:
-        data = _pd.concat(shared._DFS.values(), axis=1,
+        data = _pd.concat(shared._DFS.values(), axis=1, sort=True,
                           keys=shared._DFS.keys())
     except Exception:
         _realign_dfs()
-        data = _pd.concat(shared._DFS.values(), axis=1,
+        data = _pd.concat(shared._DFS.values(), axis=1, sort=True,
                           keys=shared._DFS.keys())
 
     # switch names back to isins if applicable
@@ -183,11 +194,11 @@ def _download_one_threaded(ticker, start=None, end=None,
                            auto_adjust=False, back_adjust=False,
                            actions=False, progress=True, period="max",
                            interval="1d", prepost=False, proxy=None,
-                           rounding=False, timeout=None):
+                           keepna=False, rounding=False, timeout=None):
 
     data = _download_one(ticker, start, end, auto_adjust, back_adjust,
                          actions, period, interval, prepost, proxy, rounding,
-                         timeout)
+                         keepna, timeout)
     shared._DFS[ticker.upper()] = data
     if progress:
         shared._PROGRESS_BAR.animate()
@@ -197,11 +208,11 @@ def _download_one(ticker, start=None, end=None,
                   auto_adjust=False, back_adjust=False,
                   actions=False, period="max", interval="1d",
                   prepost=False, proxy=None, rounding=False,
-                  timeout=None):
+                  keepna=False, timeout=None):
 
     return Ticker(ticker).history(period=period, interval=interval,
                                   start=start, end=end, prepost=prepost,
                                   actions=actions, auto_adjust=auto_adjust,
                                   back_adjust=back_adjust, proxy=proxy,
-                                  rounding=rounding, many=True,
+                                  rounding=rounding, keepna=keepna, many=True,
                                   timeout=timeout)

yfinance/shared.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
 #
-# Yahoo! Finance market data downloader (+fix for Pandas Datareader)
+# yfinance - market data downloader
 # https://github.com/ranaroussi/yfinance
 #
 # Copyright 2017-2019 Ran Aroussi

yfinance/ticker.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
 #
-# Yahoo! Finance market data downloader (+fix for Pandas Datareader)
+# yfinance - market data downloader
 # https://github.com/ranaroussi/yfinance
 #
 # Copyright 2017-2019 Ran Aroussi
@@ -84,9 +84,9 @@ class Ticker(TickerBase):
             'currency'])
 
         data['lastTradeDate'] = _pd.to_datetime(
-            data['lastTradeDate'], unit='s')
+            data['lastTradeDate'], unit='s', utc=True)
         if tz is not None:
-            data['lastTradeDate'] = data['lastTradeDate'].tz_localize(tz)
+            data['lastTradeDate'] = data['lastTradeDate'].dt.tz_convert(tz)
         return data
 
     def option_chain(self, date=None, proxy=None, tz=None):
@@ -138,6 +138,10 @@ class Ticker(TickerBase):
     def actions(self):
         return self.get_actions()
 
+    @property
+    def shares(self):
+        return self.get_shares()
+
     @property
     def info(self):
         return self.get_info()
@@ -207,3 +211,11 @@ class Ticker(TickerBase):
     @property
     def analysis(self):
         return self.get_analysis()
+
+    @property
+    def earnings_history(self):
+        return self.get_earnings_history()
+
+    @property
+    def earnings_dates(self):
+        return self.get_earnings_dates()

yfinance/tickers.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
 #
-# Yahoo! Finance market data downloader (+fix for Pandas Datareader)
+# yfinance - market data downloader
 # https://github.com/ranaroussi/yfinance
 #
 # Copyright 2017-2019 Ran Aroussi
@@ -30,14 +30,14 @@ class Tickers():
     def __repr__(self):
         return 'yfinance.Tickers object <%s>' % ",".join(self.symbols)
 
-    def __init__(self, tickers):
+    def __init__(self, tickers, session=None):
         tickers = tickers if isinstance(
             tickers, list) else tickers.replace(',', ' ').split()
         self.symbols = [ticker.upper() for ticker in tickers]
         ticker_objects = {}
 
         for ticker in self.symbols:
-            ticker_objects[ticker] = Ticker(ticker)
+            ticker_objects[ticker] = Ticker(ticker, session=session)
 
         self.tickers = ticker_objects
         # self.tickers = _namedtuple(
@@ -51,11 +51,11 @@ class Tickers():
                 timeout=None, **kwargs):
 
         return self.download(
-                period, interval,
-                start, end, prepost,
-                actions, auto_adjust, proxy,
-                threads, group_by, progress,
-                timeout, **kwargs)
+            period, interval,
+            start, end, prepost,
+            actions, auto_adjust, proxy,
+            threads, group_by, progress,
+            timeout, **kwargs)
 
     def download(self, period="1mo", interval="1d",
                  start=None, end=None, prepost=False,
@@ -85,3 +85,12 @@ class Tickers():
             data.sort_index(level=0, axis=1, inplace=True)
 
         return data
+
+    def news(self):
+        collection = {}
+        for ticker in self.symbols:
+            collection[ticker] = []
+            items = Ticker(ticker).news
+            for item in items:
+                collection[ticker].append(item)
+        return collection

yfinance/utils.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
 #
-# Yahoo! Finance market data downloader (+fix for Pandas Datareader)
+# yfinance - market data downloader
 # https://github.com/ranaroussi/yfinance
 #
 # Copyright 2017-2019 Ran Aroussi
@@ -21,11 +21,15 @@
 
 from __future__ import print_function
 
+import datetime as _datetime
+import pytz as _tz
 import requests as _requests
 import re as _re
 import pandas as _pd
 import numpy as _np
 import sys as _sys
+import os as _os
+import appdirs as _ad
 
 try:
     import ujson as _json
@@ -33,7 +37,8 @@ except ImportError:
     import json as _json
 
 
-user_agent_headers = {'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'}
+user_agent_headers = {
+    '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 is_isin(string):
@@ -88,6 +93,13 @@ def empty_df(index=[]):
     return empty
 
 
+def empty_earnings_dates_df():
+    empty = _pd.DataFrame(
+        columns=["Symbol", "Company", "Earnings Date",
+                 "EPS Estimate", "Reported EPS", "Surprise(%)"])
+    return empty
+
+
 def get_html(url, proxy=None, session=None):
     session = session or _requests
     html = session.get(url=url, proxies=proxy, headers=user_agent_headers).text
@@ -107,6 +119,13 @@ def get_json(url, proxy=None, session=None):
         '(this)')[0].split(';\n}')[0].strip()
     data = _json.loads(json_str)[
         'context']['dispatcher']['stores']['QuoteSummaryStore']
+    # add data about Shares Outstanding for companies' tickers if they are available
+    try:
+        data['annualBasicAverageShares'] = _json.loads(
+            json_str)['context']['dispatcher']['stores'][
+                'QuoteTimeSeriesStore']['timeSeries']['annualBasicAverageShares']
+    except Exception:
+        pass
 
     # return data
     new_data = _json.dumps(data).replace('{}', 'null')
@@ -120,6 +139,23 @@ def camel2title(o):
     return [_re.sub("([a-z])([A-Z])", r"\g<1> \g<2>", i).title() for i in o]
 
 
+def _parse_user_dt(dt, exchange_tz):
+    if isinstance(dt, int):
+        ## Should already be epoch, test with conversion:
+        _datetime.datetime.fromtimestamp(dt)
+    else:
+        # Convert str/date -> datetime, set tzinfo=exchange, get timestamp:
+        if isinstance(dt, str):
+            dt = _datetime.datetime.strptime(str(dt), '%Y-%m-%d')
+        if isinstance(dt, _datetime.date) and not isinstance(dt, _datetime.datetime):
+            dt = _datetime.datetime.combine(dt, _datetime.time(0))
+        if isinstance(dt, _datetime.datetime) and dt.tzinfo is None:
+            # Assume user is referring to exchange's timezone
+            dt = _tz.timezone(exchange_tz).localize(dt)
+        dt = int(dt.timestamp())
+    return dt
+
+
 def auto_adjust(data):
     df = data.copy()
     ratio = df["Close"] / df["Adj Close"]
@@ -161,7 +197,7 @@ def back_adjust(data):
     return df[["Open", "High", "Low", "Close", "Volume"]]
 
 
-def parse_quotes(data, tz=None):
+def parse_quotes(data):
     timestamps = data["timestamp"]
     ohlc = data["indicators"]["quote"][0]
     volumes = ohlc["volume"]
@@ -184,15 +220,14 @@ def parse_quotes(data, tz=None):
     quotes.index = _pd.to_datetime(timestamps, unit="s")
     quotes.sort_index(inplace=True)
 
-    if tz is not None:
-        quotes.index = quotes.index.tz_localize(tz)
-
     return quotes
 
 
-def parse_actions(data, tz=None):
-    dividends = _pd.DataFrame(columns=["Dividends"])
-    splits = _pd.DataFrame(columns=["Stock Splits"])
+def parse_actions(data):
+    dividends = _pd.DataFrame(
+        columns=["Dividends"], index=_pd.DatetimeIndex([]))
+    splits = _pd.DataFrame(
+        columns=["Stock Splits"], index=_pd.DatetimeIndex([]))
 
     if "events" in data:
         if "dividends" in data["events"]:
@@ -201,8 +236,6 @@ def parse_actions(data, tz=None):
             dividends.set_index("date", inplace=True)
             dividends.index = _pd.to_datetime(dividends.index, unit="s")
             dividends.sort_index(inplace=True)
-            if tz is not None:
-                dividends.index = dividends.index.tz_localize(tz)
 
             dividends.columns = ["Dividends"]
 
@@ -212,8 +245,6 @@ def parse_actions(data, tz=None):
             splits.set_index("date", inplace=True)
             splits.index = _pd.to_datetime(splits.index, unit="s")
             splits.sort_index(inplace=True)
-            if tz is not None:
-                splits.index = splits.index.tz_localize(tz)
             splits["Stock Splits"] = splits["numerator"] / \
                 splits["denominator"]
             splits = splits["Stock Splits"]
@@ -221,6 +252,19 @@ def parse_actions(data, tz=None):
     return dividends, splits
 
 
+def fix_Yahoo_dst_issue(df, interval):
+    if interval in ["1d","1w","1wk"]:
+        # These intervals should start at time 00:00. But for some combinations of date and timezone, 
+        # Yahoo has time off by few hours (e.g. Brazil 23:00 around Jan-2022). Suspect DST problem.
+        # The clue is (a) minutes=0 and (b) hour near 0. 
+        # Obviously Yahoo meant 00:00, so ensure this doesn't affect date conversion:
+        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')
+    return df
+
+
 class ProgressBar:
     def __init__(self, iterations, text='completed'):
         self.text = text
@@ -269,3 +313,37 @@ class ProgressBar:
 
     def __str__(self):
         return str(self.prog_bar)
+
+
+# Simple file cache of ticker->timezone:
+def get_cache_dirpath():
+    return _os.path.join(_ad.user_cache_dir(), "py-yfinance")
+def cache_lookup_tkr_tz(tkr):
+    fp = _os.path.join(get_cache_dirpath(), "tkr-tz.csv")
+    if not _os.path.isfile(fp):
+        return None
+
+    df = _pd.read_csv(fp)
+    f = df["Ticker"] == tkr
+    if sum(f) == 0:
+        return None
+
+    return df["Tz"][f].iloc[0]
+def cache_store_tkr_tz(tkr,tz):
+    df = _pd.DataFrame({"Ticker":[tkr], "Tz":[tz]})
+
+    dp = get_cache_dirpath()
+    if not _os.path.isdir(dp):
+        _os.makedirs(dp)
+    fp = _os.path.join(dp, "tkr-tz.csv")
+    if not _os.path.isfile(fp):
+        df.to_csv(fp, index=False)
+        return
+
+    df_all = _pd.read_csv(fp)
+    f = df_all["Ticker"]==tkr
+    if sum(f) > 0:
+        raise Exception("Tkr {} tz already in cache".format(tkr))
+
+    _pd.concat([df_all,df]).to_csv(fp, index=False)
+

yfinance/version.py

@@ -1 +1 @@
-version = "0.1.66"
+version = "0.1.78"