Yahoo! Finance market data downloader =====================================
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    \

    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 » <./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

        # 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


    Install ``yfinance`` using ``conda``:

    .. code:: 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

    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**
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