ranaroussi / packages / yfinance 0.1.63

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  • Last upload: 1 year and 2 months ago


pip install

To install this package run one of the following:
pip install -i https://pypi.anaconda.org/ranaroussi/simple yfinance


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.


    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 ยป <./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

        # get historical market data
        hist = msft.history(period="max")

        # show actions (dividends, splits)

        # show dividends

        # show splits

        # show financials

        # show major holders

        # show institutional holders

        # show balance sheet

        # show cashflow

        # show earnings

        # show sustainability

        # show analysts recommendations

        # show next event (earnings, etc)

        # show ISIN code - *experimental*
        # ISIN = International Securities Identification Number

        # show options expirations

        # 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.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

    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)

    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")


    Install ``yfinance`` using ``pip``:

    .. code:: bash

        $ pip install yfinance --upgrade --no-cache-dir

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

    .. code:: bash

        $ conda install -c ranaroussi yfinance


    * `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.


    Please drop me an note with any feedback you have.

    **Ran Aroussi**

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