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Yahoo! Finance market data downloader

Project description

Yahoo! Finance market data downloader

Python version PyPi version PyPi status Travis-CI build status Star this repo Follow me on twitter

Ever since Yahoo! finance decommissioned their historical data API, many programs that relied on it to stop working.

yfinance aimes 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-competability, fix-yahoo-finance now import and uses yfinance, but you should install and use yfinance directly.

Changelog »


==> Check out this Blog post for a detailed tutorial with code examples.


Quick Start

The Ticker module

The Ticker module, which allows you to access ticker data in amore Pythonic way:

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

To initialize multiple Ticker objects, use

import yfinance as yf

tickers = yf.Tickers('msft aapl goog')
# ^ returns a named tuple of Ticker objects

# access each ticker using (example)
tickers.msft.info
tickers.aapl.history(period="1mo")
tickers.goog.actions

Fetching data for multiple tickers

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 :)

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)
        treads = True,

        # proxy URL scheme use use when downloading?
        # (optional, default is None)
        proxy = None
    )

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().

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:

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

Requirements

Optional (if you want to use pandas_datareader)

P.S.

Please drop me an note with any feedback you have.

Ran Aroussi

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