import yfinance as yf

msft = yf.Ticker("MSFT")

# get all stock info (slow)
msft.info
# fast access to subset of stock info (opportunistic)
msft.fast_info

# get historical market data
hist = msft.history(period="1mo")

# show meta information about the history (requires history() to be called first)
msft.history_metadata

# show actions (dividends, splits, capital gains)
msft.actions
msft.dividends
msft.splits
msft.capital_gains  # only for mutual funds & etfs

# show share count
# - yearly summary:
msft.shares
# - accurate time-series count:
msft.get_shares_full(start="2022-01-01", end=None)

# show financials:
# - income statement
msft.income_stmt
msft.quarterly_income_stmt
# - balance sheet
msft.balance_sheet
msft.quarterly_balance_sheet
# - cash flow statement
msft.cashflow
msft.quarterly_cashflow
# see `Ticker.get_income_stmt()` for more options

# show holders
msft.major_holders
msft.institutional_holders
msft.mutualfund_holders

# show earnings
msft.earnings
msft.quarterly_earnings

# show sustainability
msft.sustainability

# show analysts recommendations
msft.recommendations
msft.recommendations_summary
# show analysts other work
msft.analyst_price_target
msft.revenue_forecasts
msft.earnings_forecasts
msft.earnings_trend

# show next event (earnings, etc)
msft.calendar

# Show future and historic earnings dates, returns at most next 4 quarters and last 8 quarters by default. 
# Note: If more are needed use msft.get_earnings_dates(limit=XX) with increased limit argument.
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

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_capital_gains(proxy="PROXY_SERVER")
msft.get_balance_sheet(proxy="PROXY_SERVER")
msft.get_cashflow(proxy="PROXY_SERVER")
msft.option_chain(..., proxy="PROXY_SERVER")
...

import requests_cache
session = requests_cache.CachedSession('yfinance.cache')
session.headers['User-agent'] = 'my-program/1.0'
ticker = yf.Ticker('msft', session=session)
# The scraped response will be stored in the cache
ticker.actions

import yfinance as yf

tickers = yf.Tickers('msft aapl goog')

# access each ticker using (example)
tickers.tickers['MSFT'].info
tickers.tickers['AAPL'].history(period="1mo")
tickers.tickers['GOOG'].actions

import yfinance as yf
data = yf.download("SPY AAPL", start="2017-01-01", end="2017-04-30")

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 = "5d",

        # Whether to ignore timezone when aligning ticker data from 
        # different timezones. Default is False.
        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,

        # attempt repair of missing data or currency mixups e.g. $/cents
        repair = False,

        # 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
    )

import yfinance as yf
yf.set_tz_cache_location("custom/cache/location")
...

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")