= yfinance =
 * https://pypi.org/project/yfinance/

yfinance aimes to solve this problem by offering a reliable, threaded, and Pythonic way to download historical market data from Yahoo! finance.

 * pip install yfinance --user

{{{#!highlight python
import yfinance
from pandas._libs.tslibs.timestamps import Timestamp
data = yfinance.download("AMZN",start="2019-01-01",end="2020-02-12")
d = data.to_dict()
d['Close'].key
# for k in d['Close'].iterkeys(): print (k)
d['Close'][Timestamp('2019-11-22 00:00:00')]
d['Close'][Timestamp('2020-02-10 00:00:00')]
}}}

== MSFT example ==
{{{#!highlight sh
cd ~/Documents/
mkdir yfinance-test
cd yfinance-test/
sudo apt install python3-venv
python3 -m venv testVenv
source testVenv/bin/activate
pip install yfinance
python3 test-msft.py
}}}

=== test-msft.py ===
{{{#!highlight python
import yfinance as yf
msft = yf.Ticker("MSFT")

historyDataFrame = msft.history(period="5d")
print("Available columns")
for colname in historyDataFrame:
    print("  "+colname)

print("Available indexes")
for row in historyDataFrame.index:
    print("  "+str(row))

columnClose = historyDataFrame['Close']
rowidx = 0
print("Symbol:"+msft.info['symbol'])
for closeValue in columnClose.values:
    print(historyDataFrame.index[rowidx],  closeValue)
    rowidx += 1
}}}