Ever since Yahoo decommissioned their historical data API, Python developers looked for a reliable workaround. As a result, my library, [yfinance](https://github.com/ranaroussi/yfinance), gained momentum and gets 300k+ 3M+ installs per month, acording to PyPi!
---
### Legal note:
**Yahoo!, Y!Finance, and Yahoo! finance are registered trademarks of Yahoo, Inc.**
yfinance is not affiliated, endorsed, or vetted by Yahoo, Inc. It's an open-source tool that uses Yahoo's publicly available APIs, and is intended for research and educational purposes.
**You should refer to Yahoo!'s terms of use ([here](https://policies.yahoo.com/us/en/yahoo/terms/product-atos/apiforydn/index.htm),
[here](https://legal.yahoo.com/us/en/yahoo/terms/otos/index.html), and
[here](https://policies.yahoo.com/us/en/yahoo/terms/index.htm)) for details on your rights to use the actual data downloaded. Remember - the Yahoo! finance API is intended for personal use only.**
---
`fix-yahoo-finance` [aimed to offer a temporary fix](https://aroussi.com/post/fix-yahoo-finance) to the problem by getting data from Yahoo! Finance and returning it in the same format as **pandas_datareader's** ``get_data_yahoo()``, thus keeping the code changes in exisiting software to minimum.
The problem was, that this hack was a bit unreliable, causing data to not being downloaded and required developers to force session re-initialization and re-fetching of cookies, by calling ``yf.get_yahoo_crumb(force=True)``.
**yfinance** is a complete re-write of the libray, offering a reliable method of downloading historical market data from Yahoo! Finance's API, up to 1 minute granularity, in a more Pythonic way.
### Introducing the ``Ticker()`` module:
The ``Ticker()`` module allows you get market and meta data for a security, using a Pythonic way:
```python
import yfinance as yf
msft = yf.Ticker("MSFT")
print(msft)
"""
returns
"""
# get stock info
msft.info
"""
returns:
{
'quoteType': 'EQUITY',
'quoteSourceName': 'Nasdaq Real Time Price',
'currency': 'USD',
'shortName': 'Microsoft Corporation',
'exchangeTimezoneName': 'America/New_York',
...
'symbol': 'MSFT'
}
"""
# get historical market data
msft.history(period="max")
"""
returns:
Open High Low Close Volume Dividends Splits
Date
1986-03-13 0.06 0.07 0.06 0.07 1031788800 0.0 0.0
1986-03-14 0.07 0.07 0.07 0.07 308160000 0.0 0.0
...
2019-04-15 120.94 121.58 120.57 121.05 15792600 0.0 0.0
2019-04-16 121.64 121.65 120.10 120.77 14059700 0.0 0.0
"""
# show actions (dividends, splits)
msft.actions
"""
returns:
Dividends Splits
Date
1987-09-21 0.00 2.0
1990-04-16 0.00 2.0
...
2018-11-14 0.46 0.0
2019-02-20 0.46 0.0
"""
# show dividends
msft.dividends
"""
returns:
Date
2003-02-19 0.08
2003-10-15 0.16
...
2018-11-14 0.46
2019-02-20 0.46
"""
# show splits
msft.splits
"""
returns:
Date
1987-09-21 2.0
1990-04-16 2.0
...
1999-03-29 2.0
2003-02-18 2.0
"""
```
Available paramaters for the ``history()`` method are:
- **period**: data period to download (Either Use period parameter or use start and end)
Valid periods are: 1d, 5d, 1mo, 3mo, 6mo, 1y, 2y, 5y, 10y, ytd, max
- **interval**: data interval (intraday data cannot extend last 60 days)
Valid intervals are: 1m, 2m, 5m, 15m, 30m, 60m, 90m, 1h, 1d, 5d, 1wk, 1mo, 3mo
- **start**: If not using period - Download start date string (YYYY-MM-DD) or datetime.
- **end**: If not using period - Download end date string (YYYY-MM-DD) or datetime.
- **prepost**: Include Pre and Post market data in results? (Default is ``False``)
- **auto_adjust**: Adjust all OHLC automatically? (Default is ``True``)
- **actions**: Download stock dividends and stock splits events? (Default is ``True``)
### Mass download of market data:
You can also download data for multiple tickers at once, like before.
```python
import yfinance as yf
data = yf.download("SPY AAPL", start="2017-01-01", end="2017-04-30")
```
To access the closing price data for **SPY**, you should use: ``data['Close']['SPY']``.
If, however, you want to group data by Symbol, use:
```python
import yfinance as yf
data = yf.download("SPY AAPL", start="2017-01-01", end="2017-04-30",
group_by="ticker")
```
To access the closing price data for **SPY**, you should use: ``data['SPY']['Close']``.
The ``download()`` method accepts an additional parameter - ``threads`` for faster completion when downloading a lot of symbols at once.
**\* NOTE:** To keep compatibility with older versions, **auto_adjust** defaults to ``False`` when using mass-download.
### Using pandas_datareader:
If your legacy code is using ``pandas_datareader`` and you wand to keep the code changes to minimum, you can simply call the override method and keep your code as it was:
```python
from pandas_datareader import data as pdr
import yfinance as yf
yf.pdr_override() # <== that's all it takes :-)
# download dataframe using pandas_datareader
data = pdr.get_data_yahoo("SPY", start="2017-01-01", end="2017-04-30")
```
---
To install/upgrade **yfinance** using pip, run:
```bash
$ pip install yfinance --upgrade --no-cache-dir
```
---
The [Github repository](https://github.com/ranaroussi/yfinance) has more information and issue tracking.
Enjoy!