Metadata-Version: 2.1
Name: yfinance
Version: 0.1.72
Summary: Download market data from Yahoo! Finance API
Home-page: https://github.com/ranaroussi/yfinance
Author: Ran Aroussi
Author-email: ran@aroussi.com
License: Apache
Keywords: pandas,yahoo finance,pandas datareader
Platform: any
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Development Status :: 5 - Production/Stable
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Developers
Classifier: Topic :: Office/Business :: Financial
Classifier: Topic :: Office/Business :: Financial :: Investment
Classifier: Topic :: Scientific/Engineering :: Interface Engine/Protocol Translator
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Description-Content-Type: text/markdown
License-File: LICENSE.txt

# Download market data from Yahoo! Finance's API

<table border=1 cellpadding=10><tr><td>

#### \*\*\* IMPORTANT LEGAL DISCLAIMER \*\*\*

---

**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.**

</td></tr></table>

---

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**yfinance** offers a threaded and Pythonic way to download market data from [Yahoo!Ⓡ finance](https://finance.yahoo.com).

→ Check out this [Blog post](https://aroussi.com/#post/python-yahoo-finance) for a detailed tutorial with code examples.

[Changelog »](https://github.com/ranaroussi/yfinance/blob/main/CHANGELOG.rst)

---

## 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.

```python
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

# show financials
msft.financials
msft.quarterly_financials

# show major holders
msft.major_holders

# show institutional holders
msft.institutional_holders

# show balance sheet
msft.balance_sheet
msft.quarterly_balance_sheet

# show cashflow
msft.cashflow
msft.quarterly_cashflow

# show earnings
msft.earnings
msft.quarterly_earnings

# show sustainability
msft.sustainability

# show analysts recommendations
msft.recommendations

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

# show all earnings dates
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
```

If you want to use a proxy server for downloading data, use:

```python
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_balance_sheet(proxy="PROXY_SERVER")
msft.get_cashflow(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.

```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
ticker.actions
```

To initialize multiple `Ticker` objects, use

```python
import yfinance as yf

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

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

### Fetching data for multiple tickers

```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 :)

```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()`.

```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")
```

---

## Installation

Install `yfinance` using `pip`:

``` {.sourceCode .bash}
$ pip install yfinance --upgrade --no-cache-dir
```

To install `yfinance` using `conda`, see
[this](https://anaconda.org/ranaroussi/yfinance).

### Requirements

-   [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.


AGAIN - 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
detailes on your rights to use the actual data downloaded.

---

### P.S.

Please drop me an note with any feedback you have.

**Ran Aroussi**
