alpha_vantage

Python module to get stock data from the Alpha Vantage API

Alpha Vantage delivers a free API for real time financial data and most used finance indicators in a simple json or pandas format. This module implements a python interface to the free API provided by Alpha Vantage (http://www.alphavantage.co/). It requires a free API, that can be requested on http://www.alphavantage.co/support/#api-key. You can have a look at all the api calls available in their documentation http://www.alphavantage.co/documentation

Install

To install the package use:

pip install alpha_vantage

If you want to install from source, then use:

git clone https://github.com/RomelTorres/alpha_vantage.git
pip install -e alpha_vantage

Usage

To get data in a python, simply import the library and call the object with your api key and get ready for some awesome free realtime finance data.

from alpha_vantage.timeseries import TimeSeries
ts = TimeSeries(key='YOUR_API_KEY')
# Get json object with the intraday data and another with  the call's metadata
data, meta_data = ts.get_intraday('GOOGL')

Internally there is a retries counter, that can be used to minimize connection errors (in case that the api is not able to respond in time), the default is set to 5 but can be increased or decreased whenever needed.

ts = TimeSeries(key='YOUR_API_KEY',retries='YOUR_RETRIES')

Finally the library supports giving its results as json dictionaries (default) or as pandas dataframe, simply pass the parameter output_format='pandas' to change the format of the output for all the api calls.

ts = TimeSeries(key='YOUR_API_KEY',output_format='pandas')

Plotting

Using pandas support we can plot the intra-minute value for 'MSFT' stock quite easily:

from alpha_vantage.timeseries import TimeSeries
import matplotlib.pyplot as plt

ts = TimeSeries(key='YOUR_API_KEY', output_format='pandas')
data, meta_data = ts.get_intraday(symbol='MSFT',interval='1min', outputsize='full')
data['close'].plot()
plt.title('Intraday Times Series for the MSFT stock (1 min)')
plt.show()

Giving us as output:

The same way we can get pandas to plot technical indicators like Bolliger Bands®

from alpha_vantage.techindicators import TechIndicators
import matplotlib.pyplot as plt

ti = TechIndicators(key='YOUR_API_KEY', output_format='pandas')
data, meta_data = ti.get_bbands(symbol='MSFT', interval='60min', time_period=60)
data.plot()
plt.title('BBbands indicator for  MSFT stock (60 min)')
plt.show()

Giving us as output:

We can also plot sector performance just as easy:

from alpha_vantage.sectorperformance import SectorPerformances
import matplotlib.pyplot as plt

sp = SectorPerformances(key='YOUR_API_KEY', output_format='pandas')
data, meta_data = sp.get_sector()
data['Rank A: Real-Time Performance'].plot(kind='bar')
plt.title('Real Time Performance (%) per Sector')
plt.tight_layout()
plt.grid()
plt.show()

Giving us as output:

Tests

In order to run the tests you have to first export your API key so that the test can use it to run.

export API_KEY=YOUR_API_KEY
cd alpha_vantage
nosetests

Documentation

The code documentation can be found at https://alpha-vantage.readthedocs.io/en/latest/

TODOS:

• Separate tests between unittests and integration test.
• Should support for csv also be added?

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