Metadata-Version: 1.1
Name: alpha-vantage
Version: 0.2.0
Summary: Python module to get stock data from the Alpha Vantage Api
Home-page: https://github.com/RomelTorres/alpha_vantage
Author: Romel J. Torres
Author-email: romel.torres@gmail.com
License: MIT
Description: alpha\_vantage
        ==============
        
        |Build Status|
        
        *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 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.
        
        Install
        -------
        
        To install the package use:
        
        .. code:: shell
        
            pip install alpha_vantage
        
        If you want to install from source, then use:
        
        .. code:: shell
        
            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.
        
        .. code:: python
        
            from alpha_vantage.timeseries import TimesSeries
            ts = TimesSeries(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.
        
        .. code:: python
        
            ts = TimesSeries(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.
        
        .. code:: python
        
            ts = TimesSeries(key='YOUR_API_KEY',output_format='pandas')
        
        Plotting
        --------
        
        Using pandas support we can plot the intra-minute value for 'MSFT' stock
        quite easily:
        
        .. code:: python
        
            from alpha_vantage.timeseries import TimesSeries
            import matplotlib.pyplot as plt
        
            ts = TimesSeries(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: |alt text|
        
        The same way we can get pandas to plot technical indicators like
        Bolliger Bands®
        
        .. code:: python
        
            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: |alt text|
        
        Tests
        -----
        
        In order to run the tests you have to first export your API key so that
        the test can use it to run.
        
        .. code:: shell
        
            export API_KEY=YOUR_API_KEY
            cd alpha_vantage
            nosetests
        
        Documentation
        -------------
        
        To find out more about the available api calls, visit the alpha-vantage
        documentation at http://www.alphavantage.co/documentation/
        
        Coming soon:
        ------------
        
        1. [STRIKEOUT:Add basic functionality: 0.0.1]
        2. [STRIKEOUT:Add retry in order to allow the calls to be retried in
           case of failure: 0.0.2]
        3. [STRIKEOUT:Implement all functions described in the alpha vantage
           documentation 0.0.3]
        4. [STRIKEOUT:Re-factor functions to have an unified method for
           accessing the api 0.1.0]
        5. [STRIKEOUT:Add pandas support through decorators 0.1.2]
        6. [STRIKEOUT:Publish on pipy 0.1.3]
        7. Add logging to tests to store api call duration 1.0.1
        8. Add unit tests for all the function parameters in the module 1.0.2
        
        .. |Build Status| image:: https://travis-ci.org/RomelTorres/alpha_vantage.png?branch=master
           :target: https://travis-ci.org/RomelTorres/alpha_vantage
        .. |alt text| image:: images/docs_ts_msft_example.png?raw=True
        .. |alt text| image:: images/docs_ti_msft_example.png?raw=True
        
        
Keywords: stocks,market,finance,alpha_vantage,quotes,shares
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Office/Business :: Financial :: Investment
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
