Metadata-Version: 2.1
Name: alpyvantage
Version: 0.2.0
Summary: A python API to Alpha Vantage
Home-page: https://github.com/gboehl/alpyvantage
Author: Gregor Boehl
Author-email: admin@gregorboehl.com
License: MIT
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Description-Content-Type: text/x-rst

alpyvantage
=============

**An alternative python backend to the Alpha Vantage API**

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    :target: https://github.com/gboehl/alpyvantage

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    :target: https://alpyvantage.readthedocs.io

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**alpyvantage** provides a python backend to the Alpha Vantage API. Alpha Vantage provides access to a wide range of financial data and time series. Details can be found in the `official API documentation <https://www.alphavantage.co/documentation/>`_. You can get a free `API key here <https://www.alphavantage.co/support/#api-key>`_.


Installation
------------

Installing the `repository version <https://pypi.org/project/econpizza/>`_ is as simple as typing

.. code-block:: bash

   pip install alpyvantage

in your terminal or Anaconda Prompt.


Documentation
-------------

API calls are straightforward. Either use the build-in functions such as ``time_series_intraday``, ``time_series_weekly``, etc.:

.. code-block:: python

    import alpyvantage as av

    api = av.API(<your_api_key>)

    data, meta_data = api.time_series_intraday('DAX', interval='1min', month='2015-01')

    print(data) # its a pandas.DataFrame

Or use the ``function`` keyword from the `official API documentation <https://www.alphavantage.co/documentation/>`_ and provide the parameters as keyword arguments:

.. code-block:: python

    data, meta_data = api('TIME_SERIES_INTRADAY', symbol='DAX', interval='1min', month='2015-01')

A detailed documentation of the individual functions can be `found here <https://alpyvantage.readthedocs.io>`_.


Issues and contributions
------------------------

Please use the `issues <https://github.com/gboehl/alpyvantage/issues>`_ for questions or if you think anything doesn't do what it is supposed to do. Pull requests are welcome, please include some documentation.
