Metadata-Version: 2.1
Name: alphavantage
Version: 0.0.11
Summary: Alphavantage API wrapper.
Home-page: https://github.com/portfoliome/alphavantage
Author: Philip Martin
Author-email: philip.martin@censible.co
License: MIT
Description: [![Build Status](https://travis-ci.org/portfoliome/alphavantage.svg?branch=master)](https://travis-ci.com/portfoliome/alpavantage)
        [![Scrutinizer Code Quality](https://scrutinizer-ci.com/g/portfoliome/alphavantage/badges/quality-score.png?b=master)](https://scrutinizer-ci.com/g/portfoliome/alphavantage/?branch=master)
        
        # alphavantage
        
        alphavantage is a Python wrapper for the Alpha Vantage API.
        
        The API wrapper can be used to retrieve historical prices such as intraday or daily prices for global equities and ETFs.
        
        ## Status
        
        The API aims to support equity time-series data as a first step.
        
        The package is currently in alpha status. It has not been used extensively yet and therefore mainly of the potential quirks of Alpha Vantage's actual API may not be accounted for. We plan on using this wrapper for price history charting in our [company lookup and ratings tool](https://esg.censible.co/companies/Apple).
        
        
        ## Design Consideration
        
        This library is intended to provide a simple wrapper with minimal dependencies, and does not intend to introduce pydata stack dependencies (numpy, pandas, etc.) in the future. Differences with existing wrappers for the Alpha Vantage API include:
         
        ### Library Differences
        
        * No Pandas dependencies or optional dependency
        * Focuses on simplifying data for ingesting
        * Avoids logical branching making the code simpler (only two if statements at moment)
        * Provides symbology mapping references
        
        The library carries out some conveniences versus using the API without a wrapper.
        
        ### Conveniences
        
        * Converts timestamps to UTC time when applicable.
        * Simplifies record field names i.e. "4. close" -> "close".
        * Appends the timestamp field to record vs. having the timestamp act as dictionary key.
        * Uses time ascending list versus a dictionary for price record data structure.
        * Returns multiple tickers over a given parameter set using threads.
        * Maps ticker symbology from other vendors.
        * Excludes intraday data in daily price history requests.
        
        ## Examples
        ```python
        from alphavantage.price_history import (
          AdjustedPriceHistory, get_results, PriceHistory, IntradayPriceHistory,
          filter_dividends
        )
        
        # weekly prices
        history = PriceHistory(period='W', output_size='compact')
        results = history.get('AAPL')
        
        # intraday prices, 5 minute interval
        history = IntradayPriceHistory(utc=True, interval=5)
        results = history.get('AAPL')
        
        # adjusted daily prices
        history = AdjustedPriceHistory(period='D')
        results = history.get('AAPL')
        dividends = list(filter_dividends(results.records))
        
        # Return multiple tickers
        parameters = {'output_size': 'compact', 'period': 'D'}
        tickers = ['AAPL', 'MSFT']
        results = dict(get_results(PriceHistory, tickers, parameters))
        ```
        
        ## Contributing
        Contributions are welcome. Someone can immediately contribute by building out wrappers for the rest of the API such as FX rates or crypto prices.
        
        ## Getting Started
        
        ### Installing
        
        ```sh
        pip install alphavantage
        ```
        
        ### Developer Installation
        
        These instructions assume Python 3.6. It is recommended that you use conda or a virtualenv.
        
        #### For conda install follow:
        Download the [conda installer](http://conda.pydata.org/miniconda.html).
        And follow setup [instructions](http://conda.pydata.org/docs/install/quick.html#id1).
        
        #### Conda Environment
        
        ```sh
        conda create --name <environment_name> python=3.6
        activate <environment_name>
        conda install --file requirements.txt
        
        python setup.py install bdist_wheel
        ```
        
        #### debian installation
        [Instruction](https://linuxconfig.org/how-to-change-from-default-to-alternative-python-version-on-debian-linux)
        
        Follow the instructions in the link provided. **DO NOT SUDO PIP INSTALL**. Alias the preferred Python installation by adding, for example:
        
        ```sh
        alias python='/usr/bin/python3.6'
        ```
        
        #### When using Pip
        ```sh
        pip install --upgrade pip
        pip install wheel
        pip install -r requirements.txt
        
        python setup.py install bdist_wheel
        ```
        
        #### Running the Tests
        ```sh
        py.test
        ```
        #### Running Coverage Report
        ```sh
        py.test --cov
        ```
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Topic :: Office/Business :: Financial :: Investment
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
Provides-Extra: test
