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Alphavantage API wrapper.

Project description

Build Status Scrutinizer Code Quality

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.

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

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

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. And follow setup instructions.

Conda Environment

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

Follow the instructions in the link provided. DO NOT SUDO PIP INSTALL. Alias the preferred Python installation by adding, for example:

alias python='/usr/bin/python3.6'

When using Pip

pip install --upgrade pip
pip install wheel
pip install -r requirements.txt

python setup.py install bdist_wheel

Running the Tests

py.test

Running Coverage Report

py.test --cov

Project details


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