quandl_data.py

#!/usr/bin/python
# -*- coding: utf-8 -*-

# quandl_data.py

from __future__ import print_function

import matplotlib.pyplot as plt
import pandas as pd
import requests


def construct_futures_symbols(
        symbol, start_year=2010, end_year=2014
    ):
    """
    Constructs a list of futures contract codes 
    for a particular symbol and timeframe.
    """
    futures = []
    # March, June, September and 
    # December delivery codes
    months = 'HMUZ' 
    for y in range(start_year, end_year+1):
        for m in months:
            futures.append("%s%s%s" % (symbol, m, y))
    return futures


def download_contract_from_quandl(contract, dl_dir):
    """
    Download an individual futures contract from Quandl and then
    store it to disk in the 'dl_dir' directory. An auth_token is 
    required, which is obtained from the Quandl upon sign-up.
    """
    # Construct the API call from the contract and auth_token 
    api_call = "http://www.quandl.com/api/v1/datasets/"   
    api_call += "OFDP/FUTURE_%s.csv" % contract
    # If you wish to add an auth token for more downloads, simply
    # comment the following line and replace MY_AUTH_TOKEN with
    # your auth token in the line below
    params = "?sort_order=asc"
    #params = "?auth_token=MY_AUTH_TOKEN&sort_order=asc"
    full_url = "%s%s" % (api_call, params)

    # Download the data from Quandl
    data = requests.get(full_url).text
    
    # Store the data to disk
    fc = open('%s/%s.csv' % (dl_dir, contract), 'w')
    fc.write(data)
    fc.close()


def download_historical_contracts(
        symbol, dl_dir, start_year=2010, end_year=2014
    ):
    """
    Downloads all futures contracts for a specified symbol
    between a start_year and an end_year.
    """
    contracts = construct_futures_symbols(
        symbol, start_year, end_year
    )
    for c in contracts:
        print("Downloading contract: %s" % c)
        download_contract_from_quandl(c, dl_dir)


if __name__ == "__main__":
    symbol = 'ES'

    # Make sure you've created this 
    # relative directory beforehand
    dl_dir = 'quandl/futures/ES'

    # Create the start and end years
    start_year = 2010
    end_year = 2014

    # Download the contracts into the directory
    download_historical_contracts(
        symbol, dl_dir, start_year, end_year
    )

    # Open up a single contract via read_csv 
    # and plot the settle price
    es = pd.io.parsers.read_csv(
        "%s/ESH2010.csv" % dl_dir, index_col="Date"
    )
    es["Settle"].plot()
    plt.show()