How to use the quandl.ApiConfig function in Quandl

def test(year, stock, window=10, up=0.05, down=0.05, get_plots=True, verbose=True):
	quandl.ApiConfig.api_key = "FDEDsMbK1E2t_PMf7X3M"
	df = quandl.get('NSE/ZEEL', start_date='2017-01-01', end_date='2017-12-31')
	prices = df["Close"]
	dates = df["Date"]

	agent = EMA_Agent(window, up, down)

	test = Backtest(agent, 10000)

	output = test.run(prices)

	# class Evaluation takes for initialization - prices, output, name of algorithm, name of security

	evaluator = Evaluation(prices, dates, output, "EMA", stock)
	return evaluator.complete_evaluation(get_plots, verbose)

from os import getenv
from quandl import ApiConfig, get
from clint.textui import colored

from app.data import to_pickle
from app.variables import QUANDL_SYMBOLS
ApiConfig.api_key = getenv('QUANDL_KEY')
from app.utils.date_utils import ensure_latest


def run_quandl(check_latest=True):
    for s in QUANDL_SYMBOLS:
        data = get(s[0])
        name = s[0].replace('/', '_')
        if check_latest:
            if s[2]:
                ensure_latest(df=data)
        to_pickle(data, 'futures', name)
        print(colored.green(name))

def fetch_compare(request):
    if request.method == 'POST':
        company = []
        company1 = ''
        company2 = ''
        company3 = ''
        start_date = '2015-12-31'
        end_date = '2016-12-31'
        stock_return1 = []
        stock_return2 = []
        stock_return3 = []
        # form = NameForm(request.POST)
        
        quandl.ApiConfig.api_key = "23KLyzjn5UvKQog-DZyM"
        company1 = request.POST.get('company_name1')
        company2 = request.POST.get('company_name2')
        company3 = request.POST.get('company_name3')
        if company1 != '':
            company.append(company1)
        if company2 != '':
            company.append(company2)
        if company3 != '':
            company.append(company3)
        
        start_date = request.POST.get('start_date')
        end_date = request.POST.get('end_date')
        
        # print(company1)
        # print(start_date)
        # print(end_date)

"""

from sysdata.futures.contracts import futuresContract
from sysdata.futures.futures_per_contract_prices import futuresContractPriceData, futuresContractPrices
from syscore.fileutils import get_filename_for_package
from sysdata.quandl.quandl_utils import load_private_key

import quandl
import pandas as pd


QUANDL_FUTURES_CONFIG_FILE = get_filename_for_package("sysdata.quandl.QuandlFuturesConfig.csv")


quandl.ApiConfig.api_key = load_private_key()

class quandlFuturesConfiguration(object):

    def __init__(self, config_file = QUANDL_FUTURES_CONFIG_FILE):

        self._config_file = config_file

    def get_list_of_instruments(self):
        config_data = self._get_config_information()

        return list(config_data.index)

    def get_instrument_config(self, instrument_code):

        if instrument_code not in self.get_list_of_instruments():
            raise Exception("Instrument %s missing from config file %s" % (instrument_code, self._config_file))

import quandl
import pandas as pd
import numpy as np
from scipy.signal import argrelextrema
import sys, os
import dill as pickle
from sklearn import preprocessing as prep
from sklearn.model_selection import train_test_split
from talib import abstract as ta
from sklearn.externals import joblib
import copy

quandl.ApiConfig.api_key = "KDH1TFmmmcrjgynvRdWg"

HI_LO_DIFF = 0.03
MIN_MAX_PERIOD = 8


def build_data(raw=False, random_split=True, start_date=None, end_date=None, test_proportion=0.1):
    # if len(sec) == 1 and os.path.isfile(secs[0]):	#it's a file
    # 	with open(secs[0]) as f:
    # 		secs = ["WIKI/" + line.strip() for line in f]

    # print("SECURITIES: ", s[5:] for s in secs)

    with open("stock_data/invalid_stocks.txt", "r+") as f:
        invalid_stock_codes = [line.strip() for line in f]
    f = open("stock_data/invalid_stocks.txt", "a")

def __init__(self, columns, config=None):
        super(QuandleDataManager, self).__init__("quandl", columns, config)
        """DataManager object used to fetch and integrate Quandl Blockchain database"""

        self.config = config
        _api_key = os.getenv("QUANDL_API_KEY")
        quandl.ApiConfig.api_key = _api_key
        self.data_dir = os.path.join(DATA_DIR, "quandle")

def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        self.period = 60 * 60  # 1h
        self.days = 1
        self.maxAge = getattr(self, "maxAge", 5)

        quandl.ApiConfig.api_key = self.api_key
        quandl.ApiConfig.api_version = '2015-04-09'

def get_data(security):
    """
    This function obtains data under certain parameters from Quandl and returns the following information as a Pandas
    DataFrame: date, adjusted closing, and percentage change in adjusted closing from the last week.

    :param security:  Holds information about the requested security
    :return: A Pandas DataFrame with columns: Date, Adjusted Close, and Percentage Change.
    """
    quandl.ApiConfig.api_key = "7NU4-sXfczxA9fsf_C8E"
    name = security.get_name()
    start = security.get_start()
    end = security.get_end()
    period = security.get_period()
    raw_df = quandl.get("YAHOO/" + name, start_date=start, end_date=end, collapse=period)
    adjusted_df = raw_df.ix[:, ['Adjusted Close']]
    adjusted_df["Percentage Change"] = adjusted_df['Adjusted Close'].pct_change() * 100
    return adjusted_df

import quandl, sys, os
import pandas as pd
import numpy as np
from scipy.signal import argrelextrema
import dill as pickle
from sklearn import preprocessing as prep
from sklearn.model_selection import train_test_split
from talib import abstract as ta
from sklearn.externals import joblib
from collections import OrderedDict
import time

np.random.seed(1337)  # for reproducibility


quandl.ApiConfig.api_key = "KDH1TFmmmcrjgynvRdWg"

HI_LO_DIFF = 0.03
MIN_MAX_PERIOD = 8


def build_data(raw=False, random_split=True, start_date=None, end_date=None, test_proportion=0.1):
    # if len(sec) == 1 and os.path.isfile(secs[0]):	#it's a file
    # 	with open(secs[0]) as f:
    # 		secs = ["WIKI/" + line.strip() for line in f]

    # print("SECURITIES: ", s[5:] for s in secs)

    with open("stock_data/invalid_stocks.txt", "r+") as f:
        invalid_stock_codes = [line.strip() for line in f]
    f = open("stock_data/invalid_stocks.txt", "a")