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if __name__ == '__main__':
    my_exchange = input("Your exchange:")
    starting_price = input("Bitcoin starting price:")
    amount = input("Bitcoin amount:")
    currency = input("Your currency (default USD):")
    check_every = input("Check every (seconds):")
    threshold = input("Choose to be notified when a certain limit is reached\n1) Percent limit: \n2) Amount limit: \n ")
    limit_type = None
    limit = 0
    if threshold == '1':

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Architecture in Elm

This document is a collection of concepts and strategies to make large Elm projects modular and extensible.

We will start by thinking about the structure of signals in our program. Broadly speaking, your application state should live in one big foldp. You will probably merge a bunch of input signals into a single stream of updates. This sounds a bit crazy at first, but it is in the same ballpark as Om or Facebook's Flux. There are a couple major benefits to having a centralized home for your application state:

1. There is a single source of truth. Traditional approaches force you to write a decent amount of custom and error prone code to synchronize state between many different stateful components. (The state of this widget needs to be synced with the application state, which needs to be synced with some other widget, etc.) By placing all of your state in one location, you eliminate an entire class of bugs in which two components get into inconsistent states. We also think yo

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https://realpython.com/blog/python/asynchronous-tasks-with-django-and-celery/

Install Celery

$ pip install celery

Install celery Broker

$ sudo apt-get install rabbitmq-server

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// Install with: > npm install bitcoinaverage

const ba = require('bitcoinaverage');
var pub = '<your public key>';
var secret = '<your secret key>';

var wsClient = ba.websocketClient(pub, secret);

wsClient.connectToTickerWebsocketV2('global', ['ETHUSD', 'BCHUSD', 'LTCUSD', 'ETCUSD'], function(response) {
  console.log(response.data.global);

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# Install with > pip install bitcoinaverage

from bitcoinaverage import TickerWebsocketClientV2

class MyWebsocketClient(TickerWebsocketClientV2):
    
    def received_message(self, message):
        print("Received price update")
        print(message)

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import hashlib
import hmac
import requests
import time

secret_key = 'enter your secret key'
public_key = 'enter your public key'
timestamp = int(time.time())
payload = '{}.{}'.format(timestamp, public_key)
hex_hash = hmac.new(secret_key.encode(), msg=payload.encode(), digestmod=hashlib.sha256).hexdigest()

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/**
 * npm install -g crypto-js
 * npm install -g request
 */

var crypto = require('crypto-js');

var public_key = 'enter your public key';
var secret_key = 'enter your secret key';
var timestamp = Math.floor(Date.now() / 1000);

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from datetime import datetime
from random import randint

class MovAvgCalculator:

    def __init__(self, starting_list=None, window_duration=3600):
        self.moving_average = None
        if starting_list:
            self.my_list = starting_list
            self.sum = sum(starting_list)

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import datetime
import operator

import requests

coins = ['BTCUSD', 'ETHUSD', 'LTCUSD', 'XRPUSD', 'XMRUSD']

API_KEY = '<your public api key>'

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def get_coin_supplies():
    metadata_url = "https://apiv2.bitcoinaverage.com/metadata"
    return make_request(metadata_url)

def get_history_at(days_back):
    history_url = "https://apiv2.bitcoinaverage.com/indices/global/history"
    history_time = datetime.datetime.utcnow() - datetime.timedelta(days=days_back)
    history_timestamp = int(history_time.timestamp())
    results = {}
    for coin in coins: